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Use CRIMEA for this exercise.(i) Reestimate the unobserved effects model for crime in Example 13.9 but use fixed effects ratherthan differencing. Are there any notable sign or magnitude changes in the coefficients? Whatabout statistical significance?(ii) Add the logs of each wage variable in the data set and estimate the model by fixed effects. Howdoes including these variables affect the coefficients on the criminal justice variables in part (i)?(iii) Do the wage variables in part (ii) all have the expected sign? Explain. Are they jointly significant?

The p-value of the F-statistic is 0.009 which is less than the critical p-value of 0.05 at 5$\%$ level ofsignificance, indicating that all the log of the nine wage variables are statistically jointly significantat 5$\%$ level of significance.

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Chapter 14

Advanced Panel Data Methods

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Mm. Part one. Okay. The left panel reports to fix effects estimates you can see the list of independent variables, their coefficients and their standard errors. Mhm. There are 90 observations and seven years. There is no intercept because we have eliminated it when we do the time demeaning the first difference and fixed effects estimates are broadly consistent. The variables that are significant with first difference ng are again significant In the fixed effect estimation, the signs are all the same. Their magnitudes are also similar mhm. But with the exception of the insignificant variable lock of average sentence, you can see that the fixed effect estimates are all larger in absolute value. Overall, we can conclude that the estimates across the two methods are similar. In part two, you will add nine lock wage variables and re estimate the equation by fixed effects. I report the results for the criminal justice variables only on the right panel. You can see that the change in these variables are minimal and doing an F test mhm. You can confirm that the wages, variables, log wages okay are jointly significant. You should get an F statistic with night and 5 20 degrees of freedom. Okay to be 2.47 and a P value of pine No. One. Roughly so. These variables are jointly significant at the 1% level.

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