前沿速递|NBER、IMF最新工作论文一览（No.2437）

       为更快更好地向广大学术爱好者及宏观金融领域研究者提供最新研究成果，“大金融思想”推出全新栏目——“NBER、IMF最新工作论文一览”，每周更新一期，汇集NBER、IMF最新发布的宏观金融领域论文，以飨读者。

本期论文搜索范围：2024.09.25-2024.10.07

  Authors 

Wei Cheng & Bruce A. Weinberg

  Series   

【 Working Papers No. 33030】

  DOI  

 10.3386/w33030

  Issue Date  

October 2024

   Abstract   

The adoption of new ideas is critical for realizing their full potential and for advancing the knowledge frontier but it involves analyzing innovators, potential adopters, and the networks that connect them. This paper applies natural language processing, network analysis, and a novel fixed effects strategy to study how the aging of the biomedical research workforce affects idea adoption. We show that the relationship between adoption and innovator career age varies with network distance. Specifically, at short distances, young innovators’ ideas are adopted the most, while at greater network distances, mid-career innovators’ ideas have the highest adoption. The main reason for this contrast is that young innovators are close to young potential adopters who are more open to new ideas, but mid-career innovators are more central in networks. Overall adoption is hump-shaped in the career age of innovators. Simulations show that the aging of innovators and of potential adopters have comparable effects on the adoption of important new ideas.

采用新想法对于充分发挥其潜力和推进知识前沿至关重要，但它涉及分析创新者、潜在采用者以及将他们联系起来的网络。本文应用自然语言处理、网络分析和一种新的固定效应策略来研究生物医学研究劳动力的老龄化如何影响想法的采用。我们表明，采用和创新者职业年龄之间的关系随网络距离而变化。具体来说，在短距离上，年轻创新者的想法被采用率最高，而在较远的网络距离上，处于职业生涯中期的创新者的想法被采用率最高。造成这种对比的主要原因是，年轻的创新者与年轻的潜在采用者关系密切，后者对新想法更开放，但处于职业生涯中期的创新者在网络中更为重要。在创新者的职业时代，总体采用率是驼峰状的。模拟表明，创新者和潜在采用者的老龄化对重要新想法的采用具有相似的影响。

  Authors  

Costas Arkolakis & Conor Walsh

  Series   

【 Working Papers No.33028】

  DOI  

 10.3386/w33028

  Issue Date  

October 2024

   Abstract   

In this paper we assess the economic impacts of moving to a renewable-dominated grid in the US. We use projections of capital costs to develop price bounds on future wholesale power prices at the local geographic level. We then use a class of spatial general equilibrium models to estimate the effect on wages and output of prices falling below these bounds in the medium term. Power prices fall anywhere between 20% and 80%, depending on local solar resources, leading to an aggregate real wage gain of 2-3%. Over the longer term, we show how moving to clean power represents a qualitative change in the aggregate growth process, alleviating the “resource drag” that has slowed recent productivity growth in the US.

在本文中，我们评估了美国转向以可再生能源为主的电网的经济影响。我们使用资本成本预测来确定当地地理级别未来批发电价的价格边界。然后，我们使用一类空间一般均衡模型来估计中期价格低于这些边界对工资和产出的影响。电价下降 20% 到 80% 之间，具体取决于当地的太阳能资源，导致总实际工资增长 2-3%。从长远来看，我们展示了转向清洁能源如何代表总增长过程的质变，缓解了减缓美国近期生产率增长的“资源拖累”。

  Authors  

Jennifer Hunt, Iain M. Cockburn & James Bessen

  Series   

【 Working Papers No.33022】

  DOI  

   10.3386/w33022

  Issue Date  

October 2024

   Abstract   

Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations.

使用我们自己的人工智能出版物数据与 2007-2019 年的 Burning Glass 职位空缺数据合并，我们调查了在远离 2007 年之前人工智能创新热点的美国地区，需要人工智能技能的工作的在线职位空缺是否增长较慢。我们发现，距离最近的 AI 热点额外 200 公里（125 英里）的通勤区，AI 工作岗位空缺份额的增长速度降低了 17%。这是由与 AI 论文的距离而不是 AI 专利驱动的。距离会减少 AI 研究工作的增长，也会减少使 AI 适应新行业的工作的增长，这对计算机和数学研究人员、软件应用程序开发人员以及金融和保险业的强烈影响证明了这一点。20% 的效果是由一些通勤区与其最近的热点之间存在州边界来解释的。这可能反映了国家边界阻碍了移民，从而阻碍了隐性知识的流动。距离并未反映面对面或远程协作的困难，也未涵盖招聘计算机职业的多机构公司内部的知识和人员流动。

