123449855 introductory econometrics chapter 1 ppt
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8/10/2019 123449855 Introductory Econometrics Chapter 1 Ppt
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Welcome to Econometrics
Introduction
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Why study Econometrics?
An empirical analysis uses data to test atheory or to estimate a relationship
A formal model can be tested
Theory may be ambiguous as to the effectof some policy change – can useeconometrics to evaluate the program
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Steps in Empirical Analysis
Careful formulation of the question ofinterestEconomic Model or Informal Economic
Intuition or ReasoningTurn an Economic Model into anEconometric ModelState Hypothesis of Interest
DataEstimationTesting of Hypothesis
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Types of Data – Cross Sectional
Cross-sectional data is a random sample
Each observation is a new individual, firm,
etc. with information at a point in time
If the data is not a random sample, we have
a sample-selection problem
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Types of Data – Cross Sectional
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Types of Data – Cross Sectional
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Types of Data – Time Series
Time series data has a separate observation
for each time period – e.g. stock prices
Since not a random sample, different
problems to consider
Trends and seasonality will be important
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Types of Data – Time Series
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Types of Data – Pooled Cross-
sections and Panel
Can pool random cross sections and treat
similar to a normal cross section – known as
pooled cross-sections data. Will just needto account for time differences.
Can follow the same random individualobservations over time – known as panel
data
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Types of Data – Pooled Cross-
sections
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Types of Data – Panel
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The Question of Causality
Simply establishing a relationship between
variables is rarely sufficient
Want to the effect to be considered causal
If we’ve truly controlled for enough other
variables, then the estimated ceteris paribus
effect can often be considered to be causalCan be difficult to establish causality
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Example: Returns to Education
A model of human capital investment implies
getting more education should lead to higher
earnings
In the simplest case, this implies an equation like
ueducation Earnings 10
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Example: (continued)
The estimate of 1, is the return to
education, but can it be considered causal?
While the error term, u, includes otherfactors affecting earnings, want to control
for as much as possible
Some things are still unobserved, whichcan be problematic