Northwest Economic Research Center

College of Urban amp Public Affairs PSU

Uncertainty in Long-Range Forecasting Annotated Literature Review

Northwest Economic Research Center July 2013

2

Northwest Economic Research Center July 2013

3

CONTENTS

Executive Summary 4

Introduction 6

Cognitive Model 9

Discounting 10

Distribution 13

Estimation Techniques 16

Model Inputs 26

Uncertainty 36

Other Literature 42

Further Work 45

Northwest Economic Research Center July 2013

4

Executive Summary Forecasting models rely on historical data and relationships to produce a best guess about future circumstances The degree to which the future resembles the past will dictate the accuracy of the modelrsquos predictions Disruptions in these historical relationships mean that models need to anticipate changes in order to maintain usefulness Based on projections climate change could cause significant breaks in the historical relationships that forecasting models are based on Climate change could change the expected values of important forecasting model inputs as well as the likelihood of rare events A change in the expected value can be accommodated fairly easily but a change in the uncertainty and volatility of model inputs can have consequences for policymakers This literature review identifies and summarizes papers that can assist forecasters in incorporating this increased uncertainty into long-range forecasting models We have also created a cognitive model that outlines the process of creating new forecasting inputs The basic idea behind the model is to identify inputs that could be affected by climate change and estimate new values of these inputs to be used in alternative forecasting scenarios The literature review is split into six categories discounting distribution estimation techniques model inputs uncertainty and other literature Discounting and model inputs cover methods for modeling the behavior and preferences of people It reflects attitudes about intertemporal tradeoffs and policy decisions The other categories cover techniques for calculating uncertainty and generating appropriate model inputs We also included several articles that may not be directly related to future work by ODOT or Metro but offer an interesting way of thinking about these issues The goal of this report the tools needed to create alternative long-range forecasts to inform policymakers Forecasts made using these techniques will provide boundary scenarios for the future and can be used to assess risk and appropriate responses

Northwest Economic Research Center July 2013

5

Figure 1 Simplified Cognitive Model

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

2

Northwest Economic Research Center July 2013

3

CONTENTS

Executive Summary 4

Introduction 6

Cognitive Model 9

Discounting 10

Distribution 13

Estimation Techniques 16

Model Inputs 26

Uncertainty 36

Other Literature 42

Further Work 45

Northwest Economic Research Center July 2013

4

Executive Summary Forecasting models rely on historical data and relationships to produce a best guess about future circumstances The degree to which the future resembles the past will dictate the accuracy of the modelrsquos predictions Disruptions in these historical relationships mean that models need to anticipate changes in order to maintain usefulness Based on projections climate change could cause significant breaks in the historical relationships that forecasting models are based on Climate change could change the expected values of important forecasting model inputs as well as the likelihood of rare events A change in the expected value can be accommodated fairly easily but a change in the uncertainty and volatility of model inputs can have consequences for policymakers This literature review identifies and summarizes papers that can assist forecasters in incorporating this increased uncertainty into long-range forecasting models We have also created a cognitive model that outlines the process of creating new forecasting inputs The basic idea behind the model is to identify inputs that could be affected by climate change and estimate new values of these inputs to be used in alternative forecasting scenarios The literature review is split into six categories discounting distribution estimation techniques model inputs uncertainty and other literature Discounting and model inputs cover methods for modeling the behavior and preferences of people It reflects attitudes about intertemporal tradeoffs and policy decisions The other categories cover techniques for calculating uncertainty and generating appropriate model inputs We also included several articles that may not be directly related to future work by ODOT or Metro but offer an interesting way of thinking about these issues The goal of this report the tools needed to create alternative long-range forecasts to inform policymakers Forecasts made using these techniques will provide boundary scenarios for the future and can be used to assess risk and appropriate responses

Northwest Economic Research Center July 2013

5

Figure 1 Simplified Cognitive Model

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

3

CONTENTS

Executive Summary 4

Introduction 6

Cognitive Model 9

Discounting 10

Distribution 13

Estimation Techniques 16

Model Inputs 26

Uncertainty 36

Other Literature 42

Further Work 45

Northwest Economic Research Center July 2013

4

Executive Summary Forecasting models rely on historical data and relationships to produce a best guess about future circumstances The degree to which the future resembles the past will dictate the accuracy of the modelrsquos predictions Disruptions in these historical relationships mean that models need to anticipate changes in order to maintain usefulness Based on projections climate change could cause significant breaks in the historical relationships that forecasting models are based on Climate change could change the expected values of important forecasting model inputs as well as the likelihood of rare events A change in the expected value can be accommodated fairly easily but a change in the uncertainty and volatility of model inputs can have consequences for policymakers This literature review identifies and summarizes papers that can assist forecasters in incorporating this increased uncertainty into long-range forecasting models We have also created a cognitive model that outlines the process of creating new forecasting inputs The basic idea behind the model is to identify inputs that could be affected by climate change and estimate new values of these inputs to be used in alternative forecasting scenarios The literature review is split into six categories discounting distribution estimation techniques model inputs uncertainty and other literature Discounting and model inputs cover methods for modeling the behavior and preferences of people It reflects attitudes about intertemporal tradeoffs and policy decisions The other categories cover techniques for calculating uncertainty and generating appropriate model inputs We also included several articles that may not be directly related to future work by ODOT or Metro but offer an interesting way of thinking about these issues The goal of this report the tools needed to create alternative long-range forecasts to inform policymakers Forecasts made using these techniques will provide boundary scenarios for the future and can be used to assess risk and appropriate responses

Northwest Economic Research Center July 2013

5

Figure 1 Simplified Cognitive Model

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

4

Executive Summary Forecasting models rely on historical data and relationships to produce a best guess about future circumstances The degree to which the future resembles the past will dictate the accuracy of the modelrsquos predictions Disruptions in these historical relationships mean that models need to anticipate changes in order to maintain usefulness Based on projections climate change could cause significant breaks in the historical relationships that forecasting models are based on Climate change could change the expected values of important forecasting model inputs as well as the likelihood of rare events A change in the expected value can be accommodated fairly easily but a change in the uncertainty and volatility of model inputs can have consequences for policymakers This literature review identifies and summarizes papers that can assist forecasters in incorporating this increased uncertainty into long-range forecasting models We have also created a cognitive model that outlines the process of creating new forecasting inputs The basic idea behind the model is to identify inputs that could be affected by climate change and estimate new values of these inputs to be used in alternative forecasting scenarios The literature review is split into six categories discounting distribution estimation techniques model inputs uncertainty and other literature Discounting and model inputs cover methods for modeling the behavior and preferences of people It reflects attitudes about intertemporal tradeoffs and policy decisions The other categories cover techniques for calculating uncertainty and generating appropriate model inputs We also included several articles that may not be directly related to future work by ODOT or Metro but offer an interesting way of thinking about these issues The goal of this report the tools needed to create alternative long-range forecasts to inform policymakers Forecasts made using these techniques will provide boundary scenarios for the future and can be used to assess risk and appropriate responses

Northwest Economic Research Center July 2013

5

Figure 1 Simplified Cognitive Model

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

5

Figure 1 Simplified Cognitive Model

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

6

Introduction Recent legislative mandates related to climate change require the Oregon Department of Transportation (ODOT) and Metro to prepare long range forecasts to accommodate analysis related to greenhouse gas (GHG) generated by transportation activity Long range economic forecasts are consistently changing regardless of the policy issues being considered at any given time Metro and ODOT seek to develop methods to produce a range of likely forecasts The primary objective is to identify the drivers of economic activity and create a cognitive model to organize and evaluate methods to conduct long range planning given the uncertain aspect of long range forecasts

ODOT requested the Northwest Economic Research Center (NERC) explore and assess the role of uncertainty in preparing long range economic and demographic forecasts at the state and metropolitan levels This report provides a literature review covering uncertainty in long-range population demographic and economic forecasting We focused on techniques and methods for introducing uncertainty directly into the model estimation process The review goes beyond the traditional disciplines previously mentioned in order to borrow the treatment of uncertainty from other fields including electricity demand and financial forecasting Information gathered from the literature review will be used to create a data-driven cognitive model that can be used to plan and design tools to be used for scenario planning and help establish future research agendas A multi-disciplinary field of study that yielded relevant literature was climate change and its impacts Because climate change is occurring over a long period of time and estimations of future impacts cannot always rely on lessons drawn from history these researchers must incorporate uncertainty into all aspects of the estimation process The literature features many examples of the effect of a specific disaster or drastic change brought about by climate change but these studies assume an outcome and calculate an impact based on projections based on current data Assuming a natural disaster like a large flood can be incorporated into current models but deciding how likely a large flood is in order to attach a probability to forecasts that include flooding is another issue When historical precedent is an unreliable guide for the future many statistical techniques familiar to economists break down Researchers must construct distributions that reflect future probabilities There is not a consensus on the best technique for doing this Techniques depend on the question being asked and the resources available to the researcher Forecasting is based on establishing historical relationships and interactions between variables and projecting these relationships into the future These relationships are used to calculate expected future values of variables and can also be used to establish the high- and low-end bounds of possible future scenarios Including forecasts that simulate low-probability events will improve regional forecasting by providing policymakers with alternate forecasts that will allow them to weigh resource allocation in light of future uncertainty As climate change increases climatic variability and the likelihood of extreme weather events separating unlikely but possible events from extremely unlikely events has important policy implications Categories We broke down the summaries in the literature review into six different categories discounting distribution estimation techniques model inputs uncertainty and other literature These categories cover the different means by which historical relationships can be altered by climate change and form the theoretical background of our cognitive model (below)

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

7

Discounting represents the value that people or institutions place on current consumption versus future consumption In theory this is a proxy for attitudes toward risk and toward intertemporal tradeoffs This can also be used to inform the policy inputs of the model Arrow (2006) discusses differences between using prescriptive or descriptive discount rate estimates Prescriptive rates incorporate normative judgments about future tradeoffs while descriptive rates are estimated using data on consumer decisions The approach adopted by forecasters can lead to different model inputs while the actual discount rate estimates can be used to model the willingness of a jurisdiction to undertake climate change mitigation in the short term Establishing an appropriate future distribution for model inputs is at the heart of our cognitive model The increased uncertainty created by climate change and the increase in likelihood of extreme events can change the mean variation or symmetry of existing distributions The possibility of fatter tails is of particular interest to forecasters If an extreme event goes from being extremely unlikely to just unlikely the appropriate policy response may change A small shift in tails of an assumed distribution can have a large impact on the expected probability of these rare events Weitzman (2009) discusses the implications of ldquofatteningrdquo the tails of model distributions and increasing the uncertainty of the predictions Zarnowitz and Lambros (1983) identify the importance of including the variation of estimates in estimate aggregations Consensus may emerge if expected values correspond even if all expected values have large confidence intervals The estimation techniques section summarizes papers that reference or explain the techniques that can be used in the transitions of the cognitive model Auffhammer et al (2011) and Azuara et al (2011) both demonstrate techniques for estimating climate change impacts on important model inputs Auffhammer estimates the potential impacts on the California energy market due to climate change Azuara uses the California Statewide Agricultural Production Model (SWAP) to estimate changes in key agricultural inputs and forecast the effect on yields and revenues The estimation techniques section is meant to help in identifying variables that will be effected by climate change and could have impacts on future economic growth Related to estimation techniques is the selection of appropriate model inputs Model inputs enter the model in the initial phase during the variable selection process as well as the distribution construction phase Model inputs include everything from scientific research related to climate change to economic forecasts and policy expectations Buumlchs et al (2011) summarise the equity and fairness concerns of climate change mitigation strategies The uneven impacts of climate change on different income classes has the potential to fundamentally change the functioning of the regional economy These changes need to be incorporated into the model Additionally policymakers will certainly act to offset regressiveness in climate change outcomes and policies affecting expected policy inputs The uncertainty section is related to distributions but takes a more abstract look at uncertainty and its definitions In order to incorporate uncertainty into the modeling process after an expected value is defined an appropriate confidence interval must be established Foley et al (2012) look at benchmarking and deviations from predicted values in wind forecasting The conceptualizations of uncertainty and techniques for quantifying it lead into establishing a distribution in the model Other literature includes papers that describe techniques and case studies that we found interesting but did not directly relate to the other categories Mendelson and Linwood (1998) estimate the economic impacts of climate change on Northwest fisheries Their methodology could serve as a useful aide for forecasting change in particular industries

