This data set is from an article by Frederick Schutt and Peter VanBergeijk in wh

Question

This data set is from an article by Frederick Schutt and Peter VanBergeijk in which they attempted to see if the pharmaceutical industry practiced international price discrimination by estimating a model of the prices of pharmaceuticals in a cross section of 32 countries. The authors felt that if price discrimination existed, then the coefficient of per capita income in a properly specified price equation would be strongly positive. In addition, the authors expected that prices would be higher if pharmaceutical patents were allowed and that prices would be lower if price controls existed, if competition was encouraged, or if the pharmaceutical market in the country was particularly large.

The variables in the data set are:

P = pharmaceutical price level in the country divided by that of the United States

GDPN = per capita gross domestic product in the country divided by that of the US

CVN = per capita volume of consumption of pharmaceuticals in the country divided by that of the US

PP = a dummy variable equal to 1 if patents for pharmaceuticals are recognized in the country

DPG = a dummy variable equal to 1 if the country applied strict price controls

IPG = a dummy variable equal to 1 if the country encouraged price competition

a. Estimate the regression model representing price as a function of the five independent variables in the data set.

b. What is the R2 for the regression? Interpret this number.

c. Develop and test the appropriate hypothesis to determine whether the regression coefficients jointly have any explanatory power using the 5-percent level of significance. (Explain what evidence you used from your regression output in reaching your conclusion).

d. Develop and test the appropriate hypotheses concerning each of the regression coefficients individually using the t-test at the 5 percent level of significance. (Explain what evidence you used from your regression output in reaching your conclusion).

e. Do you think that Schutt and VanBergeijk concluded that international price discrimination exists? Why or why not?

OBS P CVN DPC GDPN IPC PP Malawi 1 60.83 0.6 0 4.9 0 1 Kenya 2 50.63 1.1 0 6.56 0 1 India 3 31.71 6.6 1 6.56 0 0 Pakistan 4 38.76 10.4 1 8.23 1 0 Sri lanka 5 15.22 6.7 1 9.3 1 1 Zambia 6 96.58 2.2 0 10.3 0 1 Thailand 7 48.01 11.3 0 13 0 0 Philippines 8 51.14 3.9 0 13.2 0 1 South Korea 9 35.1 13.3 0 20.7 0 0 malaysia 10 70.74 8.9 0 21.5 0 1 Colombia 11 48.07 14.1 0 22.4 1 0 Jamaica 12 46.13 22 0 24 0 1 Brazil 13 63.83 21.6 0 25.2 1 0 Mexioco 14 69.68 27.6 0 34.7 0 0 Yugoslavia 15 48.24 40.6 1 36.1 1 0 Iran 16 70.42 21.3 0 37.7 0 0 Uruguay 17 65.95 33.8 0 39.6 0 0 Ireland 18 73.58 38 0 42.5 0 1 Hungary 19 57.25 47.8 1 49.6 1 0 Poland 20 53.98 50.7 1 50.1 1 0 Italy 21 69.01 45.9 1 53.8 0 0 Spain 22 69.68 54.2 0 55.9 0 0 United Kingdom 23 71.19 38 1 63.9 1 1 Japan 24 81.88 54.7 1 68.4 0 0 Austria 25 139.53 35.2 0 69.6 0 0 Netherlands 26 137.29 24.1 0 75.2 0 1 Belgium 27 101.73 76 1 77.7 0 1 France 28 91.56 101.8 1 81.9 0 1 Luxembourg 29 100.27 60.5 1 82 0 1 Denmark 30 157.56 29.5 0 82.4 0 1 Germany 31 152.52 83.9 0 83 0 1 United States 32 100 100 0 100 1 1

Explanation / Answer

a. Estimate the regression model representing price as a function of the five independent variables in the data set.

price^ = 38.2213 -0.5947*CVN -15.6286*1dpc +1.14336*GDPN -11.38455*IPC +7.3113*PP

b. What is the R2 for the regression? Interpret this number.

R^2 =

it means 81.11 % of variation in price is explained by the model

c. Develop and test the appropriate hypothesis to determine whether the regression coefficients jointly have any explanatory power using the 5-percent level of significance. (Explain what evidence you used from your regression output in reaching your conclusion).

here p-value of F = 1.17 *10^(-8) <<0.05

hence we reject the null and conclude that the model is signiifcant

d. Develop and test the appropriate hypotheses concerning each of the regression coefficients individually using the t-test at the 5 percent level of significance. (Explain what evidence you used from your regression output in reaching your conclusion).

if p-value of variable is less than 0.05 , then variable is significant

here

are significant and IPC and PP are not , as their p-value > 0.05

SUMMARY OUTPUT Regression Statistics Multiple R 0.900679098 R Square 0.811222837 Adjusted R Square 0.774919536 Standard Error 16.48646963 Observations 32 ANOVA df SS MS F Significance F Regression 5 30368.22405 6073.644809 22.34570478 1.17152E-08 Residual 26 7066.895701 271.8036808 Total 31 37435.11975 Coefficients Standard Error t Stat P-value Lower 95% Intercept 38.22131309 6.387303818 5.983951004 2.56602E-06 25.09202206 CVN -0.594732378 0.223947366 -2.65567927 0.013338204 -1.055062783 DPC -15.6286446 6.93263466 -2.254358605 0.032824983 -29.87887924 GDPN 1.433679504 0.214394539 6.687108307 4.28541E-07 0.992985217 IPC -11.38455812 7.159258319 -1.590186806 0.123880035 -26.10062435 PP 7.311330351 6.123083856 1.194060138 0.243235122 -5.27484877

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