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一类 Lévy 过程的非参数估计AI 解读

We consider estimation for a class of Lévy processes, modelled as a sum of a drift, a symmetric stable process and a compound Poisson process. We propose a nonparametric approach to estimating unknown parameters of our model, including the drift, the scale and index parameters in the stable law, the mean of the Poisson process and the underlying jump size distribution. We show that regression and nonparametric deconvolution methods, based on the empirical characteristic…

经验似然的 Bahadur 效率AI 解读

This paper studies the Bahadur efficiency of empirical likelihood for testing moment condition models. It is shown that under mild regularity conditions, the empirical likelihood overidentifying restriction test is Bahadur efficient, i.e., its p-value attains the fastest convergence rate under each fixed alternative hypothesis. Analogous results are derived for parameter hypothesis testing and set inference problems.

弱工具变量下的稳健置信集合AI 解读

This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple algorithm for finding the Conditional Likelihood Ratio (CLR) confidence sets. Full descriptions of possible forms of the CLR, Anderson-Rubin (AR) and Lagrange Multiplier (LM)…

跳跃与贝塔：系统性风险的分离和估计AI 解读

We provide a new theoretical framework for disentangling and estimating the sensitivity towards systematic diffusive and jump risks in the context of factor models. Our estimates of the sensitivities towards systematic risks, or betas, are based on the notion of increasingly finer sampled returns over fixed time intervals. We show consistency and derive the asymptotic distributions of our estimators. In an empirical application of the new procedures involving high-frequency…

工具变量可能众多时 LIML 估计量的渐近最优性AI 解读

We consider the estimation of the coefficients of a linear structural equation in a simultaneous equation system when there are many instrumental variables. We derive some asymptotic properties of the limited information maximum likelihood (LIML) estimator when the number of instruments is large; some of these results are new as well as old, and we relate them to results in some recent studies. We have found that the variance of the limiting distribution of the LIML…

利用第二 Hansen–Jagannathan 距离评价资产定价模型AI 解读

We develop a specification test and a sequence of model selection procedures for non-nested, overlapping, and nested models based on the second Hansen-Jagannathan distance, which requires a good asset pricing model to not only have small pricing errors but also be arbitrage free. Our methods have reasonably good finite sample performances and are more powerful than existing ones in detecting misspecified models with small pricing errors but are not arbitrage-free and in…

两样本工具变量估计量AI 解读

Following an influential article by Angrist and Krueger (1992) on two-sample instrumental variables (TSIV) estimation, numerous empirical researchers have applied a computationally convenient two-sample two-stage least squares (TS2SLS) variant of Angrist and Krueger's estimator. In the two-sample context, unlike the single-sample situation, the IV and 2SLS estimators are numerically distinct. We derive and compare the asymptotic distributions of the two estimators and find…

分位数回归的置信带AI 解读

Let ( X 1 , Y 1 ), …, ( X n , Y n ) be independent and identically distributed random variables and let l ( x ) be the unknown p -quantile regression curve of Y conditional on X . A quantile smoother l n ( x ) is a localized, nonlinear estimator of l ( x ). The strong uniform consistency rate is established under general conditions. In many applications it is necessary to know the stochastic fluctuation of the process { l n ( x ) – l ( x )}. Using strong approximations of…

谱密度估计的渐近理论AI 解读

We consider nonparametric estimation of spectral densities of stationary processes, a fundamental problem in spectral analysis of time series. Under natural and easily verifiable conditions, we obtain consistency and asymptotic normality of spectral density estimates. Asymptotic distribution of maximum deviations of the spectral density estimates is also derived. The latter result sheds new light on the classical problem of tests of white noises.

通过非参数回归与特征函数检验多因子连续时间马尔可夫模型AI 解读

We develop a nonparametric regression-based goodness-of-fit test for multifactor continuous-time Markov models using the conditional characteristic function, which often has a convenient closed form or can be approximated accurately for many popular continuous-time Markov models in economics and finance. An omnibus test fully utilizes the information in the joint conditional distribution of the underlying processes and hence has power against a vast class of continuous-time…

扩展至非平稳情形的 Whittle 估计AI 解读

For long memory time series models with uncorrelated but dependent errors, we establish the asymptotic normality of the Whittle estimator under mild conditions. Our framework includes the widely used fractional autoregressive integrated moving average models with generalized autoregressive conditional heteroskedastic-type innovations. To cover nonstationary fractionally integrated processes, we extend the idea of Abadir, Distaso, and Giraitis (2007, Journal of Econometrics…

