Transcription of EC 823: Applied Econometrics - Boston College
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EC 823: Applied Econometrics - Boston College
ARCH and MGARCH modelsChristopher F BaumEC 823: Applied EconometricsBoston College , Spring 2014 Christopher F Baum (BC / DIW)ARCH and MGARCH modelsBoston College , Spring 20141 / 38 ARCH modelsSingle-equation modelsARCH modelsHeteroskedasticity can occur in time series models, just as it may in across-sectional context. It has the same consequences: the OLS pointestimates are unbiased and consistent, but their standard errors will beinconsistent, as will hypothesis test statistics and confidence may prevent that loss of consistency by usingheteroskedasticity-robust standard errors. The Newey West or HACstandard errors available fromneweyin the OLS context orivreg2inthe instrumental variables context will be robust to arbitraryheteroskedasticity in the error process as well as serial F Baum (BC / DIW)ARCH and MGARCH modelsBoston College , Spring 20142 / 38 ARCH modelsSingle-equation modelsThe most common model of heteroskedasticity employed in the timeseries context is that ofautoregressive conditional heteroskedasticity,or ARCH.
ARCH and MGARCH models Christopher F Baum EC 823: Applied Econometrics Boston College, Spring 2014 Christopher F Baum (BC / DIW) ARCH and MGARCH models Boston College, Spring 2014 1 / 38
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