Answered

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Consider the following generic fixed effects model, along with a two-period (t = 1, 2), randomly sampled panel data set with dependent variable y and independent variable x: y_it = beta_0 + delta_0 d2_t + beta_1x_it + a_i + u_it where y_it = value of y for individual i at time t d2_t = binary variable equal to 1 in the second time period (t = 2), and 0 otherwise (t = l) x_it = value of x for individual i at time t a_i = unobserved (time-invariant) effect u_i = idiosyncratic error Taking the first difference of the model (that is, subtracting the regression equation for t=l from the regression equation for t=2) yields the following first-differenced equation: delta y_i = y_i2 - y_i1 = You now plan to use OLS to estimate your first-differenced equation, in order to obtain the first-differenced estimator. Suppose that delta x_i is correlated with delta u_i. True or False: The first-differenced estimator is unbiased.
A. True
B. False

Sagot :

Answer:

True

Step-by-step explanation:

The difference estimator is used to address the problem of omitted variables. It is used with standard fixed effects model and the data correlated is identified using regression model. The first differenced estimator used in the equation is unbiased.

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