PanelDataFinal2010 - Department of Economics Econometric...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Econometric Analysis of Panel Data Professor William Greene Phone: 212.998.0876 Office: KMC 7-90 Home Email: [email protected] URL for course web page: Final Examination: Spring 2010 This is a ‘take home’ examination. Today is Tuesday, April 27, 2010. Your answers are due on Friday, May 7, 2010. You may use any resources you wish – textbooks, computer, the web, etc. – but please work alone and submit only your own answers to the questions. The six parts of the exam are weighted as follows: Part I. The Hausman and Taylor Estimator 10 Part II. Panel Data Regressions 20 Part III. Instrumental Variable and GMM Estimation 10 Part IV. Binary Choice Models 20 Part V. Sample Selection 20 Part VI. A Loglinear Model 20 Note, in parts of the exam in which you are asked to report the results of computation, please filter your response so that you present the numerical results as part of an organized discussion of the question. Do not submit long, unannotated pages of computer output. Part I. (Continuing the tradition) The Hausman and Taylor Estimator Write out a full statement of the procedure that Hausman and Taylor devised for estimation of the parameters in a panel data model in which some independent variables are correlated with the time invariant part of the disturbance in a random effects model. Now, show how the Arellano/Bond/Bover estimator uses the Hausman and Taylor result. Department of Economics
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Part II. Panel Data Regressions The course website contains the following data file as well in the form of an Excel spreadsheet file, .xls format and a limdep/nlogit project file, .lpj format. The data in the file are a balanced panel on the following variables for 37 Swiss railroads observed in 13 years: id = identifying number of railroad year = 85 – 97, years 1985 to 1997 logcost = log of total cost logq1 = log of passenger output logq2 = log of freight output logpk = log of capital price logpl = log of labor price logpe = log of electricity price. tunnel = time invariant dummy variable indicates if railroad route includes long tunnels Do this exercise with Stata, R, LIMDEP (or NLOGIT ), or any other software you wish to use. The basic model of interest is Y it = β 1 X1 it + β 2 X2 it + β 3 X3 it + β 4 X4 it + β 5 X5 it + c i + ε it (1) Where Y is logcost, X1 is logq1, X2 is logq2, X3 is logpk, X4 is logpl and X5 is logpe. This is a Cobb- Douglas cost function. a. Fit the “pooled” model and report your results. (Note, the pooled and random effects models must also contain a constant term.) b. Fit a random effects model and a fixed effects model. Use your model results to decide which is the preferable model. If you find that neither panel data model is preferred to the pooled model, show how you reached that conclusion. As part of the analysis, test the hypothesis that there are no “railroad
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 01/05/2012 for the course B 55.9912 taught by Professor Willamgreene during the Fall '11 term at NYU.

Page1 / 7

PanelDataFinal2010 - Department of Economics Econometric...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online