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汇总期刊目录中的 10 个期刊来源,以及 arXiv 计量经济学与相关统计、金融分类和主题检索中的预印本。期刊题录主要来自 Crossref,可靠摘要保留补充来源;期刊官网链接可在论文检索的说明中核对。

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Clustered network connectedness: A new measurement framework with application to global equity markets

分簇网络连通性:测度框架及全球股票市场应用

Network connections, both across and within markets, are central in countless economic contexts. In recent decades, a large literature has developed and applied flexible methods for measuring network connectedness and its evolution, based on variance decompositions from vector autoregressions (VARs), as in Diebold and Yilmaz (2014). Those VARs are, however, typically identified using full orthogonalization (Sims, 1980), or no orthogonalization (Koop et al., 1996; Pesaran and…

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Locally Robust Semiparametrically Efficient Bayesian Inference

局部稳健且半参数有效的贝叶斯推断

We propose a framework for making Bayesian parametric models robust to local misspecification. Suppose in a baseline parametric model, a parameter of interest has an interpretation in an encompassing semiparametric model. Bayesian and maximum likelihood estimators are generally biased under local misspecification. We propose to augment the baseline likelihood by a multiplicative factor that involves scores for the baseline model, the efficient scores for the encompassing…

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Causal Inference for Spatial Treatments

空间处理的因果推断

Many events and policies (treatments) occur at specific spatial locations, with researchers interested in their effects on nearby units. I approach the spatial treatment setting from an experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between units near realized treatment locations and units near counterfactual (unrealized) candidate locations, which differs from…

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Double Robustness of Local Projections and Some Unpleasant VARithmetic

局部投影的双重稳健性与 VAR 推断的隐患

We consider impulse response inference in a locally misspecified vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected with probability approaching 1. This result follows from a “double robustness” property analogous to that of popular partially linear regression estimators. By contrast, the conventional VAR confidence interval with…

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Economic Growth and the Rise of Large Firms

经济增长与大型企业的崛起

I document that the right tail of the firm size distribution systematically thickens with economic development. To rationalize this fact, I develop a parsimonious idea search model in which both aggregate growth and the firm size distribution are endogenously determined. The model features an asymptotic balanced growth path along which Gibrat's law holds at each date, and the right tail of the firm size distribution thickens monotonically toward Zipf's law. The model also…

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Mechanism Design for Personalized Policy: A Field Experiment Incentivizing Exercise

个性化政策的机制设计:激励运动的实地实验

Personalizing policies can theoretically increase their effectiveness. However, personalization is difficult when individual types are unobservable and the preferences of policymakers and individuals are not aligned, which could cause individuals to misreport their type. Mechanism design offers a strategy to overcome this issue: offer an “incentive‐compatible” menu of policy choices designed to induce participants to select the variant intended for their type. Using a field…

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Continuity of the Distribution Function of the argmax of a Gaussian Process

高斯过程最大值位置分布函数的连续性

Certain extremum estimators have asymptotic distributions that are non‐Gaussian, yet characterizable as the distribution of the arg max of a Gaussian process. This paper presents high‐level sufficient conditions under which such asymptotic distributions admit a continuous distribution function. The plausibility of the sufficient conditions is demonstrated by verifying them in three examples, namely, maximum score estimation, empirical risk minimization, and threshold…

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Communicating Scientific Uncertainty via Approximate Posteriors

通过近似后验传达科学不确定性

We cast the problem of communicating scientific uncertainty as one of reporting a posterior distribution on an unknown parameter to an audience of Bayesian decision‐makers. We establish novel bounds on the audience's regret when the analyst reports an approximation to a posterior that the audience treats as exact. Under a palatable restriction on the audience's decision problems, the bounds take an especially convenient form. Under a further restriction on the audience's…

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Rural Migrants and Urban Informality: Evidence From Brazil

农村移民与城市非正规就业:来自巴西的证据

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…

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Empirical Bayes When Estimation Precision Predicts Parameters

估计精度能够预测参数时的经验贝叶斯方法

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…

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Optimally‐Transported Generalized Method of Moments

基于最优传输的广义矩估计

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,…

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Optimal Shrinkage Estimation of Fixed Effects in Linear Panel Data Models

线性面板模型中固定效应的最优收缩估计

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.…

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An Experimental Evaluation of Deferred Acceptance: Evidence From Over 100 Army Officer Labor Markets

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

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…

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Spatial Economics for Granular Settings

细粒度情境中的空间经济学

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…

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Multidimensional Screening With Precise Seller Information

卖方信息精确时的多维筛选

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…

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Subgroup Decomposition of the Gini Coefficient: A New Solution to an Old Problem

基尼系数的子群分解:老问题的新解法

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.

