Abstract
Two-stage least squares has been a widely used method of estimating the parameters of a single structural equation in a system of linear simultaneous equations. This article first considers the estimation of a full system of equations. This provides a context for understanding the place of two-stage least squares in simultaneous-equation estimation. The article concludes with some comments on the lasting contribution of the two-stage least squares approach and more generally the future of the identification and estimation of simultaneous-equations models.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsBibliography
Amemiya, T. 1974. The nonlinear two-stage least-stage estimator. Journal of Econometrics 2: 105–110.
Amemiya, T. 1985. Advanced econometrics. Cambridge, MA: Harvard University Press.
Anderson, T. 1982. Some recent developments on the distribution of single-equation estimators. In Advances in econometrics, ed. W. Hildenbrand. Cambridge: Cambridge University Press.
Anderson, T. 2005. Origins of the limited information maximum likelihood and two stage least squares estimators. Journal of Econometrics 127: 1–16.
Anderson, T., and H. Rubin. 1949. Estimator of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics 20: 46–63.
Anderson, T., and H. Rubin. 1950. The asymptotic properties of estimates of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics 21: 570–582.
Anderson, T., N. Kunitomo, and K. Morimune. 1986. Comparing single equation estimators in a simultaneous equation system. Econometric Theory 2: 1–32.
Basmann, R. 1957. A generalized classical method of linear estimation of coefficients in a structural equation. Econometrica 25: 77–83.
Bernanke, B., and A. Blinder. 1992. The federal funds rate and the channels of monetary transmission. American Economic Review 82: 901–921.
Cushman, D., and T. Zha. 1997. Identifying monetary policy in a small open economy under flexible exchange rates. Journal of Monetary Economics 39: 433–448.
DeJong, D., B. Ingram, and C. Whiteman. 2000. A Bayesian approach to dynamic macroeconomics. Journal of Econometrics 98: 203–223.
Farebrother, R. 1999. Fitting linear relationships: A history of the calculus of observations 1750–1900. New York: Springer.
Fernandez-Villaverde, J., and J. Rubio-Ramirez. 2005. Estimating dynamic equilibrium economies: Linear versus nonlinear likelihood. Journal of Applied Econometrics 20: 891–910.
Goldberger, A. 1991. A course in econometrics. Cambridge, MA: Harvard University Press.
Gordon, D., and E. Leeper. 1995. The dynamic impacts of monetary policy: An exercise in tentative identification. Journal of Political Economy 102: 1228–1247.
Hood, W., and T. Koopmans. 1953. Studies in econometric method, Cowles foundation monograph 14. New Haven: Yale University Press.
Koopmans, T. 1950. Statistical inference in dynamic economic models, Cowles commission monograph 10. New York: John Wiley and Sons.
Koopmans, T., and W. Hood. 1953. The estimation of simultaneous linear economic relationships. In Studies in econometric method, Cowles foundation monograph 14, ed. W. Hood and T. Koopmans. New Haven: Yale University Press.
Mariano, R. 2001. Simultaneous equation model estimators: Statistical properties and practical implications. In A companion to theoretical econometrics, ed. B. Baltagi. Oxford: Blackwell.
Mittelhammer, R., G. Judge, and D.J. Miller. 2000. Econometric foundations. Cambridge: Cambridge University Press.
Phillips, P. 1983. Exact small sample theory in the simultaneous equation model. In Handbook of econometrics, ed. Z. Griliches and M. Intriligator. Amsterdam: North-Holland.
Ruud, P. 2000. An introduction to classical econometric theory. Oxford: Oxford University Press.
Sargan, J. 1958. Estimation of economic relationships using instrumental variables. Econometrica 67: 557–586.
Sims, C. 1980. Macroeconomics and reality. Econometrica 48: 1–48.
Takeuchi, K., and K. Morimune. 1985. Third-order efficiency of the extended maximum likelihood estimator in a simultaneous equation system. Econometrica 53: 177–200.
Theil, H. 1953a. Repeated least-squares applied to a complete equation systems. Mimeo. The Hague: Central Planning Bureau.
Theil, H. 1953b. Estimation and simultaneous correlation in complete equation systems. Mimeo. The Hague: Central Planning Bureau.
Theil, H. 1961. Economic forecasts and policy. 2nd ed. Amsterdam: North- Holland.
Zellner, A. 1998. The finite sample properties of simultaneous equations’ estimates and estimators: Bayesian and non-Bayesian approaches. Journal of Econometrics 83: 185–212.
Author information
Authors and Affiliations
Editor information
Copyright information
© 2018 Macmillan Publishers Ltd.
About this entry
Cite this entry
Savin, N.E. (2018). Two-Stage Least Squares and The K-Class Estimator. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_1356
Download citation
DOI: https://doi.org/10.1057/978-1-349-95189-5_1356
Published:
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-95188-8
Online ISBN: 978-1-349-95189-5
eBook Packages: Economics and FinanceReference Module Humanities and Social SciencesReference Module Business, Economics and Social Sciences