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上游与下游：通用产品代码的扩散及其影响AI 解读

We study the adoption, diffusion, and impacts of the Universal Product Code (UPC) between 1975 and 1992, during the initial years of the bar code system. We find evidence of network effects in the diffusion process. Matched-sample difference-in-differences estimates show that firm size and trademark registrations increase following UPC adoption by manufacturers. Industry-level import penetration also increases with domestic UPC adoption. Our findings suggest that bar codes,…

协整与对照：利用时间序列数据评估事件影响AI 解读

Summary Control groups can provide counterfactual evidence for assessing the impact of an event or policy change on a target variable. We argue that fitting a multivariate time series model offers potential gains over a direct comparison between the target and a weighted average of controls. More importantly, it highlights the assumptions underlying methods such as difference in differences and synthetic control, suggesting ways to test these assumptions. Gains from simple…

处理前拟合不完全的合成控制方法AI 解读

We analyze the properties of the Synthetic Control (SC) and related estimators when the pre‐treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre‐treatment periods goes to infinity. Still, we show that a demeaned version of the SC method can improve in terms of bias and variance relative to the difference‐in‐difference estimator. We also…

双重稳健的双重差分估计量AI 解读

This article proposes doubly robust estimators for the average treatment effect on the treated (ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID estimators, the proposed estimators are consistent if either (but not necessarily both) a propensity score or outcome regression working models are correctly specified. We also derive the semiparametric efficiency bound for the ATT in DID designs when either panel or repeated cross-section…

相关随机系数面板模型中处理状态不变者的平均处理效应AI 解读

Summary Correlated random coefficient (CRC) models provide a useful framework for estimating average treatment effects (ATE) with panel data by accommodating heterogeneous treatment effects and flexible patterns of selection. In their simplest form, they lead to the well‐known difference‐in‐differences estimator. CRC models yield estimates of ATE for “movers” (i.e., cross‐sectional units whose treatment status changed over time) while ATE for “stayers” (i.e., cross‐sectional…

少量处理簇下双重差分的随机化推断AI 解读

Inference using difference-in-differences with clustered data requires care. Previous research has shown that, when there are few treated clusters, t-tests based on cluster-robust variance estimators (CRVEs) severely overreject, and different variants of the wild cluster bootstrap can either overreject or underreject dramatically. We study two randomization inference (RI) procedures. A procedure based on estimated coefficients may be unreliable when clusters are…

信用不良也无妨？不良信用报告的信贷与劳动市场后果AI 解读

ABSTRACT We study the financial and labor market impacts of bad credit reports. Using difference‐in‐differences variation from the staggered removal of bankruptcy flags, we show that bankruptcy flag removal leads to economically large increases in credit limits and borrowing. Using administrative tax records linked to personal bankruptcy records, we estimate economically small effects of flag removal on employment and earnings outcomes. We rationalize these contrasting…

中央清算的价值AI 解读

ABSTRACT I study a contracting innovation that suddenly insulated traders of hedging contracts against counterparty risk: central clearing counterparties (CCPs) for derivatives. The first CCP was created in Le Havre (France) in 1882, in the coffee futures market. Using triple difference‐in‐differences estimation, I show that central clearing changed the geography of trade flows Europe‐wide, to the benefit of Le Havre. Inspecting the mechanism using trader‐level data, I find…

双重差分的潜力与陷阱：对《16岁怀孕》及其他应用的反思AI 解读

We use the exchange between Kearney/Levine and Jaeger/Joyce/Kaestner on 16 and Pregnant to reexamine the use of DiD as a response to the failure of nature to properly design an experiment for us. We argue that (1) any DiD paper should address why the original levels of the experimental and control groups differed, and why this would not impact trends, (2) the parallel trends argument requires a justification of the chosen functional form and that the use of the interaction…

双重差分模型中的双重／去偏机器学习AI 解读

Summary This paper provides an orthogonal extension of the semiparametric difference-in-differences estimator proposed in earlier literature. The proposed estimator enjoys the so-called Neyman orthogonality (Chernozhukov et al., 2018), and thus it allows researchers to flexibly use a rich set of machine learning methods in the first-step estimation. It is particularly useful when researchers confront a high-dimensional data set in which the number of potential control…

识别假设检验的警示：真人秀真的降低了青少年生育率吗？AI 解读

Evaluating policy changes that occur everywhere at the same time is difficult because of the lack of a clear counterfactual. Hoping to address this problem, researchers often proxy for differential exposure using some observed characteristic in the pretreatment period. As a cautionary tale of how difficult identification is in such settings, we re-examine the results of an influential paper by Melissa Kearney and Phillip Levine, who found that the MTV program 16 and Pregnant…

