Suppose a development economist is trying to estimate the demand for locally produced sesame oil in India. Assuming a st

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Suppose A Development Economist Is Trying To Estimate The Demand For Locally Produced Sesame Oil In India Assuming A St 1 (45.9 KiB) Viewed 25 times

Suppose a development economist is trying to estimate the demand for locally produced sesame oil in India. Assuming a standard model of supply and demand, access to weekly data on purchase prices and quantities over multiple years, you would suggest that the economist should use OOLS to estimate the linear regression of quantity on price. a linear regression of quantity on price using price of peanut oil, a common substitute for mustard oil used in cooking, as an IV. a linear regression of quantity on price using the amount of rainfall in the main sesame plant-cultivation regions as an IV. O a linear regression of quantity on price using the net population growth rate as an IV.

Consider a labor economist trying to estimate the return to immigrants' English language proficiency. The economist has evidence that measurement error is present in the measure of English proficiency included in her data set. She assumes that the reported language proficiency takes the form lang: = langi + ni, where ni NO, ) is the measurement error and lang, is the true measure of language proficiency. Assuming that the model specification is not an issue, if she wants to obtain a consistent estimate of return to language proficiency she can estimate her model using OLS. can estimate her model using OLS, but the standard errors on the coefficients will be biased. needs to find an instrumental variable for language proficiency. needs to find an instrumental variable for language proficiency, though the standard errors on the coefficients will be biased.

Suppose an policy researcher is concerned about the effect of a training program participation on the monthly earnings of workers. He is trying to estimate an equation log(earn;) = Bo + Bitrain; + B2 educ; + Wig where train; is an indicator for training participation, educ; is the years of education completed. The researcher would be able to estimate this equation and obtain consistent coefficient estimates by using the distance from a worker's home to the nearest training center as an IV for training. O by using the worker's employment status in the previous month as an IV for training. by using the worker's total income in the previous month as an IV for training. in none of the above cases, as they do not completely address the endogeneity in the model.