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存在选择的非正态处理—结果模型：设定、模拟似然估计与医疗利用应用AI 解读

We develop a specification and estimation framework for a class of nonlinear, non-normal microeconometric models of treatment and outcome with selection. A latent factor structure is used to accommodate selection into treatment and a simulated likelihood method is used for estimation. The methodology is applied to examine the causal effect of managed care, a multinomial discrete choice process, on the utilization of health care services, measured as binary indicators and…

平稳与非平稳协整回归的工具变量估计AI 解读

Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least-squares estimation of cointegrating regressions between non-stationary and/or long memory stationary variables where the integration orders of regressor and disturbance sum to less than 1, as happens always for stationary regressors, and sometimes for mean-reverting non-stationary ones. Unlike in the classical…

三区制SETAR模型中的单位根检验AI 解读

This paper proposes a simple testing procedure to distinguish a unit root process from a globally stationary three-regime self-exciting threshold autoregressive process. Following the threshold cointegration literature we assume that the process follows the random walk in the corridor regime, and therefore we propose that the null of a unit root be tested by the Wald statistic for the joint significance of autoregressive parameters in both lower and upper regimes. We…

初始观测来自无条件分布时的单位根检验与结构变化AI 解读

Following Elliott (1999; International Economic Review 40, 767--83.) and Perron and Rodríguez (2003; Journal of Econometrics 115,1--27), we develop unit root tests in the context of structural change models using GLS detrended data ( Elliott, Rothenberg and Stock 1996; Econometrica 64, 813--39) when the initial observation is drawn from its unconditional distribution. We derive the limiting distributions of the M-tests ( Stock, 1999 cointegration, causality and forecasting;…

含结构突变的单位根检验：联合假设的设定AI 解读

Several tests based on a t-ratio have been proposed in the literature to decide the order of integration of a time series allowing for a structural break. However, another approach based on testing a joint hypothesis of unit root and the irrelevance of some nuisance parameters is also feasible. This paper proposes new unit root tests consistent with the presence of a structural break applying this second perspective. Our approach deals both with the case where the break is…

具有异质线性趋势的二元选择面板模型的一致估计AI 解读

This paper presents an extension of fixed effects binary choice models for panel data, to the case of heterogeneous linear trends. Two estimators are proposed: a Logit estimator based on double conditioning and a semiparametric, smoothed maximum score estimator based on double differences. We investigate small-sample properties of these estimators with a Monte Carlo simulation experiment, and compare their statistical properties with standard fixed effects procedures. An…

基于多项式系数密度的聚合AR(1)模型AI 解读

This paper develops a new kind of aggregation model. We extend the work of Linden (1999) to allow the AR coefficient to be drawn from a polynomial density function. The polynomial density incorporates a wealth of multi-modal density functions as special cases. Given the aggregate data, we provide estimation methods for the coefficients and the order of the polynomial density. A test for the functional form of the polynomial is provided. We apply the model to the consumption…

回归误差方差估计中预检验最优临界值的进一步结果AI 解读

This paper enlarges on results of Wan and Zou (Journal of Econometrics 114 (2003), 165--96) on the choice of critical values for pre-test procedures based on the minimum risk criterion. We consider a modification of the general theorem given in Wan and Zou (2003) to obtain the optimal critical value that minimizes the risks of various inequality pre-test estimators of the regression error variance under a general class of first-order differentiable loss functions.…

异质面板平稳性的均值组检验AI 解读

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard normal under the null for large N (number of groups) and large T (number of time periods). Monte Carlo results support the use of…

线性回归异方差的模拟检验：进一步结果AI 解读

As shown by the results of Dufour, Khalaf, Bernard and Genest (2004, Journal of Econometrics 122, 317--347), exact tests for heteroskedasticity in linear regression models can be obtained, by using Monte Carlo (MC) techniques, if either (i) it is assumed that the true form of the error distribution under homoskedasticity is known, or (ii) the null hypothesis specifies both homoskedasticity and the form of the error distribution. Non-parametric bootstrap tests of…

矩条件选择的自助法AI 解读

This paper proposes a bootstrap-based procedure for selecting the best moment conditions among a set of correctly specified moment conditions. The proposed method can be motivated by Edgeworth expansions and chooses moment conditions that minimize the approximate coverage error of confidence intervals and hypothesis tests for parameters. Because of the analytical intractability of Edgeworth expansions, we estimate the coverage error by the bootstrap. The proposed method can…

不依赖比例风险假设的单指标风险函数半参数估计AI 解读

This research develops a semiparametric kernel-based estimator of hazard functions which does not assume proportional hazards. The maintained assumption is that the hazard functions depend on regressors only through a linear index. The estimator permits both discrete and continuous regressors, both discrete and continuous failure times, and can be applied to right-censored data and to multiple-risks data, in which case the hazard functions are risk-specific. The estimator is…

