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We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...
Persistent link: https://www.econbiz.de/10003747376
Estimation results obtained by parametric models may be seriously misleading when the model is misspecified or poorly approximates the true model. This study proposes a test that jointly tests the specifications of multiple response probabilities in unordered multinomial choice models. The test...
Persistent link: https://www.econbiz.de/10011410669
Persistent link: https://www.econbiz.de/10003900411
This paper develops a consistent heteroskedasticity robust Lagrange Multiplier (LM) type specification test for …. Compared with the recent test in Gupta (2018), I use a different way of accounting for heteroskedasticity. I demonstrate using …
Persistent link: https://www.econbiz.de/10012862378
Persistent link: https://www.econbiz.de/10001645859
We introduce a nonparametric block bootstrap approach for Quasi-Likelihood Ratio type tests of nonlinear restrictions. Our method applies to extremum estimators, such as quasi-maximum likelihood and generalized method of moments estimators. Unlike existing parametric bootstrap procedures for...
Persistent link: https://www.econbiz.de/10014178027
Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special...
Persistent link: https://www.econbiz.de/10014178851
We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...
Persistent link: https://www.econbiz.de/10014047091
In non- and semiparametric testing, the wild bootstrap is a standard method to determine the critical values of the test. While there exists an increasing literature on how to find a proper smoothing parameter for the nonparametric alternative, almost nothing is known how to choose a smoothing...
Persistent link: https://www.econbiz.de/10014048394
We introduce tests for finite-sample linear regressions with heteroskedastic errors. The tests are exact, i.e., they have guaranteed type I error probabilities when bounds are known on the range of the dependent variable, without any assumptions about the noise structure. We provide upper bounds...
Persistent link: https://www.econbiz.de/10014197050