The following model studies human welfare using the General Social Survey in the US: happy = 0.014 +0.209regattend + 0.103occattend + 0.027income + 0.009educ +0.003 female where happy is a dummy variable equal to one if a person is happy, and 0 otherwise: regattend is a dummy variable equal to one if a person regularly attends church, and 0 otherwise: occattend is a dummy variable equal to one if a person occasionally attends church, and 0 otherwise; income is family income in tens of thousands : educ is years of schooling: female = 1 if female. = 0 otherwise Interpret the impact of religion on happiness.

The following model studies human welfare using the General Social Survey in the US: happy = 0.014 +0.209regattend + 0.103occattend + 0.027income + 0.009educ +0.003 female where happy is a dummy variable equal to one if a person is happy, and 0 otherwise: regattend is a dummy variable equal to one if a person regularly attends church, and 0 otherwise: occattend is a dummy variable equal to one if a person occasionally attends church, and 0 otherwise; income is family income in tens of thousands : educ is years of schooling: female = 1 if female. = 0 otherwise Interpret the impact of religion on happiness.

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

Consider the following unobserved effects model: Yit =B₁ it1 + ... +ßkxitk + ai + Uit You plan on using fixed effects to estimate the model. Suppose you have a panel data set consisting of 10 individuals over 6 years. However, you are missing the last 3 years of data for the third, ż = 3, individual in your data set. Your panel data set has total observations. Suppose the reason individual i is missing data for certain time periods (called attrition) is correlated with the idiosyncratic error, uit. Recall that a; is assumed to be uncorrelated with the idiosyncratic error, Uit. This correlation cause the fixed effects estimators to be biased.
Don't use chat gpt please
Please show how to do b) and c). Quantity beef consumed is the dependent variable. Each of the others are the independent variables
look at the influence of mileage on the sale price of each brand ofautomobile. Postulate the following statistical models,?_ℎ????? = ?0 + ?1?????? + ?? and ?_?ℎ??? = ?0 + ?1?????? + ?? with ??~?(0, ?2).For each model (‘model_honda’ and ‘model_chev’) perform the following,Comment on the miles variable after examining it with hist() and summary() commands.What does the assumption of non-random independent variable imply about how thedata must be collected if the same miles variable is used for both brand of automobile?
If in the study results obtained a demand and supply model for ties and suits: Demand for tie: Qdt = 410 – 5Pt – 2Ps Supply of tie: Qst = – 60 + 3Pt Demand for suit: Qds= 295 – Pt – 3Ps Supply of suit: Qss=–120 + 2Ps Based on the estimation results, then: a. Determine the general equilibrium price of a tie and suit b. What is the type of relationship between a tie and a suit? Explain your argument
Let wage denote hourly wages, educ denote years of education, and define the dummy variable: if educ > 12 D = if educ < 12 i.e. we can think of D as a dummy variable indicating graduation from high school. Suppose we want to test the null hypothesis that the marginal return to education for every year after high school is the same as the marginal return to education for each year before high school (against the alternative that they are different). Which model and test would accomplish this goal? O a. Estimate wage = B1 + B2 educ + ß3 D + e and test Ho : ß3 = B2 against H1 : ß3 # B2. O b. Estimate wage = ß1 + B2educ + ß3 D + e and test Ho : ß3 = 0 against H1 : ß3 # 0. Estimate wage = B1 + B2educ + B3(educ + D) + e and test Ho : ß3 = 62 against H1 : B3 # B2. O d. Estimate wage = B1 + B2educ + B3(D × (educ – 11)) + e and test Ho : ß3 = B2 against H : B3 # B2. c. O e. Estimate wage = Bi + B2educ + ß3(D × (educ – 11)) + e and test Ho : ß3 = 0 against H1 : ß3 + 0.
Trigleater is a hungry individual in the Grossman model deciding what to have for dinner is looking at variable options. Trigleater has a special condition called "Eaterblood" where whatever she eats will affect her health almost immediately. The following table reflects the options she is considering and the effect on health Meal Home Good Z Health H Steak and eggs +9 -4 Kale salad and broccoli -5 +18 Double cheeseburger deluxe with coke 12 -18 If Trigleater's single period utility function is given by U=5Z+2H and she can only select one item from the table above. Allpositive is a new promising pharmaceutical company came with a new supplement "Bestofboth" that will halve the negative health effect and at the same time double the positive health…
please review the second question about pareto efficeincy
Suppose that I am willing to pay $400 for anti-lock brakes that reduce my chance of dying in a car accident from 9 in 10,000 (0.0009) to 5 in 10,000, (0.0005). Based on this choice, what would be an estimate of the minimum value that I place on a statistical life? Show your work
The following model can be used to study whether campaign expenditures affect election outcomes: vote A = Bo + Bilog(expendA) + B₂log (expendB) + 33prtystrA + u where vote is the percentage of the vote received by Candidate A, expendA and expendB are campaign expenditures by Candidates A and B, and prtystrA is a mea- sure of party strength for Candidate A (the percentage of the most recent presidential vote that went to A's party). 1. What is the interpretation of ₁? 2. In terms of the parameters, state the null hypothesis that a 1% increase in A's expenditures is offset by a 1% increase in B's expenditures. 3. Estimate the given model using the data in VOTE1.dta (from Wooldridge) and report the results in usual form. Do A's expenditures affect the outcome? What about B's expenditures? Can you use these results to test the hypothesis in part 2?
Suppose we are interested in evaluating the impact on wages of being a college graduate and of residing in California. To this end we define the following dummy variables if college graduate if not college graduate coll = ncoll = if not college graduate if college graduate 1 cali = if residing in California S 1 if not residing in California ncali = if not residing in California if residing in California and for wages denoting yearly wages, we estimate the following model of returns to education wages = B1 coll+ B2ncoll + B3 cali + B4(coll x cali) + e where E[e|coll, cali] = 0. Which parameter or combination of parameters measures the increase in expected wages from obtaining a college degree (comparing to not having a college degree) when residing California? O a. None of the other options is correct O b. Bi – B2 O c. B1 – B2 + ß4 O d. B4 O e. Bi + B3 – ßi – B4 O f. Bi + B4 – ß2 – B4 Clear my choice
Econometrics Thomas Eisensee and David Stromberg wanted to measure how much news coverage of a foreign disaster impacted the amount of disaster relief provided by the U.S. government. They argue that the simple relationship would be biased. Let X = Minutes of News Coverage and Y= Disaster Aid. Choose a variable X2 that could bias the simple relationship. This variable should impact the amount of coverage and impact the amount of aid for reasons other than purely news coverage. Eisensee and Stromberg introduce an instrument Z = During the Olympics. Explain how Z could satisfy the relevant and exogenous criteria. Explain how you could use Z to estimate the impact of X on Y free from X2 bias. Hint: you should mention two stages.