Nonlinear Regression with Dependent Observations

White, Halbert; Domowitz, Ian

doi:10.2307/1911465

Cited by 352 publications

(217 citation statements)

References 23 publications

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“…It did not take long for econometricians to realize that, if heteroskedasticityrobust inference is possible, then so must be inference that is robust to both heteroskedasticity and autocorrelation of unknown form. Key early papers on what has come to be known as HAC estimation include Hansen (1982), White and Domowitz (1984), West (1987, 1994), Andrews (1991), and Andrews and Monahan (1992). New estimation methods, notably the generalized method of moments (Hansen, 1982) and its many variants and offshoots, which would not have been possible without HCCMEs and HAC estimators, were rapidly developed following the publication of White (1980).…”

Section: Introductionmentioning

confidence: 99%

Thirty Years of Heteroskedasticity-Robust Inference

MacKinnon

2012

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revolutionary idea of inference that is robust to heteroskedasticity of unknown form, an idea that was very soon extended to other forms of robust inference and also led to many new estimation methods. This paper discusses the development of heteroskedasticity-robust inference since 1980. There have been two principal lines of investigation. One approach has been to modify White's original estimator to improve its finite-sample properties, and the other has been to use bootstrap methods. The relation between these two approaches, and some ways in which they may be combined, are discussed. Finally, a simulation experiment compares various methods and shows how far heteroskedasticity-robust inference has come in just over thirty years. Terms of use: Documents in EconStor may

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Section: Introductionmentioning

confidence: 99%

Thirty Years of Heteroskedasticity-Robust Inference

MacKinnon

2012

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

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“…By White and Domowitz (1984), b θ − θ 0 = O p ¡ n −1/2 ¢ under Assumptions A1, A2(ii) and A3. Noting that the elements of H * are uniformly O p ¡ n −1 h −p ¢ , by…”

Section: B Proof Of the Main Resultsmentioning

confidence: 98%

“…Assumption A3, together with A1 and A2(ii), ensures that White and Domowitz (1984). Assumptions A4-A5 are used to obtain the uniform consistency for the local polynomial estimator due to Masry (1996) and Hansen (2008).…”

Section: Is Finite and Is Lipschitz Continuous In That |Fmentioning

confidence: 99%

A Nonparametric Goodness-of-Fit-Based Test for Conditional Heteroskedasticity

Ullah

2012

Econom. Theory

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In this paper we propose a nonparametric test for conditional heteroskedasticity based on a new measure of nonparametric goodness-of-fit (R 2 ). In analogy with the ANOVA tools for classical linear regression models, the nonparametric R 2 is obtained for the local polynomial regression of the residuals from a parametric regression on some covariates. It is close to 0 under the null hypothesis of conditional homoskedasticity and stays away from 0 otherwise. Unlike most popular parametric tests in the literature, the new test does not require the correct specification of parametric conditional heteroskedasticity form and thus is able to detect all kinds of conditional heteroskedasticity of unknown form. We show that after being appropriately centered and standardized, the nonparametric R 2 is asymptotically normally distributed under the null hypothesis of conditional homoskedasticity and a sequence of Pitman local alternatives.We also prove the consistency of the test, propose a bootstrap method to obtain the critical values or bootstrap p-values, and justify the validity of the bootstrap method. We conduct a small set of Monte Carlo simulations and compare our test with some popular parametric and nonparametric tests in the literature. Applications to the U.S. real GDP growth rate data indicate that our nonparametric test can reveal certain conditional heteroskedasticity which the parametric tests fail to detect.

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“…See Yamaguchi 1991;Blossfeld, Hamerle, and Mayer 1989;Kiefer 1988. 21 See Greene 1993: Chapters 13-15 and 21;White 1980;White and Domowitz 1984;Newey and West 1987. Specific details on the specification implemented are available from the author.…”

Section: Econometric Methods and Resultsmentioning

confidence: 99%

Budget institutions and political insulation: why states adopt the item veto

Figueiredo

2003

Journal of Public Economics

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Forty-three of the fifty states of the United States have granted item veto authority to their governors as part of state constitutions. In this paper, I test explanations of why and when a legislature would cede institutional power. Using data from 1865 to 1994, I show that these measures are most likely proposed by fiscal conservatives who fear the loss of power in the future; in order to protect their interests for those periods when they will be in the minority, they implement institutions such as the item veto which will limit future, liberal legislatures. The results therefore shed light on two important substantive areas. First, by showing how the choice of budgetary institutions is endogenous to the political process, it clarifies that they are not necessarily adopted for economic efficiency. Second, it provides evidence in support of theories that have posited that electorally weak groups will heavily 'insulate' policies in periods in which they momentarily hold power (e.g. Moe 1989, de Figueiredo 2002.

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Nonlinear Regression with Dependent Observations

Cited by 352 publications

References 23 publications

Thirty Years of Heteroskedasticity-Robust Inference

Thirty Years of Heteroskedasticity-Robust Inference

A Nonparametric Goodness-of-Fit-Based Test for Conditional Heteroskedasticity

Budget institutions and political insulation: why states adopt the item veto

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