This paper develops a framework to conduct a counterfactual analysis to regulate matching markets with regional constraints that impose lower and upper bounds on the number of matches in each region. Our work is motivated by the Japan Residency Matching Program, in which the policymaker wants to guarantee the least number of doctors working in rural regions to achieve the minimum standard of service. Among the multiple possible policies that satisfy such constraints, a policymaker wants to choose the best. To this end, we develop a discrete choice model approach that estimates the utility functions of agents from observed data and predicts agents' behavior under different counterfactual policies. Our framework also allows the policymaker to design the welfare-maximizing tax scheme, which outperforms the policy currently used in practice. Furthermore, a numerical experiment illustrates how our method works.

翻译：本文开发了一个框架,以进行反事实分析,规范市场与区域制约的匹配,这些制约对每个区域的匹配数量造成下限和上限。我们的工作受到日本居住匹配方案的推动,在该方案中,决策者希望保证农村地区最少的医生达到最低服务标准。在满足这些制约的多种可能政策中,决策者希望选择最佳政策。为此,我们制定了一个独立选择模式,根据观察到的数据估算代理人的效用功能,并预测代理人在不同的反事实政策下的行为。我们的框架还允许决策者设计福利最大化税收计划,该计划比目前实际使用的政策要好。此外,一个数字实验展示了我们的方法如何运作。