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Comment on why there exists a trade-off between variance and bias of of OLS estimators when considering the choice of including a particular explanatory variable in your underlying model. Please keep your answer precise.
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- 1.5 Version B. Consider a panel data regression model Yit = Bo + B1 Xit + a; + eit where the unobserved heterogeneity a; is a fixed effect, and the idiosyncratic error eit is white noise. Is the random effect estimator of B1 consistent? Explain briefly.1.5 Version B. Consider a panel data regression model Yit = Bo + B1Xit + a; + eit where the unobserved heterogeneity a; is a fixed effect, and the idiosyncratic error et is white noise. Is the random effect estimator of B1 consistent? Explain briefly.Nadya is worried about poor people disproportionately exposed to pollution. She suggests the model where pollution in the area is regressed on average housing price in that area, and the number of pro-environmental voters in the area. She also knows that housing price in the area depends on pollution in the area, and the number of good schools in this area. Assuming that all the variables are significant and there are no other omitted variables affecting the dependent variables, can Nadya use Indirect Least Squares in this setting? O True O False
- 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.Which one of the following is NOT an assumption of the classical linear regression model (CLRM)? Select one: a. The disturbance terms are independent of one another. b. The dependent variable is not correlated with the disturbance terms. c. The explanatory variables are uncorrelated with the error terms. d. The disturbance terms have zero mean.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.
- Using Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatoryvariables, formulate an econometric model for data that is (i) time series data (ii)cross-sectional data and (iii) panel data – (Hint: please specify the specific model herenot its general form).Define Interpretation of coefficients in polynomial regression models?Why does dependent variables must covariate in the multivariate analyses like MANOVA/MANCOVA? What happens if they don't covariate, will you be able to proceed in multivariate analyses?
- Which of the following statements is true? a) None of the other possible answers are true. b) Under the Classical Linear Model assumptions, the OLS estimator has the highest variance among unbiased estimators. c) Taking the natural log of a non-normal distribution often yields a distribution that is closer to normal. d) The Central Limit Theorem (CLT) assumes that the dependent variable is unaffected by unobserved factors. e) The mean of a non-normal distribution is 0 and the variance is σ2.(Econmetrics) Q.1 How can you test for general misspecification of model if it would have only (any of) two independent variables?Suppose that you had data on the amount of pollution in London every year. Write down the regression equation that you would need to estimate to measure the effect of ULEZ on pollution. Describe carefully what the dependent variable, the independent variable, the unit of observation (time or location), and the main coefficient of interest are. What control variables do you think should be included in this regression?
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