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农村移民与城市非正规就业：来自巴西的证据AI 解读

This paper studies the economic effects of rural‐urban migration on Brazilian cities. Using a shift‐share IV design, we show that, over a decade, drought‐induced immigration reduces informality, has no effect on unemployment, and increases the number of formal firms and jobs. Downward formal wage adjustments play a key role, as these long‐run effects are weaker in regions with stronger wage rigidity. In the short run, when wage rigidity is strongest, we replicate the…

估计精度能够预测参数时的经验贝叶斯方法AI 解读

Gaussian empirical Bayes methods usually maintain a precision independence assumption: The unknown parameters of interest are independent from the known standard errors of the estimates. This assumption is often theoretically questionable and empirically rejected. This paper proposes to model the conditional distribution of the parameter given the standard errors as a flexibly parameterized location‐scale family of distributions, leading to a family of methods that we call…

基于最优传输的广义矩估计AI 解读

We propose a novel optimal transport‐based version of the Generalized Method of Moment (GMM). Instead of handling overidentification by reweighting the data to satisfy the moment conditions (as in Generalized Empirical Likelihood methods), this method proceeds by allowing for errors in the variables of the least mean‐square magnitude necessary to simultaneously satisfy all moment conditions. This approach, based on the notions of optimal transport and Wasserstein metric,…

线性面板模型中固定效应的最优收缩估计AI 解读

Shrinkage methods are frequently used to improve the precision of least squares estimators of fixed effects. However, widely used shrinkage estimators guarantee improved precision only under strong distributional assumptions. I develop an estimator for the fixed effects that obtains the best possible mean squared error within a class of shrinkage estimators. This class includes conventional shrinkage estimators and the optimality does not require distributional assumptions.…

延迟接受算法的实验评估：来自逾百个军官劳动力市场的证据AI 解读

Internal labor markets are increasingly important for matching workers to jobs within organizations. We present evidence from a randomized trial that compares matching workers to jobs using the deferred acceptance (DA) algorithm to the traditional manager‐directed matching process. Our setting is the U.S. Army's internal labor market, which matches over 14,000 officers to units annually. We find that DA reduces administrative burden and increases match quality as measured by…

细粒度情境中的空间经济学AI 解读

We examine the application of quantitative spatial models to the growing body of fine spatial data used to study local economic outcomes. In granular settings in which people choose from a large set of potential residence‐workplace pairs, observed outcomes in part reflect idiosyncratic choices. Using analytical examples, Monte Carlo simulations, and event studies of neighborhood employment booms, we demonstrate that calibration procedures that equate observed shares and…

卖方信息精确时的多维筛选AI 解读

A multi‐product monopolist faces a buyer who is privately informed about his valuations for the goods. As is well known, optimal mechanisms are in general complicated, while simple mechanisms—such as pure bundling or separate sales—can be far from optimal and do not admit clear‐cut comparisons. We show that this changes if the monopolist has sufficiently precise information about the buyer's valuations: Now, pure bundling always outperforms separate sales; moreover, there is…

基尼系数的子群分解：老问题的新解法AI 解读

We derive a novel decomposition of the Gini coefficient into within‐ and between‐group inequality terms that sum to the aggregate Gini coefficient. This decomposition is derived from a set of axioms that ensure desirable behavior for the within‐ and between‐group inequality terms. The decomposition of the Gini coefficient is unique given our axioms, easy to compute, and can be interpreted geometrically.

选择由谁选择：能源返利项目中的自选择定向政策AI 解读

We develop an optimal policy assignment rule that integrates two distinctive approaches commonly used in economics—targeting by observables and targeting through self‐selection . Our method can be used with experimental or quasi‐experimental data to identify who should be treated, be untreated, and self‐select to achieve a policymaker's objective. Applying this method to a randomized controlled trial on a residential energy rebate program, we find that targeting that…

加价率估计指南：评估财务数据中的估计结果AI 解读

Macroeconomic outcomes depend on the distribution of markups across firms and over time, making firm‐level markup estimates key for macroeconomic analysis. Methods to obtain these estimates require data on the prices that firms charge. Firm‐level data with wide coverage, however, primarily come from financial statements, which lack information on prices. We use an analytical framework to show that trends in markups over time or the dispersion of markups across firms can…

边际声誉AI 解读

We study reputation formation where a long‐run player repeatedly observes private signals and takes actions. Short‐run players observe the long‐run player's past actions but not her past signals. The long‐run player can thus develop a reputation for playing a distribution over actions, but not necessarily for playing a particular mapping from signals to actions. Nonetheless, we show that the long‐run player can secure her Stackelberg payoff if distinct commitment types are…

