Gretl User's Guide

1 Gretl User's Guide Gnu Regression, Econometrics and Time- series Library Allin Cottrell Department of Economics Wake Forest University Riccardo Jack Lucchetti Dipartimento di Economia Universit Politecnica delle Marche March, 2018. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version or any later version published by the Free Software Foundation (see ). Contents 1 Introduction 1. Features at a glance .. 1. Acknowledgements .. 1. Installing the programs.

2 2. I Running the program 3. 2 Getting started 4. Let's run a regression .. 4. Estimation output .. 6. The main window menus .. 7. Keyboard shortcuts .. 10. The Gretl toolbar .. 10. 3 Modes of working 12. Command scripts .. 12. Saving script objects .. 14. The Gretl console .. 14. The Session concept .. 15. 4 Data files 18. Data file formats .. 18. Databases .. 18. Creating a dataset from scratch .. 19. Structuring a dataset .. 21. Panel data specifics .. 23. Missing data values .. 26. Maximum size of data sets .. 27.

3 Data file collections .. 28. Assembling data from multiple sources .. 30. 5 Sub-sampling a dataset 31. Introduction .. 31. Setting the sample .. 31. Restricting the sample .. 32. i Contents ii Panel data .. 33. Resampling and bootstrapping .. 34. 6 Graphs and plots 36. Gnuplot graphs .. 36. Plotting graphs from scripts .. 40. Boxplots .. 42. 7 Joining data sources 44. Introduction .. 44. Basic syntax .. 44. Filtering .. 45. Matching with keys .. 46. Aggregation .. 48. String-valued key variables .. 49. Importing multiple series .

4 50. A real-world case .. 51. The representation of dates .. 53. Time- series data .. 54. Special handling of time columns .. 57. Panel data .. 57. Memo: join options .. 59. 8 Realtime data 62. Introduction .. 62. Atomic format for realtime data .. 62. More on time-related options .. 64. Getting a certain data vintage .. 64. Getting the n-th release for each observation period .. 65. Getting the values at a fixed lag after the observation period .. 66. Getting the revision history for an observation .. 67. 9 Special functions in genr 70.

5 Introduction .. 70. Long-run variance .. 70. Cumulative densities and p-values .. 70. Retrieving internal variables .. 71. The discrete Fourier transform .. 72. 10 Gretl data types 75. Introduction .. 75. Contents iii series .. 75. Scalars .. 76. Matrices .. 76. Lists .. 76. Strings .. 76. Bundles .. 77. Arrays .. 79. The life cycle of Gretl objects .. 81. 11 Discrete variables 84. Declaring variables as discrete .. 84. Commands for discrete variables .. 85. 12 Loop constructs 89. Introduction .. 89. Loop control variants.

6 89. Progressive mode .. 92. Loop examples .. 92. 13 User-defined functions 96. Defining a function .. 96. Calling a function .. 99. Deleting a function .. 99. Function programming details .. 100. Function packages .. 106. 14 Named lists and strings 107. Named lists .. 107. Named strings .. 112. 15 String-valued series 116. Introduction .. 116. Creating a string-valued series .. 116. Permitted operations .. 118. String-valued series and functions .. 120. Other import formats .. 121. 16 Matrix manipulation 123. Creating matrices.

7 123. Empty matrices .. 124. Selecting sub-matrices .. 125. Contents iv Deleting rows or columns .. 126. Matrix operators .. 126. Matrix scalar operators .. 128. Matrix functions .. 128. Matrix accessors .. 135. Namespace issues .. 137. Creating a data series from a matrix .. 137. Matrices and lists .. 137. Deleting a matrix .. 138. Printing a matrix .. 138. Example: OLS using matrices .. 139. 17 Calendar dates 140. Introduction .. 140. Calendrical functions .. 140. Working with pre-Gregorian dates .. 143. Year numbering.

8 144. 18 Cheat sheet 145. Dataset handling .. 145. Creating/modifying variables .. 147. Neat tricks .. 152. II Econometric methods 156. 19 Robust covariance matrix estimation 157. Introduction .. 157. Cross-sectional data and the HCCME .. 158. Time series data and HAC covariance matrices .. 159. Special issues with panel data .. 163. The cluster-robust estimator .. 164. 20 Panel data 166. Estimation of panel models .. 166. Autoregressive panel models .. 172. 21 Dynamic panel models 174. Introduction .. 174. Usage .. 177.

9 Replication of DPD results .. 179. Cross-country growth example .. 182. Contents v Auxiliary test statistics .. 184. Memo: dpanel options .. 185. 22 Nonlinear least squares 186. Introduction and examples .. 186. Initializing the parameters .. 186. NLS dialog window .. 187. Analytical and numerical derivatives .. 187. Advanced use .. 188. Controlling termination .. 189. Details on the code .. 189. Numerical accuracy .. 189. 23 Maximum likelihood estimation 192. Generic ML estimation with Gretl .. 192. Gamma estimation.

10 194. Stochastic frontier cost function .. 195. GARCH models .. 196. Analytical derivatives .. 199. Debugging ML scripts .. 201. Using functions .. 201. Advanced use of mle: functions, analytical derivatives, algorithm choice .. 204. 24 GMM estimation 209. Introduction and terminology .. 209. GMM as Method of Moments .. 210. OLS as GMM .. 213. TSLS as GMM .. 214. Covariance matrix options .. 216. A real example: the Consumption Based Asset Pricing Model .. 217. Caveats .. 220. 25 Model selection criteria 221. Introduction.