Roswell, New Mexico case

It is 2007 and you are a newly minted MBA. Your employer sends you on a reconnaissance mission to Roswell, New Mexico. Your CEO wants to relocate the firm's customer service operation to Roswell, but she is at odds with Dilbert, the recently appointed Director of Human Resources department. Dilbert says that the residents of Roswell have had a freakishly high rate of brain tumors, and insists that the rate will rise in the near future, making a relocation to Roswell an expensive mistake (as a result of higher-than-average health care bills for the firm's Roswell employees). Dilbert attributes the high rate of brain tumors in Roswell to the 1997 crash of a mysterious flying vehicle carry... click for more

Problem Set

You have some data on a sample of investment bankers, and are interested in the impacts of height and of seniority on their success. You estimate what you call Model A using a software package (which, like most econometrics packages, always reports p-values for two-sided hypothesis tests): (A) SALARY = 90.2 + 26.7 HEIGHT_A + 13.9 SENIORITY - 52.3 PHD, Adj-R2 = 0.62 t=2.08 t=2.82 t=3.1 p-value=.050 p-value=.011 p-value=0.000 where SALARY is measured in thousands of dollars, HEIGHT_A is adult height measured in inches and as deviations from average (using the male average for men, and the female average for women), SENIORITY is years with the emplo... click for more

2 questions

1. Associated with the name of Simon Kuznets is the idea that the relationship between GDP and inequality is nonlinear. Kuznets hypothesized three phases in economic development. In the first stage of development, incomes and inequality are both low. During the process of modernization and industrialization, income and inequality both rise. Once a country has become a modern, industrialized economy, inequality declines as income continues to rise. (As you might suspect, the last 30 years of U.S. economic experience have not provided much evidence to support the Kuznets conjecture!) Which of the following equations would support the Kuznets hypothesis? The dependent variable is the... click for more

Serial correlation

(See attached file for full problem description) --- Dependent Variable: MH6 Method: Least Squares Date: 03/30/06 Time: 12:50 Sample(adjusted): 2 40 Included observations: 39 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. MR7 700.4927 4711.021 0.148692 0.8826 C 147248.6 25046.92 5.878909 0.0000 R-squared 0.000597 Mean dependent var 150540.9 Adjusted R-squared -0.026414 S.D. dependent var 72172.59 S.E. of regression 73119.55 Akaike info criterion 25.28750 Sum squared resid 1.98E+11 Schwarz criterion 25.37281 Log likelihood -491.1062 F-statistic 0.022109 Durbin-Watson stat 0.409859 Prob(F-statistic) 0.882604 Is ther... click for more

Econometrics

(See attached file for full problem description) --- 1. Based on 11 annual observations, the following regressions were obtained: Model A: Yt = 2.6911 – 0.4795Xt se = (0.1216) (0.1140) r2 = 0.6628 Model B: Yt = 0.7774 – 0.2530 ln Xt se = (0.0152) (0.0494) r2 = 0.7448 where Y = the cups of coffee consumed per person per day and X = the price of coffee in dollars per pound. a) Interpret the slope coefficients in the two models. b) You are told that Y = 2.43 and X = 1.11. At these mean values, estimate the price elasticity for Model A. c) What is price elasticity for Model B? d) From the estimated elasticities, can you say that the demand for coffee is pri... click for more