异方差下的非线性协整检验

弱工具变量与异方差下的过度识别检验

Overidentification testing with weak instruments and heteroskedasticity

本文比较弱工具变量与异方差下KP秩检验与J检验，证明KP更优，并应用于EIS估计，指出J过度拒绝导致估计差异，推荐使用KP检验。

有效的异方差稳健检验

Valid Heteroskedasticity Robust Testing

本文针对异方差稳健检验中常规临界值导致水平扭曲的问题，提出使用最小尺寸控制临界值，证明其存在性并给出可检验条件，同时提供数值求解算法和软件实现，以兼顾检验有效性与功效。

基于 Bootstrap 的异方差稳健检验有多可靠？

How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?

本文提出有限样本理论诊断方法，用于识别线性回归中存在过度拒绝问题的 wild bootstrap 异方差稳健检验，并通过大规模数值研究评估其可靠性。

Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model

This paper considers a semiparametric generalized autoregressive conditional heteroskedasticity (S-GARCH) model. For this model, we first estimate the time-varying long run component for unconditional variance by the kernel estimator, and then estimate the non-time-varying parameters in GARCH-type short run component by the quasi maximum likelihood estimator (QMLE). We show that the QMLE is asymptotically normal with the parametric convergence rate. Next, we construct a Lagrange multiplier test for linear parameter constraint and a portmanteau test for model checking, and obtain their asymptot…

Unit Root Testing with Slowly Varying Trends

A unit root test is proposed for time series with a general nonlinear deterministic trend component. It is shown that asymptotically the pooled OLS estimator of overlapping blocks filters out any trend component that satisfies some Lipschitz condition. Under both fixed-$b$ and small-$b$ block asymptotics, the limiting distribution of the t-statistic for the unit root hypothesis is derived. Nuisance parameter corrections provide heteroskedasticity-robust tests, and serial correlation is accounted for by pre-whitening. A Monte Carlo study that considers slowly varying trends yields both good siz…

Semiparametric Testing with Highly Persistent Predictors

We address the issue of semiparametric efficiency in the bivariate regression problem with a highly persistent predictor, where the joint distribution of the innovations is regarded an infinite-dimensional nuisance parameter. Using a structural representation of the limit experiment and exploiting invariance relationships therein, we construct invariant point-optimal tests for the regression coefficient of interest. This approach naturally leads to a family of feasible tests based on the component-wise ranks of the innovations that can gain considerable power relative to existing tests under n…

检验拉姆齐式空间相互作用函数的线性

Testing linearity of spatial interaction functions à la Ramsey

提出计算简便的方法检验空间相互作用函数线性，该方法基于拉格朗日乘数原理，非参数且类似拉姆齐重置法，只需原假设下估计。蒙特卡罗模拟效果良好，芬兰数据实证研究展示其实际用途，为税收竞争争论提供启示。

在可能存在平滑确定性趋势时检验分数积分顺序

Testing the order of fractional integration when smooth deterministic trends are possibly present

本文提出一种检验分数积分的测试方法，通过Chebyshev多项式建模趋势部分，并使用局部Whittle方法构造Lagrange乘数检验统计量和频域信息准则，以选择Chebyshev多项式的阶数。

通过双重随机推断检验差异-in-差异系数的显著性

Testing the Significance of the Difference-in-Differences Coefficient via Doubly Randomised Inference

本文提出基于双边边际随机化的方法检验差异-in-差异估计量的显著性，指出传统方法在小样本中存在反保守问题，通过非参数替代方案提升稳健性，并在实证数据中验证了方法的有效性。

单调异方差下的 GLS

GLS under Monotone Heteroskedasticity

本文针对异方差 GLS 中条件方差函数估计难题，提出在非参数单调性约束下使用保序回归的两阶段 GLS 估计量，并通过模拟与老龄化—增长实证应用验证其有效性。

Quantile Autoregression-based Non-causality Testing

Non-causal processes have been drawing attention recently in Macroeconomics and Finance for their ability to display nonlinear behaviors such as asymmetric dynamics, clustering volatility, and local explosiveness. In this paper, we investigate the statistical properties of empirical conditional quantiles of non-causal processes. Specifically, we show that the quantile autoregression (QAR) estimates for non-causal processes do not remain constant across different quantiles in contrast to their causal counterparts. Furthermore, we demonstrate that non-causal autoregressive processes admit nonlin…

具有弱代理变量的proxy-SVARs识别与检验策略

An identification and testing strategy for proxy-SVARs with weak proxies

针对弱代理变量下proxy-SVARs的推断问题，提出一种利用非目标冲击的强工具进行识别的策略，并基于自助法重抽样设计预检验，实现标准渐近推断且不受预检验问题影响。

协整系统中平滑结构变化的检验

Testing for Smooth Structural Change in Cointegrated Systems

本文提出一种用于检验协整系统平滑结构变化的计量经济学框架，经2022年俄乌冲突前后相关市场数据验证，该方法可区分离散体制转变与平滑演化，发现相关市场协整关系发生了平滑变化。

Time-Transformed Test for the Explosive Bubbles under Non-stationary Volatility

This paper is devoted to testing for the explosive bubble under time-varying non-stationary volatility. Because the limiting distribution of the seminal Phillips et al. (2011) test depends on the variance function and usually requires a bootstrap implementation under heteroskedasticity, we construct the test based on a deformation of the time domain. The proposed test is asymptotically pivotal under the null hypothesis and its limiting distribution coincides with that of the standard test under homoskedasticity, so that the test does not require computationally extensive methods for inference.…

预测回归中序列依赖与持久性的稳健推断

Serial-Dependence and Persistence Robust Inference in Predictive Regressions

本文提出一种检验预测回归参数显著性的新方法，通过检验统计量内嵌机制解耦序列依赖，无需修正即可处理序列相关与条件异方差，且对预测变量持久性稳健，极限零分布服从卡方分布。