  Authors  

Charles Yuji Horioka

  Series  

【 Working Papers No.33015】

  DOI  

  10.3386/w33015

  Issue Date  

October 2024

   Abstract   

In this paper, I analyze detailed data on intergenerational transfers in 4 countries (China, India, Japan, and the United States) from the “Japan Household Panel Survey on Consumer Preferences and Satisfaction (JHPS-CPS)” which has been conducted by the Institute of Social and Economic Research of Osaka University in these 4 countries since 2003, in order to shed light on the impact of intergenerational transfers on household wealth disparities and on possible reasons for the substantial differences in household wealth disparities among the 4 countries. Almost all of the evidence I present suggests that intergenerational transfers have a disequalizing impact on household wealth disparities and promote the transmission of household wealth disparities from generation to generation in all 4 countries although the magnitude of these effects varies considerably from country to country. Moreover, the evidence I present sheds considerable light on possible reasons for the substantial differences in household wealth disparities among the 4 countries.

本文分析了大阪大学社会经济研究所自 2003 年的“日本家庭消费者偏好和满意度调查 （JHPS-CPS）”中关于 4 个国家（中国、印度、日本和美国）代际转移的详细数据，以阐明代际转移对家庭财富差距的影响，以及造成巨大差异的可能原因4 个国家之间家庭财富差距的差异。我提供的几乎所有证据表明，代际转移对家庭财富差距具有不均衡的影响，并促进了所有四个国家的家庭财富差距的代际传递，尽管这些影响的程度因国家而异。此外，我提供的证据为这四个国家之间家庭财富差距存在巨大差异的可能原因提供了相当大的解释。

  Authors  

Sadegh S.M. Eshaghnia， James J. Heckman， Rasmus Landersø & Rafeh Qureshi

  Series  

【Working Paper No.33023】

  DOI  

  10.3386/w33023

  Issue Date  

October 2024

   Abstract   

This paper studies intergenerational mobility—the transmission of family influence. We develop and estimate measures of lifetime resources motivated by economic theory that account for differences in life-cycle trajectories, and uncertainty about future income. We identify the effects of parents’ resources on child outcomes through policy shocks at different childhood ages that affect family investments. Parents’ expected lifetime resources are stronger predictors of child outcomes than the income measures traditionally used in the literature on social mobility. Moreover, while effects estimated through exogenous variation in parents’ expected lifetime resources are smaller in magnitude than their correlational counterparts, they are still sizable and largest in early childhood. The paper illustrates how integrating key insights from different literatures when studying intergenerational mobility allows for a better understanding of the importance of factors such as the family’s role, changes in individual life cycles across generations, and the expectations and trajectories individuals face across their lifetimes.

本文研究了代际流动性——家庭影响力的传递。我们开发和估计由经济理论驱动的终身资源度量，这些度量考虑了生命周期轨迹的差异和未来收入的不确定性。我们通过不同童年年龄影响家庭投资的政策冲击来确定父母资源对儿童结果的影响。父母的预期终生资源比传统上用于社会流动性文献中的收入衡量标准更能预测儿童结果。此外，虽然通过父母预期终生资源的外生变化估计的影响幅度小于相关影响，但它们在儿童早期仍然相当大且最大。该论文说明了在研究代际流动性时如何整合来自不同文献的关键见解，从而更好地理解家庭角色、跨代个人生命周期的变化以及个人在其一生中面临的期望和轨迹等因素的重要性。

  Authors  

Matteo Tranchero, Cecil-Francis Brenninkmeijer, Arul Murugan & Abhishek Nagaraj

  Series  

【Working Paper No.33033】

  DOI  

  10.3386/w33033

  Issue Date  

October 2024

   Abstract   

Large Language Models (LLMs) are proving to be a powerful toolkit for management and organizational research. While early work has largely focused on the value of these tools for data processing and replicating survey-based research, the potential of LLMs for theory building is yet to be recognized. We argue that LLMs can accelerate the pace at which researchers can develop, validate, and extend strategic management theory. We propose a novel framework called Generative AI-Based Experimentation (GABE) that enables researchers to conduct exploratory in silico experiments that can mirror the complexities of real-world organizational settings, featuring multiple agents and strategic interdependencies. This approach is unique because it allows researchers to unpack the mechanisms behind results by directly modifying agents’ roles, preferences, and capabilities, and asking them to reveal the explanations behind decisions. We apply this framework to a novel theory studying strategic exploration under uncertainty. We show how our framework can not only replicate the results from experiments with human subjects at a much lower cost, but can also be used to extend theory by clarifying boundary conditions and uncovering mechanisms. We conclude that LLMs possess tremendous potential to complement existing methods for theorizing in strategy and, more broadly, the social sciences.

