本文精选了经济学领域国际顶刊《The Quarterly Journal of Economics》近期发表的论文，提供经济学研究领域最新的学术动态。

The Ant and the Grasshopper: Seasonality and the Invention of Agriculture

原刊和作者：

The Quarterly Journal of Economics Volume 139, Issue 3

Andrea Matranga （Andrea Matranga）

Abstract

The Neolithic revolution saw the independent development of agriculture among at least seven unconnected hunter-gatherer populations. I propose that the rapid spread of agricultural techniques resulted from increased climatic seasonality causing hunter-gatherers to adopt a sedentary lifestyle and store food for the season of scarcity. Their newfound sedentary lifestyle and storage habits facilitated the invention of agriculture. I present a model and support it with global climate data and Neolithic adoption dates, showing that greater seasonality increased the likelihood of agriculture’s invention and its speed of adoption by neighbors. This study suggests that seasonality patterns played a dominant role in determining our species’ transition to farming.

Link: https://doi.org/10.1093/qje/qjae012

Worker Beliefs About Outside Options

原刊和作者：

The Quarterly Journal of Economics Volume 139, Issue 3

Simon Jäger （Massachusetts Institute of Technology）

Christopher Roth （University of Cologne）

Nina Roussille （Massachusetts Institute of Technology）

Benjamin Schoefer （University of California）

Abstract

Standard labor market models assume that workers hold accurate beliefs about the external wage distribution, and hence their outside options with other employers. We test this assumption by comparing German workers’ beliefs about outside options with objective benchmarks. First, we find that workers wrongly anchor their beliefs about outside options on their current wage: workers that would experience a 10% wage change if switching to their outside option only expect a 1% change. Second, workers in low-paying firms underestimate wages elsewhere. Third, in response to information about the wages of similar workers, respondents correct their beliefs about their outside options and change their job search and wage negotiation intentions. Finally, we analyze the consequences of anchoring in a simple equilibrium model. In the model, anchored beliefs keep overly pessimistic workers stuck in low-wage jobs, which gives rise to monopsony power and labor market segmentation.

Link: https://doi.org/10.1093/qje/qjae001

The Role of the Ask Gap in Gender Pay Inequality

原刊和作者：

The Quarterly Journal of Economics Volume 139, Issue 3

Nina Roussille （Massachusetts Institute of Technology）

Abstract

The gender ask gap measures the extent to which women ask for lower salaries than comparable men. This article studies its role in generating wage inequality, using novel data from an online recruitment platform for full-time engineering jobs: Hired.com. To use the platform, job candidates must post an ask salary, stating how much they want to make in their next job. Firms then apply to candidates by offering them a bid salary, solely based on the candidate’s résumé and ask salary. If the candidate is hired, a final salary is recorded. After adjusting for résumé characteristics, the ask gap is 2.9%, the bid gap is 2.2%, and the final offer gap is 1.4%. Further controlling for the ask salary explains the entirety of the residual gender gaps in bid and final salaries. To further provide evidence of the causal effect of the ask salary on the bid salary, I exploit an unanticipated change in how candidates were prompted to provide their ask. For some candidates in mid-2018, the answer box used to solicit the ask salary was changed from an empty field to an entry prefilled with the median bid salary for similar candidates. I find that this change drove the ask, bid, and final offer gaps to zero. In addition, women did not receive fewer bids or final offers than men did due to the change, suggesting they faced little penalty for demanding comparable wages.

Link: https://doi.org/10.1093/qje/qjae004

Discrimination in Multiphase Systems: Evidence from Child Protection

原刊和作者：

The Quarterly Journal of Economics Volume 139, Issue 3

E Jason Baron （Duke University）

Joseph J Doyle （National Bureau of Economic Research）

Natalia Emanuel （Federal Reserve Bank of New York）

Peter Hull （Brown University）

Joseph Ryan （University of Michigan）

Abstract

We develop empirical tools for studying discrimination in multiphase systems and apply them to the setting of foster care placement by child protective services. Leveraging the quasi-random assignment of two sets of decision-makers—initial hotline call screeners and subsequent investigators—we study how unwarranted racial disparities arise and propagate through this system. Using a sample of over 200,000 maltreatment allegations, we find that calls involving Black children are 55% more likely to result in foster care placement than calls involving white children with the same potential for future maltreatment in the home. Call screeners account for up to 19% of this unwarranted disparity, with the remainder due to investigators. Unwarranted disparity is concentrated in cases with potential for future maltreatment, suggesting that white children may be harmed by “underplacement” in high-risk situations.

Link: https://doi.org/10.1093/qje/qjae007

Identifying Prediction Mistakes in Observational Data

The Quarterly Journal of Economics Volume 139, Issue 3

Ashesh Rambachan （Massachusetts Institute of Technology）

Abstract

Decision makers, such as doctors, judges, and managers, make consequential choices based on predictions of unknown outcomes. Do these decision makers make systematic prediction mistakes based on the available information? If so, in what ways are their predictions systematically biased? In this article, I characterize conditions under which systematic prediction mistakes can be identified in empirical settings such as hiring, medical diagnosis, and pretrial release. I derive a statistical test for whether the decision maker makes systematic prediction mistakes under these assumptions and provide methods for estimating the ways the decision maker’s predictions are systematically biased. I analyze the pretrial release decisions of judges in New York City, estimating that at least 20% of judges make systematic prediction mistakes about misconduct risk given defendant characteristics. Motivated by this analysis, I estimate the effects of replacing judges with algorithmic decision rules and find that replacing judges with algorithms where systematic prediction mistakes occur dominates the status quo.

Link: https://doi.org/10.1093/qje/qjae013