重复调查与卡尔曼滤波AI 解读

The time-series nature of repeated surveys is seldom taken into account. The few studies that do so smooth the period-wise estimates without using the cross-sectional information. This leads to inefficient estimation. We present a statistical model of repeated surveys and construct a computationally simple estimator based on the Kalman filter algorithm. The method efficiently uses the whole underlying data set, but only the first and second moments of the data are required…

针对分数积分扰动的Durbin–Watson检验有限样本功效AI 解读

We consider the finite-sample power of various tests against serial correlation in the disturbances of a linear regression model when these disturbances follow certain stationary long-memory processes. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin--Watson test and many other tests that can be written as ratios of quadratic forms in the disturbances, the power can drop to zero as the long-memory parameter approaches the…

利用横截面估计协整关系AI 解读

This paper specifies a regression model describing cointegrating relations between variables at the individual level. The models considered allow for homogeneous cointegration and heterogeneous cointegration. In both cases correlation between the regressors and the regression error can occur through aggregate shocks that are common to all cross-section units so the condition about the regressors being independent of the regression error is not imposed. It is shown that the…

存在趋势突变时基于残差的块自助法单位根检验AI 解读

In this paper, we build on the "residual-based block bootstrap unit root testing" (RBB) method, proposed by Paparoditis and Politis (2003). We develop an extension of this method to allow for bootstrap unit root testing in a model defined by an augmented Dickey--Fuller (ADF) equation that contains linear combinations of arbitrary dummies as its deterministic part. The main application of such an extension is that it allows for unit root testing in the presence of arbitrary…

GARCH均值模型中的人工回归检验AI 解读

The issue of finite-sample inference in Generalised Autoregressive Conditional Heteroskedasticity (GARCH)-like models has seldom been explored in the theoretical literature, although its potential relevance for practitioners is obvious. In some cases, asymptotic theory may provide a very poor approximation to the actual distribution of the estimators in finite samples. The aim of this paper is to propose the application of the so-called double length regressions (DLR) to…

某些基于广义逆的渐近检验统计量的任意性AI 解读

Under appropriate conditions, some asymptotic test statistics based on generalized inverses (g-inverses) are shown to be arbitrary in the sense that any desired numerical value for a statistic can be obtained by appropriately choosing a g-inverse of an estimator. Examples of statistics based on g-inverses include score-type and Hausman-type statistics. Some versions of these statistics considered in the literature can be viewed as polar cases in the sense that their…

方差未知时一元正态分布均值的估计AI 解读

variables. For this problem with known variance of innovations, the neutral Laplace weighted-average least-squares estimator was introduced in Magnus (2002). We generalize this estimator to the case where the unknown variance is estimated by least squares and find that main properties of the Laplace estimator only change marginally. Therefore we recommend the neutral Laplace estimator to be used in practice. Copyright 2005 Royal Economic Society

This paper derives second‐order expansions for the distributions of the Whittle and profile plug‐in maximum likelihood estimators of the fractional difference parameter in the ‘Autoregressive Fractionally Integrated Moving Average of order (0, d, 0)’ with unknown mean and variance. Both estimators are shown to be second‐order pivotal. This extends earlier findings of Lieberman and Phillips (2004a, Econometric Theory, 20, 464–84), who derived expansions for the Gaussian…

基于最大熵密度的部分自适应估计AI 解读

We propose a partially adaptive estimator based on information theoretic maximum entropy estimates of the error distribution. The maximum entropy (maxent) densities have simple yet flexible functional forms to nest most of the mathematical distributions. Unlike the non-parametric fully adaptive estimators, our parametric estimators do not involve choosing a bandwidth or trimming, and only require estimating a small number of nuisance parameters, which is desirable when the…

刻画高持续性波动的非线性GARCH模型AI 解读

In this paper we study a new class of nonlinear GARCH models. Special interest is devoted to models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable is mainly motivated by the desire to find useful models for highly persistent volatility. The underlying idea is that high persistence in conditional variance…

含跳跃仿射随机波动率模型推断的自适应 MCMC 方法AI 解读

In this paper we propose an efficient Markov chain Monte Carlo (MCMC) algorithm to estimate stochastic volatility models with jumps and affine structure. Our idea relies on the use of adaptive methods that aim at reducing the asymptotic variance of the estimates. We focus on the Delayed Rejection algorithm in order to find accurate proposals and to efficiently simulate the volatility path. Furthermore, Bayesian model selection is addressed through the use of reduced runs of…

利用多变量结构时间序列模型进行时间分解AI 解读

In this paper, we provide a multivariate framework for temporal disaggregation of time series observed at a given frequency into higher frequency time series. The suggested method uses the seemingly unrelated time series equations model and it is estimated by the Kalman filter. The methodology is flexible enough to allow for almost any kind of temporal disaggregation problems of both raw and seasonally adjusted time series. Comparisons with other temporal disaggregation…