Abstract
Professor A.L. Nagar was a world-renowned econometrician and an international authority on finite sample econometrics with many path-breaking papers on the statistical properties of econometric estimators and test statistics. His contributions to applied econometrics have been also widely recognized. Nagar’s 1959 Econometrica paper on the so-called k-class estimators, together with a later one in 1962 on the double-k-class estimators, provided a very general framework of bias and mean squared error approximations for a large class of estimators and had motivated researchers to study a wide variety of issues such as many and weak instruments for many decades to follow. This paper reviews Nagar’s seminal contributions to analytical finite sample econometrics by providing historical backgrounds, discussing extensions and generalization of Nagar’s approach, and suggesting future directions of this literature.
Similar content being viewed by others
Notes
References
Abadir, K.M. 1993. OLS bias in a nonstationary regression. Econometric Theory 9 (1): 81–93.
Anderson, T.W., and H. Rubin. 1949. Estimation of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics 20 (1): 46–63.
Anderson, T.W., and T. Sawa. 1973. Distributions of estimates of coefficients of a single equation in a simultaneous system and their asymptotic expansions. Econometrica 41 (4): 683–714.
Angrist, J.D., and J. Pischke. 2009. Mostly harmless econometrics: an empiricist’s companion. Princeton: Princeton University Press.
Bao, Y. 2013. Finite-sample bias of the QMLE in spatial autoregressive models. Econometric Theory 29 (1): 68–88.
Bao, Y., and R. Kan. 2013. On the moments of ratios of quadratic forms in normal random variables. Journal of Multivariate Analysis 117: 229–245.
Bao, Y., and A. Ullah. 2007a. Finite sample properties of maximum likelihood estimator in spatial models. Journal of Econometrics 137 (2): 396–413.
Bao, Y., and A. Ullah. 2007b. The second-order bias and mean squared error of estimators in time-series models. Journal of Econometrics 140 (2): 650–669.
Bao, Y., and A. Ullah. 2009. On skewness and kurtosis of econometric estimators. The Econometrics Journal 12 (2): 232–247.
Bao, Y., and A. Ullah. 2010. Expectation of quadratic forms in normal and nonnormal variables with applications. Journal of Statistical Planning and Inference 140 (5): 1193–1205.
Bao, Y., A. Ullah, and R. Zhang. 2014. Moment approximation for least-squares estimator in first-order regression models with unit root and nonnormal errors. Advances in Econometrics 33: 65–92.
Bao, Y., A. Ullah, and Y. Wang. 2019. Distribution of the mean reversion estimator in the Ornstein-Uhlenbeck process. Econometric Reviews 36 (6–9): 1039–1056.
Bao, Y., X. Liu, and A. Ullah. 2021. On the exact statistical distribution of econometric estimators and test statistics. In Advances in statistics-theory and applications, ed. I. Ghosh, N. Balakrishnan, and T. Ng, 119–131. Berlin: Springer.
Basmann, R.L. 1961. A note on the exact finite sample frequency functions of generalized classical linear estimators in two leading over-identified cases. Journal of the American Statistical Association 56 (295): 619–636.
Bekker, P.A. 1994. Alternative approximations to the distributions of instrumental variable estimators. Econometrica 62 (3): 657–681.
Bhattacharya, R.N., and J.K. Ghosh. 1978. On the validity of the formal Edgeworth expansion. Annals of Statistics 6 (2): 434–451.
Chu, J., T.-H. Lee, A. Ullah, and H. Xu. 2021. Exact distribution of the f-statistic under heteroskedasticity of unknown form for improved inference. Journal of Statistical Computation and Simulation 91 (9): 1782–1801.
Donald, S.G., and W.K. Newey. 2001. Choosing the number of instruments. Econometrica 69 (5): 1161–1191.
Dwivedi, T.D., and V.K. Srivastava. 1984. Exact finite sample properties of double \(k\)-class estimators in simultaneous equations. Journal of Econometrics 25 (3): 263–283.
