The Forecasting and Policy Analysis System (FPAS):
Application to PNG
Nikhil Vellodi, Bank of Papua New GuineaPFTAC Workshop, Apia, Samoa,
15th-23rd November, 2011, “Improving Analytical Tools for Better
Understanding”
2
Introduction Part I: Theory
◦ Model Description.◦ Solving and Estimating the Model.
Part II: Application to PNG◦ The PNG Database.◦ Impulse Response Functions and Historical
Decompositions.◦ Drawbacks, Things to Work on.
Conclusion
Outline of Presentation
Introduction 3
What is an FPAS model? How and where are they used? How do they relate to the current workshop
objectives?
Introduction
Introduction 4
Small macroeconomic model. Built at the IMF: Berg, Karam and Laxton, 2006, “A
Practical Model-Based Approach to Monetary Policy Analysis: A How-To Guide”, IMF Working Paper 06/81.
Similar to many workhorse models used at central banks. Mainly differs in the estimation technique.
Blends New Keynesian theory with DSGE modeling.◦ No explicit microfoundations, as in a DSGE model.◦ Uses IS/LM approach to aggregate demand and supply
Price stickiness in the short-run and demand equation/price setting equation.
◦ Demand and price-setting equations taken from New Keynesian Theory. Phillips Curve and Output Gap equations broadly derived from Calvo
(1982) price setting rules.
What is an FPAS Model?
Introduction 5
Used for forecasting and monetary policy analysis.
Mainly short-medium term forecasting. Both qualitative and quantitative analysis.◦Calibration and estimation, using actual
data, rather than pure calibration as for DSGE or CGE models.
Explicitly models the monetary transmission mechanism.
Mainly used in central banks and other financial economic institutions.
How and where are they used?
Introduction 6
Provide thorough yet concise analysis of current macroeconomic conditions, and implications for policy going forward.
Draw together key macroeconomic variables, such as the monetary and fiscal policy stances, the real exchange rate, the output gap, inflation and the real interest rate, all of which will be discussed in detail over the course of the workshop.
How do they relate to the workshop objectives?
Part I: Theory 7
The Model Description for PNG. Solving the model. Estimating the model.
Part I: Theory
Part I: Theory: The Model Description
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Overview of Model Structure◦ Global economy split into Home and Rest of
World. External conditions are a major determinant of
domestic conditions, especially for small, open economies.
◦ Six main equations govern each region: Aggregate Demand equation (Output Gap equation). Price-setting equation (Phillips Curve). Exchange Rate equation (Uncovered Interest Parity
condition). Monetary policy reaction function (Taylor Rule). Fiscal policy reaction function (Fiscal Balance
equation). Non-mineral revenue equation.
The Model Description
Part I: Theory: The Model Description
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The Output Gap Equation
The Output Gap equation describes the determinants of aggregate demand.
Output is determined by past and future output, as well as the real interest rate, the real exchange rate, real commodity prices, the non-mineral fiscal balance and world output.
Part I: Theory: The Model Description
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The Phillips Curve
The Phillips Curve describes the trade-off between prices and output.
An increase in the output gap implies a build-up of demand pressures, which lead to inflation.
Core inflation is determined by past and future core inflation, the past output gap and lagged headline inflation.
Part I: Theory: The Model Description
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The Uncovered Interest Parity Condition
The Interest Parity Condition links the real exchange rate with the real interest rate.
An increase in the domestic real interest rate, ceteris paribus, leads to capital inflows, and hence an appreciation of the real exchange rate.
The real exchange rate is determined by the future real exchange rate, the difference between domestic and world interest rates and the domestic risk premium on investment.
Part I: Theory: The Model Description
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The Taylor Rule
The Taylor Rule describes the manner in which monetary policy is conducted.
In response to an increase in inflation, the central bank raises the nominal interest rate, in order to reduce demand and hence inflation.
The nominal interest rate is determined by the past rate, the real interest rate, core inflation, future deviations of core inflation from trend and the output gap.
Part I: Theory: The Model Description
13
The Fiscal Balance Equation
The fiscal balance equation describes what determines the profile of government spending and saving.
An increase in the output gap correlates with increased government revenue, increases in commodity prices increases revenue through export receipts and dividend payments.
The fiscal balance is determined by the past balance, past output and past commodity prices.
Part I: Theory: The Model Description
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The Non-mineral Revenue Equation
The non-mineral revenue equation was inserted to allow a richer description of the role of non-mineral revenue in the model.
By separating the fiscal balance into both revenue and price effects, we can directly shock the revenue term, rather than just the commodity price term.
Part I: Theory: The Model Description
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Additional Equation: Headline and Core Inflation
Simply links core and headline inflation.
Part I: Theory: Solving the Model 16
In a couple of stages…1. Find the “steady-state” solution.
Variables have settled on constant values in time. To find SS, drop the t subscripts, since values same from one
period to next. e.g. yt, yt+1, yt-1 all become y.
Not unique. Many SS solutions may exist.2. Determine dynamic properties. “Two-point boundary”
technique. Pick two SS solutions. Then the dynamic solution is the path
traced by the variables in getting from one to the other. Impulse response functions similar technique.
Start at one SS solution, perturb one shock variables, and see how the model returns to equilibrium (may be same or different from starting point).
Solving the model
Part I: Theory: Estimating the Model
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Bayesian Estimation Techniques.◦ Simply application of Bayes’ Rule:
◦ Start with a prior assumption on parameter distributions, before data is analysed (Pr(M).
