Irregular Identification,Support Conditions,and Inverse Weight Estimation

In weighted moment condition models, we show a subtle link between identification and estimability that limits the practical usefulness of estimators based on these models. In particular, if it is necessary for (point) identification that the weights take arbitrarily large values, then the parameter of interest, though point identified, cannot be estimated at the regular (parametric) rate and is said to be irregularly identified. This rate depends on relative tail conditions and can be as slow in some examples as n^−1/4. This nonstandard rate of convergence can lead to numerical instability and/or large standard errors. We examine two weighted model examples: (i) the binary response model under mean restriction introduced by Lewbel (1997) and further generalized to cover endogeneity and selection, where the estimator in this class of models is weighted by the density of a special regressor, and (ii) the treatment effect model under exogenous selection (Rosenbaum and Rubin (1983)), where the resulting estimator of the average treatment effect is one that is weighted by a variant of the propensity score. Without strong relative support conditions, these models, similar to well known “identified at infinity” models, lead to estimators that converge at slower than parametric rate, since essentially, to ensure point identification, one requires some variables to take values on sets with arbitrarily small probabilities, or thin sets. For the two models above, we derive some rates of convergence and propose that one conducts inference using rate adaptive procedures that are analogous to Andrews and Schafgans (1998) for the sample selection model.     

论区域产业政策趋同的重要动因——地方政府效用

在区域经济的发展过程中,地方政府之间日益激烈的竞争必然会造成区域之间的产业政策趋同。这对于区域经济的协调发展和长远发展极为不利。化解问题的办法应当靠提高中央政府的宏观调控水平,强化地方政府的责、权、利边界,引导地方政府在区域产业政策中体现差异性。     

中印两国增长包容性“不合理趋同”问题

实现包容性增长对促进增长收益的合理分配与社会稳定具有重要性,本文在分析包容性增长长期价值的基础上,探讨从改革启动到金融危机之前,中国和印度两国包容性增长的"不合理趋同"及其差异性,并从制度层面研究了中印两国包容性增长差异以及"不合理趋同"产生的重要根源。强调实现包容性增长对中国与印度经济可持续发展的意义。     

中国农业科技创新绩效的地区差异研究——对农业科研机构创新绩效的实证分析

文章基于VRS模型测度了中国31个省（市、区）2007-2016年农业科研机构科技创新绩效,按照华东、西北、华北、中南、西南、东北六大区域进行地区差异分析,并对农业科研机构科技创新绩效差异进行σ收敛和β收敛检验分析。研究表明：从地域差异看,六大区域农业科技创新绩效存在显著差异,按绩效值由高到低依次为：华东区 > 西北区 > 华北区 > 中南区 > 西南区 > 东北区;六大区域农业科研机构科技创新绩效的总体差异并未呈现出显著的σ收敛,但绝对β收敛和条件β收敛模型研究表明,六大区域的农业科研机构科技创新绩效差异正在逐渐缩小,且存在落后者对先进者的"追赶效应";华北区以最快速度缩小省际差距达到内部稳态水平,东北区次之,华东区最为缓慢。正确认识中国农业科研机构科技创新绩效的地区差异,可以促使合理配置农业科技资源,强化农业科技创新驱动力,完善农业科技创新体系,加快现代农业实现的步伐,助力乡村振兴战略。     

Test for Parameter Change in Linear Processes Based on Whittle's Estimator

In this article, we develop a cusum test for testing for parameter changes in linear processes based on Whittle's estimator. It is shown that under regularity conditions, the test statistic converges to the sup of a Brownian bridge. The result is particularly useful in handling the change point test in stationary ARMA processes. A simulation result is provided for illustration.     

Asymptotic Results of a Nonparametric Conditional Quantile Estimator for Functional Time Series

We consider the estimation of the conditional quantile function when the covariates take values in some abstract function space. The main goal of this article is to establish the almost complete convergence and the asymptotic normality of the kernel estimator of the conditional quantile under the α-mixing assumption and on the concentration properties on small balls of the probability measure of the functional regressors. Some applications and particular cases are studied. This approach can be applied in time series analysis to the prediction and building of confidence bands. We illustrate our methodology with El Niño data.     

An Improved Test for Continuous Local Martingales

We present a new test for the “continuous martingale hypothesis”. That is, a test for the hypothesis that observed data are from a process which is a continuous local martingale. The basis of the test is an embedded random walk at first passage times, obtained from the well-known representation of a continuous local martingale as a continuous time-change of Brownian motion. With a variety of simulated diffusion processes our new test shows higher power than existing tests using either the crossing tree or the quadratic variation, including the situation where non-negligible drift is present. The power of the test in the presence of jumps is also explored with a variety of simulated jump diffusion processes. The test is also applied to two sequences of high-frequency foreign exchange trade-by-trade data. In both cases the continuous martingale hypothesis is rejected at times less than hourly and we identify significant dependence in price movements at these small scales.