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Bounds for inference with nuisance parameters present only under the alternative

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  • Filippo Altissimo
  • Valentina Corradi

Abstract

In hypothesis testing with nuisance parameters present only under the alternative two issues typically arise: (i) critical values are data dependent and so cannot be tabulated; (ii) we need to choose a functional over the nuisance parameter space. We address the first issue by providing easily computable bounds for the case of dependent and heterogeneous observations. We tackle the second issue by suggesting a weighted average statistic with weights given by the (quasi) likelihood over the nuisance parameter space. The small sample behavior of our procedure is analyzed via Monte Carlo simulations; we consider conditional moment tests and tests for nonlinearities in the SETAR model. An empirical illustration to the modeling of US male unemployment is provided. Copyright Royal Economic Society, 2002

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 5 (2002)
Issue (Month): 2 (06)
Pages: 494-519

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Handle: RePEc:ect:emjrnl:v:5:y:2002:i:2:p:494-519

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Cited by:
  1. Ana Beatriz C. Galvao, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 21(4), pages 463-487.
  2. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers, Rutgers University, Department of Economics 200423, Rutgers University, Department of Economics.
  3. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers, Rutgers University, Department of Economics 200418, Rutgers University, Department of Economics.
  4. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers, Rutgers University, Department of Economics 200618, Rutgers University, Department of Economics.
  5. Arie Preminger & Shinichi Sakata, 2007. "A model selection method for S-estimation," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 10(2), pages 294-319, 07.
  6. Peter Sephton & Janelle Mann, 2013. "Threshold Cointegration: Model Selection with an Application," Journal of Economics and Econometrics, Economics and Econometrics Research Institute (EERI), Brussels, Economics and Econometrics Research Institute (EERI), Brussels, vol. 56(2), pages 54-77.
  7. Nedeljkovic, Milan, 2008. "Testing for Smooth Transition Nonlinearity in Adjustments of Cointegrating Systems," The Warwick Economics Research Paper Series (TWERPS) 876, University of Warwick, Department of Economics.
  8. PREMINGER, Arie & STORTI, Giuseppe, 2006. "A GARCH (1,1) estimator with (almost) no moment conditions on the error term," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2006068, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, Elsevier, vol. 23(1), pages 71-84.
  10. Galvão, Ana Beatriz C & Marcellino, Massimiliano, 2010. "Endogenous Monetary Policy Regimes and the Great Moderation," CEPR Discussion Papers, C.E.P.R. Discussion Papers 7827, C.E.P.R. Discussion Papers.
  11. Marine Carrasco, 2004. "Chi-square Tests for Parameter Stability," RCER Working Papers 508, University of Rochester - Center for Economic Research (RCER).
  12. PREMINGER, Arie & HAFNER, Christian M., 2006. "Deciding between GARCH and stochastic volatility via strong decision rules," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  13. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers, Insper Working Paper, Insper Instituto de Ensino e Pesquisa wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

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