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Controlling for overdispersion in grouped conditional logit models: A computationally simple application of Dirichlet‐multinomial regression

控制分组条件 Logit 模型的过度离散:Dirichlet–多项回归的简便应用

In this article, we provide a random utility-based derivation of the Dirichlet-multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We show that this model is a natural extension of McFadden's conditional logit for grouped data and discuss its relationship with count models. Finally, we use a data set on patient choice of hospitals to illustrate an application of the Dirichlet-multinomial regression. Copyright…

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Two‐stage estimation of limited dependent variable models with errors‐in‐variables

含测量误差的受限因变量模型的两阶段估计

This paper deals with censored or truncated regression models where the explanatory variables are measured with additive errors. We propose a two-stage estimation procedure that combines the instrumental variable method and the minimum distance estimation. This approach produces consistent and asymptotically normally distributed estimators for model parameters. When the predictor and instrumental variables are normally distributed, we also propose a maximum likelihood based…

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Selection correction in panel data models: An application to the estimation of females' wage equations

面板数据模型的选择校正:女性工资方程的应用

In recent years a number of panel estimators have been suggested for sample selection models, where both the selection equation and the equation of interest contain individual effects which are correlated with the explanatory variables. Not many studies exist that use these methods in practise. We present and compare alternative estimators, and apply them to a typical problem in applied econometrics: the estimation of the wage returns to experience for females. We discuss…

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Bayesian inference for the mixed conditional heteroskedasticity model

混合条件异方差模型的贝叶斯推断

We estimate by Bayesian inference the mixed conditional heteroskedasticity model of Haas et al. (2004a Journal of Financial Econometrics 2, 211--50). We construct a Gibbs sampler algorithm to compute posterior and predictive densities. The number of mixture components is selected by the marginal likelihood criterion. We apply the model to the SP500 daily returns. Copyright Royal Economic Society 2007

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Propensity score matching without conditional independence assumption—with an application to the gender wage gap in the United Kingdom

无需条件独立假设的倾向得分匹配:英国性别工资差距应用

Propensity score matching is frequently used for estimating average treatment effects. Its applicability, however, is not confined to treatment evaluation. In this paper, it is shown that propensity score matching does not hinge on a selection on observables assumption and can be used to estimate not only adjusted means but also their distributions, even with non-i.i.d. sampling. Propensity score matching is used to analyze the gender wage gap among graduates in the UK. It…

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Numerical integration‐based Gaussian mixture filters for maximum likelihood estimation of asymmetric stochastic volatility models

基于数值积分的高斯混合滤波:非对称随机波动率模型的极大似然估计

I consider Gaussian filters based on numerical integration for maximum likelihood estimation of stochastic volatility models with leverage. I show that for this class of models, the prediction step of the Gaussian filter can be evaluated analytically without linearizing the state--space model. Monte Carlo simulations show that the mixture Gaussian filter performs remarkably well in terms of both accuracy and computation time compared to the quasi-maximum likelihood and…

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A model selection method for S‐estimation

一种适用于S估计的模型选择方法

Cleaning data or removing some data periods in least squares (LS) regression analysis is not unusual. This practice indicates that a researcher sometimes desires to estimate the parameter value, with which the regression function fits a large fraction of individuals or events in the population (behind the original data set), possibly exhibiting poor fits to some atypical individuals or events. The S-estimators are a class of estimators that are consistent with the…

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Method of moment estimation in the COGARCH(1,1) model

COGARCH(1,1)模型的矩估计

We suggest moment estimators for the parameters of a continuous time GARCH(1,1) process based on equally spaced observations. Using the fact that the increments of the COGARCH(1,1) process are strongly mixing with exponential rate, we show that the resulting estimators are consistent and asymptotically normal. We investigate the empirical quality of our estimators in a simulation study based on the variance gamma driven COGARCH(1,1) model. The estimated volatility with…

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On the inconsistency of the unrestricted estimator of the information matrix near a unit root

单位根附近无约束信息矩阵估计量的不一致性

converges to a non-degenerate random variable and contributes to the asymptotic distribution of a Wald test for the null hypothesis of a random walk versus a stable AR(1) alternative. With this newly derived asymptotic distribution, the above Wald test is found to improve its performance. A non-local criterion of asymptotic relative efficiency based on Bahadur slopes has been employed for the first time to the problem of unit root testing. The Wald test derived in the paper…

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Estimating option implied risk‐neutral densities using spline and hypergeometric functions

利用样条与合流超几何函数估计期权隐含风险中性密度

We examine the ability of two recent methods -- the smoothed implied volatility smile method (SML) and the density functionals based on confluent hypergeometric functions (DFCH) -- for estimating implied risk-neutral densities (RNDs) from European-style options. Two complementary Monte Carlo experiments are conducted and the performance of the two RND estimators is evaluated by the root mean integrated squared error (RMISE) criterion. Results from both experiments show that…

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Local sensitivity and diagnostic tests

局部敏感性与诊断检验

In this paper, we confront sensitivity analysis with diagnostic testing. Every model is misspecified (in the sense that no model coincides with the data-generating process), but a model is useful if the parameters of interest (the focus) are not sensitive to small perturbations in the underlying assumptions. The study of the effect of these violations on the focus is called sensitivity analysis. Diagnostic testing, on the other hand, attempts to find out whether a nuisance…

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Minimum distance estimation of stationary and non‐stationary ARFIMA processes

平稳与非平稳 ARFIMA 过程的最小距离估计

A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator is easy to compute and is consistent and asymptotically normally distributed for fractionally integrated (FI) processes with an integration order d strictly greater than −0.75. Therefore, it can be applied to both…

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How useful are tests for unit‐root in distinguishing unit‐root processes from stationary but non‐linear processes?

