Temple University

Economics 615

1.a.

 QB = 1.95423 + .029601 Y + e (.842) 2.321 (.00852) 3.47

1.b.

 QB = .4011 + .0245 Y + .4129 S - .355 PB +.57 PM + e (1.03) .39 (.00789) 3.10 (.112) 3.69 (.062) 5.73 (.161) 3.54

2.

 tobs = 1.954/.842 = 2.32 P(-2.32 < t < 2.32) @ .974 Therefore reject the null.

3. i.

 The observed F is above the critical value for any reasonable significance level, so reject the null.

3.ii.

 tobs = .57/.161 = 3.53 Reject Ho at the 1% level of test.

4.

 i. ii. iii. iv.

5. For the meat equation when the observations with Qm=0 are omitted

 QM = 7.512 + .0389 Y - .356 S + .146 PB - 1.179 PM + e (.95) 7.91 (.008) 4.86 (.121) 2.94 (.061) 2.39 (.149) 7.91

When all the observations are used

 QM = 7.815 + .0411 Y - .4367 S + .1625 PB - 1.2293 PM + e (1.045) 7.47 (.008) 5.13 (.114) -3.83 (.063) 2.56 (.163) -7.54

a.

 Delete Obs for which Qm=0 All Observations At the 2.5% level reject Ho

b.

 Exclude obs for which Qm = 0 All observations Define .1625+.0411(4.7719)=.3586 tobs = 6.306 Reject the null. .06352+(4.7719)2(.008)2+2(4.7719)(-.0002416)           =.003184 tobs = 6.355

6. Your answers to the meat part of this question will depend on how you dealt with the zeros in QM. The choices are to delete those observations; inadvisable since you lose valuable information. When QM = 0, let ln(QM) = 0; inadvisable since you are saying that these households are equivalent to those that consumed QM = 1. When QM = 0, reset it to QM = (some small number); inadvisable since this will tilt the regression line unduly. Add 1 to every observation on QM; best idea yet, although households with low QM experience a bigger % shift than those with high QM. You should read the text or lecture notes to decide how best to deal with missing data.

 Results when observations corresponding to Qm = 0 are deleted from both the Bread and Meat samples: LnQB = -.5633 (.465) +.719 lnY (.162) +.33 ln S (.132) -1.196 ln PB (.172) +.066 ln PM (.16) + e LnQM = -1.833 (1.54) +1.514 lnY (.54) +.899 ln S (..44) +.642 ln PB (.57) -2.282 ln PM (.54) + e
 Use all data for bread and add 1 to Qm. LnQB = -.6433 (.4207) +.7057 lnY (.1319) +.37 ln S (.1075) -1.1428 ln PB (.1555) +.6303 ln PM (.1555) + e LnQM = -.8025 +1.213 lnY -.847 ln S +.5087 ln PB -1.782 ln PM + e

a.

 All observations Delete obs for which Qm = 0 tobs = .07581/.09958 = .76126 Do not reject the null. tobs = .761

b.

 1.213-.8471-1 = -.6341 tobs = -1.041 Do not reject the null. tobs = -2.33