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This article studies international reserves’ nominal exchange rate stabilizing impact in emerging markets and developing countries, with a particular focus on its nonlinearity and asymmetry across different states of the economy. Using the fixed-effects and dynamic panel threshold models, we find the reserves to short-term debt threshold ratio after which the marginal stabilizing effect of reserves begins to fall during tranquil times. Such diminishing returns, however, do not appear to exist even at the excessive level of reserves during the global financial crisis, partly justifying precautionary demand for international reserves. These results call for extending reserve pooling or swap arrangements to enhance efficiency of reserve management by holding adequate, rather than excess, international reserves with an access to emergency lending during the crisis.

Abstract: Policy makers worldwide face tough choices over how to prioritize public funding for adaptation to climate change. One particularly difficult choice is whether to opt for policies that promote relocation away from flood risks or infrastructure investments that protect against flooding. Local communities commonly prefer protective infrastructure, but it is less obvious that the general public will support this approach due to the growing costs. We study public opinion on these adaptation approaches using a choice experiment with nationally representative samples in the United States and Germany (n = 2400 each). We asked participants to prioritize federal funding between two hypothetical, equally sized communities differing in their adaptation strategy, flood frequency, lives and economic assets at risk, economic vitality, geographic distance, and political orientation. In both countries, we find surprisingly strong support for protective infrastructure over relocation policies among the general public, even under conditions where relocation could be an attractive alternative for addressing the growing costs of protective infrastructure and rebuilding efforts.

Despite the substantial number of studies on the relationships between crime patterns and built environments, the impacts of street-level built environments on crime patterns have not been definitively determined due to the limitations of obtaining detailed streetscape data and conventional analysis models. To fill these gaps, this study focuses on the non-linear relationships and threshold effects between built environments and local crime patterns at the level of a street segment in the City of Santa Ana, California. Using Google Street View (GSV) and semantic segmentation techniques, we quantify the features of the built environment in GSV images. Then, we examine the non-linear relationships and threshold effects between built environment factors and crime by applying interpretable machine learning (IML) methods. While the machine learning models, especially Deep Neural Network (DNN), outperformed negative binomial regression in predicting future crime events, particularly advantageous was that they allowed us to obtain a deeper understanding of the complex relationship between crime patterns and environmental factors. The results of interpreting the DNN model through IML indicate that most streetscape elements showed non-linear relationships and threshold effects with crime patterns that cannot be easily captured by conventional regression model specifications. The non-linearities and threshold effects revealed in this study can shed light on the factors associated with crime patterns and contribute to policy development for public safety from crime.

AimTo assess, from a United States (US) payer's perspective, the cost-effectiveness of gels designed to separate the endometrial surfaces (intrauterine spacers) placed following intrauterine surgery.Materials and methodsA decision tree model was developed to estimate the cost-effectiveness of intrauterine spacers used to facilitate endometrial repair and prevent the formation (primary prevention) and reformation (secondary prevention) of intrauterine adhesions (IUAs) and associated pregnancy- and birth-related adverse outcomes. Event rates and costs were extrapolated from data available in the existing literature. Sensitivity analyses were conducted to corroborate the base case results.ResultsIn this model, using intrauterine spacers for adhesion prevention led to net cost savings for US payers of $2,905 per patient over a 3.5-year time horizon. These savings were driven by the direct benefit of preventing procedures associated with IUA formation ($2,162 net savings) and the indirect benefit of preventing pregnancy-related complications often associated with IUA formation ($3,002). These factors offset the incremental cost of intrauterine spacer use of $1,539 based on an assumed price of $1,800 and the related increase in normal deliveries of $931. Model outcomes were sensitive to the probability of preterm and normal deliveries. Budget impact analyses show overall cost savings of $19.96 per initial member within a US healthcare plan, translating to $20 million over a 5-year time horizon for a one-million-member plan.LimitationsThere are no available data on the effects of intrauterine spacers or IUAs on patients' quality of life. Resultingly, the model could not evaluate patients' utility related to treatment with or without intrauterine spacers and instead focused on costs and events avoided.ConclusionThis analysis robustly demonstrated that intrauterine spacers would be cost-saving to healthcare payers, including both per-patient and per-plan member, through a reduction in IUAs and improvements to patients' pregnancy-related outcomes.

