Simultaneous equation systems with heteroscedasticity

identification, estimation, and stock price elasticities

George Milunovich*, Minxian Yang

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We give a set of identifying conditions for p-dimensional (p ≥ 2) simultaneous equation systems (SES) with heteroscedasticity in the framework of Gaussian quasi-maximum likelihood (QML). Our conditions rely on the presence of heteroscedasticity in the data rather than identifying restrictions traditionally employed in the literature. The QML estimator is shown to be consistent for the true parameter point and asymptotically normal. Monte Carlo experiments indicate that the QML estimator performs well in comparison to the generalized method of moments (GMM) estimator in finite samples, even when the conditional variance is mildly misspecified. We analyze the relationship between traded stock prices and volumes in the setting of SES. Based on a sample of the Russell 3000 stocks, our findings provide new evidence against perfectly elastic demand and supply schedules for equities.

Original languageEnglish
Pages (from-to)288-308
Number of pages21
JournalJournal of Business and Economic Statistics
Volume36
Issue number2
DOIs
Publication statusPublished - 2018

Keywords

  • Asymptotics
  • Demand and supply for equities
  • Endogeneity
  • Multivariate structural models
  • Quasi maximum likelihood
  • Stock prices and volumes

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