CONSISTENT MODEL SPECIFICATION TESTS

2000 ◽  
Vol 16 (6) ◽  
pp. 1016-1041 ◽  
Author(s):  
Yanqin Fan ◽  
Qi Li
Keyword(s):  
Nonparametric Tests ◽  
Model Specification ◽  
Local Alternatives ◽  
Exponential Weight ◽  
Conditional Moment ◽  
Specification Tests ◽  
Consistent Model ◽  
Close Relationship ◽  
Complex Valued ◽  
Theoretical Results

We point out the close relationship between the integrated conditional moment tests in Bierens (1982, Journal of Econometrics 20, 105–134) and Bierens and Ploberger (1997, Econometrica 65, 1129–1152) with the complex-valued exponential weight function and the kernel-based tests in Härdle and Mammen (1993, Annals of Statistics 21, 1926–1947), Li and Wang (1998, Journal of Econometrics 87, 145–165), and Zheng (1996, Journal of Econometrics 75, 263–289). It is well established that the integrated conditional moment tests of Bierens (1982) and Bierens and Ploberger (1997) are more powerful than kernel-based nonparametric tests against Pitman local alternatives. In this paper we analyze the power properties of the kernel-based tests and the integrated conditional moment tests for a sequence of “singular” local alternatives, and show that the kernel-based tests can be more powerful than the integrated conditional moment tests for these “singular” local alternatives. These results suggest that integrated conditional moment tests and kernel-based tests should be viewed as complements to each other. Results from a simulation study are in agreement with the theoretical results.

On the Limit Behavior of a Chi-Square Type Test if the Number of Conditional Moments Tested Approaches Infinity

1994 ◽  
Vol 10 (1) ◽  
pp. 70-90 ◽  
Author(s):  
R.M. de Jong ◽  
H.J. Bierens
Keyword(s):  
Infinite Number ◽  
Fixed Number ◽  
Model Specification ◽  
Test Statistic ◽  
Conditional Moment ◽  
Chi Square ◽  
Moment Conditions ◽  
Conditional Moments ◽  
Finite Samples ◽  
Consistent Model

In this paper, a consistent model specification test is proposed. Some consistent model specification tests have been discussed in econometrics literature. Those tests are consistent by randomization, display a discontinuity in sample size, or have an asymptotic distribution that depends on the data-generating process and on the model, whereas our test does not have one of those disadvantages. Our test can be viewed upon as a conditional moment test as proposed by Newey but instead of a fixed number of conditional moments, an asymptotically infinite number of moment conditions is employed. The use of an asymptotically infinite number of conditional moments will make it possible to obtain a consistent test. Computation of the test statistic is particularly simple, since in finite samples our statistic is equivalent to a chi-square conditional moment test of a finite number of conditional moments.

Testing conditional moment restriction models using empirical likelihood

2021 ◽  
Author(s):  
Yves G Berger
Keyword(s):  
Empirical Likelihood ◽  
Model Specification ◽  
Ratio Test ◽  
Conditional Moment ◽  
Nominal Level ◽  
Empirical Likelihood Ratio Test ◽  
Likelihood Model ◽  
Heteroscedastic Errors ◽  
Endogenous Covariates ◽  
The Relationship

Abstract An empirical likelihood test is proposed for parameters of models defined by conditional moment restrictions, such as models with non-linear endogenous covariates, with or without heteroscedastic errors or non-separable transformation models. The number of empirical likelihood constraints is given by the size of the parameter, unlike alternative semi-parametric approaches. We show that the empirical likelihood ratio test is asymptotically pivotal, without explicit studentisation. A simulation study shows that the observed size is close to the nominal level, unlike alternative empirical likelihood approaches. It also offers a major advantages over two-stage least-squares, because the relationship between the endogenous and instrumental variables does not need to be known. An empirical likelihood model specification test is also proposed.

SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES

2015 ◽  
Vol 32 (4) ◽  
pp. 917-946 ◽  
Author(s):  
Marian Hristache ◽  
Valentin Patilea
Keyword(s):  
Regression Models ◽  
Supply And Demand ◽  
Simultaneous Equations ◽  
Conditional Moment ◽  
Efficient Score ◽  
Semiparametric Efficiency ◽  
Regression Quantile ◽  
New Applications ◽  
Theoretical Results ◽  
Moment Restriction

This paper addresses the problem of semiparametric efficiency bounds for conditional moment restriction models with different conditioning variables. We characterize such an efficiency bound, that in general is not explicit, as a limit of explicit efficiency bounds for a decreasing sequence of unconditional (marginal) moment restriction models. An iterative procedure for approximating the efficient score when this is not explicit is provided. Our theoretical results provide new insight for the theory of semiparametric efficiency bounds literature and open the door to new applications. In particular, we investigate a class of regression-like (mean regression, quantile regression,…) models with missing data, an example of a supply and demand simultaneous equations model and a generalized bivariate dichotomous model.

Provocation and the Strategy of Terrorist and Guerrilla Attacks

2015 ◽  
Vol 70 (1) ◽  
pp. 133-173 ◽  
Author(s):  
David B. Carter
Keyword(s):  
Empirical Model ◽  
Western Europe ◽  
Model Specification ◽  
Terrorist Attacks ◽  
Specification Tests ◽  
State Response ◽  
Target Theory ◽  
Response Groups ◽  
Using Data ◽  
State Responses

AbstractViolent nonstate groups are usually weaker than the states they target. Theory suggests that groups carefully condition their choice of tactics on anticipated state response. Yet scholars know very little about whether and how groups strategically plan attacks in anticipation of state response. Scholars do not know if and under what conditions groups employ violent tactics to provoke or avoid a forceful state response, although extant theory is consistent with both possibilities. Relatedly, there is little systematic evidence about why groups choose terrorist or guerrilla tactics and how this choice relates to anticipated state response. I develop a theoretical and empirical model of the interaction between groups and states that generates unique evidence on all three fronts. Using data on attacks in Western Europe from 1950 to 2004, I show that guerrilla attacks are sometimes associated with provoking forceful state response, whereas terrorist attacks are generally associated with avoiding forceful response. Groups effectively choose their tactics to avoid forceful state responses that are too damaging for themselves but provoke forceful responses that disproportionately harm civilians. These findings survive several robustness and model specification tests.

Synchronization of time-varying time delayed neutral-type neural networks for finite-time in complex field

2021 ◽  
Vol 8 (3) ◽  
pp. 486-498
Author(s):  
N. Jayanthi ◽  
◽  
R. Santhakumari ◽  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
State Feedback ◽  
Neutral Type ◽  
State Feedback Control ◽  
Projective Synchronization ◽  
Time Varying ◽  
Master System ◽  
Complex Valued ◽  
Theoretical Results

This paper deals with the problem of finite-time projective synchronization for a class of neutral-type complex-valued neural networks (CVNNs) with time-varying delays. A simple state feedback control protocol is developed such that slave CVNNs can be projective synchronized with the master system in finite time. By employing inequalities technique and designing new Lyapunov--Krasovskii functionals, various novel and easily verifiable conditions are obtained to ensure the finite-time projective synchronization. It is found that the settling time can be explicitly calculated for the neutral-type CVNNs. Finally, two numerical simulation results are demonstrated to validate the theoretical results of this paper.

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