Econometric take home APPS_Part_4

Econometric take home APPS_Part_4 - |Variable| Coefficient...

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+--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ Constant| 1.10587817 .56937860 1.942 .0588 INCOME | .00021575 .517619D-04 4.168 .0001 16805.0577 GASP | -.01108386 .00397812 -2.786 .0080 51.3429615 PNC | .00057735 .01284414 .045 .9644 87.5673077 PUC | -.00587463 .00487032 -1.206 .2345 77.8000000 PPT | .00690726 .00483613 1.428 .1606 89.3903846 PD | .00122888 .01188175 .103 .9181 78.2692308 PN | .01269051 .01259799 1.007 .3195 83.5980769 PS | -.02802781 .00799625 -3.505 .0011 89.7769231 T | .07250369 .01418280 5.112 .0000 26.5000000 ?======================================================================= ? b. Hypothesis that b(NC) = b(UC) $ ?======================================================================= Calc ; list ; (b(4)-b(5))/sqr(varb(4,4)+varb(5,5)-2*varb(4,5)) $ +------------------------------------+ | Listed Calculator Results | +------------------------------------+ Result = .494883 ?======================================================================= ? c. Elasticities. In each case, elasticity = b*xbar/ybar ?======================================================================= Calc ; g2004 = g(52)$ Calc ; i2004 = income(52)$ Calc ; pg2004 = gasp(52)$ Calc ; ppt2004 = ppt(52)$ Calc ; list ; ei = b(2)*i2004/g2004 ; ep = b(3)*pg2004/g2004 ; eppt = b(6)*ppt2004/g2004$ +------------------------------------+ | Listed Calculator Results | +------------------------------------+ EI = .948988 EP = -.222792 EPPT = .234311 ?======================================================================= ? d. Log regression ?======================================================================= Create ; logg = log(g) ; logpg = log(gasp) ; logi = log(income) ; logpnc=log(pnc) ; logpuc = log(puc) ; logppt = log(ppt) ; logpd = log(pd) ; logpn = log(pn) ; logps = log(ps) $ Namelist ; LogX = one,logi,logpg,logpnc,logpuc,logppt,logpd,logpn,logps,t$ Regress ; lhs = logg ; rhs = logx $ +----------------------------------------------------+ | Ordinary least squares regression | | LHS=LOGG Mean = 1.570475 | | Standard deviation = .2388115 | | WTS=none Number of observs. = 52 | | Model size Parameters = 10 | | Degrees of freedom = 42 | | Residuals Sum of squares = .3812817E-01 | | Standard error of e
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This note was uploaded on 11/13/2011 for the course ECE 4105 taught by Professor Dr.fang during the Spring '10 term at University of Florida.

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Econometric take home APPS_Part_4 - |Variable| Coefficient...

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