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Cyclicality and Asymmetry of the User Cost of Labor

We estimate wage cyclicality using the user cost of labor (UCL), a measure of marginal labor cost. We propose a novel methodology to correct composition bias from cyclical jobto-job upgrading by exploiting school-to-employment flows. We implement the methodology using rich Japanese wage data. The estimated UCL is strongly procyclical, with a semi-elasticity of 2.52 with respect to the unemployment rate, which is 1.6 and 2.3 times as large as that of the new-hire and average…

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Decomposing the Rise in Markups

分解加成率的上升

A recent literature argues that the rise in aggregate markups is due to economic activity reallocating toward high-markup firms rather than an increase in firmlevel markups. I show that standard decomposition methods used to analyze this phenomenon can estimate a non-zero reallocation effect even when the joint distribution of markups and market shares is time-invariant. This is due to churning in the firm-level distribution of markups and market shares. Empirically, I find…

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Finite-Sample Auction Inference Using Transaction Prices

利用成交价格进行有限样本拍卖推断

We first provide inference on the quantile function of the bid distribution in firstprice or descending auctions, and the quantile function of the value distribution in second-price or ascending auctions, with a known number of bidders with symmetric independent private values. Specifically, we provide finite-sample, nonparametric, tuning parameter-free, uniform confidence bands for these quantile functions when observing only the transaction price. We also show how these…

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Finite-State Markov-Chain Approximations: A Hidden Markov Approach

有限状态马尔可夫链近似:一种隐马尔可夫方法

This paper proposes a novel finite-state Markov chain approximation method for Markov processes with continuous support, providing both an optimal grid and a transition probability matrix. The method can be used for multivariate processes and processes with time-varying components. It is based on minimizing the information loss between a Hidden Markov Model and the true data-generating process. We provide sufficient conditions under which this information loss can be made…

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Fertility, Child Gender, and Parental Migration Decision: Evidence from China

生育、子女性别与父母迁移决策:来自中国的证据

We study how the number and gender of children affect rural-tourban parental migration in China. Exploiting variation from the “1.5- child policy,” which allowed a second birth only if the firstborn was a girl, we separately identify the causal effects of fertility and child gender based on a novel semi-parametric method. Using the 2010 population census, we find that an additional child increases the likelihood of joint parental migration by 12.1 percent, while the presence…

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Standard Errors when a Regressor is Randomly Assigned

当回归变量被随机分配时的标准误

We show that the OLS variance formula simplifies when values of the regressor of interest are assigned randomly and independently of other regressors. When the regressor of interest is independent not only of other regressors but also of the error term, the homoskedastic variance formula is valid even if regression errors are correlated. When the error term is heteroscedastic with respect to the regressor of interest, the variance formula has to be adjusted not only for…

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Conditional Influence Functions

条件影响函数

There are many nonparametric objects of interest that are functionals of a conditional distribution, such as average treatment effects conditional on a low-dimensional set of covariates. We define a conditional influence function (CIF) as the Gateaux derivative of a conditional parameter with respect to perturbations of the conditional law of a single observation given the conditioning variable. CIFs generalize classical influence functions and can be used to (i) construct…

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Worker-Side Discrimination: Beliefs and Preferences

劳动者侧歧视:信念与偏好

When agents choose among options with unobserved attributes to maximize expected utility, their choices conflate preferences with beliefs about those attributes. We develop a novel theory-driven identification strategy for such settings, showing that compensating differentials separately identify beliefs from preferences. Noting that workers’ preferences and beliefs shape labor market outcomes, yet remain understudied, we apply our method to provide the first evidence on the…

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Binary choice under asymmetric loss in a data‐rich environment: Theory and an application to algorithmic fairness

数据丰富环境中非对称损失下的二元选择:理论与算法公平性应用

We study the binary choice problem in a data‐rich environment with asymmetric loss functions. The econometrics literature covers nonparametric binary choice problems but does not offer computationally attractive solutions in data‐rich environments. The machine learning literature has many algorithms but is focused mostly on loss functions that are independent of covariates. We show that theoretically valid decisions on binary outcomes with general loss functions can be…

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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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Conditional choice probability estimation with an imperfectly measured latent state

潜在状态测量不完善时的条件选择概率估计

Traditional dynamic discrete choice model—Conditional Choice Probability estimator (DDCM‐CCP) literature considered identification using the likelihood of longitudinal choice only. However, such an approach has a limitation in identifying flexible dynamics for latent state due to the discrete and typically small‐dimensional nature of choice. This paper extends this literature to utilize imperfect measurements, called proxies, for a latent discrete state. I first show that…

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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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Policy learning with new treatments

