Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN: 9781305506381
Author: James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher: Cengage Learning
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Chapter 5, Problem 1.5CE
In attempting to formulate a model of the passenger arrival data on cruise ships over time would a nonlinear (perhaps a multiplicative exponential) model be preferable to a linear model of cruise ship arrivals against time? What about in the case of the passenger arrivals by ferry against time?
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Chapter 5 Solutions
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
Ch. 5 - The forecasting staff for the Prizer Corporation...Ch. 5 - Prob. 2ECh. 5 - Metropolitan Hospital has estimated its average...Ch. 5 - Prob. 4ECh. 5 - A firm experienced the demand shown in the...Ch. 5 - The economic analysis division of Mapco...Ch. 5 - The Questor Corporation has experienced the...Ch. 5 - Bell Greenhouses has estimated its monthly demand...Ch. 5 - Savings-Mart (a chain of discount department...Ch. 5 - Prob. 1.1CE
Ch. 5 - Plot the logarithm of arrivals for each...Ch. 5 - Logarithms are especially useful for comparing...Ch. 5 - Prob. 1.4CECh. 5 - In attempting to formulate a model of the...Ch. 5 - Estimate the double-log (log linear) time trend...Ch. 5 - Prob. 2.1CECh. 5 - Prob. 3.1CECh. 5 - Prob. 3.2CECh. 5 - Prob. 3.3CE
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- Estimate the double-log (log linear) time trend model for log cruise ship arrivals against log time. Estimate a linear time trend model of cruise ship arrivals against time. Calculate the root mean square error between the predicted and actual value of cruise ship arrivals. Is the root mean square error greater for the double log non-linear time trend model or for the linear time trend model?arrow_forwardConsider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=10,160.10+3147.75(Education)+1230.34(Experience) Suppose an employee with 8 years of education has been with the company for 20 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary?arrow_forwardWhich of the following is an assumption on which time series regression is based? a. A time series process follows a model that is nonlinear in parameters. b. In a time series process, no independent variable is a perfect linear combination of the others.arrow_forward
- How Regression models are used for Forecasting purpose?arrow_forwardWhat conditions must non-linear time series models, such as vector autoregressive models, satisfy in order to use impulse response functionsarrow_forwardCan we compare the linear-log model and the log-log model? Which of the log regression models best fits the data?arrow_forward
- Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,681.31+3418.97(Education)+1194.78(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree (10 years of education). How much more money would we expect the employee with a master's degree to make?arrow_forwardYou model the relationship between citizens' consumption and their monthly income. Based on your experience, you know that people with lower income usually spend 60% of their income on consumption. For people with higher income, some may spend only 40% on consumption, while others spend 70% on consumption. What is the potential problem when you use a linear regression model? E[u\x] #0 Heteroskedasticity Perfect colinearity No variability in x None of abovearrow_forwardThis is model question. I need100% accurate answer. Please review it.arrow_forward
- Consider the following Stata output for the model of house prices: lhprice=β0+β1bdrms+β2llotsize+β3lsqrft+u estimated on a random sample of 86 houses. You may assume the Gauss Markov Assumptions hold. The variables are defined as: lhprice = the natural log of the house price bedrms = the number of bedrooms llotsize = the natural log of the land or lot size lsqrft = the natural log of the floor space of the house in square feet. Source SS df MS Model Residual 4.65621742 2.09289629 3 82 1.55207247 0.025523126 Total 6.74911372 85 0.079401338 lprice coef. std. err. t P > |t| [95% Conf. Interval] bdrms 0.0581214 -0.0055282 0.121771 llotsize 0.1494716 0.0616548 0.2372884 lsqrft 0.636171 0.421989 0.850353 _cons -0.7083136 -2.221521 0.8048935 Number of obs = 86 F (3, 82) = 60.81 Prob > F = 0.0000 R-squared = 0.6899 Adj R-squared = 0.6786 Root MSE = 0.15976 Does…arrow_forward1. Suppose that we are interested in measuring the relationship between hourly wage and output productivity in the U.S economy. Variables hrwage(t) and outphr(t) denote the average hourly wage and output productivity in the U.S economy for year t. We start by estimating the model specification shown in equation (1) below: log(hrwage) = Bo + B₁ log(outphre) + ut. where log(.) denotes the natural logarithm and ut is the error term. (a) Provide a brief interpretation of parameters 0 and 1 in (1).arrow_forwardThe circulation C of a certain magazine as a function of time t is given by the formula c=5.2/0.1+0.3t Here C is measured in thousands and t is measured in years since the beginning of 2006 when the magazine was started. Find when the circulation of the magazines will reach 34.83 thousand. Write the equation you are solving.arrow_forward
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