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Charisma of top-level leaders Refer to the Academy of Management Journal (August, 2015) study of the charisma of top leaders in business. Exercise 12.76 (p. 732). The researchers analyzed data collected for 24 U.S. presidential elections where the dependent variable of interest was Democratic vote share (y), measured as the percentage of voters who voted for the Democratic candidate in the national election. One potential quantitative predictor of vote share was the difference (x1) between the Democratic and Republican candidates' charisma values. (Recall that charisma was measured on a 150-point scale based on the candidates' acceptance speeches at their party's national convention.) One potential qualitative predictor was whether or not the election was affected by a World War: x2 = {1 if war, 0 if not}.
- a. Propose a model that describes the relationship between Democratic vote share (y) and charisma difference (x1) as two nonparallel straight-lines, one for each level of World War status (x2)
- b. In terms of the β’s of the model, part a, what is the slope of the line relating Democratic vote share (y) to charisma difference (x2) for election years affected by a World War?
- c. In terms of the β’s of the model, part a, what is the slope of the line relating Democratic vote share (y) to charisma difference (x2) for election years not affected by a World War?
- d. In terms of the β’s of the model, part a, what is the effect of a World War on
mean Democratic vote share, E(y), for all election years when there is no charisma difference (i.e., x1= 0 )? - e. In terms of the β’s of the model, part a, what is the effect of a World War on mean Democratic vote share, E(y), for all election years when there the charisma -difference is x1 = 50 ?
- f. Fit the model, part a, to the data in the file. Is there sufficient evidence to indicate that the linear effect of the charisma difference on mean Democratic vote share depends on World War status? Test using α = .10.
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Chapter 12 Solutions
EBK STATISTICS FOR BUSINESS AND ECONOMI
- 7. A television station wishes to study the relationship between viewership of its 11 p.m. news program and viewer age (18 years or less, 19 to 35, 36 to 54, 55 or older). A sample of 250 television viewers in each age group is randomly selected, and the number who watch the station’s 11 p.m. news is found for each sample. The results are given in the table below.arrow_forwardSherwin-Williams Company is attempting to develop a demand model for its line of exterior house paints. The company’s chief economist feels that the most important variable affecting paint sales (Q) (measured in gallons) is the Selling price (P) (measured in Ghana cedis per gallon). The chief economist decides to collect data on the variables in a sample of 10 company sales regions that are roughly equal in population. Data on paint sales, and selling prices were obtained from the company’s marketing department. The data are shown in the table below: Sherwin-Williams Company Data Sales Region Sales (Q) Selling Price (P) (GHS/Gallon) 1 160 15 2 220 13.5 3 140 16.5 4 190 14.5 5 130 17 6 160 16 7 200 13 8 150 18 9 210 12 10 190 15.5 Specify the linear demand model for Sherwin-William’s paint. Estimate the demand…arrow_forwardWe are studying the factors that contribute to unemployment at an individual level. UE, unemployment, is our dependent variable and it is a binary variable that takes the value 1 if an individual is unemployed and 0 if they are employed. We have a random sample and we estimate the following model: UE^= 0.508−0.051educ−0.023urban+0.005age(0.122) (0.012) (0.005) (0.002)n=6214, R2=0.474 where educ = an individual’s years of education urban = a dummy equal to 1 if the individual lives in an urban area and 0 otherwise age = an individual’s age in years What is the correct interpretation of the estimated coefficient on education?arrow_forward
