This data set is from an article by Frederick Schutt and Peter VanBergeijk in wh
ID: 361081 • Letter: T
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.[1] 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.
Price discrimination in economics refers to selling the same product to different consumers at different prices. For example, providing student or senior citizen discounts. The reason the authors felt that the coefficient of per capita income would measure price discrimination went as follows: the higher the ability to pay, the lower (in absolute value) the price elasticity of demand for pharmaceuticals (that is demand is more inelastic) and the higher the price a price discriminator could charge.
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. State 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. State 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?
PLEASE ANSWER ALL PARTS
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 1Explanation / Answer
A. The estimated regression model is:-
P= 38.84 - 0.58XCVN - 15.83 X DPC + 1.41 X GDPN - 11.6 X IPC + 7.87 x PP
B. The R Square of this regression model is 0.81. The interpretation is 81% of the variation in P is explained by the given independent variables.
C. We will use the F-Statistics from the output to test this hypothesis
The hypothesis is H0: Mu1=Mu2=Mu3=Mu4=Mu5=0
Ha: At least one of the Mu(s) is non zero (Mu1, Mu2, Mu3, Mu4 and Mu5 are the coefficients of the independent variables.
The F-value is 22.64 and is significant at 0.05 level of significance as the p-value of F is 1.02 X 10 Exp(-8).
This means all the independent variables simultaneously are significant in explaining the dependent variable price.
D. The appropriate value to look at is the t-value for each of the coefficients of the independent variables. If the t-value is greater than 2 then the coefficients are significant and the variable is significantly explaining the dependent variable.
The hypothesis is Ho: Mu(a)=0
Ha: Mu(a) not equal to 0 where Mu (a) is the respective coefficient of the independent variables
t for CVN s -2.67 which is significant
t for DPC is -2.3 which is significant
t for GDPN is 6.8 which is significant
t for IPC is -1.63 which is insignificant
t for PP is 1.29 which is insignificant
So all the independent variables apart from IPC and PP are significant.
E. If they are using GDPN as a proxy of per capita income then they are right in assuming there is price discrimination as the coefficient of GDPN is positive and significant (t-value=6.8).
If they are using DPC as the proxy for per capita income then their assumption is wrong as the coefficient of DPC is negative (-0.58 with a t-value of -2.67).
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