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

8

Using the Model We created a cognitive model that shows a method for incorporating uncertainty into long-range forecasts based on our review of the literature As with all modeling the first step is to gather the raw data that can be transformed into the modelrsquos primary inputs At this point empirical analysis on the data is needed to select variables of interest Regressions can be run to find variables that have become more volatile in the recent past or variables can be selected based on existing research After variables have been identified the researcher must develop a probability distribution that reflects expected future variable outcomes This is where academic consensus breaks down and the researcher must make a decision based on existing resources and the needs of the study Factors including policy behavioral assumptions and socio-economic assumptions contribute to the future volatility of a variable In order to turn these assumptions into a distribution there are two techniques frequently cited in the literature the Bayesian approach and surveying of experts Variable distribution based on historical data can be used as a starting point Important factors to consider are if the future distribution will feature a shift in the mean a change in variance or a change in symmetry (underlying shape) Once the distribution parameters have been established a Monte Carlo process can be used to estimate values based on likelihood of realization If the values generated in this process are being used to create alternative forecasting scenarios values from the tails of the distribution can be selected rather than the expected value In this way the forecaster can have an idea of model inputs that are extreme but still within the realm of possibility The forecaster can choose values that have a 25 or 5 chance of being realized and run their forecasting model These forecasts can be used to give policymakers a stronger sense of possible boundary scenarios as well as the factors that could drive drastic change in the future The literature review covers statistical techniques that can aid in the process of developing plausible future distributions for model inputs but it is ultimately up to experienced forecasters and experts on their field to define the boundaries possibility The cognitive model is a guide for the forecasters and experts to follow when constructing these distributions

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

9

Figure 2 Uncertainty in Long-Range Forecasting

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

10

Discounting Arrow KJ Cline WR Maler K-G Munasinghe M Squitieri R Stiglitz JE 1995

Intertemporal Equity Discounting and Economic Efficiency Climate Change 1995- Economic and Social Dimensions of Climate Change Bruce James P et al Editors Cambridge University Press 1996 Pg 129-142 In this book chapter the authors explain the difference between prescriptive and descriptive approaches to discounting The prescriptive approach uses a normative perspective to arrive at a conclusion for how future costs should be valued the descriptive approach looks at how people make intertemporal decisions and estimates a discount rate The prescriptive rate tends to arrive at a lower discount rate The chapter demonstrates the difference between the two approaches but does not draw conclusions about which is superior Keywords prescriptive descriptive net present value discounting discount rate Available At httpwwweconyaleedu~nordhausResources22073-Chap4-Intertemporal20Equitypdf

Conceiccedilatildeo Pedro Zhang Yanchun Bandura Romina 2007 Brief on Discounting in the

Context of Climate Change Economics Office of Development Studies United Nations Development Programme New York The authors consider the effect of discounting under a variety of assumptions They begin by considering the effect of changing discount rates in deterministic stylized models with no distributional issues incorporated The analysis is expanded to include probabilistic discounting The likelihood of each discount level is calculated by the authors The authors then include distributional disparities into the analysis They conclude that the intergenerational deterministic trade-off framework is too simplistic Incorporating uncertainty and distributional disparities (as well as intergenerational income inequality) leads to different climate change mitigation decisions Keywords discounting rate uncertainty mitigation trade-offs Available At httphdrundporgenreportsglobalhdr2007-8papersConceicao_Zhang_Bandura_finalpdf

Dasgupta Partha 2008 Discounting Climate Change Presented to World Congress of

Environmental and Resource Economists Monterey California USA June 2002

The author presents a broad overview of methods for estimating appropriate discount rates Keywords utilitarianism well-being social discount rates uncertainty inequality aversion risk aversion rate of time preference rate of return on investment precautionary principle elasticity of marginal well-being risk-free discount rates thin-tailed distributions Available At httpareberkeleyeducoursesARE263fall2008paperDiscountingDasgupta_Discounting20Climate20Change_WP08pdf

Gollier Christina Weitzman Martin L 2009 How Should the Distant Future be Discounted

Northwest Economic Research Center July 2013

11

when Discount Rates are Uncertain Economic Letters 107(3) 350-353 This paper summarizes a simple model useful for analyzing the distant future within a cost-benefit analysis framework Keywords discount rate cost-benefit Weitzman-Gollier puzzle Available At httpideifrdocbygollierdiscounting_long_termpdf

Gollier Christian 2002 Discounting an Uncertain Future Journal of Public Economics 85 149-166

Gollier summarizes discount rate determinants for different time horizons The paper finds under assumptions of positive prudence decreasing relative risk aversion and decreasing absolute risk aversion the efficient discount rate will shrink over time Keywords discounting uncertain growth log-supermodality prudence kreps-porteus preference Available At httpideasrepecorgaeeepubecov85y2002i2p149-166html

Hepburn Cameron Groom Ben 2007 Gamma Discounting and Expected Net Future Value

Journal of Environmental Economics and Management 53 99-109 The authors suggest an alternative to the declining future discount rate They cite a paper (Gollier) that finds that the future discount rate will increase when net future value is used (rather than net present value) The authors find that this discrepancy is eliminated when an explicit evaluation date is incorporated into the analysis They find that the discount rate does indeed decline over time because of uncertainty regarding future returns but that at a future evaluation date the expected cost-benefit outcome can justify an increasing discount rate Keywords declining discount rates uncertainty intertemporal risk allocation Available At httpwwwsciencedirectcomsciencearticlepiiS0095069606000799

Newell Richard G Pizer William A 2004 Uncertain Discount Rates in Climate Policy Analysis Energy

Policy 32(4) 519-529 This paper looks at the theory behind short term discount rates in climate policy analysis and the impact of changes in future rates The research uses historical data to determine the effect of changes in future rates The distant future should be discounted at lower rates than the present rate Higher discount rates yield a larger effect from uncertainty compared to lower discount rates A key finding is that constant discount rates will undervalue the value of abatement measures By viewing the far distant future as uncertain some of the effect of using constant discount rates is mitigated Keywords discounting uncertainty climate change Available At httpwwwsciencedirectcomsciencearticlepiiS0301421503001538

Weitzman Martin L 1998 Why the Far-Distant Future Should Be Discounted at its Lowest Possible

Rate Journal of Environmental Economics and Management 36 201-208

Northwest Economic Research Center July 2013

12

The study is concerned with the proper discount rate for events in the far-distant future The author argues that those events should be discounted at the lowest possible rate The author uses a theoretical model to make his argument Discount rates should decline over time reaching their minimum at some future point Keywords forecasting discounting uncertainty Available At httpwwwsciencedirectcomsciencearticlepiiS009506969891052X

Northwest Economic Research Center July 2013

13

Distribution Bailey Adrian J 2010 Population Geographies and Climate Change Progress in Human Geography 35(5)

686ndash695

This study reviews how population geographies currently help and might further contribute in understanding the link between climate change and populations There has been research on climate change demographics theories of vulnerability and adaptation and frameworks related to risk and governmentality that help in understanding the empirical and theoretical aspects of climate change The author concluded by suggesting the development of strategies sensitive to the increasingly important role of global networks Keywords global networks governmentality migration vulnerability Available at httpphgsagepubcomcontent355686fullpdf

Beebe Nigel W Copper Robert D Mottram Pipi Sweeney Anthony W 2009 Australiarsquos Dengue Risk

Driven by Human Adaptation to Climate Change PLoS Negl Trop Dis 3(5) e429

This study examines the role of climate change in the future range of dengue in Australia For this purpose they build distributional models using a genetic algorithm to project the distribution of Ae Aegypti under todayrsquos climate and under climate change scenarios for 2030 and 2050 and then compare it with published theoretical temperature limits The results show that the increased risk of an Ae aegypti range expansion in Australia would not be due to climate change but due to human adaptation to the current and predicted drying of the region by installing large domestic water storing containers Keywords dengue Ae Aegypti Available at httpwwwplosntdsorgarticleinfo3Adoi2F1013712Fjournalpntd0000429

Dietz Simon 2011 High Impact Low Probability An Empirical Analysis of the Risk in the

Economics of Climate Change Climatic Change 108 519-541 The authors cite research that suggests that the potential negative impacts of climate change should create a willingness-to-pay to avoid these impacts that completely swamp the effects of time period impacts The PAGE model is used to test the theoretical assumptions of this argument The results of the modeling suggest that decision about welfare-maximizing policies depend on the likelihood assigned to low-probability events If the maximum possible damage caused by climate change is capped then at a particular time assumptions about intertemporal preferences and the appropriate discount rate can cause major changes to the results Keywords PAGE discount rate risk aversion damage function Available At httpeprintslseacuk37612

Foley Aoife M Leahy Paul G Marvuglia Antonino McKeogh Eamon J 2012 Current Methods and

Advances in Forecasting of Wind Power Generation Renewable Energy 37 1-8

This paper is a detailed review of the current techniques in wind power forecasting Firstly numerical wind prediction techniques including global to local scales ensemble forecasting

Northwest Economic Research Center July 2013

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upscaling and downscaling methods are overviewed Then statistical and machine learning approached are discussed Next methods used for benchmarking and uncertainty analysis are highlighted and the effectiveness of different approaches over different forecast time horizons is studied Keywords wind power forecast time horizon Available at httpwwwsciencedirectcomsciencearticlepiiS0960148111002850

Hamilton Grant Currat Mathias Ray Nicolas Heckel Gerald Beaumont Mark Excoffier Laurent

2005 Bayesian Estimation of Recent Migration Rates After a Spatial Expansion Genetics 170 409ndash417

This study examines the utility of the Approximate Bayesian computation (ABC) method to predict the parameters of range expansion in a two-dimensional stepping-stone model Then the expansion time and migration rates are estimated for five natural common vole populations in Switzerland for a nuclear marker and sex-related marker Results show that expansion took place 10000 years ago and that migration rates are biased towards males Keywords approximate bayesian computation sex-related Available at httpwwwgeneticsorgcontent1701409fullpdf

Hyndman Rob J Fan Shu 2010 Density Forecasting for Long-Term Peak Electricity Demand IEEE

Transactions on Power Systems 25(2)

This study suggests a new methodology to forecast the density of long-term peak electricity demand Firstly a semi-parametric additive models are used to predict the relationship between demand and the driver variable including temperatures calendar effects and certain economic and demographic variables Then demand distributions are forecasted using temperature simulation assumed future economic scenarios and residual bootstrapping This methodology has been used to forecast the probability distribution of weekly and annual peak electricity demand in South Australia since 2007 Keywords density forecast long-term demand forecasting simulation time series Available at httpwebdocsubgwdgdeebookserienemonash_univwp6-08pdf

