论文检索

跨国公司、买方垄断与地方发展：联合果品公司的证据AI 解读

This paper studies the role of private sector companies in the development of local amenities. We use evidence from one of the largest multinationals of the 20th century: the United Fruit Company (UFCo). The firm was given a large land concession in Costa Rica—one of the so‐called “Banana Republics”—from 1899 to 1984. Using administrative census data with census‐block geo‐references from 1973 to 2011, we implement a geographic regression discontinuity design that exploits a…

空间相关稳健推断AI 解读

We propose a method for constructing confidence intervals that account for many forms of spatial correlation. The interval has the familiar “estimator plus and minus a standard error times a critical value” form, but we propose new methods for constructing the standard error and the critical value. The standard error is constructed using population principal components from a given “worst‐case” spatial correlation model. The critical value is chosen to ensure coverage in a…

生产率分散、企业间竞争与劳动份额AI 解读

I study the effect of labor market imperfections on the labor share in a tractable model that emphasizes the interaction between productivity dispersion and firm competition for workers. I calibrate the model using administrative data covering the universe of firms in Canada from 2000 to 2015. As in the data, most firms have a high labor share, yet the aggregate labor share is low due to the disproportionate effect of a small fraction of large, highly productive firms. I…

从评论中学习：选择效应与学习速度AI 解读

This paper develops a model of Bayesian learning from online reviews and investigates the conditions for learning the quality of a product and the speed of learning under different rating systems. A rating system provides information about reviews left by previous customers. observe the ratings of a product and decide whether to purchase and review it. We study learning dynamics under two classes of rating systems: full history , where customers see the full history of…

经济学家获得同行认可的性别差异AI 解读

We study the selection of Fellows of the Econometric Society, using a new data set of publications and citations for over 40,000 actively publishing economists since the early 1900s. Conditional on achievement, we document a large negative gap in the probability that women were selected as Fellows in the 1933–1979 period. This gap became positive (though not statistically significant) from 1980 to 2010, and in the past decade has become large and highly significant, with…

大规模选举中的完全信息等价性AI 解读

We study the problem of aggregating private information in elections with two or more alternatives for a large family of scoring rules. We introduce a feasibility condition, the linear refinement condition , that characterizes when information can be aggregated asymptotically as the electorate grows large: there must exist a utility function, linear in distributions over signals, sharing the same top alternative as the primitive utility function. Our results complement the…

任务、自动化与美国工资不平等的上升AI 解读

We document that between 50% and 70% of changes in the U.S. wage structure over the last four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in industries experiencing rapid automation. We develop a conceptual framework where tasks across industries are allocated to different types of labor and capital. Automation technologies expand the set of tasks performed by capital, displacing certain worker groups from jobs for which…

为最坏情形做准备、对最好情形抱希望：稳健贝叶斯说服AI 解读

We propose a robust solution concept for Bayesian persuasion that accounts for the Sender's concern that her Bayesian belief about the environment—which we call the conjecture —may be false. Specifically, the Sender is uncertain about the exogenous sources of information the Receivers may learn from, and about strategy selection. She first identifies all information policies that yield the largest payoff in the “worst‐case scenario,” that is, when Nature provides information…

家庭杠杆与经济衰退AI 解读

We evaluate and partially challenge the household leverage view of the Great Recession. In the data, employment and consumption declined more in U.S. states where household debt declined more. We study a model of a monetary union composed of many regions in which liquidity constraints shape the response of employment and consumption to changes in debt. We estimate the model with Bayesian methods combining state and aggregate data. Changes in household credit explain 40% of…

评 Andrews（1991）《异方差与自相关一致协方差矩阵估计》AI 解读

This comment includes a solution to a problem in Section 8 in Andrews (1991) and points out a method to generalize the mean‐squared error (MSE) bounds appearing in Andrews (1988) and Andrews (1991).

巴西失业与失业保险对犯罪的影响AI 解读

We investigate the impact of job loss on crime and the mitigating role of unemployment benefits, exploiting detailed individual‐level data linking employment careers, criminal records, and welfare registries for the universe of male workers in Brazil. The probability of committing crimes increases on average by 23% for workers displaced by mass layoffs, and by slightly less for their cohabiting sons. Using causal forests, we show that the effect is entirely driven by young…

评《利用随机化打破维数灾难》AI 解读

Rust (1997b) discovered a class of dynamic programs that can be solved in polynomial time with a randomized algorithm. For these dynamic programs, the optimal values of a polynomially large sample of states are sufficient statistics for the (near) optimal values everywhere, and the values of this random sample can be bootstrapped from the sample itself. However, I show that this class is limited, as it requires all but a vanishingly small fraction of state variables to…

