Econometric analysis of panel data
This presentation is the property of its rightful owner.
Sponsored Links
1 / 25

Econometric Analysis of Panel Data PowerPoint PPT Presentation


  • 93 Views
  • Uploaded on
  • Presentation posted in: General

Econometric Analysis of Panel Data. Panel Data Analysis Fixed Effects Dummy Variable Estimator Between and Within Estimator First-Difference Estimator Panel-Robust Variance-Covariance Matrix Heteroscedasticity and Autocorrelation Cross Section Correlation Hypothesis Testing

Download Presentation

Econometric Analysis of Panel Data

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Econometric analysis of panel data

Econometric Analysis of Panel Data

  • Panel Data Analysis

    • Fixed Effects

      • Dummy Variable Estimator

      • Between and Within Estimator

      • First-Difference Estimator

      • Panel-Robust Variance-Covariance Matrix

        • Heteroscedasticity and Autocorrelation

        • Cross Section Correlation

    • Hypothesis Testing

      • To pool or Not to pool


Panel data analysis

Panel Data Analysis

  • Fixed Effects Model

    • ui is fixed, independent of eit, and may be correlated with xit.


Fixed effects model

Fixed Effects Model

  • Classical Assumptions

    • Strict Exogeneity

    • Homoschedasticity

    • No cross section and time series correlation


Fixed effects model1

Fixed Effects Model

  • Extensions

    • Weak Exogeneity


Fixed effects model2

Fixed Effects Model

  • Extensions

    • Heteroschedasticity


Fixed effects model3

Fixed Effects Model

  • Extensions

    • Time Series Correlation (with cross section independence for short panels)


Fixed effects model4

Fixed Effects Model

  • Extensions

    • Cross Section Correlation (with time series independence for long panels)


Dummy variable model

Dummy Variable Model

  • Dummy Variable Representation

    • Note: X does not include constant term, otherwise one less number of dummy variables should be used.


Dummy variable model1

Dummy Variable Model

  • Dummy Variable Estimator (LSDV)

  • Heteroscedasticity and Autocorrelation


Dummy variable model2

Dummy Variable Model

Panel-Robust Variance-Covariance Matrix


Within model

Within Model

Within Model Representation


Within model1

Within Model

Model Assumptions


Within model2

Within Model

  • Within Estimator: FE-OLS


Within model3

Within Model

  • Within Estimator: GLS

  • GLS = FE-OLS

    • Note:


Within model4

Within Model

  • Normality Assumption


Within model5

Within Model

Log-Likelihood Function

ML Estimator


Within model6

Within Model

ML Estimator of e2 is downward biased even for large N:

For balanced panel (T=Ti: ), e2 should be estimated as:


Within model7

Within Model

  • Estimated Fixed Effects

    • For , is consistent but is inconsistentunless .


Within model8

Within Model

  • Panel-Robust Variance-Covariance Matrix

    • Consistent statistical inference for general heteroscedasticity, time series and cross section correlation.


First difference model

First-Difference Model

  • First-Difference Representation

  • Model Assumptions


First difference model1

First-Difference Model

  • First-Difference Estimator: FD-OLS

  • Consistent statistical inference for general heteroscedasticity, time series and cross section correlation should be based on panel-robust variance-covariance matrix.


First difference model2

First-Difference Model

  • First-Difference Estimator: GLS


Hypothesis testing

Hypothesis Testing

  • To Pool or Not to Pool?

    • F-Test based on dummy variable model: constant or zero coefficients for D w.r.t F(N-1,NT-N-K)

    • F-test based on fixed effects (unrestricted) model vs. pooled (restricted) model


Hypothesis testing1

Hypothesis Testing

  • Heteroscedasticity

  • Serial Correlation

  • Spatial Correlation


Example investment demand

Example: Investment Demand

  • Grunfeld and Griliches [1960]

    • i = 10 firms: GM, CH, GE, WE, US, AF, DM, GY, UN, IBM; t = 20 years: 1935-1954

    • Iit = Gross investment

    • Fit = Market value

    • Cit = Value of the stock of plant and equipment


  • Login