Consistent covariance matrix estimation in probit models with autocorrelated errors
By: Arturo Estrella and Anthony P. Rodrigues.
Contributors: Rodrigues, Anthony Paul.; Federal Reserve Bank of New York.
Series: Staff reports ;; no. 39; Staff reports (Federal Reserve Bank of New York : Online) ;; no. 39.
Publisher: Federal Reserve Bank of New York
Published: 1998
Place of publication: [New York, N.Y.]
Language: eng
Format: Electronic resource
Subjects: Analysis of covariance.; Autocorrelation (Statistics); Probits.
Description: "Some recent time-series applications use probit models to measure the forecasting power of a set of variables.  Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients.  A potential source of inconsistency in maximum likelihood standard errors is serial correlation in the underlying disturbances, which may arise, for example, from overlapping forecasts.  We discuss several practical methods for constructing probit autocorrelation-consistent standard errors, drawing on the generalized method of moments techniques of Hansen (1982), Newey-West (1987) and others, and we provide simulation evidence that these methods can work well"--Federal Reserve Bank of New York web site.
Notes: Includes bibliographical references.
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