Question: (Use R programming language.. Multivariate Regression is applied through OLS formulas) (Multivariate Regression) In order to study the effect of change in hourly wage (WPH)
(Use R programming language.. Multivariate Regression is applied through OLS formulas)
(Multivariate Regression) In order to study the effect of change in hourly wage (WPH) on the supply of labor (hours worked, HRS), we have data on the 38 demographic groups. There are other factors that will affect the supply of labor, which include spouse's annual income (ERSP) and the number of years of education (SCL). We have data saved in file Wage.txt. You are asked to estimate the supply equation. Note, in all the following regressions, you should include a constant term.
(a)Estimate a univariate regression of HRS on WPH. What is the impact of a dollar change in wage on the supply, and does the sign of the coefficient makes sense? Is your estimate significant?
(b)The supply of labor may depend on how much spouse makes. In other words, we should estimate the following multivariate regression model instead, HRS = 1 + 2WPH + 3ERSP + u. What sign do you expect for 2 and 3? Are the corresponding coefficient estimates significant and have the right sign?
(c) What if you delete the 19th observation, and rerun the multivariate regression, what do you observe when comparing with those of (b)?
(d)Suppose, on average, a spouse worked 700 hours a year, we can study whether there is a complete substitution effect of spouse by testing how would you formulate the hypothesis of 2 + 3 700 = 0. Is the complete substitution hypothesis true?
(e)Finally, since both HRS and WPH are endogenous, we may interested in estimating the following multivariate regression model, (WPH HRS) = 1 + 2SCL + 3NEIN + v, where NEIN is non-wage income. Interpret your coefficient estimates, and test their significance. Does the sign of coefficient estimates make sense?
Attached Table
HRS WPH SPARE NO
2157 2.905 1121 10.5 380
2174 2.97 1128 10.5 398
2062 2.35 1214 8.9 185
2111 2.511 1203 11.5 117
2134 2.791 1013 8.8 730
2185 3.04 1135 10.7 382
2210 3.222 1100 11.2 474
2105 2.493 1180 9.3 255
2267 2.838 1298 11.1 431
2205 2.356 885 9.5 373
2121 2.922 1251 10.3 312
2109 2.499 1207 8.9 271
2108 2.796 1036 9.2 259
2047 2.453 1213 9.1 139
2174 3.582 1141 11.7 498
2067 2.909 1805 10.5 239
2159 2.511 1075 9.5 308
2257 2.516 1093 10.1 392
1985 1.423 553 6.6 146
2184 3.636 1091 11.6 560
2084 2.983 1327 10.2 296
2051 2.573 1194 9.1 172
2127 3.262 1226 10.8 408
2102 3.234 1188 10.7 352
2098 2.28 973 8.4 272
2042 2.304 1085 8.2 140
2181 2.912 1072 10.2 383
2186 3.015 1122 10.9 352
2108 2.786 1757 10.2 506
2188 3.01 990 10.6 374
2203 3.273 1109 11 430
2077 1.901 350 8.2 95
2196 3.009 947 10.6 342
2093 1.899 342 8.1 120
2173 2.959 1116 10.5 387
2179 2.971 1128 10.5 397
2200 2.98 1126 10.6 393
2197 3.413 1078 11.3 512
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