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Identification through sparsity in factor models: The ℓ 1 ‐rotation criterion

利用稀疏性识别因子模型:ℓ₁ 旋转准则

Linear factor models are generally not identified. We provide sufficient conditions for identification: Under a natural sparsity assumption (the presence of local factors that affect only subsets of observables), the true loading matrix is the sparsest rotation and can be recovered by minimizing the ℓ 1 ‐norm of the loading matrix. This enables economically meaningful interpretation of the individual factors. More generally, our ℓ 1 ‐rotation criterion offers a novel…

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Oil and the stock market revisited: A mixed functional VAR approach

重新考察石油与股市:混合函数型 VAR 方法

This paper proposes a new mixed vector autoregression (MVAR) model to examine the relationship between aggregate time series and functional variables in a multivariate setting. The model facilitates a reexamination of the oil‐stock price nexus by estimating the effects of demand and supply shocks from the global market for crude oil on the entire distribution of U.S. stock returns since the late 1980s. We show that the MVAR effectively extracts information from the returns…

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Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity

面板数据预测:估计不确定性与参数异质性

We provide a comprehensive examination of the predictive accuracy of panel forecasting methods based on individual, pooling, fixed effects, and empirical Bayes estimation, and propose optimal weights for forecast combination schemes. We consider linear panel data models, allowing for weakly exogenous regressors and correlated heterogeneity. We quantify the gains from exploiting panel data and demonstrate how forecasting performance depends on the degree of parameter…

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The local approach to causal inference under network interference

网络干扰下因果推断的局部方法

We propose a new nonparametric modeling framework for causal inference when outcomes depend on how agents are linked in a social or economic network. Such network interference describes a large literature on treatment spillovers, social interactions, social learning, information diffusion, disease and financial contagion, social capital formation, and more. Our approach works by first characterizing how an agent is linked in the network using the configuration of other…

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Identification and estimation of continuous‐time dynamic discrete choice games

连续时间动态离散选择博弈的识别与估计

This paper considers the theoretical, computational, and econometric properties of continuous‐time dynamic discrete choice games with stochastically sequential moves, introduced by Arcidiacono, Bayer, Blevins, and Ellickson (2016). We consider identification of the rate of move arrivals, which was assumed to be known in previous work, as well as a generalized version with heterogeneous move arrival rates. We reestablish conditions for existence of a Markov perfect…

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Large structural VARs with multiple sign and ranking restrictions

带多重符号与排序限制的大型结构 VAR

Large VARs are increasingly used in structural analysis as a unified framework to study the impacts of multiple structural shocks simultaneously. However, the concurrent identification of multiple shocks using sign and ranking restrictions poses significant practical challenges to the point where existing algorithms cannot be used with such large VARs. To address this, we introduce a new numerically efficient algorithm that facilitates the estimation of impulse responses and…

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Satisficing, aggregation, and quasilinear utility

满意化行为、加总与拟线性效用

This paper studies approximation error in the quasilinear utility model. Error arises because individuals do not perfectly optimize, and instead satisfice. We investigate the consequences of individual satisficing for modeling aggregate demand, providing an approximate aggregation theorem. We present a simple method for statistical inference on the minimal level of satisficing needed to explain aggregate data. In an illustrative application to scanner panel data, we find…

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Measuring inflation expectations: How the response scale shapes density forecasts

测量通胀预期:回答量表如何塑造密度预测

In density forecasts, respondents are asked to assign probabilities to a response scale with pre‐specified ranges of inflation. In two large‐scale experiments, one conducted in the US and one in Germany, we show how the specifics of the response scale determine the results: Shifting, compressing, or expanding the scale leads to shifted, compressed, and expanded forecasts. Quantifying this effect using the scale most widely used among central banks, we find that mean…

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