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识别内生解释变量参数的简约工具变量替代方法AI 解读

Abstract A review of the econometric literature on instrumental variables (IV) estimation shows that the performance of traditional IV estimation relies critically on the quality of the instruments. We discuss three different approaches that do not require the availability of observed instrumental variables: the ‘Higher Moments’ (HM) estimator, the ‘Identification trough Heteroscedasticity’ (IH) estimator, and the ‘Latent Instrumental Variable’ (LIV) approach. These methods…

对《增长决定因素的联合性》的评论AI 解读

Abstract Doppelhofer and Weeks ( 2009 ) present a statistic designed to indicate the probability that pairs of regressors appear together or individually in a Bayesian model averaged linear regression. This comment presents an alternative measure that is designed to overcome some of the limitations of Doppelhofer and Weeks' statistic. Copyright © 2009 John Wiley & Sons, Ltd.

增长决定因素的联合关联性AI 解读

Abstract This paper introduces a new measure of dependence or jointness among explanatory variables. Jointness is based on the joint posterior distribution of variables over the model space, thereby taking model uncertainty into account. By looking beyond marginal measures of variable importance, jointness reveals generally unknown forms of dependence. Positive jointness implies that regressors are complements, representing distinct but mutually reinforcing effects. Negative…

通过敏感性分析评估不完美工具变量推断的可信度AI 解读

Abstract Consistent instrumental variables (IV) estimation requires instruments uncorrelated with model errors, but this assumption is usually both suspect and untestable. Here the asymptotic sampling distribution of the IV parameter estimator is derived for any specified instrument‐error covariance vector. This result makes it possible to quantify the sensitivity of any particular IV inference result to instrument‐error correlations, allowing one to assess the robustness of…

迈向可复现的计量经济学研究：Sweave 框架AI 解读

The JAE Data Archive directory is available at http://qed.econ.queensu.ca/jae/datasets/meredith001/ . Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

公共保险与私人储蓄：谁受影响，影响多大？AI 解读

Abstract This paper employs a recently developed instrumental quantile regression method to investigate the effect of Medicaid on household savings across different wealth groups. It finds that the disincentive effect of Medicaid on household savings is heavily concentrated in the middle net‐worth households. In contrast, the effects on the bottom and top net‐worth households are quite small and insignificant. These heterogeneous incentive effects are partly explained by…

含噪声数据下的欧拉方程估计：两种精确 GMM 估计量AI 解读

Abstract In this paper we exploit the specific structure of the Euler equation and develop two alternative GMM estimators that deal explicitly with measurement error. The first estimator assumes that the measurement error is log‐normally distributed. The second estimator drops the distributional assumption at the cost of less precision. Our Monte Carlo results suggest that both proposed estimators perform much better than conventional alternatives based on the exact Euler…

国际产出趋同：来自自相关函数方法的证据AI 解读

Abstract This paper uses an autocorrelation function (ACF) approach to develop a new testing procedure for international output convergence. We define convergence in terms of sample ACFs of detrended output per capita, and construct an inference set‐up based on resampling and subsampling techniques for dependent data. Using per capita GDP for 15 OECD countries observed over a century, we find that the hypothesis of conditional convergence is unsupported; that, the USA apart,…

股票价格中的市场基本面与理性泡沫：贝叶斯视角AI 解读

Abstract Using Bayesian Markov chain Monte Carlo methods, we decompose the log price‐dividend ratio into a market fundamentals component and a bubble component. The market fundamentals component depends on expectations of future dividend growth and required returns, while the bubble component is assumed to follow a Markov switching model that allows for the possibility of exploding and collapsing regimes. If prior beliefs allow for the possibility of persistent shocks to…

随机递归划分：估计平均处理效应的匹配方法AI 解读

Abstract In this paper we introduce the Random Recursive Partitioning (RRP) matching method. RRP generates a proximity matrix which might be useful in econometric applications like average treatment effect estimation. RRP is a Monte Carlo method that randomly generates non‐empty recursive partitions of the data and evaluates the proximity between two observations as the empirical frequency they fall in a same cell of these random partitions over all Monte Carlo replications.…

一类共同价值拍卖模型的非参数识别与估计AI 解读

Abstract Structural econometric studies on auctions have mainly focused on the independent private value paradigm. In this paper, we are interested in the ‘opposite’ case known as the pure common value model. More precisely, we restrict our attention to a class of common value models defined by three functions: the density of the true value of the auctioned good, a unique function that appears in the definition of the conditional densities of the signals, and the function…

使用最小二乘法进行拍卖计量分析AI 解读

Abstract I investigate using the method of ordinary least squares (OLS) on auction data. I find that for parameterizations of the valuation distribution that are common in empirical practice, an adaptation of OLS provides unbiased estimators of structural parameters. Under symmetric independent private values, adapted OLS is a specialization of the method of moments strategy of Laffont, Ossard and Vuong ( 1995 ). In contrast to their estimator, here simulation is not…

