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Efficient GMM Estimation of Spatial Dynamic Panel Data Models
Spatial autoregression Dynamic panels Fixed effects Generalized method of moment
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2016/1/26
In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with fixed effects when n is large, and T can be large, but small relative to n. The GMM es...
High Dimensional Stochastic Regression with Latent Factors, Endogeneity and Nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
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2016/1/26
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors, a linear com-bination of some ...
Estimation of Spatial Panel Data Models with Time Varying Spatial Weights Matrices
Spatial autoregression Panel data Time varying spatial weights matrices Fixed e¤ects Maximum likelihood Impact analysis
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2016/1/26
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymp...
Identification of spatial panel Durbin models
Spatial autoregression Durbin regressors Spatial VAR Dynamic panel Fixed e¤ects Random e¤ects
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2016/1/26
Identi…cation of a spatial Durbin model is a concern in the spatial econometrics literature. The concern is similar to the identi…cation of the endogenous e¤ect, the contextual e¤ect and correlation e...
Applying the job demands–resources model to migrant workers: Exploring how and when geographical distance increases quit propensity
Applying the job demands–resources model migrant workers Exploring how
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2016/1/26
We extend the job demands–resources model to explain how and when rural migrants whoworkfarfrom theirfamilies andprovincial hometownsaremore likely toleave jobs. Through two studies, we found that the...
Comparative investigation of three Bayesian p values
Bayesian model checking Posterior predictive p value Sampled posterior p value
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2016/1/26
Please check your proof carefully and mark all corrections at the appropriate place in the proof (e.g., by using on-screen annotation in the PDF file) or compile them in a separate list. Note: if you ...
Central Limit Theorems for Supercritical Branching Nonsymmetric Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale
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2016/1/25
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
Concise Comparative Summaries (CCS) of Large Text Corpora with a Human Experiment
text summarization high-dimensional analysis sparse model- ing Lasso L1 regularized logistic regression co-occurrence tf-idf
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2016/1/25
In this paper, we propose a general framework for topic-specific summarization of large text corpora, and illustrate how it can be used for the analysis of news databases. Our framework, concise compa...
Central Limit Theorems for Supercritical Superprocesses
Central limit theorem supercritical superprocess excursion measures of superprocesses
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2016/1/25
In this paper, we establish a central limit theorem for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment condition. This c...
Closed-form expansions of discretely monitored asian options in diffusion models
discretely monitored Asian options CEV model CIR process Black-Scholes model Brennan
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2016/1/25
In this paper we propose a closed-form asymptotic expansion approach to pricing discretely monitored Asian options in general one-dimensional diffusion models. Our expansion is a small-time expansion ...
Central Limit Theorems for Supercritical Branching Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale eigenfunction expansion
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2016/1/25
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Estimation of fixed effects panel regression models with separable and nonseparable space-time filters
Panel data Spatial cointegration Explosive roots Fixed e¤ects
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2016/1/25
This paper considers a quasi-maximum likelihood estimation for a linear panel data model with time and individual …xed e¤ects, where the disturbances have dynamic and spatial correlations which might ...
Weak extinction versus global exponential growth of total mass for superdi usions corresponding to the operator Lu + βu − ku2
superdiffusion superprocess measure-valued process gauge theorem Kato class growth bound
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2016/1/25
Consider a superdiffusion X on R d corresponding to the semilinear operator A(u) = Lu + βu − ku 2 , where L is a second order elliptic operator, β(·) is in the Kato class and bounded from above,...
On Pattern Recovery of The Fused Lasso
Confidence interval jackknife empirical likelihood risk measure
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2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
Jackknife Empirical Likelihood Method for Some Risk Measures and Related Quantities
Confidence interval jackknife empirical likelihood risk measure
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2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...