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ESTIMATION FOR DYNAMIC PANEL DATA WITH INDIVIDUAL EFFECTS

Published online by Cambridge University Press:  20 March 2019

Peter M. Robinson  and
Carlos Velasco
Peter M. Robinson*
Affiliation:
London School of Economics
Carlos Velasco
Affiliation:
Universidad Carlos III de Madrid
*
*Address correspondence to Peter M. Robinson, London School of Economics, London, UK; e-mail: [email protected].
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Abstract

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The article discusses statistical inference in parametric models for panel data. The models feature dynamics of a general nature, individual effects, and possible explanatory variables. The focus is on large-cross-section inference on Gaussian pseudo maximum likelihood estimates with temporal dimension kept fixed, partially complementing and extending recent work of the authors. We focus on a particular kind of initial condition but go on to discuss implications of alternative initial conditions. Some possible further developments are briefly reviewed.

Type
ARTICLES
Information
Econometric Theory , Volume 36 , Issue 2 , April 2020 , pp. 185 - 222
Copyright
Copyright © Cambridge University Press 2019 

Footnotes

We are grateful to Peter Phillips and three referees for constructive comments that have improved the article.

References

REFERENCES

Adenstedt, R.K. (1974) On large-sample estimation for the mean of a stationary random sequence. Annals of Statistics 6, 1095–1107.10.1214/aos/1176342867CrossRefGoogle Scholar
Anderson, T.W. & Hsiao, C. (1981) Estimation of dynamic models with error components. Journal of the American Statistical Association 76, 598–606.10.1080/01621459.1981.10477691CrossRefGoogle Scholar
Arellano, M. & Bonhomme, S. (2012) Identifying distributional characteristics in random coefficients panel data models. The Review of Economic Studies 79, 987–1020.CrossRefGoogle Scholar
Eicker, F. (1963) Asymptotic normality and consistency of the least squares estimators for families of linear regressions. Annals of Mathematical Statistics 34, 447–456.10.1214/aoms/1177704156CrossRefGoogle Scholar
Ejrnaes, M. & Browning, M. (2014) The persistent-transitory representation for earnings processes. Quantitative Economics 5, 555–581.10.3982/QE239CrossRefGoogle Scholar
Hahn, J. (1999) How informative is the initial condition in the dynamic panel model with fixed effects? Journal of Econometrics 93, 309–326.10.1016/S0304-4076(99)00013-5CrossRefGoogle Scholar
Han, C. & Phillips, P.C.B. (2013) First difference maximum likelihood and dynamic panel estimation. Journal of Econometrics 175, 35–45.CrossRefGoogle Scholar
Hassler, U., Demetrescu, M., & Tarcolea, A.L. (2011) Asymptotic normal tests for integration in panels with cross-dependent units. Advances in Statistical Analysis 95, 187–204.CrossRefGoogle Scholar
Hsiao, C. (2014) Analysis of Panel Data, 3rd ed. Cambridge University Press.10.1017/CBO9781139839327CrossRefGoogle Scholar
Hsiao, C., Pesaran, M.H., & Tahmiscioglu, A.K. (2002) Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics 109, 107–150.CrossRefGoogle Scholar
Hualde, J. & Robinson, P.M. (2011a) Gaussian pseudo-maximum likelihood estimation of fractional time series models. Annals of Statistics 39, 3152–3181.10.1214/11-AOS931CrossRefGoogle Scholar
Hualde, J. & Robinson, P.M. (2011b) Supplement to Gaussian pseudo-maximum likelihood estimation of fractional time series models. Annals of Statistics. Available at https://projecteuclid.org/download/suppdf_1/euclid.aos/1330958676.CrossRefGoogle Scholar
Jennrich, R.I. (1969) Asymptotic properties of non-linear least squares estimators. Annals of Mathematical Statistics 2, 633–643.CrossRefGoogle Scholar
Johansen, S. & Nielsen, M. (2010) Likelihood inference for a nonstationary fractional autoregressive model. Journal of Econometrics 158, 51–66.CrossRefGoogle Scholar
Johansen, S. & Nielsen, M. (2016) The role of initial values in conditional sum-of-squares estimation of nonstationary fractional time-series models. Econometric Theory 32, 1095–1139.CrossRefGoogle Scholar
Moon, H.R., Perron, B., & Phillips, P.C. (2007) Incidental trends and the power of panel unit root tests. Journal of Econometrics 141, 416–459.CrossRefGoogle Scholar
Moon, H.R., Perron, B., & Phillips, P.C.B. (2015) Incidental parameters and dynamic panel models. In Baltagi, B.H. (ed.), The Oxford Handbook of Panel Data, pp. 111–148. Oxford University Press.Google Scholar
Moon, H.R. & Phillips, P.C.B. (1999) Maximum likelihood estimation in panels with incidental trends. Oxford Bulletin of Economics and Statistics 61, 711–747.10.1111/1468-0084.61.s1.17CrossRefGoogle Scholar
Nagar, A.L. (1959) The bias and moment matrix of the general k-class estimators of the parameters in simultaneous equations. Econometrica 27, 575–595.CrossRefGoogle Scholar
Neyman, J. & Scott, E. (1948) Consistent estimates based on partially consistent observations. Econometrica 16, 1–31.CrossRefGoogle Scholar
Robinson, P.M. (1987) Asymptotically efficient estimation in the presence of heteroskedasticity of unknown form. Econometrica 55, 875–891CrossRefGoogle Scholar
Robinson, P.M. & Velasco, C. (2015) Efficient inference on fractionally integrated panel data models with fixed effects. Journal of Econometrics 185, 435–452.CrossRefGoogle Scholar
Robinson, P.M. & Velasco, C. (2017) Inference on trending panel data. Journal of Econometrics, forthcoming.Google Scholar
Stone, C.J. (1975) Adaptive maximum likelihood estimators of a location parameter. Annals of Statistics 3, 267–284.10.1214/aos/1176343056CrossRefGoogle Scholar