It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.

In the past two decades, a number of banks joined global initiatives aimed to mitigate climate change by “greening” their asset portfolios. We study whether banks that made such commitments have a different emission exposure of their portfolios of syndicated loans than banks that did not. We rely on loan-level information with global coverage combined with country-industry information on emissions. We find that all banks have reduced their loan-emission exposures over the last 8 years. However, we do not find differences between banks that did and those that did not signal their sustainability goals, with the exception of early signers of Principles of Responsible Investments (PRI), who already had lower exposure to emissions through their syndicated lending. In addition, banks that signed PRI shortened the maturity of the loans extended to highly-emitting industries but only temporarily. Thus, we conclude that banks reduced their exposure to climate transition risks on average, but voluntary climate commitments did not contribute to syndicated loan reallocation away from highly-emitting sectors.

Recent shifts in global hegemony make the need for critical geographical accounts of geoeconomics and geopolitics that much more critical. They underline that we need to come to terms with their dialectical relationships and tensions, doing so in relation to both underlying struggles over international hegemony and uneven capitalist development as well as in relation to all sorts of complex overlying socio-cultural formations. Critical geographers can combine their diverse approaches more effectively to do this analytical work by adapting recent forms of conjunctural analysis in urban, economic and regional geography.

Abstract: In repeated games, where both collusive and noncollusive outcomes can be supported as equilibria, it is crucial to understand the likelihood of selection for each type of equilibrium. Controlled experiments have empirically validated a selection criterion for the two-player repeated prisoner’s dilemma: the basin of attraction for always defect. This prediction device uses the game primitives to measure the set of beliefs for which an agent would prefer to unconditionally defect rather than attempt conditional cooperation. This belief measure reflects strategic uncertainty over others’ actions, where the prediction is for noncooperative outcomes when the basin measure is full, and cooperative outcomes when empty. We expand this selection notion to multi-player social dilemmas and experimentally test the predictions, manipulating both the total number of players and the payoff tensions. Our results affirm the model as a tool for predicting long-term cooperation, while also speaking to some limitations when dealing with first-time encounters.

Governments often privatize the administration of regulations to third-party specialists paid for by the regulated parties. We study how the resulting conflict of interest can have unintended consequences for the distributional impacts of regulation. In Massachusetts, the party responsible for hazardous waste contamination must hire a licensed contractor to quantify the environmental severity. We find that contractors’ evaluations favor their clients, exhibiting substantial score bunching just below thresholds that determine government oversight of the remediation. Client favoritism is more pronounced in socioeconomically disadvantaged neighborhoods and is associated with inferior remediation quality, highlighting a novel channel for inequities in pollution exposure. (JEL D63, J15, K32, L51, Q53, R23)

Recent evidence suggests that agents may base their forecasts for macroeconomic variables mainly on their personal life experiences. We connect this behavior to the concept of constant-gain learning (CGL) in macroeconomics. Our approach incorporates both heterogeneity in the life cycle via the perpetual youth model and learning from experience (LfE) into a linear expectations model where agents are born and die with some probability every period. For LfE, agents employ a decreasing-gain learning (DGL) model using data only from their own lifetimes. While agents are using DGL individually, we show that in the aggregate, expectations follow an approach related to CGL, where the gain is now tied to the probabilities of birth and death. We provide a precise characterization of the relationship between CGL and our model of perpetual youth learning (PYL) and show that PYL can well approximate CGL while pinning down the gain parameter with demographic data. Calibrating the model to U.S. demographics leads to gain parameters similar to those found in the literature. Further, variation in birth and death rates across countries and time periods can help explain the empirical time-variation in gains. Finally, we show that our approach is robust to alternative ways of modeling individual agent learning.

Credit default swaps (CDS) played an important role in the financial crisis of 2008 leading to calls for regulation. Here, we seek to understand the impact of a CDS regulation that restricts the possibility to hold naked CDS. We use a controlled laboratory experiment analyzing CDS pricing in a bond market subject to default risk. Our results show that the regulation achieves the goal of increasing the use of CDS for hedging purposes while reducing the use of CDS for speculation. This success does not come at the expense of lower initial public offering (IPO) prices for the bonds or worse pricing of bonds or CDS in the secondary market.