Kass Robert E Wasserman Larry 1996 The Selection of Prior Distributions by Formal Rules Journal of

the American Statistical Association 91 1343-1370 In Bayesian inference a prior distribution (Prior) is meant to attribute uncertainty rather than randomness to a sample This paper reviews different methods used to construct Priors with considerable attention to Jeffreyrsquos rule for choosing a Prior The paper also discusses the issues surrounding reference Priors or default Priors for a particular model Important issues discussed surrounding priors include interpretation impropriety dependence on the sample space and sensitivity analysis In conclusion the authors find that the difficulties associated with reference Priors are less pronounced in large samples thus Jeffreyrsquos Rule applies However reference Priors with small sample sizes are problematic Keywords statistics prior distributions Jeffreyrsquos Rule

Northwest Economic Research Center July 2013

15

Available At httpwwwstatcmuedu~kasspapersrulespdf Lahiri Kajal Liu Fushang 2010 ARCH Models for Multi-Period Forecast Uncertainty-A Reality Check

using a Panel of Density Forecasts Econometric Analysis of Financial and Economic Time Series ndash Part A

This study develops a theoretical model to estimate forecast uncertainty from time series models and compare it with that available from survey density forecasts Results reveal that the sum of the average variance of the individual densities and the disagreement underestimated forecast uncertainty and this underestimation is a function of the ratio of the variance of aggregate shocks to that of the idiosyncratic shocks The authors expect this underestimation to be small given the existing empirical estimates of the ratio ARCH estimates diverge from survey measures during periods of structural break and regime change Keywords inflation survey of professional forecasters GARCH real time data disagreement Available at httpmpraubuni-muenchende21693

Laurent Thomas Kozluk Tomasz 2012 Measuring GDP Forecast Uncertainty Using Quantile

Regressions OECD Economics Department Working Papers No 978

This study develops a method to examine the uncertainty around the indicator models to forecast GDP growth of the six largest OECD countries using quantile regressions to construct a probability distribution of future GDP This approach is judgment free as the assessment of the extent of uncertainty conditional on the current state of the economy is entirely model based Then quality of the computed distributions is tried against other techniques of measuring forecast uncertainty Keywords forecasting quantile regression uncertainty density forecasts GDP Available at httpsearchoecdorgofficialdocumentsdisplaydocumentpdfcote=ECOWKP(2012)55ampdocLanguage=En

Niemeyer Victor 2000 Forecasting Long-term Electric Price Volatility for Valuation of Real Power

Options Proceedings of the 33rd Hawaii International Conference on System Sciences

Forwards prices for power determine the current value of these assets but these prices are extremely volatile This study sketches a structural method to estimate market volatility and demonstrates its application in valuing a real option for a gas-fired generating unit Keywords forward prices market volatility Available at httpieeexploreieeeorgstampstampjsptp=amparnumber=926766amptag=1

Webersik Christian Esteban Miguel Shibayama Tomoya 2010 The Economic Impact of Future

Increase in Tropical Cyclones in Japan Nat Hazards 55233ndash250

This study measures the non-first-order economic loss in Japan due to a potential increase in tropical cyclones This study computes the future regional GDP loss in a certain area that is impacted by tropical cyclones using historical storm tracks between the years 1978 and 2007 and altering the intensities Using a Monte Carlo simulation the paper computes the potential

Northwest Economic Research Center July 2013

16

GDP loss due to increase in tropical cyclone intensity for the year 2085 The results show that Japan will experience an annual GDP loss of US $65 per capita in 2085 It is possible to predict what parts of the country are under the risk of highest loss by using a spatial distribution of economic activity in Japan Keywords climate change natural hazards tropical cyclone economic loss Japan Available at httplinkspringercomcontentpdf1010072Fs11069-010-9522-9pdf

Weitzman Martin L 2001 Gamma Discounting The American Economic Review 91(1) 260-271

In order to find the appropriate discount rate to use in cost-benefit analysis the author proposes surveying experts and incorporating the distribution of estimates directly into the estimation process 2160 experts were surveyed on the appropriate discount value to use in cost-benefit analysis The results of the survey were used to estimate the two parameters of a gamma distribution Based on these results the authors find that there are five distinct future time periods each deserving a different rate The immediate future (1-5 years) is ~4 the near future (6-25 years) is ~3 the medium future (26-75 years) is ~2 the distant future (76-300 years) is ~1 and the far-distant future should have a 0 discount rate The author believes that this sliding-scale method is superior to the disagreements over one all-purpose rate and that this method is particularly useful when discussing the impacts of climate change Keywords gamma gamma distribution survey expert opinion climate change Available At httpwwwjstororgstable2677908

Zarnowitz Victor Lambros Louis A 1983 Consensus and Uncertainty in Economic

Prediction NBER Working Paper Series Working Paper No 1171 National Bureau of Economic Research Consensus in prediction is normally defined as general agreement in point predictions for economic values The authors investigate the differences between averages of point predictions and probabilistic predictions They find that means point predictions and mean probabilistic predictions are normally close but averaging point predictions tends to understate the uncertainty in the estimates By incorporating the uncertainty in each individual prediction degrees of certainty can be separated from coarse definitions of consensus Keywords point prediction probabilistic prediction inflation Available At httpwwwnberorgpapersw1171

Northwest Economic Research Center July 2013

17

Estimation Techniques Aliolfi Marco Favero Carlo A 2005 Model Uncertainty Thick Modeling and the Predictability of Stock

Returns Journal of Forecasting 24 233ndash254

This study uses the results of Pesaran and Timmerman (1995) that gave evidence on predictability of excess returns in the US stock market over the period 1959-1992The authors show that extending the sample to the nineties weakens the economic and statistical significance of the predictability of stock returns They then suggest an extension of the methodology of Pesaran and Timmerman (1995) by explicitly considering model uncertainty under rich parameterizations for the predictive models They propose a new method to tackle model uncertainty based on thick modeling which considers multiple predictive models rather than a single predictive model They also demonstrate that portfolio allocations based on thick modeling technique perform better than those based on thin modeling Keywords model uncertainty stock returns predictability thick modeling Available at httponlinelibrarywileycomdoi101002for958pdf

Armstrong J Scott Brodie Roderick J 1999 Forecasting for Marketing Quantitative Methods in

Marketing Second Edition London International Thompson Business Press 92-119

This paper is a review of the research on forecasting in order to present guidelines for forecasting for marketing The review discusses intentions Delphi role playing conjoint analysis judgmental bootstrapping analogies extrapolation rule based forecasting expert systems and econometrics methods The authors evaluate which method is most relevant for forecasting market size actions of decision makers market shares sales and financial outcomes They suggest that there is a need for statistical techniques that incorporate managerrsquos domain knowledge such as rule-based forecasting expert systems and econometric methods Keywords marketing forecasting econometric methods Available at httprepositoryupenneducgiviewcontentcgiarticle=1092ampcontext=marketing_papers

Auffhammer Maximilian Aroonruengsawat Anin 2011 Simulating the Impacts of Climate

ChangePrices and Population on Californiarsquos Residential Electricity Consumption Climatic Change 109 (Suppl 1)S191ndashS210

The study estimates Californiarsquos residential electricity consumption under climate change using panel micro-data They use exogenous weather shocks to see the impact of weather on household electricity consumption Results show that temperature response varies across climate zones Simulation results suggest that household consumption may increase up to 55 by the end of the century keeping population constant The study also simulates the impact of higher electricity prices and different scenarios of population growth to estimate the relative sensitivity of aggregate electricity consumption to changes in these factors Keywords climate change adaptation impacts estimation electricity consumption Available at httplinkspringercomcontentpdf1010072Fs10584-011-0299-ypdf

Northwest Economic Research Center July 2013

18

Azuara Josueacute M Howitt Richard E MacEwan Duncan J Lund Jay R 2011 Economic Impacts of

Climate-Related Changes to California Agriculture Climatic Change 109 (Suppl 1)S387ndashS405

This study analyzes the economic effect of climate change on California agriculture in 2050 using the Statewide Agricultural Production Model (SWAP) which is a mathematical programming model for agricultural production in California that calibrates to observed base year conditions With climate change it is expected that crop yields will decrease production costs will increase and water supplies will decline These negative effects can be partially offset by higher crop prices and improvements in technology The results reveal that climate change would reduce gross agricultural revenues and water usage across all regions However the reductions in revenue are relatively less due to shifting demand technological change and shift towards less water intensive crops Keywords crop yield water supply Available at httplinkspringercomcontentpdf1010072Fs10584-011-0314-3pdf

Beck Jan 2013 Predicting Climate Change Effects on Agriculture from Ecological Niche Modeling Who

Profits who Loses Climatic Change 116 177ndash189

In this study Ecological niche modeling (ENM) is used to map the agriculture suitability under climate change scenarios for the year 2050 ENM is a technique used to relate present records of species to environmental variables and maps the suitability of a landscape for the species in question By comparing relative average change across regions and country wide changes to wealth of nationsrsquo data deviation of predicted scenarios from current model conditions were evaluated The results show a positive relation between change in agriculture conditions and the wealth of nations and that regions differ in whether they win or lose in agricultural suitability North-eastern Europe is predicted to have more favorable conditions for agriculture whereas parts of Africa Europe and southern and eastern Asia are expected to be negatively affected Keywords ecological niche modeling agriculture suitability Available at httplinkspringercomarticle1010072Fs10584-012-0481-x

Briassoulis Helen Analysis of Land Use Change Theoretical and Modeling Approaches The Web Book of

Regional Science Chapter 463 Regional Research Institute West Virginia University This is a subchapter from a web book which specifically deals with modeling land use The section provides some detail on various modeling approaches at the urban regional and global level Keywords land use modeling techniques Available At httpwwwrriwvueduWebBookBriassoulischapter4(models5)htm463

Buumlrgenmeier Beat Baranzini Andrea Ferrier Catherine Germond-Duret Ceacuteline Ingold

Karin Perret Sylvain Rafaj Peter Kypreos Socrates Wokaum Alexander 2006 Economics in Climate Policy and Collective Decision Making Climactic Change 79 143-162

Northwest Economic Research Center July 2013

19

The authors summarize issues related to applying traditional cost-benefit analysis to long-term forecasting including uncertainty and disagreement on the appropriate discounting method To address these issues GMM econometric models that incorporate technical capacity and specification are used to estimate emissions outcomes These techno-economic models lead to decisions supporting tradable emissions permits The authors also present survey results of economic and environmental experts that demonstrate the need to combine modeling with empirical work that places the modeling specifications and results in the appropriate technological and political context Keywords GMM techno-economic modeling multi-disciplinary collaboration econometrics cost-benefit analysis Available At httpwwwiiasaacatpublicationmore_XJ-06-063php

Chung Jin-Hyuk Goulias Konstadinos G 1997 Travel Demand Forecasting Using Microsimulation-Initial

Results from Case Study in Pennsylvania Transportation Research Record 1607 24-30

This study presents a new practical technique for more accurately estimating traffic volumes in regional transportation networks by using demographic microsimulation MUVI a new demographic simulator is combined with another method (assess management impact simulation) that uses a GIS as a support tool and is able to create detailed highway networks which can be used in regional models This methodology can be applied anywhere in the US since the basic input data is available

Keywords traffic volumes transportation networks

Available at httptrbmetapresscomcontentm8nrn53766563486fulltextpdf

Dell Melissa Jones Benjamin F Olken Benjamin A 2009 Temperature and Income Reconciling New

Cross-Sectional and Panel Estimates American Economic Review Papers amp Proceedings 99(2) 198ndash204

