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Inference on time-invariant variables using panel data: a pretest estimator

Jean-Bernard Chatelain () and Kirsten Ralf

PSE Working Papers from HAL

Abstract: For static panel data models that include endogenous time-invariant variables corre- lated with individual e¤ects, exogenous averages over time of time-varying variables can be internal instruments. To pretest their exogeneity, we .rst estimate a random e¤ects model that includes all averages over time of time-varying variables (Mundlak, 1978; Kr- ishnakumar, 2006). Internal instruments are then selected if their parameter is statistically di¤erent from zero (Mundlak, 1978; Hausman and Taylor, 1981). Finally, we estimate a Hausman-Taylor (1981) model using these internal instruments. We then evaluate the bi- ases of currently used alternative estimators in a Monte-Carlo simulation: repeated between, ordinary least squares, two-stage restricted between, Oaxaca-Geisler estimator, .xed e¤ect vector decomposition, and random e¤ects (restricted generalized least squares).

Keywords: Pretest estimator; Time-series cross-sections; Panel data; Time-invariant variables; Mundlak estimator; Hausman-Taylor estimator (search for similar items in EconPapers)
Date: 2021-01
New Economics Papers: this item is included in nep-ecm
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01719835v2
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Related works:
Journal Article: Inference on time-invariant variables using panel data: A pretest estimator (2021) Downloads
Working Paper: Inference on time-invariant variables using panel data: A pretest estimator (2021)
Working Paper: Inference on time-invariant variables using panel data: A pretest estimator (2021)
Working Paper: Inference on time-invariant variables using panel data: a pretest estimator (2021) Downloads
Working Paper: Inference on time-invariant variables using panel data: a pretest estimator (2020)
Working Paper: Inference on time-invariant variables using panel data: a pretest estimator (2020)
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