包含新处理方案的政策学习

I study the problem of a decision maker choosing a policy that allocates treatment to a heterogeneous population on the basis of experimental data that includes only a subset of possible treatment values. The effects of new treatments are partially identified by shape restrictions on treatment response. Policies are compared according to the minimax regret criterion, and I show that the empirical analog of the population decision problem has a tractable linear‐ and…

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Estimation and inference in high‐dimensional panel data models with interactive fixed effects

交互固定效应高维面板模型的估计与推断

We develop new econometric methods for estimation and inference in high‐dimensional panel data models with interactive fixed effects. Our approach can be regarded as a nontrivial extension of the very popular common correlated effects (CCE) approach. Roughly speaking, we proceed as follows: We first construct a projection device to eliminate the unobserved factors from the model by applying a dimensionality reduction transform to the matrix of cross‐sectionally averaged…

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Testing homogeneity in dynamic discrete games in finite samples

有限样本下动态离散博弈的同质性检验

The literature on dynamic discrete games often assumes that the conditional choice probabilities and the state transition probabilities are homogeneous across markets and over time. We refer to this as the “homogeneity assumption” in dynamic discrete games. This assumption enables empirical studies to estimate the game's structural parameters by pooling data from multiple markets and from many time periods. In this paper, we propose a hypothesis test to evaluate whether the…

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Identification of random coefficient latent utility models

随机系数潜在效用模型的识别

This paper provides nonparametric identification results for random coefficient distributions in perturbed utility models. We cover discrete choice and models of multiple purchases. We establish identification using variation in mean quantities. The results apply even when an analyst observes only aggregate demands but not whether goods are chosen together. The identification results use exclusion restrictions on covariates and independence between random slope coefficients…

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Estimation of optimal dynamic treatment assignment rules under policy constraints

政策约束下最优动态处理分配规则的估计

Many policies involve dynamics in their treatment assignments where individuals receive sequential interventions over multiple stages. We study estimation of an optimal dynamic treatment regime that guides the optimal treatment assignment for each individual at each stage based on their history. We propose an empirical welfare maximization approach in this dynamic framework, which estimates the optimal dynamic treatment regime using data from an experimental or…

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Dynamic ordered panel logit models

动态有序面板 Logit 模型

This paper studies a dynamic ordered logit model for panel data with fixed effects. The main contribution of the paper is to construct a set of valid moment conditions that are free of the fixed effects. The moment functions can be computed using four or more periods of data, and the paper presents sufficient conditions for the moment conditions to identify the common parameters of the model, namely the regression coefficients, the autoregressive parameters, and the…

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The role of storage in commodity markets: Indirect inference based on grain data

商品市场中的储存作用:基于粮食数据的间接推断

We develop an indirect inference approach relying on a linear supply and demand model serving as an auxiliary model to provide the first full empirical test of the rational expectations commodity storage model. We build a rich storage model that incorporates a supply response and four structural shocks and show that exploiting information on both prices and quantities is critical for relaxing previous restrictive identifying assumptions and assessing the empirical…

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Economic consequences of vertical mismatch

教育与岗位纵向错配的经济后果

We study two first‐order economic consequences of vertical mismatch, using a simple (neoclassical) model of under and overemployment. Individuals of high type can perform both skilled and unskilled jobs, but only a fraction of low‐type workers can perform skilled jobs. People have different costs over these jobs. First, we calibrate the model to match U.S. CPS time series since the 1980s. To control for unobserved heterogeneity, we compute wages based on workers who have…

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An ordinal approach to the empirical analysis of games with monotone best responses

单调最佳反应博弈经验分析的序数方法

We develop a nonparametric and ordinal approach for testing pure strategy Nash equilibrium play in games with monotone best responses, such as those with strategic complements/substitutes. The approach makes minimal assumptions on unobserved heterogeneity, requires no parametric assumptions on payoff functions, and no restriction on equilibrium selection from multiple equilibria. The approach can also be extended in order to make inferences and predictions. Both…

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Can teaching be taught? Improving teachers' pedagogical skills at scale in rural Peru

教学能否被教会?秘鲁农村教师教学技能的大规模提升

We evaluate the impact of a large‐scale teacher coaching program in Peru, a context with high teacher turnover, on teachers' pedagogical skills and student learning. Previous studies find that small‐scale coaching programs can improve teaching of reading and science in developing countries. However, scaling up can reduce programs' effectiveness, and teacher turnover can erode compliance and cause spillovers onto non‐program schools. We develop a framework that defines…

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Econometrics of insurance with multidimensional types

多维类型保险模型的计量分析

In this paper, we address the identification and estimation of insurance models where insurees have private information about their risk and risk aversion. The model includes random damages and allows for several claims, while insurees choose from a finite number of coverages. We show that the joint distribution of risk and risk aversion is nonparametrically identified despite bunching due to multidimensional types and a finite number of coverages. Our identification…

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