Eviews questions

Applied Econometrics Homework Two

(Submit Completed Assignment Online via Canvas by 11:59PM on Sunday, March 5, 2022)

1. You are attempting 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. You assume that if price discrimination exists, then the coefficient of per capita income () in a properly specified price equation would be strongly positive. Your reasoning for why the coefficient of per capita income measures price discrimination is as follows: the higher the ability to pay, the lower (in absolute value) the price elasticity of demand for pharmaceuticals and the higher the price a price discriminator could charge. In addition, you expect 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 a country was relatively large. Your estimates are found below with standard errors in parentheses:

  1. Set up 90-percent confidence intervals for the estimated slope coefficients on the GDPN and CVN variables. should be positively signed while should be negatively signed.
  2. Per your confidence interval, what is the maximum impact of increasing CVN by one unit on a country’s relative pharmaceutical price level (P)?
  3. Do you conclude that international price discrimination exists? Explain why or why not using your confidence interval.
  4. Develop and test appropriate hypotheses concerning the regression coefficients for the PP, DPC, and IPC variables using the t-test at the 5-percent level. You should expect that will be positively signed while and will be negatively signed.

 

2. Consider a model of iPod prices on eBay (standard errors in parentheses):

  1. Create and test hypothesis for the coefficients of NEW and SCRATCH at the 5-percent level. (Hint: Use the critical value for 120 degrees of freedom.)
  2. In theory, the more bidders there are on a given iPod, the higher the price should be. Create and test hypotheses at the 1-percent level to see if this theory can be supported by the results.
  3. Based on the hypothesis tests you conducted in parts a and b, are there any variables that you think should be dropped from the equation? Explain.
  4. Test the overall significance of this equation with the F-test at the 5-percent level. Use the F-stat provided in the regression results above. Be sure to state the correct null and alternative hypotheses and to denote your critical value. Write down the restricted model used by EViews to compute the F-stat?

The dataset also includes a variable (PERCENT) that measures the percentage of customers of the seller of the ith iPod who gave that seller a positive rating for quality and reliability in previous transactions.12 In theory, the higher the rating of a seller, the more a potential bidder would trust that seller, and the more that potential bidder would be willing to bid. If you add PERCENT to the equation, you obtain the following results:

  1. Use our four specification criteria to decide whether you think PERCENT belongs in the equation. Be specific. (Hint: is not given, but assume that the addition of any variable with a t-score greater than one in absolute value will increase )

 

 

 

3. For each of the following situations, determine the sign (and, if possible, comment on the likely size) of the expected bias introduced by omitting a variable. Determine the sign for both components of the bias term. (Hint:  In determining the magnitude of omitted variable bias, consider how strongly related the omitted variable is to both the dependent and independent variable in question.)

  1. In an equation for the demand for peanut butter, the impact on the coefficient of disposable income of omitting the price of peanut butter variable. (Hint: Start by hypothesizing signs.)
  2. In an earnings equation for workers, the impact on the coefficient of experience of omitting the variable for age.
  3. In a production function for airplanes, the impact on the coefficient of labor of omitting the capital variable.
  4. In an equation for daily attendance at outdoor concerts, the impact on the coefficient of the weekend dummy variable (1 = weekend) of omitting a variable that measures the probability of precipitation at concert time.

4. Assume that you’ve been hired by the surgeon general of the United States to study the determinants of smoking behavior and that you estimate the following cross-sectional model based on data for all 50 states (standard errors in parentheses):

    1. Develop and test (at the 5-percent level) appropriate hypotheses for the coefficients of the variables in this equation.
    2. Which variables might be candidates as irrelevant variables? Why did you choose these variables?
    3. Omitted variable bias may be impacting the slope coefficient for cigarette consumption. Explain why we might think this is so.
    4. One of the purposes of running the equation was to determine the effectiveness of antismoking advertising on television and radio. What are your conclusions?
    5. The surgeon general decides that tax rates are irrelevant to cigarette smoking and orders you to drop the variable from your equation. Given the following results, use our four specification criteria to decide whether you agree with her conclusion. Carefully explain your reasoning (standard errors in parentheses).
    6. In answering part e, you surely noticed that the figures were identical. Did this surprise you? Why or why not?