This study presents new evidence on the relationship between temperature and income using data from 12 countries in the Americas Results show that there is a negative cross-sectional relationship between temperature and income within countries and across countries This suggests that omitted country characteristics are not solely driving the cross-sectional relationship between temperature and income Then the authors use a theoretical framework for integrating the strong cross-sectional effects of temperature with even stronger short-run effects of temperature suggested by panel models The results indicate that half of the negative short-term effects of temperature are offset in the long run by adaptation Keywords temperature income cross-sectional relationship Available at httpwwwnberorgpapersw14680pdfnew_window=1

Dettinger Michael 2006 A Component-Resampling Approach for Estimating Probability

Distributions from Small Forecast Ensembles Climactic Change 76 (1-2) 149-168 The authors use an ensemble decomposition technique to make statistical analysis and validation more useful by creating additional ensembles The method is applied to medium-range weather forecasts

Northwest Economic Research Center July 2013

20

Keywords meteorology climatology Available At httptenayaucsdedu~dettingecc_ensemblepdf

Egbendewe M Aklesso Musumba Mark McCarl A Bruce Wu Ximing 2011 Climate Change and

Vector-borne Diseases An Economic Impact Analysis of Malaria in Africa Int J Environ Res Public Health 8 913-930

This study uses an econometric model to examine the link between malaria cases and climatic factors in 25 African countries The results reveal that climate factors have a significant impact on the number of malaria cases per 1000 people in most of the counties studied This effect is mixed as predicted by the biophysical malaria models Some countries will experience an increase in malaria cases but others will see a decrease More so the cost of malaria treatment is projected to increase in most of the countries Also economic growth and better income distribution can reduce the number of malaria cases Keywords malaria climate change semi-parametric modeling cost of malaria treatment Available at httpwwwncbinlmnihgovpmcarticlesPMC3083677

Fischer Gunther Shah Mahendra Tubiello Francesco N Velhuizen Harrij V 2005 Socio-Economic

and Climate Change Impacts on Agriculture An Integrated Assessment 1990ndash2080 Philosophical Transactions of the Royal Society B 360 2067ndash2083

This paper develops an integrated ecological-economic modeling framework including climate scenarios agro-ecological zoning information socio-economic drivers and world food trade dynamics The paper assesses the effect of different scenarios of climate change on bio-physical soil and crop growth and computes and range of potential agriculture land and related potential crop production The results are then used for economic analysis to study how climate change may lead to alternate development pathways and to compute future trends of food demand and production trade and indices of risk of hunger and malnutrition The results of the paper reveal that climate change and variability may lead to irreversible damage with severe consequences for food production The losses would felt more intensely in the developing countries thereby widening the production and consumption gaps between developed and developing countries The paper suggests that adaptation of agricultural techniques to climate change is critically important to limit potential damages particularly in many developing counties Keywords crop production climate change food security sub-Saharan Africa risk of hunger Available at httprstbroyalsocietypublishingorgcontent36014632067fullhtml

Fried Jeremy S Torn Margaret S Mills Evan 2004 The Impact of Climate Change on Wildfire

Severity A Regional Forecast for Northern California Climatic Change 64 169ndash191

This study assesses the impact of climate change on wildland fire It also estimates effectiveness of suppression in northern California by linking general circulation model to local weather and fire records and predicting fire outcomes with an initial attack suppression model With increased fire intensity scenarios and corresponding greater fire suppression efforts the number of escaped fires increased 51 in south San Francisco Bay area 125 in the Sierra

Northwest Economic Research Center July 2013

21

Nevada and did not change in the north coast When the results were interpolated there is an average annual increase of 114 escapes and a 50 increase in area burned by contained fires Changes in fire severity will increase suppression costs and economic damages In addition it would impact vegetation distribution forest condition storage of carbon and would increase risk to property natural resources and humans Keywords climate change fire suppression Available at httpevanmillslblgovpubspdfwildfire_and_climate_changepdf

Friedman David M Monteith Micheal C Kay Douglas H Couts Vivian B Trombly Jeffrey W

Bratvold Delma Hirschman Ira 2006 Disruption Impact Estimating ToolmdashTransportation (DIETT) A Tool for Prioritizing High-Value Transportation Choke Points Surface Transportation Security 11

The purpose of this report was to develop an analytical tool to identify and prioritize state-specific choke points according to their potential economic impact on US commerce Keywords commerce Available at httponlinepubstrborgonlinepubsnchrpnchrp_rpt_525v11pdf

Hall Jim W Sayers Paul B Walkden Mike JA Panzeri Mike 2006 Impacts of Climate Change on

Coastal Flood Risk in England and Wales 2030ndash2100 Philosophical Transactions of the Royal Society A 364 1027ndash1049

This study uses a national scale and quantifies flood risk methodology to analyze the coasted flood risk due to changes in climate society and economy over the twenty-first century Given that there is no adaptation to increasing coastal flood risk the estimated annual damage in England and Wales will be between pound10 and pound135 billion depending on the climate and socio-economic change scenario Adaptation to increasing flood risk by constructing coastal dikes or retreat from coastal floodplains is shown to reduce risk to between pound02 and pound08 billion The cost of coastal engineering works is predicted to be between pound12 and pound40 billion Nonstructural methods to reduce risk can significantly reduce the cost and environmental impact of engineering works Keywords coastal flood risk climate change socio-economic scenarios adaptation Available at httprstaroyalsocietypublishingorgcontent36418411027fullpdf+html

Ham Heejoo Kim Tschangho J Boyce David 2005 Assessment of Economic Impacts from Unexpected

Events with an Interregional Commodity Flow and Multimodal Transportation Network Model Transportation Research Part A 39 849ndash860

This study uses an interregional commodity flow model incorporating input-output relationships and the corresponding transportation network flows for the US highway and railways to predict flows of 11 commodity sectors The model was solved using a partial linearization algorithm and it generated estimates for each sector of intraregional and interregional flows and link flows by mode The model was used to assess the economic impact of transportation network disruptions caused a catastrophic event This was done by evaluating changes in commodity flows and their mean shipment distances based on three hypothetical scenarios For each scenario the model predicted the commodity flows among regions the

Northwest Economic Research Center July 2013

22

mean shipment length and the shift in commodity flows from highways to railways The results reveal that the I-94 highway section of Scenario A is the most important section amongst the three scenarios Keywords economic impacts on networks earthquake impact on networks commodity flow modeling combined inputndashoutput with network modeling Available at httpwwwcivilnorthwesternedudocsBoyceassessment_of_economic_impactspdf

Iacono Michael Levinson David El-Geneidy Ahmed Wasfi Rania 2012 A Markov Chain Model of

Land Use Change in the Twin Cities 1958-2005 This research presents the concept of a Markov chain as a way to forecast land use changes A Markov chain uses a transition matrix recording the probability of moving between states in order to transition between states Thus land use in the future can be determined as a function of current land use The paper discusses the theoretical concepts of a Markov chain model and tests it using data from the Twin Cities Minnesota Results demonstrated that a Markov chain method can be used to describe the process of land use change Keywords markov chain land use forecasting Available At httpnexusumneduPapersMarkovLU

Lundmark Linda Pashkevich Albina Jansson Bruno Wiberg Ulf 2008 Effects of Climate Change and

Extreme Events on Forest Communities in the European North Climatic Change 87235ndash249

This study highlights the consequences of extreme events and vulnerability to short-term hazards for the forest-related employment in Norrbotten Lappi and Arkhangelsk oblast using a modified multiplier analysis of the employment effects The implications of an extreme storm are compared to the baseline trend of employment on predicted climate change Results indicate that Arkhangelsk oblast is more vulnerable to climate variability than Norrbotten and Lappi This may be due to continuously depending on natural resources combined with different capacities to counteract negative impact or benefit from the opportunities offered by climate change Keywords multiplier analysis employment effects Available at httplinkspringercomcontentpdf1010072Fs10584-007-9343-3pdf

Mcleman R Smit B 2006 Migration as an Adaptation to Climate Change Climatic Change 76 31ndash53

This study uses a conceptual model to explore population migration as an adaptive response to the risks associated with climate change The model is based upon concepts of vulnerability risk exposure and adaptive capacity The model is then applied to the case of 1930rsquos migration in rural Eastern Oklahoma that took place in a period of crop failures owing to drought and flooding Keywords migration vulnerability exposure of risk adaptive capacity

Northwest Economic Research Center July 2013

23

Available at httppercevalbionauedudownloadsgrailclimate_seminarsection3McLeman_and_Smit06pdf

Pascual Lorenzo Romo Juan Ruiz Esther Forecasting Returns and Volatilities in GARCH Processes

Using the Bootstrap

This paper suggests a new bootstrap resampling scheme to get prediction densities of levels and volatilities of time series generated by GARCH processes The advantage of this method is that it incorporates the variability owing to parameter estimation and thus bootstrap prediction densities for the volatility process can be obtained The finite sample properties are examined using Monte Carlo experiments revealing its good behavior compared to alternative methods Then the procedure is applied to forecast prediction densities of returns and volatilities of the Madrid Stock Market index Keywords time series resampling methods Available at httphalwebuc3mesespPersonalpersonasromo_papersjbespdf

Parry ML Rosenzweig C Iglesias A Livermored M Fischere G 2004 Effects of Climate Change on

Global Food Production under SRES Emissions and Socio-Economic scenarios Global Environmental Change 14 53ndash67

This study examines the potential climate change consequences to crop yields production and risk of hunger For this purpose climate change scenarios are developed from the HadCM3 global climate model under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) To estimate yield changes crop model simulations are used with projected climate change scenarios Then the basic linked system (BLS) is used to predict changes in global cereal production cereal prices and the number of people at risk from hunger The results reveal that in most cases of the SRES scenarios there is a negative effect on simulated global crop yields even after taking beneficial effects of CO2 and farm level adaptations Also with greater amounts of climate change there is a significantly larger disparity in cereal yields between developed and developing nations In SRES scenarios of a more globalized world there is a greater yield reduction than under a scenario of a more regionalized world The BLS world food trade system model indicates that the most of the world will be able to feed itself under the SRES scenarios during the remaining part of the century Though global production seems stable regional differences in crop production will increase over time resulting in significant increase in prices and risk of hunger amongst the poorer countries Keywords climate change SRES emissions scenarios global food security cereal yields risk of hunger Available at httppubsgissnasagovdocs20042004_Parry_etalpdf

Pendleton Lindwood King Philip Mohn Craig Webster D G Vaughn Ryan Adams Peter N 2011

Estimating the Potential Economic Impacts of Climate Change on Southern California Beaches Climatic Change 109 (Suppl 1)S277ndashS298

This study assesses the physical and economic impact of permanent beach loss caused by inundation from sea level rise of a meter erosion and accretion from a single stormy year For this purpose a random utility model is used that allows beachgoers to have different

Northwest Economic Research Center July 2013

24

preferences for beach width depending on beach size The authors simulate the impact of climate-related beach loss on attendance at 51 beaches beach expenditures and consumer surplus for the beaches Results show that rise in sea level will reduce the overall economic value in beach going Potential economic impact from a single stormy year is as high as that caused by permanent inundation from rise in sea level by a meter The economic impact of permanent inundation and erosion from storm varies across regions Keywords permanent inundation erosion stormy year Available at httplinkspringercomcontentpdf1010072Fs10584-011-0309-0pdf

Tol Richard SJ 2013 The Economic Impact of Climate Change in the 20th and 21st Centuries Climatic