经验相似性模型的渐近理论AI 解读

We consider the stochastic process $Y_t = \sum\nolimits_{i < t} {s_w } (x_t ,x_i)Y_i /\sum\nolimits_{i < t} {s_w } (x_t ,x_i) + \varepsilon _t$ , t = 2, …, n , where s w ( x t , x i ) is a similarity function between the t th and the i th observations and { ε t } is a random disturbance term. This process was originally axiomatized by Gilboa, Lieberman, and Schmeidler (2006, Review of Economics and Statistics 88, 433–444) as a way by which agents, or…

利用可行准广义最小二乘改进和扩展样本末端不稳定性检验AI 解读

This paper extends the Andrews (2002, Econometrica 71, 1661–1694) and Andrews and Kim (2006, Journal of Business & Economic Statistics 24, 379–394) ordinary least squares–based end-of-sample instability tests for linear regression models. The author proposes to quasi-difference the data first using a consistent estimate of the sum of the autoregressive coefficients of the error process and then test for the end-of-sample instability. For the cointegration model, the feasible…

一般非线性 AR(1) 模型的线性性上确界检验AI 解读

We consider linearity testing in a general class of nonlinear time series models of order one, involving a nonnegative nuisance parameter that (a) is not identified under the null hypothesis and (b) gives the linear model when equal to zero. This paper studies the asymptotic distribution of the likelihood ratio test and asymptotically equivalent supremum tests. The asymptotic distribution is described as a functional of chi-square processes and is obtained without imposing a…

存在截面依赖的面板单位根检验：进一步研究AI 解读

An effective way to control for cross-section correlation when conducting a panel unit root test is to remove the common factors from the data. However, there remain many ways to use the defactored residuals to construct a test. In this paper, we use the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) residuals to form two new tests. One estimates the pooled autoregressive coefficient, and one simply uses a sample moment. We establish their…

关于特征价格函数的非参数估计AI 解读

Abstract Recently, using mixed data on Canadian housing, Parmeter, Henderson, and Kumbhakar ( Journal of Applied Econometrics 2007; 22 : 695–699) found that a nonparametric approach for estimating a hedonic house price function is superior to formerly suggested parametric and semiparametric specifications. We carefully reanalyze these specifications for this dataset by applying a recent nonparametric specification test and simulation‐based prediction comparisons. For the…

欧洲电力价格的长期关系AI 解读

Abstract This paper analyses the interdependencies existing in wholesale electricity prices in six major European countries. The results of a robust multivariate long‐run dynamic analysis reveal the presence of four highly integrated central European markets (France, Germany, the Netherlands and Austria). The trend shared by these four electricity markets appears to be common also to gas prices, but not to oil prices. The existence of a common long‐term dynamics among…

未知异方差下空间自回归模型的 GMM 估计AI 解读

In the presence of heteroskedastic disturbances, the MLE for the SAR models without taking into account the heteroskedasticity is generally inconsistent. The 2SLS estimates can have large variances and biases for cases where regressors do not have strong effects. In contrast, GMM estimators obtained from certain moment conditions can be robust. Asymptotically valid inferences can be drawn with consistently estimated covariance matrices. Efficiency can be improved by…

允许截面依赖的面板数据广义非线性工具变量单位根检验AI 解读

This paper proposes a unit root test for panel data with cross-sectional dependence. The test generalizes the nonlinear IV unit root test of Chang (2002) to the case where there exist some common factors in panels. The main idea is to eliminate the cross-sectional dependence through the method of principal components as in Bai and Ng (2004) and then apply Chang's test to the treated data. Under certain conditions, the proposed test is consistent and has a standard normal…

半参数协整回归：年龄分布对消费与储蓄的影响AI 解读

We consider a semiparametric cointegrating regression model, for which the disequilibrium error is further explained nonparametrically by a functional of distributions changing over time. The paper develops the statistical theories of the model. We propose an efficient econometric estimator and obtain its asymptotic distribution. A specification test for the model is also investigated. The model and methodology are applied to analyze how an aging population in the US…

非参数传递函数模型AI 解读

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between 'input' and 'output' time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more…

数据依赖平滑参数下的非参数与半参数估计及检验AI 解读

We consider nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters. Most of the existing works on asymptotic distributions of a nonparametric/semiparametric estimator or a test statistic are based on some deterministic smoothing parameters, while in practice it is important to use data-driven methods to select the smoothing parameters. In this paper we give a simple sufficient condition that can be used to establish…

含自回归与异方差扰动的空间自回归模型：设定与估计AI 解读

This study develops a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first generalize the GMM estimator suggested in (Kelejian and Prucha, 1998) and (Kelejian and Prucha, 1999) for the spatial autoregressive parameter in the disturbance process. We also define IV estimators for the…

动态面板模型的间接推断AI 解读

Maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size and large cross section sample size asymptotics. This paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference, shows unbiasedness and analyzes efficiency. Monte Carlo studies show that our procedure achieves substantial bias reductions with only mild…