Edgeworth, F.Y. 1896. The asymmetrical probability curve. Philosophical Magazine Series 41 (249): 90–99.
Edgeworth, F.Y. 1905. The law of error. Transactions of the Cambridge Philosophical Society 20 (36–65): 113–141.
Fisher, R.A. 1921. On the probable error of a coefficient of correlation deduced from a small sample. Metron 1: 3–32.
Fisher, R.A. 1922. The goodness of fit of regression formulae and the distribution of regression coefficients. Journal of the Royal Statistical Society 85 (4): 597–612.
Fisher, R.A. 1928. The general sampling distribution of the multiple correlation coefficient. Proceedings of the Royal Society A 121 (788): 654–673.
Fisher, R.A. 1935. The mathematical distributions used in the common tests of significance. Econometrica 3 (4): 353–365.
Forchini, G. 2002. The exact cumulative distribution function of a ratio of quadratic forms in normal variables, with application to the AR (1) model. Econometric Theory 18 (4): 823–852.
Franguridi, G., B. Gafarov, and K. Wüthrich. 2021. Conditional quantile estimators: a small sample theory. CESifo Working Paper Series 9046, CESifo. https://www.cesifo.org/DocDL/cesifo1_wp9046.pdf.
Fuller, W.A. 1977. Some properties of a modification of the limited information estimator. Econometrica 45 (4): 939–953.
Gil-Pelaez, J. 1951. Note on the inversion theorem. Biometrika 38 (3–4): 481–482.
Götze, F. 1987. Approximations for multivariate \(U\) -statistics. Journal of Multivariate Analysis 22 (2): 212–229.
Gupta, Y.P., and A. Ullah. 1970. A note on the moments of the Wald’s estimator. Statistica Neerlandica 24 (3): 109–123.
Gurland, J. 1948. Inversion formula for the distribution of ratios. Annals of Mathematical Statistics 19 (2): 228–237.
Haavelmo, T. 1947. Methods of measuring the marginal propensity to consume. Journal of the American Statistical Association 42 (237): 105–122.
Hahn, J., and W. Newey. 2004. Jackknife and analytical bias reduction for nonlinear panel models. Econometrica 72 (4): 1295–1319.
Hahn, J., J. Hausman, and G. Kuersteiner. 2004. Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations. The Econometrics Journal 7 (1): 272–306.
Hall, P. 1992. The bootstrap and Edgeworth Expansion. New York: Springer-Verlag.
Harding, M., J. Hausman, and C.J. Palmer. 2016. Finite sample bias corrected IV estimation for weak and many Instruments. Advances in Econometrics 36: 245–273.
Hashiguchi, H., N. Takayama, and A. Takemura. 2018. Distribution of the ratio of two Wishart matrices and cumulative probability evaluation by the holonomic gradient method. Journal of Multivariate Analysis 165: 270–278.
Hillier, G., and R. Kan. 2021a. Moments of a Wishart matrix. Journal of Quantitative Economics (this issue).
Hillier, G., and R. Kan. 2021b. Properties of the inverse of a noncentral Wishart matrix. Econometric Theory (forthcoming).
Hillier, G., T.W. Kinal, and V.K. Srivastava. 1984. On the moments of ordinary least squares and instrumental variables estimators in a general structural equation. Econometrica 52 (1): 185–202.
Hillier, G., R. Kan, and X. Wang. 2009. Computationally efficient recursions for top-order invariant polynomials with applications. Econometric Theory 25 (1): 211–242.
Hillier, G., R. Kan, and X. Wang. 2014. Generating functions and short recursions, with applications to the moments of quadratic forms in noncentral normal vectors. Econometric Theory 30 (2): 436–473.
Horowitz, J.L. 2001. The bootstrap. In Handbook of econometrics, vol. 5, ed. J. Heckman and E. Leamer, 3159–3228. Amsterdam: Elsevier.
Hurwicz, L. 1950. Least squares bias in time series. In Statistical inference in dynamic economic models, ed. T.C. Koopmans, 365–383. New York: Wiley.