Change 117(4) 795-808 In this paper the author researches the past impacts of climate change An integrated model is used to estimate the impacts of climate change from 1900 to 2100 in 5 year increments Climate impact categories include agriculture forestry sea level rise cardiovascular and respiratory disorders malaria dengue fever schistosomiasis diarrhea energy consumption water resources unmanaged ecosystems and tropical and extra tropical storms The study found that past climate change brought positive net benefits though some categories were affected negatively and others positively The trend shows the impact of climate change after 1980 was negative for poor countries and positive for rich countries In the 21st century impacts turn negative for both rich and poor counties Keywords climate change impact history Available At httplinkspringercomarticle1010072Fs10584-012-0613-3page-1

Tol Richard SJ 2002 Estimates of the Damage Costs of Climate Change Part II Dynamic Estimates

Environmental and Resource Economics 21 135ndash160

This study derives monetized estimates of climate change Impacts are estimated for nine world regions for the period 2000-2200 for agriculture forestry water resources energy consumption sea level rise ecosystems fatal vector- borne diseases and fatal cardiovascular and respiratory disorders Results show that in short term estimated sensitivity of a sector to climate change is a critical parameter In long term the change in vulnerability of the sector is more important for the total impact The direction Impacts (negative or positive) depends on the time region and the sector Negative impacts are prevalent in the poorer regions Keywords adaptation climate change impacts Available at httplinkspringercomcontentpdf1010232FA3A1014539414591pdf

Thurlow James Dorosh Paul Yu Winston 2012 A Stochastic Simulation Approach to Estimating the

Economic Impacts of Climate Change in Bangladesh Review of Development Economics 16(3) 412ndash428

In this study a recursive dynamic CGE model is developed to estimate the economic impact of future anthropogenic climate changes and distinguish it from historical climate variability The results show that historical climate variability will decrease rice production in Bangladesh by 88 on average over 2005-2050 This would lead to a loss of US$25 billion per year in total GDP from historical climate variability However the GDP damage from anthropogenic climate

Northwest Economic Research Center July 2013

25

change is one-fifth Anthropogenic climate change modifies the seasonal distribution of damages and slows the long run shift in significance of the wet season relative to the dry (winter) season production Keywords anthropogenic climate change historical climate variability Available at httppapersssrncomsol3paperscfmabstract_id=2105886

Tseng Wei-Chun Chen Chi-Chung Chang Ching-Cheng Chu Yu-Hsien 2009 Estimating the Economic

Impacts of Climate Change on Infectious Diseases A Case Study on Dengue Fever in Taiwan Climatic Change 92123ndash140

This study examines the impact of climate change on dengue fever in Taiwan For this purpose a panel data model and the Contingent Valuation Method (CVM) is used The results of the panel data estimation show that climate change has a significant positive impact on the probability of people being infected by dengue fever Keywords dengue CVM

Available at httpwwwncbinlmnihgovpmcarticlesPMC3037052

Weitzman Martin L 2009 On Modeling and Interpreting the Economics of Catastrophic Climate

Change The Review of Economics and Statistics 91(1) 1-19 This research discusses the uncertainty surrounding the modeling of low-probability high ndashimpact catastrophes These events have ldquofat-tailedrdquo probability distribution functions which assign relatively higher probability to extreme events compared to a thin tailed distribution The fat tailed distribution implies high level of uncertainty surrounding conclusions The paper concludes that the cost-benefit estimates from a catastrophic climate event might ldquoconceivably be arbitrarily inaccuraterdquo Keywords catastrophic climate change structural uncertainty probability distributions Available At httpdashharvardedubitstreamhandle13693423Weitzman_OnModelingpdfsequence=2

Northwest Economic Research Center July 2013

26

Model Inputs ARTBA Transportation Development Foundation 2010 The Economic Impact of Interrupted Service

Case studies presented give an idea of the economic cost of disruption in a transportation network Collapse of the Minnesota I‐35W Bridge over the Mississippi River in 2007 caused a loss of $60 million before the replacement bridge opened in 2008 New Yorkrsquos subway and buses strike for two and half days in December 2005 caused loss of about $400 million the first day and $300 million each of the next two days The shutdown of six largest container ports in the West Coast in 2002 cost the US economy about $15 billion The US Congressional Budget Office estimated that a week shutdown of just the Los Angeles and Long Beach ports would result in a loss of $65 million and $150 million per day More than 50 of the trade from the Los Angeles and Long Beach ports goes through Terminal Island which is connected to the mainland by three highway bridges and one rail bridge An analysis by Peter Gordon James E Moore II and Harry W Richardson of the University of Southern California and Qisheng Pan of Texas Southern University indicates that destruction of these four bridges would result in an economic loss between $225 billion to $90 billion depending on how long it would take to rebuild access to the Island The Iceland Volcanic eruption cost the US economy more than $813 million in travel spending and $90 million in taxes Also the grounding of airplanes in the US following terrorists attacks of September 11 2001 cost the airline industry more than $14 billion Keywords economic cost transportation network

Available at httpwwwartbaorgEconomicsEconBreakouts04_EconomicImpactInterruptedServicepdf

Backlund P A Janetos DS Schimel J Hatfield M Ryan S Archer D Lettenmaier 2008 Executive Summary In The Effects of Climate Change on Agriculture Land Resources Water Resources and Biodiversity A Report by the US Climate Change Science Program and the Subcommittee on Global Change Research Washington DC USA Pg 362

This report examines the impact of climate change on US agriculture land resources water resources and biodiversity Climate change affects the services the ecosystems provide such as removing carbon from air and cleaning water Climate change is affecting the countryrsquos ecosystem in important ways The United States became warmer and wetter during the twentieth century Parts in the north have warmed whereas southern regions have cooled Climate change will accelerate in the future and in some instances drastically The interaction between climate land use changes and species invasion is complex which confounds simple causal relations and complicates the development of adaptation strategies The current monitoring systems are not optimal for detecting effect of climate change on ecosystems

Keywords climate change ecosystem Available At wwwamwanetgalleriesclimate-changeCCSP_Ag_Reportpdf

Bosello Francesco Roson Roberto Tol Richard SJ 2006 Economy-Wide Estimates of the Implications

of Climate Change Human Health Ecological Economics 58 579ndash591

This study assesses the economic impact of climate-change-induced change in human health via changes in labor productivity and demand for health care The results show that GDP welfare and investment will fall (increase) in regions with net negative (positive) health impacts In

Northwest Economic Research Center July 2013

27

particular in 2050 climate-change-induced health impacts might increase GDP by 008 or reduce it by 007 Keywords impacts of climate change human health Available at httpwwwsciencedirectcomsciencearticlepiiS0921800905003423

Brown Oli 2008 Migration and Climate Change International Organization for Migration

This report examines the link between human migration and climate change There are two distinct climate change determinants of migration namely climate processes such as sea-level rise desertification and increasing water scarcity and climate events such as flooding storms and glacial floods Though temporary migration is a response to climate stress people most likely to migrate are not necessarily those who are most vulnerable to climate change This study lays out three scenarios based on different emission forecasts to predict future flows of climate migrants It is important to realize that forced migration impedes development by increasing pressure on urban infrastructure by declining economic growth by increasing conflict risk and worsening health education and social indicators amongst migrants There has been a collective attempt to not take into account the gravity of the problem There is resistance to the notion of broadening the definition of political refugees to include climate refugees Keywords climate processes climate events migration Available at httpwwwiisdorgpdf2008migration_climatepdf

Buumlchs Milena Bardsley Nicholas Duwe Sebastian 2011 Who Bears the Brunt Distributional Effects

of Climate Change Mitigation Policies Critical Social Policy 31 285

One of the main hurdles in the adoption of effective mitigation policies is that climate change mitigation policies are generally perceived to have regressive impacts This study evaluates whether climate change policies have regressive effects by comparing different mitigation policies The authors find that though several policies have regressive effects there are many policies that counteract the regressive effects Keywords emissions environment fairness inequality taxation Available at httpcspsagepubcomcontent312285fullpdf

Buyck Sofie 2008 Economic loss estimation along transportation corridors

This study is an overview of existing model for estimating economic loss and presents a methodology to estimate the economic loss of a temporary disruption of the infrastructure The methodology is based on the Input-Output approach and the classic four-step transport model Keywords input-output model transport model Available at httpdocutwentenl773131Buyck08economicpdf

Edwards Phil Roberts Ian 2009 Population Adiposity and Climate Change International Journal of

Epidemiology 381137ndash1140

Northwest Economic Research Center July 2013

28

This study examines the impact of increases in the population distribution of body mass index (BMI) on greenhouse gas emissions For this purpose the Schofield equations for males and females are used to estimate the food energy needed to maintain basal metabolic rate in two hypothetical adult populations Results show that a population with 40 obesity needs 19 more energy for their total energy expenditure Greenhouse gas emissions due to increases in adiposity in a population of 1 billion is estimated to be between 04 and 1 Giga tonnes (GT) of carbon dioxide equivalents per year Keywords climate greenhouse effect body mass index obesity Available at httpijeoxfordjournalsorgcontentearly20090419ijedyp172full

Fang Zhao Chung Soon 2006 A Study of Alternative Land Use Forecasting Models Lehman Center for

Transportation Research Florida International University This deals specifically land use forecasting models It gives description and methodology of many different types of modeling techniques There is some discussion of demographic change in some models Keywords land use modeling techniques Available At httpwwwdotstateflusresearch-centerCompleted_ProjSummary_PLFDOT_BD015_10_rptpdf

Figliozzi Miguel A Zhang Zeyan 2009 A Study of Transportation Disruption Causes and Costs in

Containerized Maritime Transportation

The focus of this study is to understand and estimate the costs and causes of transportation related supply chain disruptions For this purpose in-depth interviews were conducted with logistics managers The response of managers reveals that disruption costs include lost sales expediting costs intangibles such as reputation loss and financial impacts on companiesrsquo cash flows This research study shows that it is possible to estimate transportation disruption costs using discrete choice models and data collected from interviews with managers Results indicate that shippersrsquo willingness to pay for travel time reduction increases five times when there is transportation disruption In case the disruptions are frequent freight travel time values can severely underestimate the economic costs of delay and expediting Keywords supply chain disruptions containerized maritime transport value of time and reliability Available at httpwwwtrforumorgforumdownloads2009_93_TransportationDisruption_paperpdf

Galbreath Jeremy 2011 To What Extent is Business Responding to Climate Change Evidence from a

Global Wine Producer Journal of Business Ethics 104421ndash432

This study examines how and to what extent business responds to climate change For this purpose a firm in the wine industry is studied and the research approach used is not constrained by structured methodologies or biased toward GHG emissions Results how that both lsquoinside outrsquo and lsquoinside inrsquo actions are taken in response to climate change Also response to climate change is shaped by situated attention structural controls and industry type

Northwest Economic Research Center July 2013

29

Keywords Climate change wine Available at httpideasrepecorgakapjbusetv104y2011i3p421-432html

Gay C Estrada FConde C Eakin H Villers L 2006 Potential Impacts of Climate Change on

Agriculture A Case study of Coffee Production in Veracruz Mexico Climatic Change 79 259ndash288

This study examines the potential impact of climate change on coffee production in Veracruz The authors present an approach for constructing simple probability scenarios for future climate change and use it to analyze the effect of climate change The model reveals that temperature is the most important climatic factor for coffee production The results of the projected climate change for year 2020 shows a 34 reduction in current coffee production The model also suggests that the state real minimum wage is the most important economic factor for coffee production Here real minimum wage is considered a proxy for the price of labor employed for coffee production Coffee production is a very labor intensive activity comprising up to 80 of coffee production costs in Mexico Therefore increase in real minimum wage would increase production costs and negatively impact coffee production Keywords temperature real minimum wage Available at httplinkspringercomcontentpdf1010072Fs10584-006-9066-xpdf

