This workbook is based upon the content of the RATS e-course on Panel and Grouped Data, offered in spring 2012. While it covers the basic techniques of panel data econometrics, the emphasis is on the "time-series" aspects, with Dynamic Panels (Chapter 7), Unit Root Tests (Chapter 9), Cointegration (Chapter 10) and VAR's (Chapter 13). It also includes several examples of the use of Gibbs sampling for panel data including linear and non-linear random effects in Chapter 11 and random coefficients models in Chapter 12 and applied to VAR's in Chapter (13).

This makes use of a number of important features for dealing with panel data added with RATS versions 8 and 8.1. The improvements to the core instructions PREGRESS, PANEL and PFORM provide greater flexibility for dealing with both panel and general grouped data.

(195 pages, 18 examples)

1.2 Panel vs Grouped Data

1.3 Balanced vs Unbalanced Panels

1.4 PANEL date scheme

2.2 Changing the Blocking

2.3 Mixed Time-Varying and Time-Invariant Data

3.2 PANEL

3.3 SWEEP

3.4 PSTATS

3.5 BOOT and Bootstrapping

3.6 LWINDOW=PANEL and Clustered Standard Errors

4.2 Balanced vs Unbalanced Samples

4.3 Implementing with RATS

4.4 Testing Fixed Effects

4.5 METHOD=BETWEEN

5.2 Estimating the Component Variances

5.3 Using RATS

5.4 Hausman Test

5.5 Direct Calculation of Component Variances

5.6 Random Effects Transformations

6.2 Using RATS

6.3 Hausman Tests

6.4 PANEL instruction

7.2 The Examples

7.3 First Difference Instrumental Variables Estimators

7.4 Expanded Instrument Sets

7.5 Bias Correction

8.2 Probit and Logit Models

8.2.1 Conditional (Fixed Effects) Logit

8.2.2 Random Effects Probit

9.2 Levin-Lin-Chu test

9.3 Harris-Tzavalis Test

9.4 Im-Pesaran-Shin Test

9.5 Breitung Test

9.6 Hadri Test

10.2 Estimation with Heterogeneous Cointegrating Vectors

10.2.1 Fully-Modified Least Squares

10.2.2 Dynamic OLS

10.3 Estimation with Homogeneous Cointegrating Vectors

10.3.1 Mark and Sul DOLS

10.3.2 Pesaran-Shin-Smith Pooled Mean Group

11.2 Random Effects Probit

11.3 Bootstrapping

12.2 Swamy Random Coefficients Models

12.3 MCMC Estimation for Random Coefficients

13.2 Shrinkage Estimators, Univariate Autoregressions

13.3 Shrinkage Estimators, VAR's

13.4 Causality Tests

A.1.1 Wallace-Hussain (OLS-based)

A.1.2 Amemiya or Wansbeek-Kapteyn (Fixed Effects-based)

A.1.3 Swamy-Arora (Fixed and Between)

A.2 Two-Way Effects

A.2.1 Wallace-Hussain

A.2.2 Amemiya (Fixed Effects-based)

A.2.3 Swamy-Arora (Fixed and Between)

C.2 Univariate Normal

C.3 Multivariate Normal

C.4 Gamma Distribution

C.5 Inverse Gamma Distribution

C.6 Wishart Distribution