BackgroundInvolving patients in the health-care delivery innovation has many benefits. Open social innovation (OSI) presents a fitting lens to examine and advance patient engagement in innovation. OSI offers a participatory approach to innovation, in which diverse groups of participants collaboratively generate ideas and scale solutions on complex social challenges.PurposeThis study: (1) describes a pilot application of OSI, in which individuals serving on a hospital's patients and family advisory councils (PFACs) were invited to participate in an innovation contest; and (2) explores the extent to which patients' beliefs about their role in innovation relate to their participation in the contest.Methodology/approachWe conducted an innovation contest that invited PFAC members to share ideas that would improve patient experiences and then vote on and select the ideas that they wanted to see move forward. We measured patients' beliefs about their role in innovation in a survey before the contest.ResultsTwenty individuals submitted 27 ideas. Patients who expressed preference for more involvement in innovation were more likely to participate.ConclusionsUsing OSI may help expand patient engagement in innovation, particularly among those who want to be more involved but do not feel authorized to voice ideas in traditional advisory committees.Practical implicationsOSI spurred collaboration among patients, clinicians, quality improvement staff, hospital administrators, and other stakeholders in idea generation, elaboration, and implementation. More experimentation and research are needed to understand how OSI can be leveraged to capture patients' voice and incorporate them in care delivery innovation.

Economists tend to favour price-based approaches, such as gasoline and carbon taxes, to address the negative impacts of car travel, while urban planners tend to emphasise land use planning such as compact development. In this paper, we argue that the two approaches are synergistic. We use precinct-level data from two California referenda to show that land use planning makes pricing more feasible: voters in dense, transit-oriented neighbourhoods are more willing to support a carbon price and increased gasoline taxes. Political ideology is a more important determinant of voting patterns, but in a closely divided election, land use patterns, public transportation, and other aspects of the built environment can determine the success of a referendum on driving taxes. Our results also imply that the voluminous research on land use and transportation underestimates the long-run impacts of compact development on driving, through ignoring the ways in which urban form shapes the politics of taxation.

How much should electric utilities pay to maintain a reliable electricity system? This paper describes an open-ended stated-preference experiment that generates estimates for how advanced notification impacts household willingness-to-pay (WTP) to avoid outages. We find positive and statistically significant WTP to avoid power outages of $10/kWh, consistent with the expectation that outages are costly to the residential sector. We find notification reduces the WTP, but the effects are not statistically significant. There is limited evidence that these results vary by income and wealth levels. Back-up power ownership is positively correlated with respondents’ WTP to avoid outages.

We report on a laboratory experiment testing the predictions of the Diamond–Mortensen–Pissarides (DMP) search-and-matching model, which is a workhorse, decentralized model of unemployment and the labor market. We focus on the job vacancy posting problem that firms face in the DMP model. We explore the model's comparative statics predictions concerning variations in the separation rate, the vacancy posting cost, and the firm's surplus earned per employee. Across all treatments, we find strong evidence for an inverse relationship between vacancies and unemployment, consistent with the Beveridge curve. We also find that the results of our various comparative statics exercises are in-line with the predictions of the theory.

Attrition is a common and potentially important threat to internal validity in treatment effect studies. We extend the changes-in-changes approach to identify the average treatment effect for respondents and the entire study population in the presence of attrition. Our method, which exploits baseline outcome data, can be applied to randomized experiments as well as quasi-experimental difference-in-difference designs. A formal comparison highlights that while widely used corrections typically impose restrictions on whether or how response depends on treatment, our proposed attrition correction exploits restrictions on the outcome model. We further show that the conditions required for our correction can accommodate a broad class of response models that depend on treatment in an arbitrary way. We illustrate the implementation of the proposed corrections in an application to a large-scale randomized experiment.

Abstract: How does legislature size impact public service provision? Despite the importance of institutional design for democratic governance, the effect of legislative features on citizen welfare remains little understood. In this article, we use a formal model to show that increasing legislature size improves public goods delivery. We argue that changes in bargaining costs depend on whether additional legislators share the executive's party affiliation: More opposition members reduce the equilibrium public goods provision, while more government‐aligned members increase it. We test this theory by exploiting sharp discontinuities in city‐council size in Brazil. We show that an additional city councilor has a 91% chance of belonging to the mayoral coalition, and this significantly improves primary school enrollment and infant mortality rates. To explore possible mechanisms, we surveyed 174 former city councilors and analyzed 346,553 bills proposed between 2005 and 2008. This article has implications for the design of representative institutions.