Gosling Simon N Warren Rachel Arnell Nigel W Good Peter Caesar John Bernie Dan Lowe Jason

A Lindsen Paul V OrsquoHanley Jesse R Smith Stephen M 2011 A Review of Recent Developments in Climate Change Science Part II The Global-Scale Impacts of Climate Change Progress in Physical Geography 35(4) 443ndash464

This study reviews the recent studies assessing the global scale impacts of climate change published since the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) The review covers six main impact sectors namely sea level rise and coastal impacts ocean acidification ecosystems and biodiversity water resources and desertification agriculture and food security and human health Three main themes emerge from the review First there is a move towards probabilistic techniques to assess impacts Second there is movement towards analyzing potential impacts that could be evaded under different climate change mitigation scenarios Third there are uncertainties in understanding the relation between climate and naturalhuman systems There seems to be a heightened risk of damage to natural systems and in some parts of human system Keywords agriculture climate change impacts ecosystems health Intergovernmental Panel on Climate Change (IPCC) ocean acidification sea-level rise water resources Available at httpppgsagepubcomcontent354443fullpdf+html

The Government Office for Science 2011 Foresight Migration and Global Environmental Change Final

Project Report London

This study focuses on migration in face of environmental change in the next 50 years In addition to assessing global migration trends internal migration trends mainly within low-income countries are also examined The report suggests that tackling environment-induced migration needs a new strategic policy approach The main message of the report is that migration in the context of environmental change might not merely be a part of the problem but can also be a

Northwest Economic Research Center July 2013

30

part of the solution And this is possible if planned and facilitated approaches are undertaken to deal with migration If policy makers give urgent attention to human migration they can avoid a more serious and costly situation in the future

Keywords migration low-income policy

Available at httpwwwbisgovukassetsforesightdocsmigration11-1116-migration-and-global-environmental-changepdf

Feng Shuaizhang Krueger Alan B Oppenheimer Michael Schneider Stephen H 2010 Linkages

among Climate Change Crop Yields and MexicondashUS Cross-Border Migration Proceedings of the National Academy of Sciences of the United States of America 107(32) 14257-14262

This study uses an instrumental variable approach to examine the relationship between climate change agricultural yields and human migration responses for the case of Mexico The results indicate that there is a significant impact of climate change on crop yields and emigration rates from Mexico In particular a 10 reduction in crop yields leads to an additional 2 of the population to emigrate By 2080 climate change is predicted to cause 14 to 67 million adult Mexicans to emigrate owing to decline in agriculture productivity depending on warming scenarios and adaptation levels assumed Keywords human migration environmental migrants agricultural productivity instrumental variables approach Available at httpwwwpnasorgcontentearly201007161002632107fullpdf

Hugo Graeme 1996 Environmental Concerns and International Migration International Migration

Review 30 (1) Special Issue Ethics Migration and Global Stewardship105-131

The emphasis of this paper is on international migration that occurs due to changes in environment It reviews the studies that have theorized environment led migration and also examines the how influential environmental factors have been in initiating migration The ethical and policy aspects are also discussed

Keywords migration environmental factors

Available at httpwwwjstororgstable2547462

Iglesias Ana Garrote Luis Quiroga Sonia Moneo Marta 2012 A Regional Comparison of the Effects

of Climate Change on Agricultural Crops in Europe Climatic Change 11229ndash46

This study examines the impact of climate change on agriculture in Europe using high resolution climate data socio-economic data and impact assessment models Three main results emerge from this study Firstly all scenario projects are consistent in the spatial distribution of effects ie crop productivity increases in northern Europe and decreases in southern Europe Secondly results may be optimistic from the production viewpoint and pessimistic from the environmental standpoint since the study assumes no restriction on water use for irrigation Lastly trade patterns appear to be the main drivers of economic impacts since export and import changes vary relatively more than other GDP components Keywords climate change trade patterns Available at httpcatinistfraModele=afficheNampcpsidt=25747264

Northwest Economic Research Center July 2013

31

Karl Thomas R Melillo Jerry M Peterson Thomas C (eds) Global Climate Change Impacts in the

United States Cambridge University Press 2009

This report highlights the observed and future climate change and its impacts on the United States The key findings are that global warming is mainly human induced Climate changes and their impacts are occurring in the United States and are likely to increase Climate change will strain water resources and negatively impact crop and livestock production Risks to humans will also increase Coastal areas are also at risk from increasing sea-level rise Finally future climate change and its effects depend on current choices Keywords climate change human-induced Available at wwwglobalchangegovusimpacts

Kitamura Ryuichi 2009 Life-Style and Travel Demand From Special Report 220 A Look Ahead Year

2020 Transportation Research Board National Research Council Washington DC 1988 pp 149ndash189 This paper reviews life-style definitions used in the literature and finds variables that been linked with life-style Then US consumer expenditure data is used to examine trends longitudinally for the period 1953-1983 Cross-sectional analysis is also done by comparing sections of population stratified by income life-cycle stage and age

Keywords lifestyle congestion travel behavior long-range forecasting

Available at httplinkspringercomcontentpdf1010072Fs11116-009-9244-6pdf

Kjellstrom Tord Kovats R Sari Lloyd Simon J Holt Tom Tol Richard S J 2009 The Direct Impact of

Climate Change on Regional Labor Productivity Archives of Environmental amp Occupational Health 64 (4)

This study estimates the impact of two climate scenarios on future labor productivity In most regions climate change will decrease labor productivity given no specific adaptation By 2080 the decrease will be greatest in Southeast Asia Andean and Central America and the Caribbean Keywords climate change labor productivity Available at httpwwwesriieUserFilespublications20081023140839WP260pdf

Liao Shu-Yi Tseng Wei-Chun Chen Pin-Yu Chen Chi-Chung Wu Wei-Min 2010 Estimating the

Economic Impact of Climate Change on Cardiovascular DiseasesmdashEvidence from Taiwan Int J Environ Res Public Health 7 4250-4266

This paper uses a panel data regression model to study the impact of climate change on blood vessel-related heart disease and hypertension during 1971 to 2006 in Taiwan The results reveal that the number of deaths from cardiovascular diseases would increase by 0226 as the temperature variation increases by 1 The contingent valuation method (CVM) is also applied to assess the economic impacts of climate change on cardiovascular diseases The results reveal that each person would be willing to pay US$51 to US$97 per year to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change

Northwest Economic Research Center July 2013

32

Keywords cardiovascular diseases climate change panel model contingent valuation method Available at httpwwwmdpicom1660-46017124250

Linnenluecke Martina Griffiths Andrew 2010 Beyond Adaptation Resilience for Business in Light of

Climate Change and Weather Extremes Business Society 49 477

This study highlights that there is a need to broaden the discussions on organizational adaptation and that new approaches are required to incorporate the impact of climate change on corporate strategy and decision making The authors suggest that a resilience framework will be useful in tackling new types of environmental change They assert that organizations by developing resilience can acquire capabilities to minimize organizational collapse and to reorganize in face of discontinuities due to climate change Keywords climate change extreme weather events adaptation resilience adaptive cycle Available at httpbassagepubcomcontent493477fullpdf+html

Martinez Francisco 1996 MUSSA Land Use Model for Santiago City Transportation Research Board of

National Academies (1552) 126-134 This paper studies MUSSA a land use model used in Santiago Chile The model follows BID-CHOICE location economic theory and assumes a competitive urban land market The model forecasts location choices for households and firms within 264 urban zones The paper also provides cognitive models depicting how MUSSA operates The utility forecasts showed that high-income groups would be worse off due to population increases and an increase in average income thus increasing the standard of living At the firm level retail and service were forecasted to have higher utility than industry and education Keywords land use model santiago chile competitive urban land market Available At httptrbmetapresscomcontentu35602wp7uw367m3fulltextpdf

Pijanowski Bryan C Brown Daniel G Shellito Bradley A Manik Gaurav A 2002 Using Neural

Networks and GIS to Forecast Land Use Changes A Land Transformation Model Computers Environment and Urban Systems 26 553-575 This research presents a Land Transformation Model (LTM) coupling geographic information systems (GIS) with artificial neural networks (ANNs) The model was used to predict how land use changes due to social political and environmental factors The paper focuses specifically on the Michigan Grand Traverse Bay Watershed At larger scales the predictive ability of the model improves Keywords land transformation model geographic information systems land use Available At httpproceedingsesricomlibraryuserconfproc04docspap1995pdf

Rasouli Soora Timmermans Harry 2012 Uncertainty in Travel Demand Forecasting Models Literature

Review and Research Agenda Transportation Letters the International Journal of Transportation Research 4(1)

Northwest Economic Research Center July 2013

33

This paper reviews existing work on uncertainty analysis in travel demand forecasting In particular studies exploring different uncertainty sources are summarized distinguishing between four step models discrete choice models and activity based models Also avenues for future research are outlined with an emphasis on advanced activity-based models

Keywords uncertainty analysis travel demand forecasting

Available at httpwwwuncertweborguploadspapersfb8c49bb0ef9c11d2aa4890220beeeb4488e510epdf

Rosenzweig Cynthia Parry Martin P 1994 Potential Impact of Climate Change on World Food Supply

Nature 367 133-138

This study assesses the potential impact of climate change on world food supply The results reveal that doubling of the atmospheric carbon dioxide concentration will results in only a small decline in global crop production Climate change will increase the disparities in cereal production between developed and developing nations Simulations of adaptive measures taken by farmers indicate that they will not have significant impact on reducing the disparity between developed and developing countries Keywords world food supply global crop production Available at httpwwwnaturecomnaturejournalv367n6459pdf367133a0pdf

Tao Fulu Yokozowa Masayuki Liu Jiyuan Zhang Zhong 2009 Climate Change Land Use Change and

Chinarsquos Food Security in the Twenty-First Century An Integrated Perspective Climatic Change 93 433ndash445

The authors present an integrated view on Chinarsquos food supply and food demand in the twenty-first century using official statistics and state of the art future scenarios The scenarios include a range of future characteristics such as population growth economic development and technological change The authors estimate the impact of change in harvest areas particularly due to climate change on the productivity needed to meet the food demand They also estimate the effect of changes in productivity and land use on the population at risk of malnutrition They conclude that China has the potential to feed itsef without disturbing the global food market in the twenty-first century

Keywords food demand harvest area Available At httplinkspringercomcontentpdf1010072Fs10584-008-9491-0pdf

Tol Richard SJ 2002 Estimates of the Damage Costs of Climate Change Environmental and Resource

Economics 21 135-160 The author investigates the monetary effect of climate change on specific impact categories These categories include agriculture forestry water resources energy consumption sea level rise ecosystems vector-borne diseases and cardiovascular and respiratory diseases The paper looks at the impact through the year 2200 The author finds that the impact can be positive or negative depending on the sector being looked at The negative impacts dominate in later years

Northwest Economic Research Center July 2013

34

Keywords climate change short term impacts long term impacts Available At httplinkspringercomcontentpdf1010232FA3A1014500930521pdf

