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BEKK-GARCH模型中的多元方差目标估计AI 解读

In this paper, we consider asymptotic inference in the multivariate BEKK model based on (co)variance targeting (VT). By definition the VT estimator is a two‐step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding to these two steps. Strong consistency is established under weak moment conditions, while sixth‐order moment restrictions are imposed to establish asymptotic normality. The simulations…

非线性时间序列模型中的随机等度连续性AI 解读

In this paper, I provide simple and easily verifiable conditions under which a strong form of stochastic equicontinuity holds in a wide variety of modern time series models. In contrast to most results currently available in the literature, my methods avoid mixing conditions. I discuss several applications in detail.

固定效应面板变系数模型的直接半参数估计AI 解读

In this paper, we present a new technique to estimate varying coefficient models of unknown form in a panel data framework where individual effects are arbitrarily correlated with the explanatory variables in an unknown way. The estimator is based on first differences and then a local linear regression is applied to estimate the unknown coefficients. To avoid a non‐negligible asymptotic bias, we need to introduce a higher‐dimensional kernel weight. This enables us to remove…

固定效应面板部分线性可加回归模型的估计AI 解读

In this paper, we investigate the estimation problem of fixed effects panel data partially linear additive regression models. Semi‐parametric fixed effects panel data regression models are tools that are well suited to econometric analysis and the analysis of cDNA micro‐arrays. By applying a polynomial spline series approximation and a profile least‐squares procedure, we propose a semi‐parametric least‐squares dummy variables estimator (SLSDVE) for the parametric component…

社会互动下处理反应的识别AI 解读

This paper studies identification of potential outcome distributions when treatment response may have social interactions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when non‐parametric shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response is a polar case…

采用正交级数方差估计量的异方差与自相关稳健 F 检验AI 解读

The paper develops a new heteroskedasticity and autocorrelation robust test in a time series setting. The test is based on a series long‐run variance matrix estimator that involves projecting the time series of interest onto a set of orthonormal bases and using the sample variance of the projection coefficients as the long‐run variance estimator. When the number of orthonormal bases K is fixed, a finite‐sample‐corrected Wald statistic converges to a standard F distribution.…

因变量随机缺失时空间自回归模型的估计AI 解读

We suggest and compare different methods for estimating spatial autoregressive models with randomly missing data in the dependent variable. Aside from the traditional expectation-maximization (EM) algorithm, a nonlinear least squares method is suggested and a generalized method of moments estimation is developed for the model. A two-stage least squares estimation with imputation is proposed as well. We analytically compare these estimation methods and find that generalized…

不同信息集与抽样方案下联立方程的识别和推断AI 解读

In simple static linear simultaneous equation models the empirical distributions of IV and OLS are examined under alternative sampling schemes and compared with their first-order asymptotic approximations. We demonstrate that the limiting distribution of consistent IV is not affected by conditioning on exogenous regressors, whereas that of inconsistent OLS is. The OLS asymptotic and simulated actual variances are shown to diminish by extending the set of exogenous variables…

线性及面板回归中空间误差相关的标准化LM检验AI 解读

The robustness of the Lagrange Multiplier (LM) tests for spatial error dependence of Burridge (1980) and Born and Breitung (2011) for the linear regression model, and Anselin (1988) and Debarsy and Etur (2010) for the panel regression model with random or fixed effects are examined. While all tests are asymptotically robust against distributional mis‐specification, their finite sample behaviour may be sensitive to the spatial layout. To overcome this shortcoming,…

存在大量外生回归变量时的工具变量估计与推断AI 解读

We consider a standard instrumental variables model contaminated by the presence of a large number of exogenous regressors. In an asymptotic framework where this number is proportional to the sample size, we study the impact of their ratio on the validity of existing estimators and tests. When the instruments are few, the inference using the conventional 2SLS estimator and associated t and J statistics, as well as the Anderson–Rubin and Kleibergen tests, is still valid. When…

不假定独立性时非对称拍卖的部分识别AI 解读

This paper examines identification in second‐price and ascending auctions within the private‐values framework. The first part of the paper considers an arbitrary type of dependence of bidders’ values and analyses identification under several observational scenarios, in which the highest bid is never observed. In a basic scenario, only the winner’s identity and the winning price are observed. The most informative is the scenario in which all the identities and all the bids…

潜变量模型中的集合推断AI 解读

We propose a methodology for constructing valid confidence regions in incomplete models with latent variables satisfying moment equality restrictions. These include moment equality and inequality models with latent variables. The confidence regions are obtained by inverting tests based on the characterization of the identified set derived in Ekeland et al. (2010). A valid bootstrap approximation of the distribution of the test statistic is derived under mild conditions and…