HighlightsWe illustrate the steps involved in carrying out cost-effectiveness analysis using net benefit regressions with possibly censored demo data by providing step-by-step guidance and code applied to a data set.We demonstrate the importance of these new methods by illustrating how naïve methods for handling censoring can lead to biased cost-effectiveness results.

We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over twenty years, in tandem with a randomized experiment (deworming) that has exogenously boosted education and living standards. The main finding is that the program reduces the likelihood of membership in a Pentecostal denomination up to 20 years later when respondents are in their mid-thirties, while there is a comparable increase in membership in traditional Christian denominations. The effect is concentrated and statistically significant among a sub-group of participants who benefited most from the program in terms of increased education and income. The effects are unlikely due to increased secularization, because the program does not reduce measures of religiosity. The results help explain why the global growth of the Pentecostal movement, sometimes described a "New Reformation", is centered in low-income communities.

We experimentally document persistence of suboptimal behavior despite ample opportunities to learn from feedback in a canonical updating problem where people suffer from base-rate neglect. Our results provide insights on the mechanisms hindering learning from feedback. Importantly, our results suggest mistakes are more likely to be persistent when they are driven by incorrect mental models that miss or misrepresent important aspects of the environment. Such models induce confidence in initial answers, limiting engagement with and learning from feedback. We substantiate these insights in an alternative scenario where individuals involved in a voting problem overlook the importance of being pivotal. (JEL D83, D91)

Concerns around reliability in China's electricity sector have rekindled interest in a traditional solution: building more coal-fired generation. However, over the past decade China's electricity sector has seen significant changes in supply costs, demand patterns, and regulation and markets, with falling costs for renewable and storage generation, "peakier" demand, and the creation of wholesale markets. These changes suggest that traditional approaches to evaluating the economics of different supply options may be outdated. This paper illustrates how a net capacity cost metric - fixed costs minus net market revenues - might be a useful metric for evaluating supply options to meet peak demand growth in China. Using a simplified example with recent resource cost data, the paper illustrates how, with a net capacity cost metric, electricity storage and solar PV may be a more cost-effective option for meeting peak demand growth than coal-fired generation.

A mid-century net zero target creates a challenge for reducing the emissions of emissions-intensive, trade-exposed sectors with high cost mitigation options. These sectors include aluminium, cement, chemicals, iron and steel, lime, pulp and paper and petroleum refining. Available studies agree that decarbonization of these sectors is possible by mid-century if more ambitious policies are implemented soon. Existing carbon pricing policies have had limited impact on the emissions of these sectors because their marginal abatement costs almost always exceed the tax rate or allowance price. But emissions trading systems with free allowance allocations to emissions-intensive, trade-exposed sectors have minimized the adverse economic impacts and associated leakage. Internationally coordinated policies are unlikely, so implementing more ambitious policies creates a risk of leakage. This paper presents policy packages a country can implement to accelerate emission reduction by these sectors with minimal risk of leakage. To comply with international trade law the policy packages differ for producers whose goods compete with imports in the domestic market and producers whose goods are exported. Carbon pricing is a critical component of each package due its ability to minimize the risk of adverse economic impacts on domestic industry, support innovation and generate revenue. The revenue can be used to assist groups adversely impacted by the domestic price and production changes due to carbon pricing and to build public support for the policies.

ABSTRACT: Disinfection byproducts (DBPs), residual compounds formed from the chemical disinfection of drinking water, can cause a host of damaging public health and environmental impacts. This study evaluates the landscape of regulations designed to reduce the occurrence and/or impact of DBPs, focusing on regulations issued by the US states. Drawing on a systematic search of state administrative codes and agency websites, we first identify the presence, absence, and layering of DBP-related regulations. We then evaluate the number and types of policy tools – the specific approaches required by each regulation, such as monitoring requirements, economic incentives, and required treatment technologies – to identify how DBPs are being managed and how states cluster with relatively more and less robust regulatory frameworks. Finally, we evaluate the relationship between the regulatory approach and the frequency of drinking water quality violations for DBP compounds. While most states have at least one DBP-specific regulation, these vary substantially in their comprehensiveness. The most-used policy tools (monitoring, compliance schedules, and reporting) directly reflect federal regulations; few states have adopted innovative tools such as collaboration or financial incentives. We observe no relationship between regulatory efforts and water quality violations, suggesting that current policy implementation may not adequately address the complex risk of DBPs.

