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PANEL DATA MODELS WITH FINITE NUMBER OF MULTIPLE EQUILIBRIA

具有有限个多重均衡的面板数据模型

We study a nonlinear panel data model in which the fixed effects are assumed to have finite support. The fixed effects estimator is known to have the incidental parameters problem. We contribute to the literature by making a qualitative observation that the incidental parameters problem in this model may not be not as severe as in the conventional case. Because fixed effects have finite support, the probability of correctly identifying the fixed effect converges to one even…

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Dynamic discrete choice structural models: A survey

动态离散选择结构模型:综述

This paper reviews methods for the estimation of dynamic discrete choice structural models and discusses related econometric issues. We consider single-agent models, competitive equilibrium models and dynamic games. The methods are illustrated with descriptions of empirical studies which have applied these techniques to problems in different areas of economics. Programming codes for some of the estimation methods are available in a companion web page.

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Comparing IV with structural models: What simple IV can and cannot identify

工具变量与结构模型的比较:简单 IV 能识别什么

This paper compares the economic questions addressed by instrumental variables estimators with those addressed by structural approaches. We discuss Marschak's Maxim: estimators should be selected on the basis of their ability to answer well-posed economic problems with minimal assumptions. A key identifying assumption that allows structural methods to be more informative than IV can be tested with data and does not have to be imposed.

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Quasi-structural estimation of a model of childcare choices and child cognitive ability production

儿童照护选择与认知能力生产模型的准结构估计

This article evaluates the effects of maternal vs. alternative care providers' time inputs on children's cognitive development using the sample of single mothers in the National Longitudinal Survey of Youth. To deal with the selection problem created by unobserved heterogeneity of mothers and children, we develop a model of mother's employment and childcare decisions. We then obtain approximate decision rules for employment and childcare use, and estimate these jointly with…

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Structural vs. atheoretic approaches to econometrics

计量经济学中的结构方法与非理论方法

In this paper I attempt to lay out the sources of conflict between the so-called "structural" and "experimentalist" camps in econometrics. Critics of the structural approach often assert that it produces results that rely on too many assumptions to be credible, and that the experimentalist approach provides an alternative that relies on fewer assumptions. Here, I argue that this is a false dichotomy. All econometric work relies heavily on a priori assumptions. The main…

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Health, economic resources and the work decisions of older men

健康、经济资源与高龄男性的工作决策

We specify a dynamic programming model that addresses the interplay among health, financial resources, and the labor market behavior of men late in their working lives. We model health as a latent variable, for which self-reported disability status is an indicator, and allow self-reported disability to be endogenous to labor market behavior. We use panel data from the Health and Retirement Study. While we find large impacts of health on behavior, they are substantially…

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Quantile estimation with adaptive importance sampling

利用自适应重要性抽样估计分位数

We introduce new quantile estimators with adaptive importance sampling. The adaptive estimators are based on weighted samples that are neither independent nor identically distributed. Using a new law of iterated logarithm for martingales, we prove the convergence of the adaptive quantile estimators for general distributions with nonunique quantiles thereby extending the work of Feldman and Tucker [Ann. Math. Statist. 37 (1996) 451–457]. We illustrate the algorithm with an…

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Covariate adjusted functional principal components analysis for longitudinal data

纵向数据的协变量调整函数主成分分析

Classical multivariate principal component analysis has been extended to functional data and termed functional principal component analysis (FPCA). Most existing FPCA approaches do not accommodate covariate information, and it is the goal of this paper to develop two methods that do. In the first approach, both the mean and covariance functions depend on the covariate Z and time scale t while in the second approach only the mean function depends on the covariate Z. Both new…

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Discussion

讨论:条件多元分位数的建模选择

First I would like to congratulate the authors for developing a new concept of directional quantile contours.The work will contribute well to the pursuit of multivariate quantiles.The multiple output regression provides a new way of estimating the conditional multivariate quantile functions, which will certainly facilitate a large number of applications.I enjoy the paper for its mathematical rigor and computational savvy.My discussion will focus on the modeling aspect of…

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Efficient semiparametric estimation of multi-valued treatment effects under ignorability

可忽略性下多值处理效应的有效半参数估计

This paper studies the efficient estimation of a large class of multi-valued treatment effects as implicitly defined by a collection of possibly over-identified non-smooth moment conditions when the treatment assignment is assumed to be ignorable. Two estimators are introduced together with a set of sufficient conditions that ensure their -consistency, asymptotic normality and efficiency. Under mild assumptions, these conditions are satisfied for the Marginal Mean Treatment…

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The dynamic invariant multinomial probit model: Identification, pretesting and estimation

动态不变性多项 Probit 模型:识别、预检验与估计

We present a new specification for the multinomial multiperiod probit model with autocorrelated errors. In sharp contrast with commonly used specifications, ours is invariant with respect to the choice of a baseline alternative for utility differencing. It also nests these standard models as special cases, allowing for data-based selection of the baseline alternatives for the latter. Likelihood evaluation is achieved under an Efficient Importance Sampling (EIS) version of…

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Heterogeneous treatment effects: Instrumental variables without monotonicity?

异质性处理效应:没有单调性的工具变量?

Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify a local average treatment effect parameter using instrumental variables. More recently, Heckman and Vytlacil (1999) suggested the estimation of a variety of treatment effect parameters using a local version of their approach. We investigate the sensitivity of the respective estimates to random departures from monotonicity. Approximations to the respective bias terms are derived.…

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Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics

广义非参数反卷积及其在收入动态中的应用

In this paper, we construct a non-parametric estimator of the distributions of latent factors in linear independent multi-factor models under the assumption that factor loadings are known. Our approach allows estimation of the distributions of up to L(L+ 1)/2 factors given L measurements. The estimator uses empirical characteristic functions, like many available deconvolution estimators. We show that it is consistent, and derive asymptotic convergence rates. Monte Carlo…

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Nonparametric Discrete Choice Models With Unobserved Heterogeneity

含不可观测异质性的非参数离散选择模型

In this research, we provide a new method to estimate discrete choice models with unobserved heterogeneity that can be used with either cross-sectional or panel data. The method imposes nonparametric assumptions on the systematic subutility functions and on the distributions of the unobservable random vectors and the heterogeneity parameter. The estimators are computationally feasible and strongly consistent. We provide an empirical application of the estimator to a model of…

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Another Look at the Identification of Dynamic Discrete Decision Processes: An Application to Retirement Behavior

重新审视动态离散决策过程的识别:退休行为应用

This article deals with the estimation of behavioral and welfare effects of counterfactual policy interventions using dynamic structural models where all the primitive functions are nonparametrically specified (i.e., preferences, technology, transition rules, and distribution of unobserved variables). It proves the nonparametric identification of agents’ decision rules, before and after the policy intervention, and of the change in agents’ welfare. Based on these results, I…

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SEMIPARAMETRIC EFFICIENCY BOUND IN TIME-SERIES MODELS FOR CONDITIONAL QUANTILES

条件分位数时间序列模型的半参数效率界

We derive the semiparametric efficiency bound in dynamic models of conditional quantiles under a sole strong mixing assumption. We also provide an expression of Stein’s (1956) least favorable parametric submodel. Our approach is as follows: First, we construct a fully parametric submodel of the semiparametric model defined by the conditional quantile restriction that contains the data generating process. We then compare the asymptotic covariance matrix of the MLE obtained in…

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A SPATIAL DYNAMIC PANEL DATA MODEL WITH BOTH TIME AND INDIVIDUAL FIXED EFFECTS

同时含时间与个体固定效应的空间动态面板模型

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with both time and individual fixed effects when the number of individuals n and the number of time periods T can be large. We propose a data transformation approach to eliminate the time effects. When n / T → 0, the estimators are $\root \of {nT}$ consistent and asymptotically centered normal; when n is asymptotically proportional to T , they are $\root \of {nT}$…

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THE IMPACT OF A HAUSMAN PRETEST ON THE ASYMPTOTIC SIZE OF A HYPOTHESIS TEST

Hausman 预检验对假设检验渐近尺寸的影响

This paper investigates the asymptotic size properties of a two-stage test in the linear instrumental variables model when in the first stage a Hausman (1978) specification test is used as a pretest of exogeneity of a regressor. In the second stage, a simple hypothesis about a component of the structural parameter vector is tested, using a t -statistic that is based on either the ordinary least squares (OLS) or the two-stage least squares estimator (2SLS), depending on the…

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Dynamic treatment effect analysis of TV effects on child cognitive development

电视观看对儿童认知发展的动态处理效应分析

Abstract We investigate whether TV watching at ages 6–7 and 8–9 affects cognitive development measured by math and reading scores at ages 8–9, using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child‐specific factor, endogeneity of TV watching, and dynamic nature of the causal relation . A special emphasis is placed on the last aspect, where TV watching affects cognitive development, which in turn affects…

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Mean–variance econometric analysis of household portfolios

家庭投资组合的均值—方差计量分析

Abstract We investigate households' portfolio choice using a microeconometric approach derived from mean–variance optimization. We assume that households have heterogeneous expectations on the distribution of excess returns and that they cannot take short positions in risky assets. Assuming two such assets, we derive an explicit solution of the model characterized by four possible portfolio regimes, which are analyzed using two structural probit and tobit specifications with…

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Semiparametric estimation of consumer demand systems in real expenditure

以实际支出为基础的消费者需求系统半参数估计

Abstract Microdata concerning consumer demand typically show considerable variation in real expenditures, but very little variation in prices. We propose a semiparametric strategy for the consumer demand problem in which expenditure share equations are estimated nonparametrically in the real expenditure direction and estimated parametrically (with fixed or varying coefficients) in price directions. In our model, Engel curves are unrestricted: demands may have any rank.…

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Semiparametric Mean–Covariance Regression Analysis for Longitudinal Data

纵向数据的半参数均值—协方差回归分析

Efficient estimation of the regression coefficients in longitudinal data analysis requires a correct specification of the covariance structure. Existing approaches usually focus on modeling the mean with specification of certain covariance structures, which may lead to inefficient or biased estimators of parameters in the mean if misspecification occurs. In this article, we propose a data-driven approach based on semiparametric regression models for the mean and the…

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Marginal and Nested Structural Models Using Instrumental Variables

使用工具变量的边际与嵌套结构模型

The objective of many scientific studies is to evaluate the effect of a treatment on an outcome of interest ceteris paribus. Instrumental variables (IVs) serve as an experimental handle, independent of potential outcomes and potential treatment status and affecting potential outcomes only through potential treatment status. We propose marginal and nested structural models using IVs, in the spirit of marginal and nested structural models under no unmeasured confounding. A…

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Variational Inference for Large-Scale Models of Discrete Choice

大规模离散选择模型的变分推断

Discrete choice models are commonly used by applied statisticians in numerous fields, such as marketing, economics, finance, and operations research. When agents in discrete choice models are assumed to have differing preferences, exact inference is often intractable. Markov chain Monte Carlo techniques make approximate inference possible, but the computational cost is prohibitive on the large datasets now becoming routinely available. Variational methods provide a…

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