Fixed effects model with three time periods Consider the following general fixed effects model for use with a panel data set with three time periods (T = 3): yir = 51 +82 d2: +63 d31 + ẞ1x11 + ... + ẞkxisk + Vit where, for t=1, 2, 3, and time period 1 is the base year: yir = value of dependent variable y for i, in year t, in pounds d2, 1 in the second time period (t = 2), and 0 otherwise d3, =1 in the third time period (t = 3), and 0 otherwise Xirl,..., Xink value of explanatory variables for individual i at time f Vir = composite error consisting of the unobserved, time-constant effect (a) and the idiosyncratic error (uir) If there are 106 cross-sectional units in your balanced panel data set, then the total number of observations you have in your data set is For the first time period (1), the intercept is Which of the following would cause pooled OLS estimation of the model to yield biased and consistent estimators? Check all that apply. Measurement error in any explanatory variable under the classical errors in variables (CEV) assumption a, being uncorrelated with Xit Omitting a time-varying variable that influences y and is correlated with one of the explanatory variables

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Fixed effects model with three time periods
Consider the following general fixed effects model for use with a panel data set with three time periods (T = 3):
yir = 51 +82 d2: +63 d31 + ẞ1x11 + ... + ẞkxisk + Vit
where, for t=1, 2, 3, and time period 1 is the base year:
yir = value of dependent variable y for i, in year t, in pounds
d2, 1 in the second time period (t = 2), and 0 otherwise
d3, =1 in the third time period (t = 3), and 0 otherwise
Xirl,..., Xink value of explanatory variables for individual i at time f
Vir = composite error consisting of the unobserved, time-constant effect (a) and the idiosyncratic error (uir)
If there are 106 cross-sectional units in your balanced panel data set, then the total number of observations you have in your data set is
For the first time period (1), the intercept is
Which of the following would cause pooled OLS estimation of the model to yield biased and consistent estimators? Check all that apply.
Measurement error in any explanatory variable under the classical errors in variables (CEV) assumption
a, being uncorrelated with Xit
Omitting a time-varying variable that influences y and is correlated with one of the explanatory variables
Transcribed Image Text:Fixed effects model with three time periods Consider the following general fixed effects model for use with a panel data set with three time periods (T = 3): yir = 51 +82 d2: +63 d31 + ẞ1x11 + ... + ẞkxisk + Vit where, for t=1, 2, 3, and time period 1 is the base year: yir = value of dependent variable y for i, in year t, in pounds d2, 1 in the second time period (t = 2), and 0 otherwise d3, =1 in the third time period (t = 3), and 0 otherwise Xirl,..., Xink value of explanatory variables for individual i at time f Vir = composite error consisting of the unobserved, time-constant effect (a) and the idiosyncratic error (uir) If there are 106 cross-sectional units in your balanced panel data set, then the total number of observations you have in your data set is For the first time period (1), the intercept is Which of the following would cause pooled OLS estimation of the model to yield biased and consistent estimators? Check all that apply. Measurement error in any explanatory variable under the classical errors in variables (CEV) assumption a, being uncorrelated with Xit Omitting a time-varying variable that influences y and is correlated with one of the explanatory variables
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