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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…

基于条件异方差识别日度油价冲击及其不确定性AI 解读

This paper develops a daily structural VAR for identifying oil price shocks from conditional heteroskedasticity and quantifies the transmission of their timevarying uncertainty. Identification exploits volatility clustering and spillovers in a structural GARCH specification and the complete identified set is derived. We derive covariance impulse response functions and introduce a time-varying forecast error variance decomposition (TV-FEVD) that allows for a decomposition of…

分解加成率的上升AI 解读

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…

紧识别SVAR中基于“软”符号限制的快速后验抽样AI 解读

We propose algorithms for conducting Bayesian inference in structural vector autoregressions identified using sign restrictions. The key feature of our approach is a sampling step based on ‘soft’ sign restrictions. This step draws from a target density that smoothly penalises parameter values that violate the restrictions, facilitating the use of computationally efficient Markov chain Monte Carlo sampling algorithms. An importance-sampling step yields draws conditional on…

利用成交价格进行有限样本拍卖推断AI 解读

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…

有限状态马尔可夫链近似：一种隐马尔可夫方法AI 解读

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…

生育、子女性别与父母迁移决策：来自中国的证据AI 解读

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…

用统计决策理论全面评估预测算法的样本外表现AI 解读

We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research on prediction. SDT provides a formal frequentist framework for performing comprehensive OOS evaluation across all possible (1) training samples, (2) populations that may generate training data, and (3) populations of prediction interest. Regarding feature (3), we…

即期相关过程日内变动的非参数检验AI 解读

The association between log-price increments of exchange-traded equities, as measured by their spot correlation estimated from high-frequency data, exhibits a pronounced upwardsloping and almost piecewise linear relationship at the intraday horizon. There is notably lower—on average less positive—correlation in the morning than in the afternoon. We develop a nonparametric testing procedure to detect such variation in a correlation process. The test statistic has a known…

当回归变量被随机分配时的标准误AI 解读

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…

条件影响函数AI 解读

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…

劳动者侧歧视：信念与偏好AI 解读

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…