Review Autocorrelation-Corrected Standard Errors in Panel Probits: An Application to Currency Crisis Prediction

Autocorrelation-Corrected Standard Errors in Panel Probits: An Application to Currency Crisis Prediction High quality books

Autocorrelation-Corrected Standard Errors in Panel Probits: An Application to Currency Crisis Prediction
By:Andrew Berg,Rebecca N. Coke
Published on 2004-03-01 by International Monetary Fund

Many estimates of early-warning-system (EWS) models of currency crisis have reported incorrect standard errors because of serial correlation in the context of panel probit regressions. This paper documents the magnitude of the problem, proposes and tests a solution, and applies it to previously published EWS estimates. We find that (1) the uncorrected probit estimates substantially underestimate the true standard errors, by up to a factor of four; (2) a heteroskedasicity- and autocorrelation-corrected (HAC) procedure produces accurate estimates; and (3) most variables from the original models remain significant, though substantially less so than had been previously thought.

This Book was ranked at 19 by Google Books for keyword Currency crisis.

Book ID of Autocorrelation-Corrected Standard Errors in Panel Probits: An Application to Currency Crisis Prediction's Books is P3SZQ0NxlwEC, Book which was written byAndrew Berg,Rebecca N. Cokehave ETAG "eS681dbR70o"

Book which was published by International Monetary Fund since 2004-03-01 have ISBNs, ISBN 13 Code is and ISBN 10 Code is

Reading Mode in Text Status is true and Reading Mode in Image Status is true

Book which have "20 Pages" is Printed at BOOK under CategoryAutocorrelation (Statistics)

This Book was rated by Raters and have average rate at ""

This eBook Maturity (Adult Book) status is NOT_MATURE

Book was written in en

eBook Version Availability Status at PDF is falseand in ePub is true

Book Preview

Comments

Popular posts from this blog

Review The Essential Keynes

Review The Growth of Currency Organisations in India

Review Unlock the Power of Your Credit Score