Dougherty С. Introduction to Econometrics, 3Ed
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422 14: Introduction to Panel Data Models
22 = Sweden, 23 = Switzerland, 24 = Turkey, 25 = United Kingdom,
26 = United States. Four countries that have recently joined the OECD,
the Czech Republic, Hungary, Poland, and Slovakia, are excluded because
their data do not go back far enough.
ID01–26 These are individual country dummy variables. For example, ID09 is the
dummy variable for Greece.
E Average annual percentage rate of growth of employment for country i
during time period t.
G Average annual percentage rate of growth of GDP for country i during
time period t.
TIME There are three time periods, denoted 1, 2, and 3. They refer to average
annual data for 1971–80, 1981–90, and 1991–2000.
TIME2 Dummy variable defined to be equal to 1 when TIME = 2, 0 otherwise.
TIME3 Dummy variable defined to be equal to 1 when TIME = 3, 0 otherwise.
Perform a pooled OLS regression of E on G. Regress E on G, TIME2, and TIME3.
Perform appropriate statistical tests and give an interpretation of the regression
results.
14.2 Using the OECD2000 data set, perform a (within-groups) fixed effects regression
of E on G, TIME2, and TIME3. Perform appropriate statistical tests, give an
interpretation of the regression coefficients, and comment on R
2
.
14.3 Perform the corresponding LSDV regression, using OLS to regress E on G, TIME2,
TIME3, and the country dummy variables (a) dropping the intercept, and (b) drop-
ping one of the dummy variables. Perform appropriate statistical tests and give an
interpretation of the coefficients in each case. Explain why either the intercept or one
of the dummy variables must be dropped.
14.4 Perform a test for fixed effects in the OECD2000 regression by evaluating the
explanatory power of the country dummy variables as a group.
14.5 Download the NLSY2000 data set from the website. See Appendix B for details. This
contains the variables found in the EAEF data sets for the years 1980–94, 1996,
1998, and 2000 (there were no surveys in 1995, 1997, or 1999). Assuming that a
random effects model is appropriate, investigate the apparent impact of unobserved
heterogeneity on estimates of the coefficient of schooling by fitting the same earnings
function, first using pooled OLS, then using random effects.
14.6 The UNION variable in the NLSY2000 data set is defined to be equal to 1 if the
respondent was a member of a union in the year in question and 0 otherwise.
Assuming that a random effects model is appropriate, add UNION to the earnings
function specification and fit it using pooled OLS and random effects.
14.7 Using the NLSY2000 data set, perform a fixed effects regression of the earnings
function specification used in Exercise 14.5 and compare the estimated coefficients
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Introduction to Econometrics 423
with those obtained using OLS and random effects. Perform a Durbin–Wu–Hausman
test to discriminate between random effects and fixed effects.
14.8 Using the NLSY2000 data set, perform a fixed effects regression of the earnings
function specification used in Exercise 14.6 and compare the estimated coefficients
with those obtained using OLS and random effects. Perform a Durbin–Wu–Hausman
test to discriminate between random effects and fixed effects.
14.9 The within-groups version of the fixed effects regression model involved subtracting
the group mean relationship
Y
i
= β
1
+
k
j=2
(β
j
X
ij
) + δt + α
i
+ ε
it
from the original specification in order to eliminate the individual-specific effect α
i
.
Regressions using the group mean relationship are described as between effects regres-
sions. Explain why the between effects model is in general inappropriate for estimating
the parameters of a model using panel data. (Consider the two cases where the α
i
are
correlated and uncorrelated with the X
j
controls.)