大型语言模型 （LLM） 被证明是管理和组织研究的强大工具包。虽然早期工作主要集中在这些工具在数据处理和复制基于调查的研究方面的价值，但 LLM 在理论构建方面的潜力尚未得到认可。我们认为 LLM 可以加快研究人员开发、验证和扩展战略管理理论的速度。我们提出了一种称为基于生成式 AI 的实验 （GABE） 的新框架，使研究人员能够进行探索性计算机实验，这些实验可以反映现实世界组织设置的复杂性，具有多个代理和战略相互依赖关系。这种方法是独一无二的，因为它允许研究人员通过直接修改代理的角色、偏好和能力，并要求他们揭示决策背后的解释来解开结果背后的机制。我们将该框架应用于研究不确定性下战略探索的新理论。我们展示了我们的框架如何不仅以更低的成本复制人类受试者的实验结果，而且还可以通过阐明边界条件和揭示机制来扩展理论。我们得出的结论是，LLM 具有巨大的潜力，可以补充现有的战略理论化方法，更广泛地说，是社会科学的理论化方法。

  Authors  

Jocelyn Boussard, Chiara Castrovillari, Tomohide Mineyama, Marta Spinella, Bilal Tabti, Maxwell Tuuli 

  Series  

【Working Paper No.2024/214】

  Issue Date  

October 4, 2024

   Abstract   

This paper investigates the consequences of global shocks on a sample of low- and lower-middle-income countries with a particular focus on fragile and conflict-affected states (FCS). FCS are a group of countries that display institutional weakness and/or are negatively affected by active conflict, thereby facing challenges in macroeconomic policy management. Examining different global shocks associated with commodity prices, external demand, and financing conditions, this paper establishes that FCS economies are more vulnerable to these shocks compared to non-FCS peers. The higher sensitivity of FCS economies is mainly driven by procyclical fiscal responses, aggravated by the lack of effective spending controls and timely access to financial sources. External financing serves as a source of stability, partially mitigating the adverse impact of global shocks. This paper contributes to a better understanding of how conditions of fragility, which are on the rise in many parts of the world today, can amplify the effects of negative exogenous shocks. Its results highlight the diverse nature of underlying sources of vulnerabilities, spanning from fiscal and external buffers to institutional quality and economic structure, with lessons applicable to a broader set of countries. Efficient and timely external financial support from external partners, including international financial institutions, should help countries’ counter-cyclical responses to mitigate adverse shocks and achieve macroeconomic stability.

本文调查了全球冲击对低收入和中低收入国家样本的影响，特别关注脆弱和受冲突影响的国家 （FCS）。FCS 是一组表现出制度弱点和/或受到活跃冲突负面影响的国家，因此在宏观经济政策管理方面面临挑战。通过研究与大宗商品价格、外部需求和融资条件相关的不同全球冲击，本文确定，与非FCS经济体相比，FCS经济体更容易受到这些冲击的影响。FCS 经济体的较高敏感性主要是由顺周期财政反应驱动的，而缺乏有效的支出控制和及时获得资金来源则加剧了这一问题。外部融资是稳定的来源，在一定程度上减轻了全球冲击的不利影响。本文有助于更好地了解当今世界许多地方正在上升的脆弱性状况如何放大负面外生冲击的影响。研究结果凸显了脆弱性潜在来源的多样性，从财政和外部缓冲到制度质量和经济结构，其经验教训适用于更广泛的国家。来自外部合作伙伴（包括国际金融机构）的高效、及时的外部资金支持应有助于各国采取反周期应对措施，以减轻不利冲击并实现宏观经济稳定。

  Authors  

Gee Hee Hong, Shikun (Barry) Ke, Anh D. M. Nguyen

  Series  

【Working Paper No.2024/209】

  Issue Date  

September 27, 2024

   Abstract   

Fiscal policy uncertainty (FPU)—ambiguity in government spending and tax plans, as well as in public debt valuation—is widely regarded as a source of economic and financial disruptions. However, assessing its impact has so far been limited to a few large economies. In this paper, we construct a novel database of news-based fiscal policy uncertainty for 189 countries. Importantly, we track fiscal uncertainty events that generate global attention that we refer to as the “global fiscal policy uncertainty." This uncertainty has contractionary effects, reducing industrial production in both advanced and emerging market economies, with impacts greater than country-specific fiscal policy uncertainty. Additionally, global fiscal policy uncertainty raises sovereign borrowing costs and generates synchronous movements in the global financial variables, even after accounting for US monetary policy shocks.

财政政策不确定性 （FPU） — 政府支出和税收计划以及公共债务估值的模糊性 — 被广泛认为是经济和金融动荡的根源。然而，到目前为止，评估其影响仅限于少数大型经济体。在本文中，我们为 189 个国家构建了一个基于新闻的财政政策不确定性的新数据库。重要的是，我们跟踪引起全球关注的财政不确定性事件，我们称之为“全球财政政策不确定性”。这种不确定性具有收缩效应，减少了发达经济体和新兴市场经济体的工业生产，其影响大于特定国家的财政政策不确定性。此外，全球财政政策的不确定性提高了主权借贷成本，并导致全球金融变量的同步变动，即使在考虑了美国货币政策冲击之后也是如此。

（选文、整理：杨致瑗）