Abstract: Communication technology helps protesters organize, but also allows the government to monitor and repress their actions. We study this trade‐off in a model where protesters want to show up at the same time and place, but also want to avoid government forces. If leaders of a movement can send messages observed only by other protesters, they can successfully coordinate on a variety of sites and force the government to spread resources thin, helping the success of the movement. If the government always observes the messages too, protesters can do no better than always going to a “focal site” knowing that the government will send all resources there as well, and thus experience higher levels of repression for the sake of coordinating tactics. Intermediate cases where messages are partially observed generate dynamics where new technologies and media that are relatively known to other protesters and not the government are used until the government can reliably infiltrate them and the protesters move on to a new medium. When some protesters are more informed than others, the model can explain protest tactics observed in recent prominent cases like having smaller “parallel” protests at the same time but different location of the main gathering.

When do political risks lead to divestment from a profitable market? Existing theories argue both that foreign investors may be sensitive to political tensions, but that they may only be sensitive to violent conflict. Using the crucial case of the US–China Trade War, we outline how political risks increased rates of exit among foreign firms while firm entrenchment mitigated these risks. Using a new dataset on all foreign-invested enterprises registered in China between 2017 and 2019, we implement triple interaction models to isolate the impact of increased political risks, investor national origin, and entrenchment on firm exit. Our findings show that heightened political risks during the trade war did increase firm exits by 34%–3% points over the pre-conflict baseline. Tariffs, the targeted effect of the trade war, increase US firm exits by 1% point. Firm exit is determined by the balance of heightened political risks against the availability of firm-level resources to mitigate these risks. These findings reconcile the conflicting expectations of the ‘business as usual’ and ‘follow the flag’ literatures about how firms respond to political risk, highlighting the tremendous collateral damage tariffs can cause in an age of global value chains.

Private renting increasingly comprises a complex ecosystem of actors who assemble housing within the market, and collect rental income and data from tenants, and data on the material assets themselves. Our analysis – at the intersection of rentier and platform capitalism – focuses on landed (material real estate) and technological (digital infrastructure and data) property in Australia’s private rental system. Drawing out relationships between the various actors – landlords, rental property managers and real estate agencies, software developers and providers, property developers and investors – and both their properties and their uses of Proptech (property technology), we show how housing and technology are being leveraged for profit in new ways. In Australia, landed property retains its precedence for established (individual and institutional) landlords, whose interest in Proptech relates to enhancing or value-adding to rental housing assets. For Proptech and institutional real estate players seeking to consolidate both landed and technology property, capturing the tech landscape is increasingly important; indeed, securing control and/or consolidation of technology property is a key motivation for building and/or using Proptech among the largest property developers. Our findings show how rent extraction operates across and between different types and scales of property and market actors, and in new ways that differentiate the figure of the rentier while upholding the dynamics of the rentier model.

ABSTRACT: All‐cash homebuyers account for one‐third of U.S. home purchases between 1980 and 2017. We use multiple data sets and research designs to robustly estimate that mortgaged buyers pay an 11% premium over all‐cash buyers to compensate home sellers for mortgage transaction frictions. A dynamic, representative‐seller model implies only a 3% premium, which would suggest an 8% puzzle. Accounting for heterogeneity in selling conditions explains half of this difference, but a puzzle holds in conditions with high transaction risk. An experimental survey of U.S. homeowners replicates these patterns and suggests that belief distortions can explain the puzzle in these high‐risk states.