Transportation Research Board 2012 Methodologies to Estimate the Economic Impacts of Disruptions

to the Goods Movement System National Highway Research Program- Report 732

This study synthesizes the current state of knowledge of the economic impact of transportation disruptions on movement of goods It also develops conceptual methodologies to estimate the economic impacts for different geographic and temporal scales Furthermore it demonstrates the use of these methods at different scales and in different contexts In particular the study develops a five-step process as a comprehensive framework to assess the economic impact of freight network disruptions The first step identifies the direct physical effects of a network disruption The second step identifies the current and future network flows that are affected The third step finds supply chain characteristics and parameters The fourth step models the response of the supply chain to disruptions The final step models the economic impact of network disruptions Keywords economic impact network disruption Available at httponlinepubstrborgonlinepubsnchrpnchrp_rpt_732pdf

Vischio Andrew 2010 An Analysis of Methodologies to Estimate the Economic Impacts of Freight

Transportation System Disruptions Georgia Institute of Technology

This study depicts that many different approaches can be used to study the economic impacts of similar disruptive events It also conceptualizes the link between the supply chains disruptions and their economic impacts Keywords supply chain disruptions Available at httpssmartechgatechedubitstreamhandle185337284vischio_andrew_j_201012_mastpdf

Zegras P Christopher 2007 As if Kyoto mattered The Clean Development Mechanism and

Transportation Energy Policy 35 5136ndash5150

Transportation is a fast growing anthropogenic source of greenhouse gas (GHG) emissions Four components namely activities (A) mode share (S) fuel intensity (I) and fuel choice (F) (ASIF) result in transportation energy consumption and GHG emissions Presently the Kyoto Protocolrsquos clean development mechanism (CDM) is the primary international international market-based tool meant to reduce GHG emissions in developing countries This study examines overall CDM activities and analyzes three case studies of transportation CDM possibilities with the ASIF framework in Santiago de Chile The results reveal that bus technology switch (I) is a good project fit for the CDM whereas choices directed at inducing mode share (S) to bicycle or changing travel demand by modifying land use (ASI) face many challenges

Keywords clean development mechanism transportation greenhouse gases

Available at httpwebmiteduczegraswwwZegras_CDM26Transportpdf

Northwest Economic Research Center July 2013

35

Zhu Shanjiang Levinsony David 2011 Disruptions to Transportation Networks A Review

This paper reviews the theoretical and empirical studies on traffic and behavioral impacts of network disruptions Keywords network disruption travel behavior Available at httpnexusumneduPapersDisruptionReviewpdf

Northwest Economic Research Center July 2013

36

Uncertainty Arcas Diego Uslu Burak 2010 PMEL Tsunami Forecast Series Vol 2 A Tsunami Forecast Model for

Crescent City California NOAA OAR Special Report

The purpose of this report is to develop a forecast model for tsunami that would give timely and reliable estimates of tsunami wave heights for Crescent City California The development process is based on Method of Splitting Tsunamis numerical code and stability simulations with artificial extreme events to test the model for robustness To test validity and stability of the Crescent City Forecast model 11 historical tsunamis and 16 synthetic events were used A high-resolution reference model is also constructed to monitor the deviation of forecast estimates from those calculated with a more accurate high-resolution model Results indicate that a forecast model with resolution of 2 arc second is able to generate 4 hour of tsunami simulation in less than 10 minute of CPU time and yields results similar to those obtained from a high-resolution reference model that has an exceedingly long computational time Keywords forecast model tsunami high-resolution Available at httpnctrpmelnoaagovforecast_reportsfinal_reports02_CrescentCityCA_3341_webpdf

Costello Christopher J Neubert Michael G Polasky Stephen A Solow Andrew R 2010

Bounded Uncertainty and Climate Change Economics Proceedings of the National Academy of Sciences 107 (18) 8108-8110 The authors investigate the effect of placing an upper bound on estimates of temperature increases caused by climate change They find that no upper bound is possible that will reduce the willingness-to-pay to avoid the adverse effects of climate change to something other than infinite Keywords risk aversion truncated distribution temperature sensitivity Available At httpwwwpnasorgcontent107188108short

Enei Riccardo Claus Doll Klug Stefan Partzsch Ina Sedlacek Norbert Kiel Jan Nesterova Nina

Rudzikaite Loreta Papanikolaou Anestis Mitsakis Vangelis 2011 Vulnerability of Transport Systems- Main Report Transport Sector Vulnerabilities within the Research Project WEATHER (Weather Extremes Impacts on Transport Systems and Hazards for European Regions) funded under the 7th Framework Program of the European Commission

This study reports impacts of the various weather extremes on different modes of transport The total cost is about euro 25 billion yearly About 97 of the total costs are related to the transport modes (road rail waterborne air) for which generalization at the EU level have been carried out This means that the conclusions drawn are representative of the impacts experienced by the overall European transport system Keywords modes of transport Available at httpwwwweather-projecteuweatherdownloadsDeliverablesWEATHER_Deliverable-2_main-report_20110614pdf

Northwest Economic Research Center July 2013

37

Ericsson Neil R 2001 Forecast Uncertainty in Economic Modeling Board of Governors of the Federal

Reserve System International Finance Discussion Papers Number 697 The paper is an introduction to forecast uncertainty in empirical economic modeling The author covers definitions of forecast uncertainty sources of uncertainty measures of uncertainty and how these measures can be used The author finds that variance and mean square errors are the most common measures of forecast uncertainty Because uncertainty springs from the fact that ldquowe donrsquot know what we donrsquot knowrdquo measures of uncertainty can be used to estimate the importance of the unmodeled elements of a system Keywords econometrics economics forecasting models uncertainty Available At httpwwwfederalreservegovpubsifdp2001697ifdp697pdf

Flyvbjerg Bent 2005 Measuring Inaccuracy in Travel Demand Forecasting Methodological

considerations regarding Ramp up and Sampling Transportation Research Part A 39522ndash530

The two main objections to measuring in travel demand forecasting is the use of the forecast made at the time of decision making as the basis for measuring inaccuracy and the use of traffic during the first year of operation as the basis for measurement This paper argues against the two objections The paper points out that large samples of inaccuracy in travel demand forecasts are probably biased conservatively and that the bias must be incorporated in results of the statistical analyses of inaccuracy in travel demand forecasting

Keywords travel demand forecasting inaccuracy of travel forecasts demand ramp up sampling for measuring inaccuracy bias

Available at httparxivorgpdf13037401pdf

Fraisse CW Breuer NE Zierden D Bellow JG Pazd J Cabrera VE Garcia A Ingram KT

Hatch U Hoogenboom G Jones JW OrsquoBrien JJ 2006 AgClimate A Climate Forecast Information System for Agricultural Risk Management in the Southeastern USA Computers and Electronics in Agriculture 53 13ndash27

The main premise of this study was that a climate forecast information system can be effectively implemented to assist agricultural producers in reducing climate variability risks in the southeastern USA Though initial feedback is positive a formal evaluation process must be completed in order to corroborate the main hypothesis The system (AgClimate) is in the process of transfer to the Florida State Extension System and efforts are being made to do the transfer to Extension services in Georgia and Alabama Keywords crop models climate variability decision making extension Available at httpwwwuwexeducesdairymgtdocumentscea06pdf

Gossling Stefan Hall Michael 2006 Uncertainties in Predicting Tourist Flows under Scenarios of

Climate Change Climatic Change 79 163ndash173

There is an increased concern that tourist flows affect climatic and socio-economic parameters However the role of climate in destination choices is more complex than assumed in current models Current models use databases that do not differentiate between business and leisure

Northwest Economic Research Center July 2013

38

tourism whereas these groups have different elasticities of demand Also there is uncertainty about the role of other weather parameters such as rain air pollution or humidity The future costs of transport and its effect on travel are uncertain Hence caution is needed when using top-down models that use a few climate-related parameters to estimate travel flows Keywords socio-economic parameters tourism elasticities of demand Available at httpdevthegncsorgsitefilesfileIndonesia_Tourism_Gossling_2006pdf

Guilleacuten Osmani TC Isslery Joatildeo V Athanasopoulos George 2005 Forecasting Accuracy and

Estimation Uncertainty using VAR Models with Short- and Long-Term Economic Restrictions A Monte-Carlo Study Monash Econometrics and Business Statistics Working Papers Monash University Department of Econometrics and Business Statistics

This paper uses vector autoregressive (VAR) and Monte-Carlo simulation methods to examine the potential gains for forecasting accuracy and uncertainty estimation of two commonly used restrictions in economic relationships The authors investigate the performance of standard and modified information criteria in selecting lag length for co-integrated VARs with SCCF restrictions They also give a comparison of forecasting accuracy of fitted VARs when co-integration restrictions are imposed and when co-integration and SCCF restrictions are imposed together The authors suggest a new estimation algorithm where short and long term restrictions interact to predict the co-integrating and co-feature spaces There are three main results in this study First there is high cost in terms of model selection if SCCF restrictions are ignored Second the forecasting performance of restricted VECM is superior to that of VECM Finally new algorithm suggested performs well in terms of parameter estimation even for estimation of long-term parameters Keywords reduced rank models model selection criteria forecasting accuracy Available at httpbibliotecadigitalfgvbrdspacebitstreamhandle104383581823pdfjsessionid=7CCC1513AEFE077D2AB73E407A32A37Fsequence=1

Hallegatte Steacutephan Henriet Fanny Corfee M Jan 2011 The Economics of Climate Change Impacts

and Policy Benefits at City Scale A Conceptual Framework Climatic Change 104 51ndash87

This study presents a methodological framework to evaluate the economic impact of climate change in cities The paper focuses on model-based analysis of future scenarios and also includes a structuring of uncertainty for these projections The study points out the main difficulties in evaluation and the tools and methods used in assessment Also that many challenges are unique to evaluation of climate change impact and others are specific to working at local scales Keywords cities climate change Available at httplinkspringercomarticle1010072Fs10584-010-9976-5

Jurado Kyle Ludvigson Sydney C Ng Serena 2013 Measuring Uncertainty Working Paper

This paper presents new econometric measures of uncertainty and links them to macroeconomic activity They use a measure of uncertainty that has three main aspects First a forecasting model with predictors that covers a rich information set Second a stochastic

Northwest Economic Research Center July 2013

39

volatility model for the forecast innovation errors Third a measure of macro uncertainty given by uncertainty factors that is common in individual measures of uncertainty across a large number of economic time series The uncertainty factors include three major periods of macro uncertainty in the post war period the 1973-74 and 1981-82 recessions and the Great Recession of 2007-09 In comparison to stock market volatility estimated uncertainty factors accounted for than double the variance in one-year ahead forecast errors for both industrial production and hours from a typical vector autoregression Keywords uncertainty volatility

Available at httpwwweconnyueduuserludvigsonsvolpdf

Lundmark Linda Pashkevich Almina Jansson Bruno Wiberg Ulf 2007 Effects of Climate Change and

Extreme Events on Communities in the European North Climatic Change 87 235-249 This study attempts to quantify the potential effect of extreme events as well as vulnerability to short term hazards on the forest industry in Norrbotten Lappi and Arkhangelsk of Sweden Finland and Russia respectively The research is specifically interested in employment and uses a modified multiplier model An extreme weather related scenario would result in large economic losses which could be partially mitigated with by anticipatory measures Keywords extreme climate events employment forest sector Available At httplinkspringercomcontentpdf1010072Fs10584-007-9343-3pdf

