Short Answer 2 Consider the market equilibrium model on the regression practice prob- lems where prices and quantities are determined jointly by the intersection of the supply and demand curves. We showed that, in this case, OLS of Q on P does not recover the supply nor demand elasticity. A solution to this endogeneity problem is an instrument. One popular instrument for a firm's price setting decision is the characteristics of products produced by rival firms. Why do you think such an instrument would be relevant? Do you think such an instrument would satisfy the exclusion restriction? Why?

Short Answer 2 Consider the market equilibrium model on the regression practice prob- lems where prices and quantities are determined jointly by the intersection of the supply and demand curves. We showed that, in this case, OLS of Q on P does not recover the supply nor demand elasticity. A solution to this endogeneity problem is an instrument. One popular instrument for a firm's price setting decision is the characteristics of products produced by rival firms. Why do you think such an instrument would be relevant? Do you think such an instrument would satisfy the exclusion restriction? Why?

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

See similar textbooks

Similar questions

3
Imagine you are an economist working for the Government of Econville. You are tasked with developing a model to predict the GDP of the country based on various factors such as interest rates, inflation, unemployment rate, and population growth. You collect quarterly data for the past 20 years and start building your model. After running your initial regression, you notice some peculiar patterns in the residuals: (1) residuals do not have identical variances across different levels of the independent variables; (2) two or more independent variables in a regression model are highly correlated with each other; (3) the correlation of a variable with its own past values. You suspect that your model might be suffering from 3 potential issues in the regression analysis that can affect reliability and validity. List 2 factors in your model that might be causing the Heteroscedasticity and give a reason
Other Companies (Part 2) You directed your research department to do some research on the demand for Tesla sedans. They selected BMW i3 Sedans and Chevy Bolts as comparative offerings. Using regression analysis, the research department comes up the following estimate for yearly demand. Qx = -40,000 -1*Px +0.02*M +2*PB +2*PC Where: Px = $70,000, M = $150,000, PB = $65,000, PC = $40,000 a. Is the own price elasticity of demand for Tesla sedans at the point defined above elastic or inelastic? If Mr. Musk decides to raise his prices, what will happen to his revenue. b. PB and PC represent the price for i3 sedans and Bolt sedans respectively. Are these items compliments or substitutes when compared to Teslas? Give evidence to support your answer. c. Is the demand for Tesla sedans elastic or inelastic to price changes of BMW i3 and Bolt at the price points given in the problem? Interpret the result you find and explain what it means.
Econometrics question
Imagine you are an economist working for the Government of Econville. You are tasked with developing a model to predict the GDP of the country based on various factors such as interest rates, inflation, unemployment rate, and population growth. You collect quarterly data for the past 20 years and start building your model. After running your initial regression, you notice some peculiar patterns in the residuals: (1) residuals do not have identical variances across different levels of the independent variables; (2) two or more independent variables in a regression model are highly correlated with each other; (3) the correlation of a variable with its own past values. You suspect that your model might be suffering from 3 potential issues in the regression analysis that can affect reliability and validity. Based on Addressing Heteroscedasticity list one test you would employ to test this potential issue?
It is known that beef increased its weekly demand from 70 to 85 tons/week (although its price remained unchanged) when the price of pork increased from $45 to $65/kg. Determine a) The linear model where the demand “Qx” s for beef depends on the price of pork, in its form Qx = mPy + b; any other way of representing the model will not be evaluated.b) The type of elasticity of beef with respect to pork c)The coefficient of elasticity d)How much is Exy worth when 90 tons/week of beef is demanded?How much will the variation in the price of pork affect the income of beef producers?
Define Interpretation of coefficients in polynomial regression models?
Imagine you are trying to explain the effect of square footage on home sale prices in the United States. You collect a random sample of 100,000 homes that recently sold. a) Homes can be one of three types: single-family houses, townhomes, or condos. How would you control for a home’s type in a regression model? b) Write down a regression model that includes controls for home type, square footage, and number of bedrooms. c) How would you interpret the es3mated coefficients for each of the variables from part b? Be specific.
Please answer all three sub-sections of this question
5. Confounding variables and multiple regressions Suppose you are interested in studying the effect of square footage on the price of houses. You propose the following regression of housing prices on square footage: price - Bo + P sqft + u where price the price of the house. sqft = the square footage of the house residual Failing to account for the number of bathrooms in a house, which may influence housing prices and may be positively correlated with square footage, could lead to estimate of the effect . This issue of confounding variables would likely bias the estimate of
The Physics Club sells E = mc2 T-shirts at the local flea market. Unfortunately, the club's previous administration has been losing money for years, so you decide to do an analysis of the sales. A quadratic regression based on old sales data reveals the following demand equation for the T-shirts. q = −2p2 + 30p (9 ≤ p ≤ 15) Here, p is the price the club charges per T-shirt, and q is the number it can sell each day at the flea market. (a) Obtain a formula for the price elasticity of demand for E = mc2 T-shirts. E = (b) Compute the elasticity of demand if the price is set at $9 per shirt. (Round your answer to two decimal places.) Interpret the result. The demand for E = mc2 T-shirts is going down by about ____% per 1% increase in the price. (c) How much should the Physics Club charge for the T-shirts to obtain the maximum daily revenue? $ What will the revenue be? $
What are the four assumptions of linear regression (simple linear and multiple)?