CAREER: Macroeconomic Policies: from Optimal Government Transfers to Regulating New Technologies

政府政策在现代经济中发挥着关键作用。短期内，政府帮助稳定商业周期。刺激支票等财政转移支付最近已成为缓解美国经济衰退的重要工具。该奖项资助的两个项目量化了刺激性转移支付的规模以及它们在财政联盟中稳定区域商业周期的程度。在较长时期内，政府有责任监管新技术并管理其后果。数字和自动化技术带来的新挑战推动了该奖项资助的其余三个项目。这些项目调查了滥用人工智能来支持监视国家、数据可能导致集中的数字行业的最佳监管，以及政府应如何管理新技术取代工人的劳动力重新分配事件。通过为政策提供信息，这些项目将使美国受经济衰退和自动化影响尤为严重的弱势群体受益，促进美国的国家安全利益和民主稳定，并有助于确保美国在未来数字产业中保持领先地位。该奖项的教育部分将通过国家经济研究局举办的教程向政策制定者和记者以及研究生传播研究成果。该奖项资助的项目增进了我们对宏观经济学核心问题的理解，但也与政治经济学、产业组织和劳动经济学等更广泛的问题相关。第一个项目认识到家庭因刺激转移而产生的边际消费倾向随刺激转移的规模而变化。这种尺寸依赖性的一个关键决定因素是商品的耐用性。该项目开发了最先进的耐用品需求模型，对其进行校准以匹配美国微观数据的关键时刻，并用它来量化刺激转移的最佳规模。第二个项目将政策反事实的半结构方法应用于美国州级数据，以构建一个没有财政一体化的美国经济。第三个项目收集全球面部识别人工智能贸易数据。它记录了美国和中国向独裁国家和民主国家出口这种监控技术的新事实。第四个项目构建了寡头垄断行业的生命周期模型，例如以数据为关键输入的数字行业。均衡的特点是最初的企业进入阶段，随后是洗牌和后来的行业集中。该模型经过校准以匹配美国数字行业数据，并用于研究最佳行业监管。最后一个项目始于观察到工人流离失所是许多劳动力重新分配事件的共同特征，例如由自动化或向清洁技术过渡引起的事件。在这种情况下，流离失所的工人面临着重新分配和借贷摩擦。该项目开发了一个包含这些摩擦的异构代理模型。它用它来研究减缓技术采用或帮助工人重新分配的次佳政策。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Government policy plays a key role in modern economies. In the short-term, governments help stabilize business cycles. Fiscal transfers, such as stimulus checks, have recently become an important tool in alleviating US recessions. Two projects funded by this award quantify how large stimulus transfers should be and to what extent they stabilize regional business cycles in a fiscal union. Over longer periods of time, governments are responsible for regulating new technologies and managing their consequences. New challenges brought to the fore by digital and automation technologies motivate the remaining three projects funded by this award. The projects investigate the misuse of artifical intelligence to support surveillance states, the optimal regulation of digital industries where data can lead to concentration, and how governments should manage episodes of labor reallocation where new technologies displace workers. By informing policy, these projects will benefit disadvantaged populations in the US who are disproportionately impacted by recessions and automation, foster US national security interests and democratic stability, and help ensure the US remains a leader in the digital industries of the future. The educational component of this award will disseminate the research findings to policymakers and journalists, as well to graduate students through a tutorial ran by the National Bureau of Economic Research.The projects funded by the award advance our understanding of core issues in macroeconomics, but also connect to broader questions in political economy, industrial organization, and labor economics. The first project recognizes that households' marginal propensity to consume out of a stimulus transfer varies with its size. A key determinant of such size-dependence is the durability of goods. The project develops a state-of-the art model of durables demand, calibrates it to match key moments in US micro-data, and uses it to quantify the optimal size of stimulus transfers. The second project applies a semi-structural methodology for policy counterfactuals to state-level US data to construct a US economy without fiscal integration. The third project collects global data on facial recognition AI trade. It documents new facts about US and Chinese exports of this surveillance technology to autocracies and democracies. The fourth project builds a model of the life-cycle of oligopolistic industries, such as digital industries where data is a key input. The equilibrium features an initial firm entry phase, followed by a shakeout and later industry concentration. The model is calibrated to match US data on digital industries and is used to study optimal industry regulation. The last project begins from the observation that worker displacement is a common feature of many episodes of labor reallocation, such as those induced by automation or the transition to clean technologies. Displaced workers face reallocation and borrowing frictions in such episodes. The project develops a heterogeneous agents model which incorporates these frictions. It uses it to study second best policies that slow down technological adoption or help worker reallocation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.