Imhof, J.P. 1961. Computing the distribution of quadratic forms in normal variables. Biometrika 48 (3–4): 419–426.
Kabe, D.G. 1963. A note on the exact distributions of the gcl estimators in two leading over identified cases. Journal of the American Statistical Association 58 (302): 535–537.
Kabe, D.G. 1964. On the exact distributions of the GCL estimators in a leading three-equation case. Journal of the American Statistical Association 59 (307): 881–894.
Kadane, J.B. 1971. Comparison of k-class estimators when the disturbances are small. Econometrica 39 (5): 723–737.
Kakwani, N.C. 1967. The unbiasedness of Zellner’s seemingly unrelated regression equations estimators. Journal of the American Statistical Association 62 (317): 141–142.
Kakwani, N.C. 1971. The bias of the three-stage least-squares estimators in simultaneous equations. Australian Journal of Statistics 13: 19–26.
Kinal, T.W. 1980. The existence of moments of \(k\)-class estimators. Econometrica 48 (1): 241–249.
Kiviet, J.F., and G.D.A. Phillips. 1993. Alternative bias approximations in regressions with a lagged-dependent variable. Econometric Theory 9 (1): 62–80.
Kiviet, J.F., and G.D.A. Phillips. 2005. Moment approximation for least-squares estimators in dynamic regression models with a unit root. Econometrics Journal 8 (2): 115–142.
Kollo, T., and D. von Rosen. 1998. A unified approach to the approximation of multivariate densities. Scandinavian Journal of Statistics 25 (1): 93–109.
Kundhi, G., and P. Rilstone. 2012. Edgeworth expansions for GEL estimators. Journal of Multivariate Analysis 106: 118–146.
Kundhi, G., and P. Rilstone. 2013. Edgeworth and saddlepoint expansions for nonlinear estimators. Econometric Theory 29 (5): 1–22.
Kundhi, G., and P. Rilstone. 2020. Simplified matrix methods for multivariate Edgeworth expansions. Journal of Quantitative Economics 18: 293–326.
Lee, T.-H., A. Ullah, and H. Wang. 2018. The second-order bias of quantile estimators. Economics Letters 173: 143–147.
Maasoumi, E. 1978. A modified Stein-like estimator for the reduced form coefficients of simultaneous equations. Econometrica 46 (3): 695–703.
Maasoumi, E., and P.C.B. Phillips. 1982. On the behavior of inconsistent instrumental variable estimators. Journal of Econometrics 19 (2–3): 183–201.
Mariano, R.S. 1982. Analytical small-sample distribution theory in econometrics: the simultaneous-equations case. International Economic Review 23 (3): 503–533.
Mariano, R., and T. Sawa. 1972. The exact finite-sample distribution of the limited-information maximum likelihood estimator in the case of two included endogenous variables. Journal of the American Statistical Association 67 (337): 159–163.
Nagar, A.L. 1959. The bias and moment matrix of the general \(k\) -class estimators of the parameters in simultaneous equations. Econometrica 27 (4): 575–595.
Nagar, A.L. 1962. Double \(k\)-class estimators of parameters in simultaneous equations and their small sample properties. International Economic Review 3 (2): 168–188.
Nagar, A.L., and Y.P. Gupta. 1968. The bias of Liviatan’s consistent estimator in a distributed lag model. Econometrica 36 (2): 337–342.
Nagar, A.L., and N.C. Kakwani. 1965. Note on the use of prior information in statistical estimation of economic relations. Sankhy ā 27 (1): 105–112.
Nagar, A.L., and A. Ullah. 1973. Note on approximate skewness, and kurtosis of the two stage least squares estimator. Indian Economic Review 7: 70–80.
Phillips, P.C.B. 1977. Approximations to some finite sample distributions associated with a first-order stochastic difference equation. Econometrica 45 (2): 463–485.
