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A Generalized Fast Algorithm for BDS-Type Statistics
Mayer-Foulkes, David - In: Studies in Nonlinear Dynamics & Econometrics 4 (2007) 1, pp. 45-50
's (1987) BDS-type statistics are based. The algorithm generalizes a fast algorithm due to LeBaron by calculating the histogram …
Persistent link: https://www.econbiz.de/10004966222
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A Fast Algorithm for the BDS Statistic
LeBaron, Blake - In: Studies in Nonlinear Dynamics & Econometrics 2 (1997) 2, pp. 53-59
The BDS statistic has proved to be one of several useful nonlinear diagnostics. It has been shown to have good power …, extensive Monte Carlo results have proved it useful in relatively small samples. However, the BDS test is not trivial to … short paper presents a fast algorithm for the BDS statistic, and outlines how these speed improvements are achieved. Source …
Persistent link: https://www.econbiz.de/10005751410
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A Generalized Fast Algorithm for BDS-Type Statistics
Mayer-Foulkes, David - In: Studies in Nonlinear Dynamics & Econometrics 4 (2000) 1, pp. 45-50
's (1987) BDS-type statistics are based. The algorithm generalizes a fast algorithm due to LeBaron by calculating the histogram …
Persistent link: https://www.econbiz.de/10005584891
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An Improved Nonparametric Unit-Root Test
Gao, Jiti; King, Maxwell - Department of Econometrics and Business Statistics, … - 2012
This paper proposes a simple and improved nonparametric unit-root test. An asymptotic distribution of the proposed test is established. Finite sample comparisons with an existing nonparametric test are discussed. Some issues about possible extensions are outlined.
Persistent link: https://www.econbiz.de/10010860412
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Specification Testing in Nonstationary Time Series Models
Chen, Jia; Gao, Jiti; Li, Degui; Lin, Zhengyan - Department of Economics and Related Studies, University … - 2014
In this paper, we consider a specification testing problem in nonlinear time series models with nonstationary regressors and propose using a nonparametric kernel-based test statistic. The nullasymptotics for the proposed nonparametric test statistic have been well developed in the existing...
Persistent link: https://www.econbiz.de/10010932928
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Poorly Measured Confounders Are More Useful on the Left Than on the Right
Pei, Zhuan; Pischke, Jörn-Steffen; Schwandt, Hannes - 2017
Researchers frequently test identifying assumptions in regression based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right hand side of the regression. If such additions do not affect the coefficient of...
Persistent link: https://www.econbiz.de/10011653375
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Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions
Fu, Jia-Young Michael; Horowitz, Joel; Parey, Matthias - 2015
This paper presents a test for exogeneity of explanatory variables in a nonparametric instrumental variables (IV) model whose structural function is identified through a conditional quantile restriction. Quantile regression models are increasingly important in applied econometrics. As with...
Persistent link: https://www.econbiz.de/10011445771
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Development and validation of credit-scoring models
Glennon, Dennis; Kiefer, Nicholas M.; Larson, C. Erik; … - 2007
Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many financial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit...
Persistent link: https://www.econbiz.de/10010292074
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A note on model selection in (time series) regression models - General-to-specific or specific-to-general?
Herwartz, Helmut - 2007
The paper provides Monte Carlo evidence on the performance of general-to-specific and specific-to-general selection of explanatory variables in linear (auto)regressions. In small samples the former is markedly inefficient in terms of ex-ante forecasting performance.
Persistent link: https://www.econbiz.de/10010296273
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Stochastic volatility : maximum likelihood estimation and specification testing
White, Scott Ian - 2006
Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financial asset returns. While SV models have a number of theoretical advantages over competing variance modelling procedures they are notoriously difficult to estimate. The distinguishing feature of...
Persistent link: https://www.econbiz.de/10009437989