Inference in Partially Identified Heteroskedastic Simultaneous Equations Models

48 Pages Posted: 2 Feb 2017

See all articles by Helmut Luetkepohl

Helmut Luetkepohl

German Institute for Economic Research (DIW Berlin)

George Milunovich

Macquarie University - Department of Economics; Macquarie University, Macquarie Business School

Minxian Yang

UNSW Australia Business School, School of Economics

Date Written: December 22, 2016

Abstract

Identification through heteroskedasticity in heteroskedastic simultaneous equations models (HSEMs) is considered. The possibility that heteroskedasticity identifies the structural parameters only partially is explicitly allowed for. The asymptotic properties of the identified parameters are derived. Moreover, tests for identification through heteroskedasticity are developed and their asymptotic distributions are derived. Monte Carlo simulations are used to explore the small sample properties of the asymptotically valid methods. Finally, the approach is applied to investigate the relation between the extent of economic openness and inflation.

Keywords: Heteroskedasticity, Simultaneous Equations Models, Testing for Identification, Davies' Problem

JEL Classification: C30

Suggested Citation

Luetkepohl, Helmut and Milunovich, George and Yang, Minxian, Inference in Partially Identified Heteroskedastic Simultaneous Equations Models (December 22, 2016). UNSW Business School Research Paper No. 2016-19. Available at SSRN: https://ssrn.com/abstract=2910098 or http://dx.doi.org/10.2139/ssrn.2910098

Helmut Luetkepohl (Contact Author)

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstra├če 58
Berlin, 10117
Germany

George Milunovich

Macquarie University - Department of Economics ( email )

Sydney NSW 2109
Australia

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Minxian Yang

UNSW Australia Business School, School of Economics ( email )

School of Economics
The University of New South Wales
Sydney, NSW NSW 2052
Australia
93853353 (Phone)

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