PanelDataProblemSet3 - Department of Economics Econometric...

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Econometric Analysis of Panel Data Professor William Greene Phone: 212.998.0876 Office: KMC 7-78 Home Email: [email protected] URL for course web page: Assignment 3 Part I. Instrumental Variable Estimation This exercise is based on Baltagi/Griffin’s gasoline demand model, which we extend to the folowing random effects model: log G i,t = β 1 + β 2 log Y i,t + β 3 log P i,t + β 4 log C i,t + β 5 log G i,t-1 + u i + ε i,t where G = per capita gasoline consumption, Y = income, P = price, C = cars per capita. (Use Baltagi’s gasoline data posted on the course web site, for the computations.) Note the appearance of the lagged value of the dependent variable. (1) Will the ordinary least squares estimator of β for this model be unbiased? Consistent? Efficient? Explain. (2) What about the GLS estimator? Consistent? Explain. (3) Estimate the model by OLS and report your results. (4) Estimate the model by FGLS, ignoring its dynamic nature, and report your results. (Note that a year of data is lost because of the presence of the lagged dependent variable.) (5) Suitable instruments for this model, using data within the model, might include a time trend and lagged values of income, price and cars per capita. What are the explicit assumptions which would justify this suggestion. (6)
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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.

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PanelDataProblemSet3 - Department of Economics Econometric...

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