单位根检验能否区分单位根过程与平稳非线性过程?

Standard unit-root tests are known to be biased towards the non-rejection of a unit-root when they are applied to time series with non-linear dynamics. Unfortunately, not much is known about the source of the power loss mainly because the analysis on nonstationarity and nonlinearity to this date has been fragmentary. By means of a Monte Carlo study, the current paper investigates the finite sample performance of five popular unit-root tests against a wide class of non-linear…

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Lag‐augmented two‐ and three‐stage least squares estimators for integrated structural dynamic models

单整结构动态模型的滞后增广两阶段与三阶段最小二乘估计

We consider a lag-augmented two- or three-stage least-squares estimator for a structural dynamic model of non-stationary and possibly cointegrated variables without the prior knowledge of unit roots or rank of cointegration. We show that the conventional two-and three-stage least-squares estimators are consistent but contain non-standard distributions without the strict exogeneity assumption; hence the conventional Wald type test statistics may not be chi-square distributed.…

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Semiparametric efficiency bounds in dynamic non‐linear systems under elliptical symmetry

椭圆对称条件下动态非线性系统的半参数效率界

We analyze semiparametric efficient estimation of non-linear simultaneous equation models in a time series context and derive a semiparametric efficiency bound for estimation of the parameters when the errors are i.i.d. from an unknown elliptically symmetric density. We derive the bound in the case of errors that are elliptically symmetric conditional on predetermined variables. Copyright Royal Economic Society 2007

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Uniform convergence rate of the seminonparametric density estimator and testing for similarity of two unknown densities

半非参数密度估计的一致收敛速度与两未知密度的相似性检验

This paper studies the uniform convergence rate of the truncated seminonparametric (SNP) density estimator. Using the uniform convergence rate result we obtain, we propose a test statistic testing the equivalence of two unknown densities where two densities are estimated using the SNP estimator and supports of densities are possibly unbounded. Copyright Royal Economic Society 2007

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Testing for time series linearity

时间序列线性检验

process, and is consistent against non-linearity of either form. Finite sample simulation evidence, together with empirical evidence from an application to US Dollar real exchange rates, suggests that our procedure should work well in practice. Copyright Royal Economic Society 2007

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A sequential procedure for determining the number of regimes in a threshold autoregressive model

确定门限自回归模型状态数的序贯程序

In this paper, we propose a sequential method for determining the number of regimes in threshold autoregressive models. The proposed method relies on the superconsistency of sequential threshold estimates and uses general linearity tests to determine the number of thresholds. A simulation study is performed in order to find out the finite-sample properties of our procedure and to compare it with two other procedures available in the literature. We find that our method works…

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Cross‐validation and non‐parametric k nearest‐neighbour estimation

交叉验证与非参数 k 最近邻估计

In this paper we consider the problem of estimating a non-parametric regression function using the k nearest-neighbour method. We provide asymptotic theories for the least-squares cross validation (CV) selected smoothing parameter k for both local constant and local linear estimation methods. We also establish the asymptotic normality results for the resulting non-parametric regression function estimators. Some limited Monte Carlo experiments show that the CV method performs…

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Optimal Fractional Dickey–Fuller tests

最优分数阶 Dickey–Fuller 检验

This article analyzes the fractional Dickey-Fuller (FDF) test for unit roots recently introduced by Dolado, Gonzalo and Mayoral (2002 Econometrica 70, 1963--2006) within a more general setup. These authors motivate their test with a particular analogy with the Dickey-Fuller test, whereas we interpret the FDF test as a class of tests indexed by an auxiliary parameter, which can be chosen to maximize the power of the test. Within this framework, we investigate optimality…

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The asymptotic distribution of the F‐test statistic for individual effects

个体效应 F 检验统计量的渐近分布

(the number of cross-sections) and T is fixed (the number of time periods). Three theoretical results emerge: (i) the standard F-test procedure will still deliver asymptotically valid inferences; (ii) under (pure) local random effects, the F-test and random effects test procedures have identical asymptotic power; (iii) under local fixed, or random effects which are correlated with the regressors, the F-test will have higher asymptotic power than the random effects test.…

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Temporal disaggregation by state space methods: Dynamic regression methods revisited

用状态空间方法进行时间分解:重访动态回归方法

The paper advocates the use of state space methods to deal with the problem of temporal disaggregation by dynamic regression models, which encompass the most popular techniques for the distribution of economic flow variables, such as Chow-Lin, Fernandez and Litterman. The state space methodology offers the generality that is required to address a variety of inferential issues that have not been dealt with previously. The paper contributes to the available literature in three…

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Non-parametric regression for binary dependent variables

二元因变量的非参数回归

Finite-sample properties of non-parametric regression for binary dependent variables are analyzed. Non parametric regression is generally considered as highly variable in small samples when the number of regressors is large. In binary choice models, however, it may be more reliable since its variance is bounded. The precision in estimating conditional means as well as marginal effects is investigated in settings with many explanatory variables (14 regressors) and small…

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Semiparametric estimation and testing of the trend of temperature series

气温序列趋势的半参数估计与检验

The application of a partially linear model to global and hemispheric temperature series is proposed. Partially linear modelling allows the trend to take a very general form rather than imposing the restriction of linearity seen in existing studies. The removal of the linearity restriction is based on the fact that it is well accepted that a significant trend is present in global temperature series. The model will allow for the data to "speak for themselves" with regard to…

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