in 2'30], Donald Kenkel and Joseph Tera published a research article in which they analyzed the impact on an individual's alcohol constunption of a physical's advice to reduce drinking. The authors used econometric techniques that are well beyond the scope of this Course to conclude that such physician advice can play a signicant role in reducing alcohol consumption. Taking one fifth of the author's dataset allows for estimation of the following model {standard errors in parenthesis}: Ema = 13.09 + 11.36ADVICEI - iEDUCI + ZSSDIVSEE + 14.20UNEMFI {2.12} {(1.31} {2.55) {5.16} N = 500 E2 = {H}? Where : DRINKSE = Drinks consumed by the ith individual in the last two weeks : ADVICEI = 1 if a physician had advised the ith individual to cut back on drinking alcohol, {l otherwise : E DUE; = Years of schooling of the ith individual : DIVSEP; = 1 if the ith individual was divorced or separated, otherwise : UN E MP; = 1 if the ith individual was unemployed, I} otherwise a] Careilly state the meaning of the estimated coefficient on DIVSEPI and UNEMPI in the regression output above. Do the relative sizes of the coefficients make sense to you? Explain. b) Create and test appropriate one-sided hypotheses for the coefficients on DIVSEP; and UNEMP; at the 5-percent level. (Hint: Use the critical value of 12C! degrees of 'eedom}. c) Carefully state the meaning of the estimated coefficient of ADVICE. Does the sign of the coefficient make sense to you'iI If so, explain. If not, the unexpected sign might be related to a violation of one of the Classical Assumptions. 'What Classical Assumption {other than Assumption I} is this equation almost surely violating? Explain. d) Breaking down the sample of 5m) observations into five different samples of lt} observations each and calculated '33 for four of the five samples. The results (for gnomes} WEE: lEl sample: 15ch = 1&43 2'"1 sample: gnomes = 13.52 3'\" sample: gum\"; = 14.39 4'11 EMPIE: ADVICE =31\" The 35 are quite different! Explain how it's possible to get different if; when you're estimating identical specications of data that are drawn from the same population. What term would you use to describe this group of 135