
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010X
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010XSuppose that, for a given state in the United States, you wish to use annual time series data to estimate the effect of the state-level minimum wage on the employment of those 18 to 25 years old (EMP). A simple model is
gEMPt = ?0 + ?1gMINt + ?2gPOPt+ ?3gGSPt + ?4gGDPt + ut,
where MIN is the minimum wage, in real dollars, POP is the population from 18 to 25 years old, GSPt is gross state product, and GDPt is U.S. gross domestic product. The g prefix indicates the growth rate from year t — 1 to year t, which would typically be approximated by the difference in the logs.
(i) If we are worried that the state chooses its minimum wage partly based on unobserved (to us) factors that affect youth employment, what is the problem with OLS estimation?
(ii) Let USMINt be the U.S. minimum wage, which is also measured in real terms. Do you think gUSMINt is uncorrelated with ut?
(iii) By law, any state's minimum wage must be at least as large as the U.S. minimum. Explain why this makes gUSMINt a potential IV candidate for gMINt.
Step 1 of 3
(i)
In the context
, if the State of US chooses its minimum wage partly based on unobserved factors that affect youth employment, such unobserved factors would be accounted by the error term which in turn would lead to certain degree of correlation between the error term
and 
In this scenario, the OLS estimates of the coefficients of the model would be biased and inconsistent
Step 2 of 3
Step 3 of 3
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