Newbold Stephen C Daigneault Adam 2009 Climate Response Uncertainty and the Benefits of Greenhouse Gas Emissions Reductions Environmental and Resource Economics 44 351-377 Research has suggested that the degree of uncertainty in climate forecast models could be a more important factor than the selection of the discount rate The authors run multiple simulations that demonstrate the effect of uncertainty on long-term estimates They conclude that the willingness-to-pay of a representative agent increases with the level of uncertainty The risk premium paid by the agent is sensitive to the definition of upper bound temperatures as well as the specification of the damage function Keywords climate change climate sensitivity uncertainty catastrophe Available At httpideasrepecorgakapenreecv44y2009i3p351-377html

Papaefthymiou George Pinson Pierre 2008 Modeling of spatial dependence in wind power forecast

uncertainty Probabilistic Methods Applied to Power Systems Proceedings of the 10th International Conference

This study outlines a method that allows for interdependent scenarios of wind generation for spatially distributed wind power production for specific times in the future The method is applied to western Denmark which is split in 5 zones Keywords wind power uncertainty probabilistic forecasting Monte-Carlo simulation stochastic dependence multivariate Normal transformation scenarios Available at httpieeexploreieeeorgstampstampjsptp=amparnumber=4912606

Northwest Economic Research Center July 2013

40

Sousa Joatildeo Portugal Banco de Sousay Ricardo M 2011 Asset Returns Under Model Uncertainty Evidence from the Euro Area the UK and the US Nuacutecleo de Investigaccedilatildeo em Poliacuteticas Econoacutemicas Working Paper

This paper examines future asset return predictability in the context of model uncertainty The results show that using data from the US and UK forecasts of stock returns can be improved using a Bayesian Model Averaging (BMA) approach Empirical evidence indicates that many macroeconomic financial macro-financial variables are important determinants of risk premium For US only a few predictors play an important role whereas for UK financial variables are important predictors of stock returns This study points out that BMA approach has a strong predictive ability at longer periods and outperforms the constant expected returns and the autoregressive benchmark models Keywords stock returns model uncertainty bayesian model averaging Available at httpwwwbportugalpten-USBdP20Publications20Researchwp201119pdf

Stern Nicholas 2008 The Economics of Climate Change The American Economic Review

Vol 98 No 2 Paper and Proceedings of the One Hundred Twentieth Annual Meeting of the American Economic Association Pg 1-37 This paper is the transcript of a lecture covering the proper methodology for estimating the long-term economic effects of climate change Stern stresses that temperature rises are only important insomuch as they correspond to sea-level rises extreme weather and other negative impacts Impact sensitivities are summarized It is shown that the optimal discount rate varies based on a number of assumptions including how risks are weighted Keywords stern review uncertainty modeling policy Available At httpwwwjstororgstable29729990

Tol Richard SJ 2012 On the Uncertainty About the Total Economic Impact of Climate Change

Environmental Resource Economics 53(1) 97-116 This paper estimates the probability density function of the total economic impact of climate change as a parabolic function of global warming A vote-counting procedure is used in the estimation to allow for a wide range of uncertainty The estimates found that the impacts of climate change do follow a parabolic shape The research estimates the social cost of carbon to be $29tC in 2015 and rises to $379tC by 2215 though future uncertainty provides an extremely wide confidence interval in distant future estimates In general the social cost of carbon rises at about 2 per year Keywords climate change economic impact social cost Available At httplinkspringercomarticle1010072Fs10640-012-9549-3page-1

Vere-Jones David 1995 Forecasting Earthquakes and Earthquake Risk International Journal of

Forecasting 11 503-538

This study is a review of methodologies for predicting earthquake and risks associated with it with an emphasis on statistical methods that quantify probability of earthquake occurring within specified time

Northwest Economic Research Center July 2013

41

Keywords earthquake prediction seismic hazards point process modeling conditional intensity models probability forecasting Available at httpwebdocsubgwdgdeebookserienemonash_univwp6-08pdf

Northwest Economic Research Center July 2013

42

Other Bauer Nico Brecha Robert J Luderer Gunnar 2012 Economics of Nuclear Power and Climate Change

Mitigation Policies

The study uses an energy economy model framework to do a systematic analysis of nuclear power policies Such an analysis including early retirement of existing nuclear power plants has been missing in the climate change mitigation literature The results show that early retirement of nuclear power plants leads to discounted cumulative global GDP loss of 007 by the year 2020 Also the losses will double if new nuclear investments are excluded The climate policies have a greater impact than policies that restrict the use of nuclear power The intertemporal carbon budget results in a discounted cumulative global GDP loss of 064 by 2020 Keywords early retirement carbon budget Available at httpwwwpnasorgcontentearly201209271201264109

Ahn Soeun De Steiguer Joseph E Palmquist Raymond B Holmes Thomas P 2000 Economic Analysis

of the Potential Impact of Climate Change on Recreational Trout Fishing in the Southern Appalachian Mountains An Application of a Nested Multinomial Logit Model Climatic Change 45 493ndash509

This study analyzes the economic impact of climate change on recreational trout fishing in the Southern Appalachian Mountains of North Carolina The study estimates the potential welfare loss of trout anglers due to global warming using a nested multinomial logit model Keywords economic impact trout logit Available at httplinkspringercomarticle1010232FA3A1005511627247page-1

Grenzeback Lance R Lukmann Andrew T Case Study of the Transportation Sectorrsquos Response to and

Recovery from Hurricanes Katrina and Rita Cambridge Systematics Inc

This report looks at the transportation sectorrsquos response to the Hurricanes Katrina and Rita and recovery from them This study lists the destruction to the road rail waterborne pipeline and air transportation system of the Gulf Coast from Hurricanes Katrina and Rita It highlights the measures that were taken and that still have to be taken to reinstate the transportation infrastructure of the region and also reports estimated time and cost Keywords hurricane gulf coast Available at httpwwwarddorgLIBRARYDISASTER20RECOVERYCase_Study_Katrinatransportationpdf

Karagyozov Kiril RazmovTodor Todorova Mirena Varadinova Julia Dzhaleva C Anna 2012 Impact

of Natural Disasters on Transport Systems ndash Case Studies from Bulgaria Report from the International Panel of the WEATHER project funded by the European Commissionrsquos 7th framework programme

This report analyzes the impact of natural disasters on transportation systems in Bulgaria The main problem in Bulgaria is related to floods due to inefficient management of dams that

Northwest Economic Research Center July 2013

43

overflow after intense rainfall and snow melting The flood in July 2005 caused a loss of $274 million The second flood in the same year in August caused a loss of $200 million The government authorities have not increased the prevention measures against natural disasters Keywords floods loss transportation systems Available at httpwwwweather-projecteuweatherdownloadsDeliverablesWEATHER-IP_BG-Karagyozov_pubpdfWSESSIONID=b5f600b222266cb1f37de607ec480a8a

Kim Tschangho John Ham Heejoo Boyce David E 2002 Economic Impacts of Transportation Network

Changes Implementation of a Combined Transportation Network and Input-Output Model Papers in Regional Science 81 223ndash246

This study analyzes the economic impacts from a catastrophic earthquake at regional and national level The analytical frameworks used are a multi-regional input-output model and a regional commodity flow model The results of the model can be used to identify critical sections in the transportation network and examine post-earthquake reconstruction strategies In particular the information can be used in policy making to reduce damage from a possible earthquake by reinforcing existing critical bridges roads and railroads and by planning to construct new transportation network sections for strengthening the existing transportation network Keywords economic impacts of transportation changes transportation network changes input-output analysis earthquake impacts on transportation costs

Available at httpideasrepecorgasprpresciv81y2002i2p223-246html

Mendelsohn Robert Linwood H 1998 Estimating the Economic Impact of Climate Change on the

Freshwater Sports Fisheries of the Northeastern USLand Economics 74 (4) 483

This study uses global climate models ecological models of fish catch rates and economic models to see the impact of global warming on freshwater sport fishing in the northeastern US The results of the linear random utility model (RUM) estimate the range of net effects from a $46 million loss to a $204 million benefit depending on the climate scenario Keywords global warming random utility model Available at httpwebebscohostcomehostpdfviewerpdfviewersid=9781dbda-d078-46b3-93f7-ec0b5c57327b40sessionmgr10ampvid=2amphid=25

Schmidhuber Josef Tubiello Francesco 2007 Global Food Security under Climate Change Proceedings

of the National Academy of Sciences of the United Stated of America 104(50) 19703-19708

This study is a review of the potential impact of climate change on food security Existing simulation studies only address one of the four elements of food security ie availability However climate change will affect all four aspects of food security namely availability (production and trade) access to food stability of food and food utilization All qualitative analysis indicates that climate change will have an adverse effect on food security the severity depending on the socio-economic development of a country It appears that climate change will make the developing countries more dependent on imports and increase the focus on food security in sub-Saharan Africa and to a lesser degree on South Asia The quantitative analysis does not tell much about the impact of climate change on stability and utilization Nonetheless

Northwest Economic Research Center July 2013

44

socio-economic development will be a critical determinant of food utilization in the long run The study also discusses the strengths and weaknesses of the current studies and proposes improvements and avenues for new assessment Keywords hunger vulnerability food supply Available at httpwwwpnasorgcontent1045019703fullpdf

Washington State Transportation Commission and the Washington State Department of Transportation

2006 Washington Transportation Plan 2007-2026

This report using current data identifies the need for transportation investment of $67 billion This investment over the next 20 years will build the statersquos economy meet the social needs of citizens and enhance personal health and safety Since there is a $38 billion shortfall in meeting the proposed investment budget the report presents investment guidelines that set priorities for future spending The report also makes several policy recommendations for other areas Keywords transportation investment policy recommendations Available at httpwwwwsdotwagovNRrdonlyres083D185B-7B1F-49F5-B865-C0A21D0DCE320FinalWTP111406pdf

Northwest Economic Research Center July 2013

45

FUTURE WORK Urban Development-

There is a need for more integrated and systemic methods to deal with climate change as a part of the urban development task

There is a need to evaluate the economic impacts of climate change and response policy at local scale

Transportation-

Further research is needed to find methods to incorporate disruption costs in the economic evaluation of freight transportation projects

Further research is needed to do cost-benefit analysis of retrofit policies for longer time periods

Future research must not consider regional final demand as fixed Instead the response of regional final demands to the catastrophic events should be estimated

Agriculture-

In future research the lsquodumb farmerrsquo assumption commonly should be substituted by endogenous adaptation responses

Health-

Future research should incorporate economic growth income distribution and changes in level of public expenditure on healthcare to gauge the effect of socio-economic changes and disease control variables on malaria prevalence

Distributional Impacts-

Further research is needed to identify the characteristics of low-income groups which will lose due to high fossil fuel energy use under lump-sum recycling arrangements

There is a need for research to examine the distributional impact of compensatory policies that may be required to assist households in making a transition to low-impact lifestyles such as having home insulation microgeneration and public transport programs

There is a need to investigate the hurdles in adopting effective mitigation policies generating from power asymmetries and economic and political contexts

Research is needed to gauge whether steps to reduce regressive impacts will be more effective if they assist people in making practical transitions towards a low carbon future rather than income alone

Other-

To have a better measure of the vulnerability level to natural disasters in countries that are severely affected by tropical cyclones future work should incorporate variables such as infant mortality rates as a proxy for the level of development

Northwest Economic Research Center Post Office Box 751 Portland Oregon 97207

College of Urban amp Public Affairs Portland State University Urban Center 506 SW Mill Street

Portland Oregon 97201

wwwpdxedunerc

nercpdx

Northwest Economic Research Center Post Office Box 751 Portland Oregon 97207

College of Urban amp Public Affairs Portland State University Urban Center 506 SW Mill Street

Portland Oregon 97201

wwwpdxedunerc

nercpdx