◦ Use likelihood function (Pr(D|M) )/Pr(D)) to generate posterior (Pr(M|D)). This is the impact of the data on the choice of the model.
◦ Modeling rationale for using Bayesian estimation. Formation of priors goes hand-in-hand with economic
understanding. Choosing the initial values for the parameters requires an intuition for their role in the economy.
Estimating the Model
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The PNG Database. Impulse Response Functions. Historical Decompositions. Drawbacks of FPAS model. Things to Work on.
Part II: Application to PNG
The PNG Database 19
The PNG Database
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q3
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
Non-mineral real GDP output gap (HP, 1600)
The PNG Database 20
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q3
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
-5
0
5
10
15
20
25
Output Gap and Core Inflation (Y-o-Y, Annual Rate, Right Axis)
Non-mineral real GDP output gap (HP, 1600) Core CPI, Change y-o-y annual rate
The PNG Database 21
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q30.00
5.00
10.00
15.00
20.00
25.00
Mineral Revenue in % non-mineral GDP
The PNG Database 22
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q3-10.00
-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
8.00
10.00
Deviation of Non-Mineral Deficit from MTFS Target in % of Non-mineral GDP (+ Fiscal Expansion)
Deviation of fiscal expenditures from MTSF norm in % of nonmin GDPDeviation of nonmineral revenues from long-run trend in % of nonmin GDP (+ expansionary fiscal policy/revenue shortfall re-lative to trend)Deviation of nonmineral fiscal deficit from MTFS target in % of nonmin GDP (+ expansionary fiscal policy)
The PNG Database 23
1997
Q1
1997
Q3
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q3
-10
-5
0
5
10
15
20
25
Nominal and Real Interest Rates (commercial lend-ing rates, weighted average total advances)
Commercial lending rates (weighted Average Total Advances)
Real lending rate (core, y-o-y)
The PNG Database 24
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q3
-20
-15
-10
-5
0
5
10
15
Deviation of Real Effective Exchange Rate from Trend in % (+ Depreciation)
The PNG Database 25
1998
Q1
1998
Q3
1999
Q1
1999
Q3
2000
Q1
2000
Q3
2001
Q1
2001
Q3
2002
Q1
2002
Q3
2003
Q1
2003
Q3
2004
Q1
2004
Q3
2005
Q1
2005
Q3
2006
Q1
2006
Q3
2007
Q1
2007
Q3
2008
Q1
2008
Q3
2009
Q1
2009
Q3
2010
Q1
2010
Q3
2011
Q1
2011
Q30
50
100
150
200
250
Commodity Price Index (in US$ and in DC, real terms)
Commodity Price Index, 2005 = 100, includes both Fuel and Non-Fuel Price IndicesReal Commodity Price Index (Index expressed in Kina, divided by PNG Headline CPI), 2005=100
Impulse Response Functions 26
Selected charts.◦ Shocks to domestic demand and non-mineral .◦ Charts generated from prior distributions.
Not using the posterior distributions generated via estimation.
Impulse Response Functions
Impulse Response Functions 27
Shock to the Output Gap
Impulse Response Functions 28
Shock to nonmin fiscal balance
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For a given equation, demonstrates the relate explanatory power of each variable throughout the sample period.
E.g. for the output gap, gives a reasonably clear and thorough impression of what the model thinks is driving demand conditions in the PNG economy.
Historical Decomposition
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Historical Decomposition: The Output Gap
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The Chart tells a compelling story of PNG’s macroeconomic history over the last decade…◦ The global financial crisis clearly hit demand,
through an appreciation in the real exchange rate and external demand conditions, but a fiscal spending stimulus compensated, keeping the output gap almost at zero.
◦ In the years leading to that, there had been a period of fiscal tightening, which had a negative effect on demand.
◦ The real interest rate goes through periods of being more or less significant. E.g. there was a large decline in real lending rates
around the crisis (2008), which had a stimulating effect on demand.
Historical Decomposition: The Output Gap
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What it doesn’t talk about. ◦Aggregate supply, current account.
These are captured indirectly through the other endogenous variables.
Modeling changes in supply through potential output is difficult. Too computational intensive, couldn’t estimate
the model. May require more explicit microfoundations, with
sectors, etc. Technical requirements
◦Have to leave model estimation running overnight!
Sensitivity to priors
Drawbacks of the FPAS Model
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Elaborating the inflation process◦ May split inflation into imported and domestic.
There have been secular shifts in the causes of inflation over the last decade.
Refining the transmission mechanism.◦ Spread between commercial lending rates and OMO rates
large and erratic. Employing one interest rate to act as both the Bank signaling
rate and the domestic demand determining rate may be infeasible.
Could use two separate rates, and add an equation linking the two.
Revisiting the sample period.◦ Was there a trend break in fiscal policy in the early 2000s?
Things to work on
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How does the FPAS fit in with PNG and the other South Pacific Islands?◦ Compliments larger DSGE model, both in terms of time-
frame and explanatory power. DSGE model has sectoral elaboration, models supply side in
greater depth. Operates over the medium-long term. Qualitative analysis only.
Calibration only, no data or estimation involved.
◦ Just building the model is useful in itself. Compiling the database puts the user in touch with key data
series. Calibrating priors forces user to think about how key variables
interact.
◦ Point towards which all of the current work is leading.
Conclusion
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THANK YOU!