Phillips, P.C.B. 1978. Edgeworth and saddlepoint approximations in the first-order noncircular autoregression. Biometrika 65 (1): 91–98.
Phillips, P.C.B. 1980. The exact distribution of instrumental variable estimators in an equation containing \(n+1\) endogenous variables. Econometrica 48 (4): 861–878.
Phillips, P.C.B. 1983. Exact small sample theory in the simultaneous equations model. In Handbook of econometrics, ed. Z. Griliches and M. Intriligator, 449–516. Amsterdam: Elsevier.
Phillips, P.C.B., and J.H. Lee. 2013. Predictive regression under various degrees of persistence and robust long-horizon regression. Journal of Econometrics 177 (2): 250–264.
Phillips, P.C.B., and J.Y. Park. 1988. On the formulation of Wald tests of nonlinear restrictions. Econometrica 56 (5): 1065–1083.
Richardson, D.H. 1968. The exact distribution of a structural coefficient estimator. Journal of the American Statistical Association 63 (324): 1214–1226.
Rilstone, P., and A. Ullah. 2002. Sampling bias in Heckman’s sample selection estimator. In Recent advances in statistical methods, ed. Y.P. Chaubey, 263–273. London: World Scientific Publishing Company.
Rilstone, P., V.K. Srivastava, and A. Ullah. 1996. The second-order bias and mean squared error of nonlinear estimators. Journal of Econometrics 75 (2): 369–395.
Rothenberg, T.J. 1984a. Approximating the distributions of econometric estimators and test statistics. In Handbook of econometrics, vol. 2, ed. Z. Griliches and M. Intriligator, 881–893. Amsterdam: Elsevier.
Rothenberg, T.J. 1984b. Approximate normality of generalized least squares estimates. Econometrica 52 (4): 811–825.
Sargan, J.D. 1975. Gram-Charlier approximations applied to t ratios of k-class estimators. Econometrica 43 (2): 327–346.
Sargan, J.D. 1976. Econometric estimators and the Edgeworth approximation. Econometrica 44 (3): 421–448.
Sargan, J.D. 1980. Some tests for dynamic specification for a single equation. Econometrica 48 (4): 879–897.
Sawa, T. 1969. The exact sampling distribution of ordinary least squares and two-stage least squares estimators. Journal of the American Statistical Association 64 (327): 923–937.
Sawa, T. 1972. Finite sample properties of the \(k\)-class estimators. Econometrica 40 (4): 653–680.
Skovgaard, Ib. M. 1986. On multivariate Edgeworth expansions. International Statistical Review 54 (2): 169–186.
Srinivasan, T. 1970. Approximations to finite sample moments of estimators whose exact sampling distributions are unknown. Econometrica 38 (3): 533–541.
Srivastava, V., and D.E.A. Giles. 1987. Seemingly unrelated regression equations models: estimation and inference. New York: Marcel Dekker.
Srivastava, V.K., and K. Maekawa. 1995. Efficiency properties of feasible generalized least squares estimators in SURE models under non-normal disturbances. Journal of Econometrics 66 (1–2): 99–121.
Taylor, W.E. 1983. On the relevance of finite sample distribution theory. Econometric Reviews 2 (1): 1–39.
Ullah, A. 2004. Finite sample econometrics. New York: Oxford University Press.
Ullah, A., and A.L. Nagar. 1974. The exact mean of the two stage least squares estimator of the structural parameters in the equation having three endogenous variables. Econometrica 42 (4): 749–758.
Zhou, Q., and J. Yu. 2015. Asymptotic theory for linear diffusions under alternative sampling schemes. Economics Letters 128: 1–5.
Acknowledgements
This paper is dedicated to Professor A.L.Nagar for this special issue. We thank Essie Maasoumi for his helpful comments.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bao, Y., Ullah, A. Analytical Finite Sample Econometrics: From A. L. Nagar to Now. J. Quant. Econ. 19 (Suppl 1), 17–37 (2021). https://doi.org/10.1007/s40953-021-00261-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40953-021-00261-z