Econometric Analysis of Panel Data
Professor William Greene
Phone: 212.998.0876
Office: KMC
778
Home page:www.stern.nyu.edu/~wgreene
Office Hours:
TR, 3:00  5:00
Email: [email protected]
URL for course web page:
www.stern.nyu.edu/~wgreene/Econometrics/PanelDataEconometrics.htm
Final Examination: Spring 2009
This is a ‘take home’ examination.
Today is Friday, May 1, 2009.
Your answers are due on
Friday, May 15, 2009.
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.
Part II.
Panel Data Regressions
The course website contains Munnell’s data set on statewide production, in ASCII text form,
http://pages.stern.nyu.edu/~wgreene/Econometrics/productivity.txt
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 panel on the following variables for the lower 48 states, 17 years,
STATE = state name
YR = year, 1970,...,1986
P_CAP = public capital
Department of Economics
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HWY = highway capital
WATER = water utility capital
UTIL = utility capital
PC = private capital
GSP = gross state product
EMP = employment
UNEMP = unemployment rate
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
Where Y is logGSP, X1 is logPC, X2 is logHWY, X3 is logWATER,
X4 is logUTIL and X5 is
logEMP.
This is a CobbDouglas production function.
a.
Fit the “pooled” model and report your results
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 “state effects.”
c.
Assuming that there are “latent individual (state) effects,” the asymptotic covariance matrix that is
computed for the pooled estimator,
s
2
(
X′X
)
1
, is inappropriate.
What estimator can be computed for the
covariance matrix of the pooled estimator that will give appropriate standard errors?
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 Fall '11
 WillamGreene
 Econometrics, Regression Analysis, Maximum likelihood, Estimation theory, Random effects model

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