The Economic Determinants of Domestic Violence

在美国，每天大约有1.4万名女性受到亲密伴侣的殴打，其中4人被杀害，这促使前卫生部长C. Everett Koop将家庭暴力列为美国最重要的健康问题。尽管家庭暴力很普遍，代价也很高，但关于家庭暴力的经济决定因素，仍有许多问题有待了解。该项目分析了妇女收入对遭受殴打的影响。关于收入对暴力的影响，现有的理论是模糊的。一个讨价还价的经济模型预测，当一个女人的资源相对于她丈夫的资源增加时，针对她的暴力就会减少。其他理论（交换理论和男性反冲）的预测正好相反。这种关系的性质必须由经验来确定。利用调查数据考察妇女工资对暴力的影响的现有实证研究普遍发现，工资较低的妇女遭受的暴力更多。然而，这项工作在两个主要方面受到限制。首先，调查容易漏报。其次，这些研究未能建立家庭暴力和工资之间的因果关系，例如，未能解释被忽略的变量偏差或反向因果关系的可能性。本项目采用两种策略来克服这些障碍。首先，它使用多个行政数据集来制定家庭暴力的措施。这些数据包括：因袭击而住院、报警、因家庭暴力而被捕以及亲密伴侣谋杀率。它还使用了个人层面的调查数据，以及来自加州妇女健康调查的不太严重的暴力、威胁和控制行为的自我报告。使用这些多种暴力措施将揭示暴力关系的不同方面如何受到妇女相对收入变化的影响。为了克服第二个障碍并确立收入与家庭暴力之间的因果关系，该项目利用了某些行业由妇女主导（例如服务业）而其他行业由男子主导（例如建筑业）的事实。这些部门需求的增加分别导致女性和男性工资的外生增长。通过关注当地劳动力市场状况和外生劳动力需求冲击，该项目可以确定相对收入变化对家庭暴力的影响。在这项工作的基础上，该项目还探讨了暴力对孕产妇和儿童健康的影响以及经济资源的潜在缓解作用。以前的工作已经证实，当母亲控制更多的家庭资源时，儿童的健康状况会得到改善。这些进步很大程度上归因于女性在子女身上投入了更多的物质。然而，这项研究提出了另一种潜在的机制：减少暴力。该项目使用了一个独特的出生结果数据集，该数据集与怀孕期间因遭受殴打而住院的数据相关联，利用工具变量策略首次提供了暴力对出生结果影响的因果估计。接下来是对暴力影响生育结果的途径的分析：钝性创伤的直接影响或冒险和产前护理不足的间接影响。更广泛的影响：这项研究不仅为老的研究问题带来了替代工具，而且还开发了新的数据集来回答这些问题。研究结果将对预防暴力项目以及有关工资平等和劳动力性别歧视的劳工政策产生重要的政策影响。此外，关于暴力对生育结果的影响的调查结果是第一次因果估计，将有助于使从业人员了解家庭暴力对健康的影响以及暴力影响生育结果的机制。

Everyday roughly fourteen thousand women in the US are battered and four are killed by their intimate partners, prompting former Surgeon General C. Everett Koop to label domestic violence the single most important health issue in the US. Despite the prevalence and high costs of domestic violence, much remains to be understood about the economic determinants of battering. This project analyzes the impact of women's earnings on battering. Existing theory is ambiguous with respect to the impact of income on violence. An economic model of bargaining predicts that as a woman's resources increase relative to those of her husband, violence against her should decline. Other theories, (exchange theory and male backlash) predict the opposite. The nature of the relationship must be determined empirically. Existing empirical research examining the impact of women's wages on violence using survey data has generally found that women with lower wages experience more violence. However, this work is limited in two main respects. First, surveys are prone to underreporting. Second, these studies fail to establish a causal relationship between domestic violence and wages by, for example, failing to account for the potential for omitted variable bias or reverse causality. This project pursues two strategies to overcome these obstacles. First, it uses multiple administrative datasets to develop measures of domestic violence. These data include: hospitalizations for assaults, calls to the police, arrests for domestic violence as well as intimate partner homicide rates. It also use individual level survey data with self-reports of less severe violence, threats and controlling behavior from the California Women's Health Survey. Using these multiple measures of violence will shed light on how different aspects of violent relationships are affected by changes in women's relative earnings. To overcome the second obstacle and establish a causal relationship between earnings and domestic violence, the project takes advantage of the fact that certain industries are dominated by women (e.g., services) and others by men (eg, construction). Increases in demand in these sectors results in exogenous increases in female and male wages, respectively. By focusing on local labor market conditions and exogenous labor demand shocks, the project can identify the impact of changes in relative income on domestic violence.Based on this work, the project also explores the impact of violence on maternal and child health and the potential mitigating effects of economic resources. Previous work has established that child health improves when mothers control a greater share of the household resources. These improvements have largely been attributed to women's greater material investments in their children. However, this research suggests another potential mechanism: reductions in violence. Using a unique dataset of birth outcomes linked to data onhospitalization for assault during the pregnancy, this project provides the first causal estimates of the impact of violence on birth outcomes using an instrumental variable strategy. This is followed by an analysis of the pathways by which violence affects birth outcomes: direct effect of blunt trauma or indirect effects of risk taking and inadequate prenatal care.Broader Impact: This research not only brings alternative tools to bear on an old research question, but also develops new datasets to answer these questions. The research findings will have important policy implications for violence prevention programs as well as for labor policies regarding pay parity and gender discrimination in the workforce. In addition, the findings with respect to the impact of violence on birth outcomes represent the first causal estimates and will serve to inform practitioners of the health consequences of domestic violence and the mechanisms by which violence affects birth outcomes.