Hausman and Taylor Estimator Analysis on The Linear Data Panel Model
Keywords:
Panel Data, Panel Data; Estimator, Hausman and Taylor, Consistency
Abstract
Panel data modelling in the field of econometrics applies two main approaches, namely fixed effect estimators and random effects. The application of the Hausman and Taylor estimator to real data is used to test for fixed effects or random effects based on the idea that the set of estimated coefficients obtained from the fixed effect estimates is taken as a group. A good estimator is an estimator that is as close as possible to represent the characteristics of the population. The characteristics of a good estimator include unbiasedness, efficiency, and consistency. The purpose of this study is to identify the properties of the Hausman and Taylor estimator in the linear model of panel data. Based on the analysis using panel data, it is found that the Hausman and Taylor estimator on the random effects panel data is an estimator that is consistent and efficient even though it is not unbiased.
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Ahn, S. C. and Schmidt, P. (2019). Efficient Estimation of Models for Dynamic Panel Data. Arizona State University, pages 1–30.
Arellano, M. (1993). On The Testing of Correlated Effects with Panel Data. Journal of Econometrics, 59(1-2):87–97.
Baltagi, B. and Bresson, G. (2012). A Robust Hausman-Taylor Estimator.
Baltagi, B. H., Bresson, G., and Pirotte, A. (2003). Fixed Effects, Random Effects or Hausman-Taylor? A Pretest Estimator.
Economics Letters, 79(3):361–369.
Baltagi, B. H., Egger, P., and Kesina, M. (2014). Firm-Level Productivity Spillovers in China’s Chemical Industry: A Spatial
Hausman-Taylor Approach. CESifo Working Paper, 5114:1–37.
Baltagi, B. H. and KhantiAkom, S. (1990). On Efficient Estimation with Panel Data: An Empirical Comparison of Instrumental
Variables Estimators. Journal of Applied Econometrics, 5(4):401–406.
Baltagi, B. H. and Liu, L. (2012). The Hausman-Taylor Panel Data Model with Serial Correlation. Statistics and Probability Letters,
82(7):1401–1406.
Chan, F. K., So, H. C., Zheng, J., and Lui, K. W. (2008). Best linear Unbiased Estimator Approach for Time-Of-Arrival Based
Localisation. IET Signal Processing, 2(2):156–162.
Chapman, D. G. and Robbins, H. (1951). Minimum Variance Estimation Without Regularity Assumptions. The Annals of Mathematical Statistics, 22(4):581–586.
Cng, H. C., Th, ., Ngc, B., Th, B., and Linh, n. H. (2013). Trade Liberalization and Foreign Direct Investment in Vietnam : A
Gravity Model Using Hausman - Taylor Estimator Approach M t cach ti p c n th ´ ong qua m ˆ o h ˆ ` ınh L c h p d n. Journal of
Science and Development, 11(1):85–96.
Egger, P. and Pfaffemayr, M. (2001). Distance, Trade and FDI: A Hausman-Taylor SUR Approach. WIFO Working Papers,
164:1–27.
Elhorst, J. P. (2014). Spatial Panel Data Models.
Frondel, M. and Vance, C. (2010). Fixed, Random, or Something in Between? A Variant of HAUSMAN’s Specification Test for
Panel Data Estimators. Ruhr Economic Papers, 160:1–13.
Gardebroek, C. and Lansink, A. O. (2003). Estimating Farm Productivity Differentials Using Panel Data: The Hausman-Taylor
Approach. Journal of Agricultural Economics, 54(3):397–415.
Greene, W. H. (2018). Econometric Analysis. Pearson Education, Inc., New York, 8 edition.
Kojima, Y., Parcell, J., Cain, J., Kojima Charles, Y. H., Parcell, J., and Cain, J. (2016). A Global Demand Analysis of Vegetable
Oils for Food and Industrial Use: A Cross-Country Panel Data Analysis with Spatial Econometrics. Agricultural & Applied
Economics Association, pages 0–27.
Maani, S., Wang, X., and Rogers, A. (2015). Network Effects, Ethnic Capital and Immigrants’ Earnings Assimilation: Evidence
From a Spatial, Hausman-Taylor Estimation. IZA Discussion Paper, (9308).
Millo, G. and Piras, G. (2012). Splm: Spatial Panel Data Models in R. Journal of Statistical Software, 47(1).
Sarafidis, V. and Wansbeek, T. (2010). Cross-Sectional Dependence in Panel Data Analysis. MPRA Paper, 20367(75086):1–44.
Xu, Y. and Li, A. (2020). The Relationship Between Innovative Human Capital and Interprovincial Economic Growth Based on
Panel Data Model and Spatial Econometrics. Journal of Computational and Applied Mathematics, 365:112381.
Yusra, I., Hadya, R., Begawati, N., Istiqomah, L., Afriyeni, and Kurniasih, N. (2019). Panel Data Model Estimation: The Effect
Of Managerial Ownership, Capital Structure, and Company Size on Corporate Value. Journal of Physics: Conference Series,
1175(1).
Published
2021-11-10
How to Cite
[1]
B. Utami, A. Irawan, M. Gumanti, and G. Primajati, “Hausman and Taylor Estimator Analysis on The Linear Data Panel Model”, Jurnal Varian, vol. 5, no. 1, pp. 81 - 88, Nov. 2021.
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