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Questions › GATE › GATE 2024 › Q39
1 markEconometrics › Data types and panel data › Panel data: fixed and random effectsHardabout 2 min

GATE 2024 Question 39: Data types and panel data

Consider a simple pooled regression model: yit=β0+β1xit+vity_{it} = \beta_0+\beta_1x_{it}+v_{it}yit​=β0​+β1​xit​+vit​ where vit=μi+ϵitv_{it}=\mu_i+\epsilon_{it}vit​=μi​+ϵit​ and Cov(xit,μi)≠0Cov(x_{it},\mu_i)\ne 0Cov(xit​,μi​)=0. Here, μi\mu_iμi​ captures the unknown individual specific effects and ϵit\epsilon_{it}ϵit​ is the idiosyncratic error uncorrelated with both xitx_{it}xit​ and μi\mu_iμi​. If the parameters of this model are estimated using the ordinary least squares (OLS) method, then the estimated slope coefficient will be

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Consider a simple pooled regression model: yᵢₜ = β₀+β₁xᵢₜ+vᵢₜ where vᵢₜ=μᵢ+ϵᵢₜ and Cov(xᵢₜ,μᵢ)≠ 0. Here, μᵢ captures the unknown individual specific effects and ϵᵢₜ is the idiosyncratic error uncorrelated with both xᵢₜ and μᵢ. If the parameters of this model are estimated using the ordinary least squares (OLS) method, then the estimated slope coefficient will be (A) biased (B) inconsistent (C) unbiased but consistent (D) unbiased but efficient

Also written as: Consider a simple pooled regression model: y_(it) = beta_0+beta_1x_(it)+v_(it) where v_(it)=mu_i+epsilon_(it) and Cov(x_(it),mu_i)!= 0. Here, mu_i captures the unknown individual specific effects and epsilon_(it) is the idiosyncratic error uncorrelated with both x_(it) and mu_i. If the parameters of this model are estimated using the ordinary least squares (OLS) method, then the estimated slope coefficient will be

Data types and panel data has come up 5 times in 4 exams since 2015.

What this question tests

This question is on Panel data: fixed and random effects, part of Data types and panel data in Econometrics.

Models for data on the same units over time, and how to choose between them.

TestStop has 2 past-paper questions on this subtopic.

Take this paper as a timed mockMore on Panel data: fixed and random effects

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