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Econometric Analysis of Panel Data

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Econometric Analysis of Panel Data Panel Data Analysis: Extension Generalized Random Effects Model Seemingly Unrelated Regression Cross Section Correlation – PowerPoint PPT presentation

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Title: Econometric Analysis of Panel Data


1
Econometric Analysis of Panel Data
  • Panel Data Analysis Extension
  • Generalized Random Effects Model
  • Seemingly Unrelated Regression
  • Cross Section Correlation
  • Parametric representation
  • Spatial dependence defined by cross section
    contiguity or distance

2
Panel Data Analysis Extension
  • Generalized Random Effects Model

3
Panel Data Analysis Extension
  • Seemingly Unrelated Regression

4
Panel Data Analysis Extension
  • Cross Section Correlation
  • Unobserved heterogeneity fixed effects or random
    effects
  • OLS with robust inference
  • GLS allowing time serial correlation

5
Panel Data Analysis Extension
  • Cross Section Correlation
  • Parametric Representation

6
Panel Data Analysis Extension
  • Spatial Lag Variables
  • Spatial Weights

7
Panel Data Analysis Extension
  • Spatial Lag Model
  • OLS is biased and inconsistent
  • Unobserved heterogeneity fixed effects or random
    effects
  • Observed heterogeneity

8
Panel Data Analysis Extension
  • Spatial Error Model
  • Unobserved heterogeneity
  • Fixed effects
  • Random effects
  • Observed heterogeneity

9
Panel Data Analysis Extension
  • Spatial Panel Data Analysis
  • Model specification could be a mixed structure of
    spatial lag and spatial error model.
  • Unobserved heterogeneity could be fixed effects
    or random effects.
  • OLS is biased and inconsistent Consistent IV or
    2SLS should be used, with robust inference.
  • If normality assumption of the model is
    maintained, efficient ML estimation could be used
    but with computational complexity.
  • Efficient GMM estimation is recommended.

10
Panel Data Analysis Extension
  • Panel Spatial Model Estimation
  • IV / 2SLS / GMM
  • Instrumental variables for the spatial lag
    variable Wyt Xt, WXt, W2Xt,
  • W is a predetermined spatial weights matrix based
    on geographical contiguity or distance

11
Panel Data Analysis Extension
  • Space-Time Dynamic Model
  • Arellano-Bond estimator may be extended to
    include cross section correlation in the
    space-time dynamic models.

12
Example U. S. Productivity
  • The Model (Munnell 1988)
  • One-way panel data model
  • 48 U.S. lower states
  • 17 years from 1970 to 1986
  • Variables gsp (gross state output) cap (private
    capital) 3 components of public capital (hwy,
    water, util) emp (labor employment) unemp
    (unemployment rate)

13
Example U. S. Productivity
  • Spatial Panel Data Model
  • Cross Section Correlation
  • Cross section dependence is defined by state
    contiguity if state i is adjacent with state j,
    then wij1 otherwise wij0. The spatial weights
    matrix W is then row-standardized with diagonal
    0.
  • Pooled, fixed effects, random effects models are
    all biased and inconsistent. IV or 2SLS methods
    should be used with proper instruments.

14
Example U. S. Productivity
  • Spatial Panel Data Model
  • Space-Time Dynamics
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