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Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010XIntroductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010XUse the data from JTRAIN.RAW for this exercise.
(i) Consider the simple regression model
log(scrap) = ?0+ ?grant + u,
where scrap is the firm scrap rate and grant is a dummy variable indicating whether a firm received a job training grant. Can you think of some reasons why the unobserved factors in u might be correlated with grant?
(ii) Estimate the simple regression model using the data for 1988. (You should have 54 observation
s.) Does receiving a job training grant significantly lower a firm's scrap rate?
(iii) Now, add as an explanatory variable log(scrap87). How does this change the estimated effect of grant? Interpret the coefficient on grant. Is it statistically significant at the 5% level against the one-sided alternative H1: ?grant<0?
(iv) Test the null hypothesis that the parameter on log(scrap87) is one against the two-sided alternative. Report the p-value for the test.
(v) Repeat parts (iii) and (iv), using heteroskedasticity-robust standard errors, and briefly discuss any notable differences.
Verified
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(i)
In the simple regression model
The unobserved factors in
might be correlated with
due some important omitted variables in the regression model that exhibit significant degree of correlation with
Such omitted variables could be the factors that effects both
and
such as the ability and education of the employees and other firm characteristics such as degree of sophistication of operations, level of attrition-rate, the nature of the firm-priority sector, profit-making or departmental undertaking etc
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