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- We are interested in analysing the effect of the lockout laws introduced in some areas of the Sydney CBD and nearby surrounds on the number of alcohol-related violent incidents. Suppose we have two samples of data on the number of violent incidents in a number of local areas of the Sydney CBD and nearby surrounds. Pubs, hotels and clubs located in a subset of these areas became subject to the lockout laws when they were introduced in 2014. The first sample is from 2010 before the introduction of the lockout laws, and the second is from 2015 after the introduction of the law. The hypothesis we wish to test is that the introduction of the lockout laws reduces violent incidents in the areas in which the lockout laws were put in place. We use a difference-in-difference model on the pooled data from 2010 and 2015. We find the following results: viol_inc hat = 33.21 (5.29) + 12.43lockout (7.01) – 4.19Yr2015 (2.98) – 3.32 (lockout x Yr2015) (1.85) N = 181, R^2 = 0.128 Where: viol_incis the…arrow_forwardTaubman et al., (2014) used data collected in the Portland, OR metro area to study the Impact Medicaid on emergency department (ED) use. The figure below shows the percent of respondents who have been to the ED at all (left hand side of the figure) and the average number of ED visits (right hand side of the figure). The dark blue bars represent the mean for the control group, and the light blue bars add in the "Medicaid" effect found in the paper. The black "capped" bar represents the confidence interval for the Medicaid effect. Percent with Any Visits 50 €30 20 10 O Any O O Any and Total ED Use Emergency Department Data Control Mean Control Mean plus Medicaid Effect Cl for Medicaid Effect The results above imply that the price elasticity of demand for emergency department use is Number of Visits perfectly inelastic not perfectly inelastic perfectly elasticarrow_forwardSales of sugar-sweetened beverages at stores in Seattle dropped about 30.5% in the months after the city adopted a tax on such beverages, says a new study that also looked at sales at stores in Portland, which has no such tax.Sales in Portland declined only 10.5%, suggesting sales in Seattle dropped much more than they would have without a tax, according to the peer-reviewed study by University of Illinois at Chicago researchers.The study’s results are the first to measure the impact of Seattle’s tax on beverage sales in the city, and they may bolster claims by supporters that the controversial policy is working as intended.“From a public health perspective, this is good,” said Jay Krieger, a University of Washington professor who heads the nonprofit Healthy Food America. “People are purchasing less sugary drinks, and we know that sugary drinks are associated with heart disease, diabetes,high blood pressure and strokes.”Seattle’s tax of 1.75 cents per fluid ounce, which took effect on…arrow_forward
- Sales of sugar-sweetened beverages at stores in Seattle dropped about 30.5% in the months after the city adopted a tax on such beverages, says a new study that also looked at sales at stores in Portland, which has no such tax.Sales in Portland declined only 10.5%, suggesting sales in Seattle dropped much more than they would have without a tax, according to the peer-reviewed study by University of Illinois at Chicago researchers.The study’s results are the first to measure the impact of Seattle’s tax on beverage sales in the city, and they may bolster claims by supporters that the controversial policy is working as intended.“From a public health perspective, this is good,” said Jay Krieger, a University of Washington professor who heads the nonprofit Healthy Food America. “People are purchasing less sugary drinks, and we know that sugary drinks are associated with heart disease, diabetes, high blood pressure and strokes.”Seattle’s tax of 1.75 cents per fluid ounce, which took effect on…arrow_forwardThe questions has two parts: A departmental store sells stereo systems, television sets and radios. The percentage distribution of the total sales volume (in rupees) is estimated as 30 per cent stereos, 50 per cent televisions and 20 per cent radios. The prices of one stereo, one television and one radio in 1990 were $ 20,000, $15,000 and $ 500 respectively while their respective prices in 1995 were $25,000, $ 20,000 and $ 800. A weighted price index for 1995 with base 1990 is to be computed. (i) Which index number formula is appropriate, why? (ii) Compute the index.arrow_forwardA stock analyst wants to determine whether there is a difference in the mean rate of return for three types of stock: utility, retail, and banking stocks. The following output is obtained: Using the 0.05 level of significance, is there a difference in the mean rate of return among the three types of stock? Can the analyst conclude there is a difference between the mean rates of return for utility and retail stocks? For utility and banking stocks? For banking and retail stocks? (Negative value should be indicated by a minus sign.)arrow_forward
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