Circa 2023, after receiving much hype and investment, two agri-food technologies touted for their world-changing potential, bioengineered animal protein substitutes and vertical (indoor) farms, began to falter economically. Tech sector observers attributed the fall to typical hype cycle dynamics; this paper provides a deeper read. Based on research involving over ninety interviews with agri-food tech sector actors and observation at nearly 100 industry events, we show an unrealized socioecological fix as first conceptualized by Ekers and Prudham. As attempts at preemption, these technologies were able to attract excess capital to an area believed to be in need of fixing, and their backers anticipated and in some cases tried to promote the devaluation of legacy production systems. But the technologies on offer failed to become cost competitive in a timely way since legacy production systems continued to be productive and profitable. It was these new companies that became uncompetitive and overvalued, which in turn turned investments in them into bad ones. Ironically, the agri-food tech sector has eschewed a path which might have made their products competitive, which is social regulation of legacy production systems. Instead they effectively speculated that such systems would implode under their own contradictions.

Abstract: Influential theories doubt that partisan television's audience is sufficiently large, moderate, or isolated from cross‐cutting sources for it to meaningfully influence public opinion. However, limitations of survey‐based television consumption measures leave these questions unresolved. We argue that nonpolitical attributes of partisan channels can attract voters to form habits for watching channels with slants they do not fully share. We report findings from three novel datasets which each link behavioral measures of television consumption to political administrative or survey data. We find that approximately 15% of Americans consume over 8 hours/month of partisan television. Additionally, weak partisans, independents, and outpartisans comprise over half of partisan channels’ audiences. Finally, partisan television consumers largely consume only one partisan channel and remain loyal to it over time, consistent with “echo chambers.” These findings support our argument and suggest partisan television's potential to influence public opinion cannot be dismissed.

Abstract: Health and safety standards offer a convenient means by which governments can claim to be protecting the population, even while pursuing more parochial goals. In the realm of international trade, such standards have most often been studied as a means of veiled protectionism. Yet precisely because health and safety standards create ambiguity about their intent, nations may seek to use them for goals that extend well beyond protecting domestic industry. We theorize that governments will, at times, enforce regulations in ways intended to exact political retribution. To show this, we collect original data on import refusals by Chinese border inspectors between 2011 and 2019. Though ostensibly intended to keep dangerous products out of the hands of Chinese consumers, we demonstrate that import refusals have systematically been used by the Chinese government as a way to punish states that act against China's interest.

Abstract: Water diversions for agriculture reduce ecosystem services provided by saline lakes around the world. Exposed lakebed surfaces are major sources of dust emissions that may exacerbate existing environmental inequities. This paper studies the effects of water diversions and their impacts on particulate pollution arising from reduced inflows to the Salton Sea in California via a spatially explicit particle transport model and changing lakebed exposure. We demonstrate that lakebed dust emissions increased ambient and concentrations and worsened environmental inequalities, with historically disadvantaged communities receiving a disproportionate increase in pollution. Water diversion decisions are often determined by political processes; our findings demonstrate the need for distributional analysis of such decisions to ensure equitable compensation.

While the geography of land use control is shaped by various forces operating at multiple levels, how land use is regulated in the U.S. has been examined with a narrow focus on either intraregional variation (within a single region) or aggregate differences between regions. This article presents an investigation of the geographical distribution of land use control with explicit consideration of both local and regional factors. Using data from two nation-wide surveys and other sources of information, it shows that substantial variation exists not only between regions but also within regions, calling for more attention to what matters and at what level. It is also found that the multilevel determinants of land use regulations are not uniform across regulation types. While low-density zoning is largely determined by local factors with limited interregional variation, a higher level of heterogeneity between regions is detected for impact fees and affordable housing requirements.

Summary: We propose the construction of conditional growth densities under stressed factor scenarios to assess the level of exposure of an economy to small probability but potentially catastrophic economic and/or financial scenarios, which can be either domestic or international. The choice of severe yet plausible stress scenarios is based on the joint probability distribution of the underlying factors driving growth, which are extracted with a multilevel dynamic factor model (DFM) from a wide set of domestic/worldwide and/or macroeconomic/financial variables. All together, we provide a risk management tool that allows for a complete visualization of the dynamics of the growth densities under average scenarios and extreme scenarios. We calculate growth‐in‐stress (GiS) measures, defined as the 5% quantile of the stressed growth densities, and show that GiS is a useful and complementary tool to growth‐at‐risk (GaR) when policymakers wish to carry out a multidimensional scenario analysis. The unprecedented economic shock brought by the COVID‐19 pandemic provides a natural environment to assess the vulnerability of US growth with the proposed methodology.