利用模拟非参数矩估计动态潜变量模型AI 解读

We propose a novel estimation method for dynamic latent variable (DLV) models that combines simulations and non‐parametric kernel smoothing techniques to obtain a generalised method of moments (GMM) estimator based on a set of conditional moments. As such it extends the simulated method of moments (SMM) of Duffie and Singleton (1993) to allow for the use of conditional moments, instead of unconditional ones. It can also be seen as a generalisation of the SMM for static…

参数不稳定下的弱工具变量推断AI 解读

This paper addresses the question of how to conduct inference on weakly identified coefficients in unstable econometric models. The weak correlations between the instruments and the relevant first‐order condition are modelled as local to zero, and we focus on moderate parameter instabilities. We show that, in the presence of weak identification, asymptotic distributions on the estimators and tests remain robust to moderate instability. Therefore, inference on the subset of…

IV与GMM框架下参数函数对非参数备择的检验AI 解读

This paper develops a specification test for functional form for models identified by a conditional moment restriction, including IV and GMM settings. The framework is one where the moment restriction is specified as a function of data, a finite-dimensional parameter vector and a non-parametric function (an infinite-dimensional parameter vector). The null hypothesis is that the moment restriction does not depend on the non-parametric function. The test is relatively easy to…

ARMA误差不相关性检验：非标准Andrews–Ploberger检验AI 解读

A problem of interest in economic and finance applications is testing whether ARMA (Autoregressive moving average) errors are uncorrelated under weak assumptions, namely assumptions where the errors are neither iid nor a martingale difference. In this paper, non‐standard versions of the tests of serial correlation introduced by Andrews and Ploberger (1996, hereafter AP) are proposed for diagnostic checking of ARMA errors. The original AP tests are designed for the case where…

结构变化的非参数检测与估计AI 解读

We propose a semi‐non‐parametric approach to the estimation and testing of structural change in time series regression models. Under the null of a given set of the coefficients being constant, we develop estimators of both the time‐varying (non‐parametric) and constant (parametric) components. Given the estimators under null and alternative, generalized F and Wald tests are developed. The asymptotic distributions of the estimators and test statistics are derived. A…

基于分位数残差的误设检验AI 解读

We develop quantile residual‐based misspecification tests and apply them to non‐linear time series models for which conventional residuals are unsuited. We formulate a general framework and use it to obtain computationally simple tests aimed at detecting autocorrelation, conditional heteroscedasticity and non‐normality in quantile residuals. These tests are generalizations of similar previous tests based on conventional residuals and the Lagrange Multiplier principle.…

高维线性模型中单个变量效应的估计AI 解读

A problem encountered in some empirical research, e.g. growth empirics, is that the potential number of explanatory variables is large compared to the number of observations. This makes it infeasible to condition on all variables in order to determine whether a variable of interest has an effect. We assume that the effect is identified in a high‐dimensional linear model specified by unconditional moment restrictions. We propose a new method that provides a consistent…

部分线性模型中的工具变量回归AI 解读

We consider the semiparametric regression Xtβ + φ (Z) where β and φ(.) are unknown slope coefficient vector and function, and where the variables (X, Z) are endogeneous. We propose necessary and sufficient conditions for the identification of the parameters in the presence of instrumental variables. We also focus on the estimation of β. An incorrect parametrization of φ generally leads to an inconsistent estimator of β, whereas consistent nonparametric estimators for β have…

利用大型非平衡期权面板估计与检验非仿射期权定价模型AI 解读

In this paper, we consider joint estimation of objective and risk‐neutral parameters for stochastic volatility option pricing models using both stock and option prices. A common strategy simplifies the task by limiting the analysis to just one option per date. We first discuss its drawbacks on the basis of model interpretation, estimation results and pricing exercises. We then turn the attention to a more flexible approach, that successfully exploits the wealth of…

共爆炸向量自回归中的理性泡沫检验AI 解读

We derive the parameter restrictions that a standard equity market model implies for a bivariate vector autoregression for stock prices and dividends, and we show how to test these restrictions using likelihood ratio tests. The restrictions, which imply that stock returns are unpredictable, are derived both for a model without bubbles and for a model with a rational bubble. In both cases we show how the restrictions can be tested through standard chi-squared inference. The…

《非线性经济时间序列建模》书评AI 解读

Nonlinear modelling is becoming part of the ‘standard’ toolkit used by empirical macroeconomics researchers and this book provides a valuable introduction to the methods commonly (and, in some cases, not so commonly) employed in practice. Granger and Teräsvirta provided a slim volume on nonlinear economic modelling in 1993. However, as well as being updated, this new book covers much more territory, so it should not be viewed as simply a second edition of the previous…

隐含概率自助法的崩溃点理论AI 解读

This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the uniform weight and implied probability bootstraps by analysing behaviours of the bootstrap quantiles when outliers take arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties characterize the situation where the implied probability bootstrap is more robust against outliers than the uniform weight…