Tests of Functional Form and Heteroscedasticity

This paper considers tests of misspecification in a heteroscedastic transformation model. We derive Lagrange multiplier (LM) statistics for (i) testing functional form and heteroscedasticity jointly, (ii) testing functional form in the presence of heteroscedasticity, and (iii) testing heteroscedasti...

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Main Author: YANG, Zhenlin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2004
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Online Access:https://ink.library.smu.edu.sg/soe_research/841
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spelling sg-smu-ink.soe_research-18402010-09-23T05:48:03Z Tests of Functional Form and Heteroscedasticity YANG, Zhenlin This paper considers tests of misspecification in a heteroscedastic transformation model. We derive Lagrange multiplier (LM) statistics for (i) testing functional form and heteroscedasticity jointly, (ii) testing functional form in the presence of heteroscedasticity, and (iii) testing heteroscedasticity in the presence of data transformation. We present LM statistics based on the expected information matrix. For cases (i) and (ii), this is done assuming the Box-Cox transformation. For case (iii), the test does not depend on whether the functional form is estimated or pre-specified. Small-sample properties of the tests are assessed by Monte Carlo simulation, and comparisons are made with the likelihood ratio test and other versions of LM test. The results show that the expected-information based LM test has the most appropriate finite-sample empirical size 2004-07-07T07:00:00Z text https://ink.library.smu.edu.sg/soe_research/841 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Econometrics
spellingShingle Econometrics
YANG, Zhenlin
Tests of Functional Form and Heteroscedasticity
description This paper considers tests of misspecification in a heteroscedastic transformation model. We derive Lagrange multiplier (LM) statistics for (i) testing functional form and heteroscedasticity jointly, (ii) testing functional form in the presence of heteroscedasticity, and (iii) testing heteroscedasticity in the presence of data transformation. We present LM statistics based on the expected information matrix. For cases (i) and (ii), this is done assuming the Box-Cox transformation. For case (iii), the test does not depend on whether the functional form is estimated or pre-specified. Small-sample properties of the tests are assessed by Monte Carlo simulation, and comparisons are made with the likelihood ratio test and other versions of LM test. The results show that the expected-information based LM test has the most appropriate finite-sample empirical size
format text
author YANG, Zhenlin
author_facet YANG, Zhenlin
author_sort YANG, Zhenlin
title Tests of Functional Form and Heteroscedasticity
title_short Tests of Functional Form and Heteroscedasticity
title_full Tests of Functional Form and Heteroscedasticity
title_fullStr Tests of Functional Form and Heteroscedasticity
title_full_unstemmed Tests of Functional Form and Heteroscedasticity
title_sort tests of functional form and heteroscedasticity
publisher Institutional Knowledge at Singapore Management University
publishDate 2004
url https://ink.library.smu.edu.sg/soe_research/841
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