ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN: 9780190931919
Author: NEWNAN
Publisher: Oxford University Press
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- In 2017, Philadelphia launched a sweetened beverage tax of 1.5 cents per ounce, raising the cost of a 2-liter soda bottle from about $1.50 to $2.50. One year later, the Philadelphia mayor wants to evaluate if this "sugar tax" improves the health status of Philadelphia
Propose ONE method (i.e. difference-in-difference, instrumental variables, or regression discontinuity) to address these questions. write down its implementation details (the type of data you need, potential sources to get the data, equations) its pros and cons
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- When Y is regressed on X, B, > 0, sx+ 0, sy # 0, and the fraction of the variation in Y explained by the least-squares regression of Y on X does not equal 1. In this example, the sum of the squares of the deviations of the actual Y-values from their mean would definitely be greater than the sum of the squares of the deviations of the predicted Y-values from their mean. 1 A) B) true false 4. When Y is regressed on X, the sample slope is negative, sx + 0, sy + 0, and Y; = Y; for every observation. In this example, the sum of the squares of the deviations of the predicted Y-values from their mean would definitely be less than the sum of the squares of the deviations of the actual Y-values from their mean. A) В) true false 3.arrow_forwardProve that the slope of the sample regression function (beta2) is the BLUE if the assumptions of Gauss Marko theorem are satisfied make sure to show all the steps and the underlying assumptionsarrow_forwardConsider the population regression of log earnings [Y;, where Y,= In(Earnings,;)] against two binary variables: whether a worker is married (D₁, where D₁;= 1 if the th person is married) and the worker's gender (D2;, where D₂;= 1 if the th person is female), and the product of the two binary variables Y₁ = Po+B₁D₁+P₂D2i + P3 (D₁¡ × D₂i) + Hi- The interaction term: O A. indicates the effect of being married on log earnings. B. does not make sense since it could be zero for married males. C. allows the population effect on log earnings of being married to depend on gender. D. cannot be estimated without the presence of a continuous variable.arrow_forward
- (Yi, X1i, X2i) satisfy the assumptions of the attachment. You are interestedin β1, the causal effect of X1 on Y. Suppose that X1 and X2 are uncorrelated.You estimate β1 by regressing Y onto X1 (so that X2 is not included in theregression). Does this estimator suffer from omitted variable bias? Explain.arrow_forwardThe model initial setup is• The number of vacancies posted in the economy during a particular month is v = 100.• There were initially u = 225 unemployed workers at the beginning of the month.• Suppose that the average wage is 0.6 relative to their productivity. Unemployed workersreceive benefits that are half the wage, i.e., b = 0.3 relative to productivity.• Suppose that the number of matches between firms and workers are given by thefollowing matching functionsM = Au^0.5v^0.5• Suppose that 45 workers were able to find a job by the end of the month.Answer the following questions.a) What is the monthly job finding rate?b) What is the probability that an average vacancy is filled in a month?c) What is the job creation cost, k?d) What is the value of A?e) Explain how introducing a searching cost to this model would affect the queue length,the number of vacancy and unemployment rate, and wage.arrow_forward19. The White test test statistic is n*R² ~x²(S-1). Where is the R² in the test statistic measured? A. The original econometric model when estimated using the White Robust Estimator B. The average from all the auxiliary regressions estimated with each explanatory variable as a function of the other explanatory variables C. The original econometric model before any test of heteroskedasticity has been performed D. The auxiliary regression of residuals as a function of the explanatory variables generating the heteroscedasticity 20. With annual times series data of 50 observations, how many observations are available to estimate the consumption econometric model CONt = Bo+ ß₁DISPYt + B₂CONt-1+ut A. 50 B. 47 C. 45 D. 49 21. Suppose the estimated simple linear demand equation for single-game tickets for a major football league is q=4.58-0.51p where q is the number of tickets sold measured in thousands and p is the dollar price of a ticket. Further assume that the point of the means_is…arrow_forward
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