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高维随机向量相互独立性的秩最大值—求和检验AI 解读

We consider the problem of testing mutual independence of high-dimensional random vectors, and propose a series of high-dimensional rank-based max-sum tests, which are suitable for high-dimensional data and can be robust to distribution types of the variables, form of the dependence between variables and the sparsity of correlation coefficients. Further, we demonstrate the application of some representative members of the proposed tests on testing cross-sectional…

基于汇总表数据的免调参非参数密度估计AI 解读

Administrative data are often easier to access as tabulated summaries than in the original format due to confidentiality concerns. Motivated by this practical feature, we propose a novel nonparametric density estimation method from tabulated summary data based on maximum entropy and prove its strong uniform consistency. Unlike existing kernel-based estimators, our estimator is free from tuning parameters and admits a closed-form density that is convenient for post-estimation…

基于局部线性化的矩不等式子向量推断AI 解读

This paper introduces a bootstrap-based profiling inference method for subvectors in moment inequality models following insights from Bugni et al. (2017). Compared to their paper, the new method calculates the critical value by searching over a local neighborhood of a pre-estimator, instead of the whole null parameter space, to profile out nuisance parameters. In this way, non-linear moment conditions are simplified by linear expansion and the bootstrap iterates over…

匹配点：在三角模型中用协变量补充工具变量AI 解读

Models with a discrete endogenous variable and an instrument that takes on fewer values are common in economics. This paper presents a new method that matches pairs of covariates and instruments to restore the order condition in this scenario and to achieve point-identification of the outcome function. The outcome function must be monotonic in a scalar disturbance, but it can be nonseparable. The first stage for the discrete endogenous variable needs to have a multi-index…

含不可观测异质性的时空模型估计与自助法AI 解读

Proposed herein is a novel spatiotemporal model to characterize the unobserved heterogeneity across individuals using quantile-function-based correlated random effects and heteroscedastic innovations in a general framework. This model can be used to explore the influence of space-specific factors on latent effects at different quantile levels by controlling for spatiotemporal effects. A two-stage estimation procedure is introduced in which (i) the method of moments is used…

无单调性条件下弱可分模型的内生性处理AI 解读

We identify and estimate treatment effects when potential outcomes are weakly separable with a binary endogenous treatment. Vytlacil and Yildiz (2007) proposed an identification strategy that exploits the mean of observed outcomes, but their approach requires a monotonicity condition. In comparison, we exploit full information in the entire outcome distribution, instead of just its mean. As a result, our method does not require monotonicity and is also applicable to general…

参与状态误报时项目收益的界限识别AI 解读

Instrumental variables (IV) are commonly used to estimate treatment effects in case of noncompliance. However, program participation is often misreported in survey data and standard techniques are not sufficient to point identify and consistently estimate the effects of interest. In this paper, we show that the identifiable IV estimand that ignores treatment misclassification is a weighted average of local average treatment effects with weights that can also be negative.…

高维分位数回归的假设检验AI 解读

Quantile regression has been an important analytical tool in econometrics since it was proposed in 1970s. Many advantages make it still popular in the era of big data. This paper focuses on the testing problems of high-dimensional quantile regression, supplementing to robust methods in the literature of high-dimensional hypothesis testing. We first construct a new test statistic based on the quantile regression score function. The new test statistic avoids the inverse…

应税收入弹性的极大似然聚束估计AI 解读

Summary This paper develops a maximum likelihood (ML) bunching estimator of the elasticity of taxable income (ETI). Our structural approach provides a natural framework to simultaneously account for unobserved preference heterogeneity and optimization errors and for measuring their relative importance. We characterize the conditions under which the parameters of the model are identified and show that the ML estimator performs well in terms of bias and precision. The paper…

住房市场繁荣与衰退期间边际消费倾向是否改变？AI 解读

Summary We extend a widely used semi‐structural model to identify and estimate dynamic consumption elasticities with respect to transitory income shocks. Applying our model to household survey data, we find a structural break in marginal propensities to consume following the end of the housing market boom, with the average across households increasing significantly. There is important heterogeneity by different household balance sheet characteristics, and the increase in the…

网络模型中的异质性与动态变化AI 解读

Summary We propose an empirical spatial modeling framework that allows for both heterogeneity and dynamics in economic network connections. We establish the model's stationarity and ergodicity properties and show that the model's implied filter is invertible. While highly flexible, the model is straightforward to estimate by maximum likelihood. We apply the model to three datasets for Eurozone sovereign credit risk over the period Dec‐2009 to Dec‐2022. Accounting for both…

条件处理效应分布的部分识别与推断AI 解读

Summary This paper considers identification and inference for the distribution of treatment effects conditional on observable covariates. Since the conditional distribution of treatment effects is not point identified without strong assumptions, we obtain bounds on the conditional distribution of treatment effects by using the Makarov bounds. We also consider the case where the treatment is endogenous and propose two stochastic dominance assumptions to tighten the bounds. We…

