Question

Estimate from 1975-1980:

i.month naturally coded Imonth 1 omitted) Source Number of obs 251046282 033427535 13 .019311252 Prob > F 0.000O 0.882!5 Adj R-squared-0.8500 02667 Residual 000711224 R-squared . 284473817 00474123 Root MSE ïnGas Coef Std. Err [95% Conf. Interval] -.3350421 . 4666989 -.0501979 059844 0580051 0922258 0984848 1095921 .1210783 0511898 0811551 0204031 0788326 -.6931444 0268061 -1 0.000 0.000 0.005 0.001 0.001 0.000 0.000 0.000 0.000 0.004 0.000 0.214 0.000 0.564 -.388969 .2163058 -, 0841454 0257594 0240455 0582386 0644243 0755359 0869694 0169535 0470963 -.0121574 0448497 -3.091252 - .2811151 . 7170919 - ,0162505 0939286 0919647 .1262131 .1325454 .1436482 1551872 085426 115214 0529636 .1128155 1.704963 lnInc Imonth 2 .1244659 0168747 0169428 0168807 0168944 0169309 0169287 0169549 0170182 01693 0161852 0168923 1.192056 Imonth 6 Imonth 8 Imonth 9 month 10 Imonth 12 cons

Estimate from 2001 – 2006:

a. Compare the estimated price elasticity during these years with your estimate from 1975-1980 above.

b. Interpret the estimated coefficient on logged per capita income (lnInc). Discuss the sign, magnitude and statistical significance. What does this estimate tell us about how gasoline demand in the 2000’s responded to changes in income?

(Please answer a & b completely) Thank you!

[lnGas = ln(gascap)

lnP = ln(realprice)

lnInc = ln(inccap)

realprice = Real price of gasoline (2000 $)

gascap = Gas demanded per capita (gallons per month)

inccap = Real income per capita (2000 $)

date = Year and month of observation (text)

year = Year of observation

month = Month of observation]

Answer 1

a) The estimated price elasticity of demand is -0.0415 in 2001-06 period as compared to -0.335 in 1975-80 period. We see that the elasticity in absolute terms has decreased. The demand has become less elastic this may be due to the rise in income of the overall population. This makes them decrease their demand by a lesser amount in case of price rise.

b) The estimated coefficient on logged per capita income is 0.5298 ~ 0.53. The positive sign of the coefficient indicates the rise in income increase the gasoline consumption (or demand). Also, the coefficient is statistically significant at 95% level of significance (with t= 5.61).

Moreover, this estimate tells us that 1% increase in income will lead to 0.53% increase in demand for gasoline.