Testing for multiplicative heteroskedasticity

Godfrey, L. G.

doi:10.1016/0304-4076(78)90031-3

Cited by 237 publications

(86 citation statements)

References 6 publications

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“…White tests the null hypothesis of no heteroskedasticity against heteroskedasticity of unknown general form in the residuals (White, 1980). B-P-G is the Breusch-PaganGodfrey test which is a Lagrange multiplier test of the null hypothesis of no heteroskedasticity against heteroskedasticity of the form ( ), where is a vector of the independent variables from the mean equation (see Breusch andPagan, 1979, andGodfrey, 1978). The null hypothesis of the heteroskedasticity tests is no heteroskedasticity.…”

Section: Notes To Tables 1 2 and 2bmentioning

confidence: 99%

Estimating United States Phillips curves with expectations consistent with the statistical process of inflation

Russell¹,

Chowdhury²

2013

Journal of Macroeconomics

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Section: Notes To Tables 1 2 and 2bmentioning

confidence: 99%

Estimating United States Phillips curves with expectations consistent with the statistical process of inflation

Russell¹,

Chowdhury²

2013

Journal of Macroeconomics

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“…Integrating (4a) from t to T, letting T approach ,and using the transversality condition (iv) yields Breusch and Pagan (1979), Godfrey (1978), and Kao (1983).…”

Section: The Current Value Hamiltonian Ismentioning

confidence: 99%

Entry, Industry Growth, and the Microdynamics of Industry Supply

Hause¹,

Rietz²

1984

Journal of Political Economy

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“…Then, the regression-based test simplifies to regressing the squared returns on a constant and x t and to computing T R 2 which resembles the Godfrey (1978) test for multiplicative heteroskedasticity. Finally, the Engle (1982) test for ARCH effects is obtained if we choose…”

Section: In This Situation It Directly Follows That Equation (20) Camentioning

confidence: 99%

Misspecification Testing in GARCH-MIDAS Models

Conrad

Schienle

2015

SSRN Journal

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We develop a misspecification test for the multiplicative two-component GARCH-MIDAS model suggested in Engle et al. (2013). In the GARCH-MIDAS model a short-term unit variance GARCH component fluctuates around a smoothly timevarying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange Multiplier statistic for testing the null hypothesis that the variable has no explanatory power. Hence, under the null hypothesis the long-term component is constant and the GARCH-MIDAS reduces to the simple GARCH model. We derive the asymptotic theory for our test statistic and investigate its finite sample properties by Monte-Carlo simulation. The usefulness of our procedure is illustrated by an empirical application to S&P 500 return data.

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Testing for multiplicative heteroskedasticity

Cited by 237 publications

References 6 publications

Estimating United States Phillips curves with expectations consistent with the statistical process of inflation

Estimating United States Phillips curves with expectations consistent with the statistical process of inflation

Entry, Industry Growth, and the Microdynamics of Industry Supply

Misspecification Testing in GARCH-MIDAS Models

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