工具变量模型中的异常值稳健推断及因果效应应用AI 解读

Summary The Anderson‐Rubin (AR) test is an important method that allows for reliable inference in the instrumental variable model when the instruments are weak. Yet, the robustness properties of this test have not been formally studied. As it turns out that the AR test is not robust to outliers, we show how to construct an outlier robust alternative—the robust AR test. We investigate the robustness properties of the robust AR test and show that the robust AR statistic…

含零无效率质量点的随机前沿惩罚筛估计AI 解读

Summary Stochastic frontier models for cross‐sectional data typically assume that the one‐sided distribution of firm‐level inefficiency is continuous. However, it may be reasonable to hypothesize that inefficiency is continuous except for a discrete mass at zero capturing fully efficient firms (zero‐inefficiency). We propose a sieve‐type density estimator for such a mixture distribution in a nonparametric stochastic frontier setting under a unimodality‐at‐zero assumption.…

英国部门放缓：传导概率与经济联系的证据AI 解读

Summary This paper studies spillovers across macroeconomic sectors in the United Kingdom, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of economic deterioration to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of spillovers between them. The combination of both approaches reveals the Monetary Financial…

能力代理变量估计教育回报的有效性：基于因子模型的评估AI 解读

Summary A common approach to addressing ability bias is to augment the earnings‐schooling regression with proxies for cognitive and non‐cognitive skills. We evaluate this approach using a factor model framework, which allows consistent estimation of the returns to schooling without relying on proxies. The factor model estimators may be viewed as implicitly estimating proxy measurement error and/or accounting for omitted dimensions of ability. A bias decomposition quantifies…

管理自主权对企业结果的影响AI 解读

The allocation of decision‐making power is a critical choice that organizations make to mitigate agency problems and information frictions. This paper investigates the role of delegation for organizations where the agency problem is both pervasive and has potentially high welfare consequences: state‐owned enterprises (SOEs). I use a natural experiment in India to uncover the causal effects of granting SOE managers more autonomy over strategic decisions. Managers meaningfully…

匹配与集聚：来自日本企业间贸易的理论与证据AI 解读

This paper shows that matching frictions and a thick market externality in firm‐to‐firm trade shape the agglomeration of economic activity. Using panel data of firm‐to‐firm trade in Japan, I demonstrate that firms gradually match with alternative suppliers following an unanticipated supplier bankruptcy, and that the rate of rematching increases in the geographic density of alternative suppliers. Motivated by these empirical findings, I develop a general equilibrium model of…

可能误设下逻辑回归的稀疏网络渐近理论AI 解读

Consider a bipartite network where N consumers choose to buy or not to buy M different products. This paper considers the properties of the logit fit of the N × M array of “ i ‐buys‐ j ” purchase decisions, Y = [ Y i j ] 1 ≤ i ≤ N , 1 ≤ j ≤ M , onto a vector of known functions of consumer and product attributes under asymptotic sequences where (i) both N and M grow large, (ii) the average number of products purchased per consumer is finite in the limit, (iii) there exists…

非参数工具变量模型中的自适应速率最优假设检验AI 解读

We propose a new adaptive hypothesis test for inequality (e.g., monotonicity, convexity) and equality (e.g., parametric, semiparametric) restrictions on a structural function in a nonparametric instrumental variables (NPIV) model. Our test statistic is based on a modified leave‐one‐out sample analog of a quadratic distance between the restricted and unrestricted sieve two‐stage least squares estimators. We provide computationally simple, data‐driven choices of sieve tuning…

随机对照试验线性调整的精确偏差校正AI 解读

Freedman (2008a,b) showed that the linear regression estimator is biased for the analysis of randomized controlled trials under the randomization model. Under Freedman's assumptions, we derive exact closed‐form bias corrections for the linear regression estimator. We show that the limiting distribution of the bias corrected estimator is identical to the uncorrected estimator. Taken together with results from Lin (2013), our results show that Freedman's theoretical arguments…

利用微观数据非参数识别差异化产品需求AI 解读

We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market‐level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market‐level data and instruments for all prices and…

跨国执行劳动法：强化职业安全与健康委员会的实验证据AI 解读

Annually, work‐related mortality is responsible for 5–7% of all global deaths, and at least 1‐in‐9 workers experience nonfatal occupational accidents (ILO (2019a,b)). Occupational Safety and Health (OSH) committees are considered the key worker voice institution through which to improve workplace safety and health (ILO (1981)). I present evidence of OSH committees' causal effects on workers and on factories. To do so, I collaborated with 29 multinational apparel buyers that…

无转移支付多对一双边匹配的识别与估计AI 解读

In a setting of many‐to‐one two‐sided matching with nontransferable utilities, for example, college admissions, we study conditions under which preferences of both sides are identified with data on one single market. Regardless of whether the market is centralized or decentralized, assuming that the observed matching is stable, we show nonparametric identification of preferences of both sides under certain exclusion restrictions. To take our results to the data, we use Monte…