适应模型误设的估计AI 解读

Empirical research typically involves a robustness‐efficiency tradeoff. A researcher seeking to estimate a scalar parameter can invoke strong assumptions to motivate a restricted estimator that is precise but may be heavily biased, or they can relax some of these assumptions to motivate a more robust, but variable, unrestricted estimator. When a bound on the bias of the restricted estimator is available, it is optimal to shrink the unrestricted estimator towards the…

帮派、劳动流动与发展AI 解读

We study how criminal organizations affect economic development. We exploit a natural experiment in El Salvador, where these criminal organizations emerged due to an exogenous shift in American immigration policy that led to the deportation of gang leaders from the United States to El Salvador. Using a spatial regression discontinuity design that focuses on the gang‐created system of borders, we find that individuals in gang‐controlled neighborhoods have less material…

社会税：再分配压力与劳动供给AI 解读

In low‐income communities in both rich and poor countries, redistributive transfers within kin and social networks are frequent. Such arrangements may distort labor supply—acting as a “social tax” that dampens the incentive to work. We document that across countries, from the United States to Côte d'Ivoire, low‐income groups report strong pressure to share earned income with others; in addition, social groups that undertake more interpersonal transfers work fewer hours.…

高阶风险偏好的结构估计AI 解读

Structural measures of higher order risk attitudes have well‐developed foundations in Expected Utility Theory (EUT), but little is known about their empirical magnitudes. We introduce a novel experimental design and a companion econometric model that allows us to structurally estimate indices of risk aversion, prudence, and temperance under EUT without imposing restrictions on their interdependence. We find that indices of absolute risk aversion, prudence, and temperance…

信息性先验的贝叶斯影响评估：哥伦比亚管理与出口改善项目AI 解读

Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. We evaluate a Colombian program for 200 firms which aimed to increase exporting. Priors were elicited from academics, policymakers, and firms. Contrary to these priors, frequentist estimation cannot reject null effects in 2019, and finds some negative impacts in 2020. For…

农村养老金、劳动力再配置与总收入：中国的实证和量化分析AI 解读

We exploit the implementation of a rural pension policy in China to estimate the average rural‐to‐urban migration cost for workers affected by the policy and the average underlying sectoral productivity difference. Our estimates, based on a large panel data set, reveal significant migration costs and substantial sectoral productivity differences, with sorting playing a minor role in accounting for sectoral labor income gaps. We construct and structurally estimate a general…

高斯变换建模与分布回归函数估计AI 解读

We propose flexible Gaussian representations for conditional cumulative distribution functions and give a concave likelihood criterion for their estimation. Optimal representations satisfy the monotonicity property of conditional cumulative distribution functions, including in finite samples and under general misspecification. We use these representations to provide a unified framework for the flexible maximum likelihood estimation of conditional density, cumulative…

研究者与社会偏好不一致时的最优估计AI 解读

Econometric analysis typically focuses on the statistical properties of fixed estimators and ignores researcher choices. In this article, I instead approach the analysis of experimental data as a mechanism‐design problem that acknowledges that researchers choose between estimators, sometimes based on the data and often according to their own preferences. Specifically, I focus on covariate adjustments, which can increase the precision of a treatment‐effect estimate, but open…

摘要暂缺

异质性处理效应机器学习推断评论：序贯验证方法AI 解读

We use the martingale construction of Luedtke and van der Laan (2016) to develop tests for the presence of treatment heterogeneity. The resulting sequential validation approach can be instantiated using various validation metrics, such as BLPs, GATES, QINI curves, etc., and provides an alternative to cross‐validation‐like cross‐fold application of these metrics. This note was prepared as a comment on the Fisher–Schultz paper by Chernozhukov, Demirer, Duflo, and…

异质性处理效应机器学习推断评论：随机化推断方法AI 解读

We examine the split‐sample robust inference (SSRI) methodology introduced by Chernozhukov, Demirer, Duflo, and Fernandez‐Val for quantifying uncertainty in heterogeneous treatment effect estimates produced by machine learning (ML) models. Although SSRI properly accounts for the additional variability due to sample splitting, its computational cost becomes prohibitive with complex ML models. We propose an alternative approach based on randomization inference (RI) that…

对模型误设的动态担忧AI 解读

I consider an agent who posits a set of probabilistic models for the payoff‐relevant outcomes. The agent has a prior over this set but fears the actual model is omitted and hedges against this possibility. The concern for misspecification is endogenous: If a model explains the previous observations well, the concern attenuates. I show that different static preferences under uncertainty (subjective expected utility, maxmin, robust control) arise in the long run, depending on…

随机实验中异质性处理效应的通用机器学习推断及印度免疫接种应用AI 解读

We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments. These key features include best linear predictors of the effects using machine learning proxies, average effects sorted by impact groups , and average characteristics of most and least impacted units . The approach is valid in high‐dimensional settings, where the effects are proxied (but not necessarily consistently estimated) by predictive and causal…