刺激住房市场AI 解读

ABSTRACT We study temporary fiscal stimulus designed to support distressed housing markets by inducing demand from buyers in the private market. Using difference‐in‐differences and regression kink research designs, we find that the First‐Time Homebuyer Credit increased home sales by 490,000 (9.8%), median home prices by $2,400 (1.1%) per standard deviation increase in program exposure, and the transition rate into homeownership by 53%. The policy response did not reverse…

聚类数量较少时处理效应的安慰剂推断AI 解读

I introduce a general, Fisher-style randomization testing framework to conduct nearly exact inference about the lack of effect of a binary treatment in the presence of very few, large clusters when the treatment effect is identified across clusters. The proposed randomization test formalizes and extends the intuitive notion of generating null distributions by assigning placebo treatments to untreated clusters. I show that under simple and easily verifiable conditions, the…

基于双重差分的直接与间接效应：越战征兵抽签后的政治偏好AI 解读

We propose a difference-in-differences approach for disentangling a total treatment effect within specific subpopulations into a direct effect and an indirect effect operating through a binary mediating variable. Random treatment assignment along with specific common trend and effect homogeneity assumptions identify the direct effects on the always and never takers, whose mediator is not affected by the treatment, as well as the direct and indirect effects on the compliers,…

双重差分平均处理效应推断：固定 b 方法AI 解读

This paper provides an analysis of the standard errors proposed by Driscoll and Kraay (1998) (DK) in linear Difference-in-Differences (DD) models with fixed effects and individual-specific time trends. The analysis is accomplished within the fixed-b asymptotic framework developed by Kiefer and Vogelsang (2005) for heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimator based tests. For both the fixed-N, large-T, and large-N, large-T cases, it is…

少量处理组与异方差下的双重差分推断AI 解读

We derive an inference method that works in differences-in-differences settings with few treated and many control groups in the presence of heteroskedasticity. As a leading example, we provide theoretical justification and empirical evidence that heteroskedasticity generated by variation in group sizes can invalidate existing inference methods, even in data sets with a large number of observations per group. In contrast, our inference method remains valid in this case. Our…

双重差分回归中简便可靠的渐近 t 检验AI 解读

We propose an asymptotically valid t test that uses Student’s t distribution as the reference distribution in a difference-in-differences regression. For the asymptotic variance estimation, we adopt the clustering-by-time approach to accommodate cross-sectional dependence. This approach often assumes the clusters to be independent across time, but we allow them to be temporally dependent. The proposed t test is based on a special heteroscedasticity and autocorrelation robust…

是否应限制散户投资者的杠杆？AI 解读

Does the provision of leverage to retail traders improve market quality or facilitate socially inefficient speculation that enriches financial intermediaries? We evaluate the effects of 2010 regulations that cap leverage in the U.S. retail foreign exchange market. Using three unique data sets and a difference-in-differences approach, we document that the leverage-constraint reduces trading volume by 23%, alleviates high-leverage traders’ losses by 40%, and reduces…

谁愿意让保障性住房建在自家附近？低收入住房开发的均衡分析AI 解读

We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5 percent, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher-income areas causes house price declines of 2.5 percent and attracts…

测量不准的混杂因素放在回归左侧更有用AI 解读

Researchers frequently test identifying assumptions in regression-based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right-hand side of the regression. If such additions do not affect the coefficient of interest (much), a study is presumed to be reliable. We caution that such invariance may result from the fact that the observed variables used in such robustness checks are often poor…

大衰退期间融资约束的就业效应AI 解读

Abstract Employment declined substantially during the 2007–2009 recession, especially in small and young firms. Using confidential firm-level data of the universe of firms and a difference-in-differences methodology, this paper estimates that financial constraints reduced employment growth by 4 to 8 percentage points in small firms relative to large firms and by 7 to 9 percentage points in young relative to old firms. I find that the effect of financial constraints on small…

文化与税收AI 解读

We propose a difference-in-differences strategy to identify the existence of interjurisdictional tax competition. Our strategy rests on differences between desired tax levels determined by culture-specific preferences and equilibrium tax levels determined by fiscal externalities and by preferences. While preferences differ systematically between French-speaking and German-speaking Swiss municipalities, local income tax burdens exhibit smooth spatial gradients. To qualify the…

面板双重差分模型中的分位数处理效应AI 解读

This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT). Identification of the QTT is more complicated than the ATT though because it depends on the unknown dependence (or copula) between the change in untreated potential outcomes and the…

依赖结构限制下仅有两期数据的双重差分分位数处理效应AI 解读

This paper shows that the Conditional Quantile Treatment Effect on the Treated is identified under (i) a Conditional Distributional Difference in Differences assumption and (ii) a new assumption that the dependence (the copula) between the change in untreated potential outcomes and the initial level of untreated potential outcomes is the same for the treated group and untreated group. We consider estimation and inference with discrete covariates and propose a uniform…