Question Two A researcher is interested in estimating the determinants of rice production in the United States using the following model. Data is obtained from 44 firms from 1990 to 1997. log(prodit) = Bo + Blaborit + Bzareait +Bzareat + B4 log(fert) it + B5year94 it + Uit where i= firm subscript, t-year subscript, prod = Rice production (tonnes), labor = number of employees, area =area of land that rice is planted (hectares), fert = Fertilizer applied (kilograms), year94=1 from 1994 onwards and equals ( before 1994, u is the random error term. The results of the estimated regression from Stata is presented in Table 2 below. Table 2: Regression Results of US rice production Source SS df MS Model Residual 219.824708 46.825521 5 346 43.9649416 .135333876 Number of obs F(5, 346) Prob > F R-squared Adj R-squared Root MSE 352 324.86 0.0000 0.8244 0.8219 .36788 Total | 266.650229 351 .759687262 logprod Coef. Std. Err. t P>ti [95% Conf. Interval] labor area areasar logfert year 94 .0026882 .5877957 -.0695422 .3048084 -.0171145 -.9945019 .0006855 .0628393 .0088591 .0396158 .0398007 .1343339 3.92 0.000 9.35 0.000 -7.85 0.000 7.69 0.000 -0.43 0.667 -7.400.000 .0013399 .4642007 -.0869666 .2268904 -.0953964 -1.258716 .0040365 .7113907 -.0521178 .3827264 .0611673 -.7302881 _cons a) Interpret the regression result (i.e. the regression coefficients and the t- statistics or p-values). [12 marks] b) In the context of the above model of rice production, describe autocorrelation? a) Interpret the regression result (i.e. the regression coefficients and the t- statistics or p-values). [12 marks] b) In the context of the above model of rice production, describe autocorrelation? If autocorrelation exists in the data, how would this affect your interpretation of the regression results in part (a). [4 marks] c) Using the results from the Wooldridge test for autocorrelation below, is there any evidence of first order autocorrelation? [2 marks] Wooldridge test for autocorrelation in panel data HO: no first-order autocorrelation FC 1, 43) = 1.357 Prob > F = 0.2505 May 2020 Quantitative Methods and Econometrics ECON1142 Page 4 of 10 Approved d) Given the autocorrelation results in part (c), would you re-run the regression using standard errors that are robust to autocorrelation? [2 marks] Total:20 Marks NO Word Limit