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Full-Text Articles in Social and Behavioral Sciences
Specification Test For Spatial Autoregressive Models, Liangjun Su, Xi Qu
Specification Test For Spatial Autoregressive Models, Liangjun Su, Xi Qu
Research Collection School Of Economics
This article considers a simple test for the correct specification of linear spatial autoregressive models, assuming that the choice of the weight matrix Wn is true. We derive the limiting distributions of the test under the null hypothesis of correct specification and a sequence of local alternatives. We show that the test is free of nuisance parameters asymptotically under the null and prove the consistency of our test. To improve the finite sample performance of our test, we also propose a residual-based wild bootstrap and justify its asymptotic validity. We conduct a small set of Monte Carlo simulations to investigate …
A Martingale Difference-Divergence-Based Test For Specification, Liangjun Su, Xin Zheng
A Martingale Difference-Divergence-Based Test For Specification, Liangjun Su, Xin Zheng
Research Collection School Of Economics
In this paper we propose a novel consistent model specification test based on the martingale difference divergence (MDD) of the error term given the covariates. The MDD equals zero if and only if error term is conditionally mean independent of the covariates. Our MDD test does not require any nonparametric estimation under the alternative and it is applicable even if we have many covariates in the regression model. We establish the asymptotic distributions of our test statistic under the null and a sequence of Pitman local alternatives converging to the null at the usual parametric rate. Simulations suggest that our …
A Specification Test Based On The Mcmc Output, Yong Li, Jun Yu, Tao Zeng
A Specification Test Based On The Mcmc Output, Yong Li, Jun Yu, Tao Zeng
Research Collection School Of Economics
A test statistic is proposed to assess themodel specification after the model is estimated by Bayesian MCMC methods. Thenew test is motivated from the power enhancement technique of Fan, Liao and Yao(2015). It combines a component (J1) that tests anull point hypothesis in an expanded model and a power enhancement component (J0) obtained from the null model. It is shown that J0 converges to zero when the null model is correctly specified anddiverges when the null model is misspecified. Also shown is that J1 is asymptotically X2-distributed, suggesting that theproposed test is asymptotically pivotal, when the null model is correctlyspecified. …
Jump Regressions, Jia Li, Viktor Todorov, George Tauchen
Jump Regressions, Jia Li, Viktor Todorov, George Tauchen
Research Collection School Of Economics
We develop econometric tools for studying jump dependence of two processes from high-frequency observations on a fixed time interval. In this context, only segments of data around a few outlying observations are informative for the inference. We derive an asymptotically valid test for stability of a linear jump relation over regions of the jump size domain. The test has power against general forms of nonlinearity in the jump dependence as well as temporal instabilities. We further propose an efficient estimator for the linear jump regression model that is formed by optimally weighting the detected jumps with weights based on the …