协变量依赖转移概率的马尔可夫状态转换模型最大似然估计AI 解读

This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of the ML estimator and local asymptotic normality for the models under general conditions, which allow for autoregressive dynamics in the observable process, Markov regime sequences with covariate‐dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite‐sample properties of the ML…

局部稳健的半参数估计AI 解读

Many economic and causal parameters depend on nonparametric or high dimensional first steps. We give a general construction of locally robust/orthogonal moment functions for GMM, where first steps have no effect, locally, on average moment functions. Using these orthogonal moments reduces model selection and regularization bias, as is important in many applications, especially for machine learning first steps. Also, associated standard errors are robust to misspecification…

现代高斯—马尔可夫定理AI 解读

This paper presents finite‐sample efficiency bounds for the core econometric problem of estimation of linear regression coefficients. We show that the classical Gauss–Markov theorem can be restated omitting the unnatural restriction to linear estimators, without adding any extra conditions. Our results are lower bounds on the variances of unbiased estimators. These lower bounds correspond to the variances of the the least squares estimator and the generalized least squares…

因果与结构效应的自动去偏机器学习AI 解读

Many causal and structural effects depend on regressions. Examples include policy effects, average derivatives, regression decompositions, average treatment effects, causal mediation, and parameters of economic structural models. The regressions may be high‐dimensional, making machine learning useful. Plugging machine learners into identifying equations can lead to poor inference due to bias from regularization and/or model selection. This paper gives automatic debiasing for…

随机网络结构差异检验AI 解读

How can one determine whether a treatment, such as the introduction of a social program or trade shock, alters agents' incentives to form links in a network? This paper proposes analogs of a two‐sample Kolmogorov–Smirnov test, widely used in the literature to test the null hypothesis of no treatment effects, for network data. It first specifies a testing problem in which the null hypothesis is that two networks are drawn from the same random graph model. It then describes…

平滑性与稀疏性下离散—连续分布的自适应贝叶斯估计AI 解读

We consider nonparametric estimation of a mixed discrete‐continuous distribution under anisotropic smoothness conditions and a possibly increasing number of support points for the discrete part of the distribution. For these settings, we derive lower bounds on the estimation rates. Next, we consider a nonparametric mixture of normals model that uses continuous latent variables for the discrete part of the observations. We show that the posterior in this model contracts at…

动态分配处理的长期效应：新方法与培训收入效应评估AI 解读

We propose and implement a new method to estimate treatment effects in settings where individuals need to be in a certain state (e.g., unemployment) to be eligible for a treatment, treatments may commence at different points in time, and the outcome of interest is realized after the individual left the initial state. An example concerns the effect of training on earnings in subsequent employment. Any evaluation needs to take into account that some of those who are not…

错配、选择与生产率：基于中国面板数据的定量分析AI 解读

We use household‐level panel data from China and a quantitative framework to document the extent and consequences of factor misallocation in agriculture. We find that there are substantial within‐village frictions in both the land and capital markets linked to land institutions in rural China that disproportionately constrain the more productive farmers. These frictions reduce aggregate agricultural productivity by affecting two key margins: (1) the allocation of resources…

弱识别 GMM 的最优决策规则AI 解读

This paper studies optimal decision rules, including estimators and tests, for weakly identified GMM models. We derive the limit experiment for weakly identified GMM, and propose a theoretically‐motivated class of priors which give rise to quasi‐Bayes decision rules as a limiting case. Together with results in the previous literature, this establishes desirable properties for the quasi‐Bayes approach regardless of model identification status, and we recommend quasi‐Bayes for…

未观测异质性的离散化AI 解读

We study discrete panel data methods where unobserved heterogeneity is revealed in a first step, in environments where population heterogeneity is not discrete. We focus on two‐step grouped fixed‐effects (GFE) estimators, where individuals are first classified into groups using kmeans clustering, and the model is then estimated allowing for group‐specific heterogeneity. Our framework relies on two key properties: heterogeneity is a function—possibly nonlinear and…

宏观—金融解耦：宏观资产定价模型的稳健评估AI 解读

This paper shows that robust inference under weak identification is important to the evaluation of many influential macro asset pricing models, including (time‐varying) rare‐disaster risk models and long‐run risk models. Building on recent developments in the conditional inference literature, we provide a novel conditional specification test by simulating the critical value conditional on a sufficient statistic. This sufficient statistic can be intuitively interpreted as a…

利用网络数据识别与估计部分线性回归模型AI 解读

I study a regression model in which one covariate is an unknown function of a latent driver of link formation in a network. Rather than specify and fit a parametric network formation model, I introduce a new method based on matching pairs of agents with similar columns of the squared adjacency matrix, the ij th entry of which contains the number of other agents linked to both agents i and j . The intuition behind this approach is that for a large class of network formation…