Just need c and d
1. (50 points) The file Ch13_Exercise3_James Bond contains data on James Bond films from 1962 to 2012. We want to know how budget and ratings mattered for how well the movies did at the box office. TABLE 13.6 Variables for James Bond Movie Data Variable name Description GrossRev Gross revenue, measured in millions of U.S. dollars and adjusted for inflation Rating Average rating by viewers on online review sites (IMD) and Rotten Tomatoes) as of April 2013 Budget Production budget, measured in millions of U.S. dollars and adjusted for inflation Actor Name of main actor Order A variable indicating the order of the movies, we use this variable as our "time" indicator even though movies are not evenly spaced in time (a) Estimate an OLS model in which the amount each film grossed is the dependent variable and ratings and budgets are the independent variables. Assess whether there is autocorrelation. (b) Estimate the model from part (a) with Newey-West standard errors. Compare the coefficients and standard errors to those produced by a standard OLS model. (c) Correct for autocorrelation using the p-transformation approach. Did the results change? Did the autocorrelation go away? (d) Assess the stationarity of the revenue, rating, and budget variables. You can use: library(tseries) adf.test(VariableName, k=1)
1. (50 points) The file Ch13_Exercise3_James Bond contains data on James Bond films from 1962 to 2012. We want to know h
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1. (50 points) The file Ch13_Exercise3_James Bond contains data on James Bond films from 1962 to 2012. We want to know h
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