从升价与密封投标拍卖估计风险厌恶：木材拍卖案例AI 解读

Abstract Estimating bidders' risk aversion in auctions is a challenging problem because of identification issues. This paper takes advantage of bidding data from two auction designs to identify nonparametrically the bidders' utility function within a private value framework. In particular, ascending auction data allow one to recover the latent distribution of private values, while first‐price sealed‐bid auction data allow one to recover the bidders' utility function. This…

风险厌恶者是否更乐观？一种贝叶斯估计方法AI 解读

Abstract Our aim is to analyze the link between optimism and risk aversion in a subjective expected utility setting and to estimate the average level of optimism when weighted by risk tolerance. Its estimation leads to a non‐trivial statistical problem. We start from a large lottery survey (1536 individuals). We assume that individuals have true unobservable characteristics. We adopt a Bayesian approach and use a hybrid MCMC approximation method to numerically estimate the…

企业层面的研发与补贴：参数和半参数两步选择模型的应用AI 解读

Abstract This paper analyzes the effect of public R&D subsidies on firms' private R&D investment per employee and new product sales in German manufacturing. Parametric and semiparametric two‐step selection models are applied to this evaluation problem. The results show that the average treatment effect on the treated firms' R&D intensity is positive. The estimated effects are robust with respect to the different selection models. Further results show that publicly induced…

BMI 与工资：偏态处理—响应模型及非参数内生性的贝叶斯分析AI 解读

Abstract We generalize the specifications used in previous studies of the effect of body mass index (BMI) on earnings by allowing the potentially endogenous BMI variable to enter the log wage equation nonparametrically. We introduce a Bayesian posterior simulator for fitting our model that permits a nonparametric treatment of the endogenous BMI variable, flexibly accommodates skew in the BMI distribution, and whose implementation requires only Gibbs steps. Using data from…

半参数特征价格模型：评估农业面源污染的影响AI 解读

Abstract In the area of environmental analysis using hedonic price models, we investigate the performance of various nonparametric and semiparametric specifications. The proposed model specifications are made up of two parts: a linear component for house characteristics and a non‐(semi)parametric component representing the nonlinear influence of environmental indicators on house prices. We adopt a general‐to‐specific search procedure, based on recent specification tests…

含不可观测异质性的动态 Tobit 面板模型：半参数贝叶斯推断AI 解读

Abstract This paper develops semiparametric Bayesian methods for inference of dynamic Tobit panel data models. Our approach requires that the conditional mean dependence of the unobserved heterogeneity on the initial conditions and the strictly exogenous variables be specified. Important quantities of economic interest such as the average partial effect and average transition probabilities can be readily obtained as a by‐product of the Markov chain Monte Carlo run. We apply…

众数、加权众数与校准众数：基于多峰性检验的聚类证据AI 解读

Abstract We apply recent results from the statistics literature to test for multimodality of worldwide distributions of several (unweighted and population‐weighted) measures of labor productivity. Specifically, we employ Silverman (Bump) and Dip modality tests, calibrated to correct for their incorrect asymptotic levels. We show that test results are sensitive to the test statistic employed and to population weighting. But regardless of the statistical criterion used,…

学习、预测与结构突变AI 解读

Abstract We provide a general methodology for forecasting in the presence of structural breaks induced by unpredictable changes to model parameters. Bayesian methods of learning and model comparison are used to derive a predictive density that takes into account the possibility that a break will occur before the next observation. Estimates for the posterior distribution of the most recent break are generated as a by‐product of our procedure. We discuss the importance of…

横截面收益排名跳跃与预期收益：一个混合模型AI 解读

Abstract We propose a new nonlinear time series model of expected returns based on the dynamics of the cross‐sectional rank of realized returns. We model the joint dynamics of a sharp jump in the cross‐sectional rank and the asset return by analyzing (1) the marginal probability distribution of a jump in the cross‐sectional rank within the context of a duration model, and (2) the probability distribution of the asset return conditional on a jump, for which we specify…

新凯恩斯主义菲利普斯曲线的识别AI 解读

Abstract Phillips curves are central to discussions of inflation dynamics and monetary policy. The hybrid new Keynesian Phillips curve (NKPC) describes how past inflation, expected future inflation, and a measure of real aggregate demand drive the current inflation rate. This paper studies the (potential) weak identification of the NKPC under Generalized Method of Moments and traces this syndrome to a lack of higher‐order dynamics in exogenous variables. We employ analytic…

利用模拟得分估计与效用一致的劳动供给模型AI 解读

Abstract We consider a utility‐consistent static labor supply model with flexible preferences and a nonlinear and possibly non‐convex budget set. Stochastic error terms are introduced to represent optimization and reporting errors, stochastic preferences, and heterogeneity in wages. Coherency conditions on the parameters and the support of error distributions are imposed for all observations. The complexity of the model makes it impossible to write down the probability of…

美国失业率的平滑转换与马尔可夫转换自回归模型比较AI 解读

Abstract Logistic smooth transition and Markov switching autoregressive models of a logistic transform of the monthly US unemployment rate are estimated by Markov chain Monte Carlo methods. The Markov switching model is identified by constraining the first autoregression coefficient to differ across regimes. The transition variable in the LSTAR model is the lagged seasonal difference of the unemployment rate. Out‐of‐sample forecasts are obtained from Bayesian predictive…