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Abstract This article develops the uniform asymptotic theory for local projection (LP) regression when the true lag order of the model is unknown and potentially infinite. The theory allows for varying degrees of persistence in the data, growing response horizons, and general conditionally heteroskedastic martingale-difference shocks. Based on the theory, we make two main contributions. First, we show that LPs can achieve semiparametric efficiency at a given horizon under…

存在干扰参数时的局部回归推断AI 解读

We consider inference based on local estimating equations in the presence of nuisance parameters. The framework is useful for a number of applications including those in economic policy evaluation based on discontinuities or kinks and in real-time financial risk management. We focus on the criterion-function-based (in particular, empirical likelihood-based) inference, and establish conditions under which the test statistic has a pivotal asymptotic distribution. In the key…

离散持续时间结果的断点回归半非参数估计AI 解读

We consider the regression discontinuity (RD) design with the duration outcome which has discrete support. The parameters of policy interest are treatment effects on unconditional (duration effect) and conditional (hazard effect) exiting probabilities for each discrete level. We propose a novel semi-nonparametric estimator which exploits a flexible separability structure of the underlying continuous-time duration process. Simultaneous inference over discrete levels is…

分类结果变量的回归不连续设计AI 解读

We consider the regression discontinuity (RD) design with categorical outcomes, and exploit the possibility of adapting well-developed microeconometric models to the RD setting. The channels through which the forcing variable affects the potential outcome distributions are constrained to be minimal, to preserve the nonparametric feature of the RD design. Focusing on general categorical outcomes (nominal or ordinal), we develop a new RD estimator based on a nonparametric…

尾部风险度量的无模型推断AI 解读

Understanding uncertainty in estimating risk measures is important in modern financial risk management. In this paper we consider a nonparametric framework that incorporates auxiliary information available in covariates and propose a family of inferential methods for the value at risk, expected shortfall, and related risk measures. A two-step generalized empirical likelihood test statistic is constructed and is shown to be asymptotically pivotal without requiring variance…

回归不连续设计的经验似然推断AI 解读

This paper proposes empirical likelihood based inference methods for causal effects identified from regression discontinuity designs. We consider both the sharp and fuzzy regression discontinuity designs and treat the regression functions as nonparametric. The proposed inference procedures do not require asymptotic variance estimation and the confidence sets have natural shapes, unlike the conventional Wald-type method. These features are illustrated by simulations and an…

密度不连续性的估计与推断AI 解读

Continuity or discontinuity of probability density functions of data often plays a fundamental role in empirical economic analysis. For example, for identification and inference of causal effects in regression discontinuity designs it is typically assumed that the density function of a conditioning variable is continuous at a cutoff point that determines assignment of a treatment. Also, discontinuity in density functions can be a parameter of economic interest, such as in…

时间序列条件分位数的非参数推断AI 解读

This paper considers model-free hypothesis testing and confidence interval construction for conditional quantiles of time series. A new method, which is based on inversion of the smoothed empirical likelihood of the conditional distribution function around the local polynomial estimator, is proposed. The associated inferential procedures do not require variance estimation, and the confidence intervals are automatically shaped by data. We also construct the bias-corrected…

波动率结构变化的高功效检验AI 解读

Detecting structural changes in volatility is important for understanding volatility dynamics and stylized facts observed for financial returns such as volatility persistence. We propose modified CUSUM and LM tests that are built on a robust estimator of the long-run variance of squared series. We establish conditions under which the new tests have standard null distributions and diverge faster than standard tests under the alternative. The theory allows smooth and abrupt…

对非平稳波动率稳健的多变量趋势检验AI 解读

This article studies inference of multivariate trend model when the volatility process is nonstationary. Within a quite general framework we analyze four classes of tests based on least squares estimation, one of which is robust to both weak serial correlation and nonstationary volatility. The existing multivariate trend tests, which either use non-robust standard errors or rely on non-standard distribution theory, are generally non-pivotal involving the unknown time-varying…

波动率函数的倾斜非参数估计及实证应用AI 解读

This article proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local-level nonparametric regression applied to squared residuals of the mean regression. The estimator is shown to be asymptotically equivalent to the local linear estimator in the case of unbounded support but, unlike that estimator, is…

扩散模型的重加权函数估计AI 解读

The local linear method is popular in estimating nonparametric continuous-time diffusion models, but it may produce negative results for the diffusion (or volatility) functions and thus lead to insensible inference. We demonstrate this using U.S. interest rate data. We propose a new functional estimation method of the diffusion coefficient based on reweighting the conventional Nadaraya–Watson estimator. It preserves the appealing bias properties of the local linear estimator…

非参数常返扩散过程的经验似然推断AI 解读

This paper provides a new approach to constructing confidence intervals for nonparametric drift and diffusion functions in the continuous-time diffusion model via empirical likelihood (EL). The log EL ratios are constructed through the estimating equations satisfied by the local linear estimators. Limit theories are developed by means of increasing time span and shrinking observational intervals. The results apply to both stationary and nonstationary recurrent diffusion…

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