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Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative
, 1995
"... . The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly ex ..."
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Cited by 84 (13 self)
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. The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly extend the nuisance parameter approach. How and why the nuisance parameter approach works and how it can be extended bears closely on recent developments in artificial neural networks. Statistical content is provided by viewing specification tests with nuisance parameters as tests of hypotheses about Banachvalued random elements and applying the Banach Central Limit Theorem and Law of Iterated Logarithm, leading to simple procedures that can be used as a guide to when computationally more elaborate procedures may be warranted. 1. Introduction In testing whether or not a parametric statistical model is correctly specified, there are a number of apparently distinct approaches one might take. T...
Regime Switching as a Test for Exchange Rate Bubbles
 Journal of Applied Econometrics
, 1996
"... : This paper develops a new test for speculative bubbles, which is applied to data for the Japanese yen, the German mark and the Canadian dollar exchange rates from 1977 to 1991. The test assumes that bubbles display a particular kind of regimeswitching behaviour, which is shown to imply coefficie ..."
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Cited by 20 (6 self)
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: This paper develops a new test for speculative bubbles, which is applied to data for the Japanese yen, the German mark and the Canadian dollar exchange rates from 1977 to 1991. The test assumes that bubbles display a particular kind of regimeswitching behaviour, which is shown to imply coefficient restrictions on a simple switchingregression model of exchange rate innovations. Test results are sensitive to the specification of exchange rate fundamentals and other factors. Evidence most consistent with the bubble hypothesis is found using an overshooting model of the Canadian dollar and a PPP model of the Japanese yen. Page 1 of 57 /home/int/vann/fm/swpfx/swfx_jae.acc 9 August 1995 13:50 Introduction This paper develops a new test for speculative bubbles in exchange rates and then applies this test to data for three bilateral exchange rates over the 1977  1991 period. Recent work in testing for bubbles has shifted from general tests that should detect any kind of bubble (Meese...
Nonlinear time series, complexity theory and finance
 Handbook of Statistics Volume 14: Statistical Methods in Finance
, 1995
"... ..."
Neural network test and nonparametric kernel test for neglected nonlinearity in regression models
 Studies in Nonlinear Dynamics and Econometrics
, 2000
"... We consider two conditional moment tests for neglected nonlinearity in regression models and examine their finite sample performance. The two tests are the nonparametric kernel test by Li and Wang (1998) and Zheng (1996) and the neural network test of White (1989). We examine asymptotic test, naive ..."
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Cited by 7 (1 self)
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We consider two conditional moment tests for neglected nonlinearity in regression models and examine their finite sample performance. The two tests are the nonparametric kernel test by Li and Wang (1998) and Zheng (1996) and the neural network test of White (1989). We examine asymptotic test, naive bootstrap test, and wild bootstrap test for weakly dependent time series and independent data.
Testing additive separability of error term in nonparametric structural models. Econometric Reviews, forthcoming
, 2014
"... This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model nonadditively. We propose a test statistic under a set of identification conditions considered by Hoderlein, Su and ..."
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Cited by 3 (1 self)
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This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model nonadditively. We propose a test statistic under a set of identification conditions considered by Hoderlein, Su and White (2012), which require the existence of a control variable such that the regressor is independent of the error term given the control variable. The test statistic is motivated from the observation that, under the additive error structure, the partial derivative of the nonparametric structural function with respect to the error term is one under identification. The asymptotic distribution of the test is established and a bootstrap version is proposed to enhance its finite sample performance. Monte Carlo simulations show that the test has proper size and reasonable power in finite samples.
HeavyTail and PlugIn Robust Consistent Conditional Moment Tests of Functional Form
, 2012
"... We present asymptotic powerone tests of regression model functional form for heavy tailed time series. Under the null hypothesis of correct specification the model errors must have a …nite mean, and otherwise only need to have a fractional moment. If the errors have an infinite variance then in p ..."
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Cited by 3 (3 self)
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We present asymptotic powerone tests of regression model functional form for heavy tailed time series. Under the null hypothesis of correct specification the model errors must have a …nite mean, and otherwise only need to have a fractional moment. If the errors have an infinite variance then in principle any consistent plugin is allowed, depending on the model, including those with nonGaussian limits and/or a subp convergence rate. One test statistic exploits an orthogonalized test equation that promotes plugin robustness irrespective of tails. We derive chisquared weak limits of the statistics, we characterize an empirical process method for smoothing over a trimming parameter, and we study the finite sample properties of the test statistics.
On tests for global maximum of the loglikelihood function
 IEEE Trans. Inform. Theory
, 2004
"... Abstract — Given the location of a relative maximum of the loglikelihood function, how to assess whether it is the global maximum? This paper investigates a statistical tool, which answers this question by posing it as a hypothesis testing problem. A general framework for constructing tests for glo ..."
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Cited by 3 (1 self)
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Abstract — Given the location of a relative maximum of the loglikelihood function, how to assess whether it is the global maximum? This paper investigates a statistical tool, which answers this question by posing it as a hypothesis testing problem. A general framework for constructing tests for global maximum is given. The characteristics of the tests are investigated for two cases: correctly specified model and model mismatch. A finite sample approximation to the power is given, which gives a tool for performance prediction and a measure for comparison between tests. The sensitivity of the tests to model mismatch is analyzed in terms of the Renyi divergence and the KullbackLeibler distance between the true underlying distribution and the assumed parametric class and tests that are insensitive to small deviations from the model are derived. The tests are illustrated for three applications: passive localization or direction finding using an array of sensors, estimating the parameters of a Gaussian mixture model, and estimation of superimposed exponentials in noise problems that are known to suffer from local maxima. Index Terms — Parameter estimation, maximum likelihood, global optimization, local maxima, array processing, Gaussian
MertonStyle Option Pricing under Regime Switching
"... This paper develops a valuation framework for a perpetual American call option when the underlying asset return dynamic is modelled by a regime switching process. In particular, asset return dynamic is governed by a stochastic dividend process which randomly switches between two regimes that are cha ..."
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Cited by 2 (0 self)
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This paper develops a valuation framework for a perpetual American call option when the underlying asset return dynamic is modelled by a regime switching process. In particular, asset return dynamic is governed by a stochastic dividend process which randomly switches between two regimes that are characterized by different rates of both drift and volatility. This regimeswitching characterization of dividend growth is supported by empirical works. We provide analytical results by solving the fundamental differential equation. The analysis reveals that the option value may differ between states. Our empirical application shows that these differences may be quantitatively very important.