Large balls left empty by a critical branching Wiener field

The particles distributed according to a Poisson random field execute independent critical branching Wiener processes. It looks natural that the largest empty ball around the origin becomes larger and larger with time. The asymptotic behaviour of the radius of the largest empty ball is studied.     

Semiparametric quantile regression estimation in dynamic models with partially varying coefficients

We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimators are derived. We demonstrate that the parametric estimators are root-n$n$ consistent and the estimation of the functional coefficients is oracle. In addition, efficiency of parameter estimation is discussed and a simple efficient estimator is proposed. A simple and easily implemented test for the hypothesis of a varying-coefficient is proposed. A Monte Carlo experiment is conducted to evaluate the performance of the proposed estimators.     

中国是否存在最优通货膨胀区间——通货膨胀和经济增长关系实证研究

利用门限回归模型(threshold regression model)分析中国通货膨胀与经济增长之间的关系,实证研究发现中国通货膨胀对经济增长的影响不是单一形态,而是具有非线性特征。中国经济存在最优通货膨胀区间1.4%～5.1%,而当通货膨胀高于5.1%或低于1.4%时,通货膨胀(通过影响生产要素)对经济增长有负的影响。     

农业保险促进了农民增收吗?——基于省级面板门槛模型的实证检验

本文基于2007～2016年中国31个省（区、市）面板数据,实证检验了农业保险发展对农民收入（以人均农业收入衡量）的影响。结果发现:受农民收入水平制约,农业保险对农民农业收入的影响表现出鲜明的门槛特征:只有当农民收入水平超过一定的门槛值以后,发展农业保险才会显著提高农民收入;而当农民收入水平较低时,投保农业保险反而会显著降低农民收入。此外,对农业保险的政策性补贴并不会造成福利耗散效应;相反,保费补贴有助于增加农民收入。     

Goodness-of-fit tests for discrete models based on the integrated distribution function

This paper presents a new widely applicable omnibus test for discrete distributions which is based on the difference between the integrated distribution function Ψ(t)=∫_t ^∞ (1−F(x))dx and its empirical counterpart. A bootstrap version of the test for common lattice models has accurate error rates even for small samples and exhibits high power with respect to competitive procedures over a large range of alternatives. Received: July 1998     

Influence analysis for Poisson inverse Gaussian regression models based on the EM algorithm

For Poisson inverse Gaussian regression models, it is very complicated to obtain the influence measures based on the traditional method, because the associated likelihood function involves intractable expressions, such as the modified Bessel function. In this paper, the EM algorithm is employed as a basis to derive diagnostic measures for the models by treating them as a mixed Poisson regression with the weights from the inverse Gaussian distributions. Several diagnostic measures are obtained in both case-deletion model and local influence analysis, based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. Two numerical examples are given to illustrate the results.     

Bootstrapping rank statistics

The bootstrap, which provides powerful approximations for many classes of statistics, is studied for simple linear rank statistics employing bounded and smooth score functions. To verify consistency we view a rank statistic as a statistic induced by a statistical functional ψ which is evaluated at a pair of dependent signed measures. Thus, we can apply the von Mises method to verify asymptotic results for the bootstrap. The strong consistency of the bootstrap distribution estimator is derived for the bootstrap based on resampling from the original data. Further, the residual bootstrap is studied. The accuracy of the bootstrap approximations for small sample sizes is studied by simulations. The simulations indicate that the bootstrap provides better results than a normal approximation.     

Functional-coefficient cointegration models

This paper studies estimation and inference of functional coefficient cointegration models. The proposed model offers a more flexible structure of cointegration where the value of cointegrating coefficients may be affected by informative covariates and thus may vary over time. The model may be viewed as a stochastic cointegration model and includes the conventional cointegration model as a special case. The proposed new model provides a useful complement to the conventional fixed coefficient cointegration models. Both kernel and local polynomial estimators are investigated. Inference procedures for instability of cointegrating parameters and a test for cointegration are proposed based on the functional-coefficient estimates. Limiting distributions of the estimates and testing statistics are derived.     

"公司+农户"农产品物流配送模式优化

文中回顾了"公司 农户"经营模式的状况,分析了农产品物流配送的重要性,并针对该模式实际存在的问题给出了解决问题的思路。站在公司和农户的角度,提高农产品销售物流配送的效率和效益,必须在上游环节降低农产品的采购物流成本,进而将采购与配送物流一体化,从而使配送模式达到优化的目的。     

Estimating regression coefficients from survey data by asymptotic design-cum-model based approach

Postulating a linear regression of a variable of interest on an auxiliary variable with values of the latter known for all units of a survey population, we consider appropriate ways of choosing a sample and estimating the regression parameters. Recalling Thomsen’s (1978) results on non-existence of ‘design-cum-model’ based minimum variance unbiased estimators of regression coefficients we apply Brewer’s (1979) ‘asymptotic’ analysis to derive ‘asymptotic-design-cummodel’ based optimal estimators assuming large population and sample sizes. A variance estimation procedure is also proposed.     

The tourism forecasting competition

We evaluate the performances of various methods for forecasting tourism data. The data used include 366 monthly series, 427 quarterly series and 518 annual series, all supplied to us by either tourism bodies or academics who had used them in previous tourism forecasting studies. The forecasting methods implemented in the competition are univariate and multivariate time series approaches, and econometric models. This forecasting competition differs from previous competitions in several ways: (i) we concentrate on tourism data only; (ii) we include approaches with explanatory variables; (iii) we evaluate the forecast interval coverage as well as the point forecast accuracy; (iv) we observe the effect of temporal aggregation on the forecasting accuracy; and (v) we consider the mean absolute scaled error as an alternative forecasting accuracy measure. We find that pure time series approaches provide more accurate forecasts for tourism data than models with explanatory variables. For seasonal data we implement three fully automated pure time series algorithms that generate accurate point forecasts, and two of these also produce forecast coverage probabilities which are satisfactorily close to the nominal rates. For annual data we find that Naïve forecasts are hard to beat.     

The smoothing dichotomy in nonparametric regression under long-memory errors

The phenomenon of smoothing dichotomy in random-design nonparametric regression is exposed in nontechnical terms from two recent papers published jointly with Jan Mielniczuk. This concerns the asymptotic distribution of kernel estimators when the errors exhibit long-range dependence, being instantaneous functions either of Gaussian sequences or of infinite-order moving averages, depending on the amount of smoothing.     

Generalized runs tests for the IID hypothesis

We provide a family of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to tests designed for specific alternatives, such as serial correlation, GARCH, or structural breaks. Our tests have appealing computational simplicity in that they do not require kernel density estimation, with the associated challenge of bandwidth selection. Simulations show levels close to nominal asymptotic levels. Our tests have power against both dependent and heterogeneous alternatives, as both theory and simulations demonstrate.     

经济发展对城市基建和外商投资的创新门槛效应研究

创新是引领城市经济高质量发展的核心引擎之一,基于2003—2018年间中国271个地级及以上城市的面板数据,以经济发展程度为门槛变量着重考察基础设施建设和外商投资对城市创新活动的非线性影响机制以及城市间的空间溢出效应。研究结果表明,基础设施建设和外商投资对城市创新都具有经济发展的双门槛效应,当经济发展程度达到第一个门槛值时,才会显著促使城市创新产出的提升。当经济发展程度跨越第二个门槛值时,会进一步增加城市的创新产。城市间的创新活动具有明显的空间依赖性,对于经济发展程度差距较大的城市之间,基础设施建设显著增强创新溢出效应。