By: Barthélémy Bonadio, Zhen Huo, Elliot Kang, Andrei A. Levchenko, Nitya Pandalai-Nayar, and Hiroshi Toma

Related Working Paper: Playing with blocs: Quantifying decoupling

As geopolitical tensions rise between major powers, concerns intensify over the economic implications of trade fragmentation. Policymakers worldwide are concerned that the US-China trade war, Brexit, and the breakdown of economic ties between the West and Russia are all signs of a hazardous trend toward “deglobalization.” Yet despite these challenges, global trade remained surprisingly resilient. A recent paper, Bonadio et al. (2024), presents new evidence that during this period, the global trading system reconfigured itself into distinct blocs. The authors find that, contrary to popular belief, this realignment prior to 2024 did not result in significant welfare losses. In contrast, the 2025 US tariff increases and retaliation by trade partners announced as of mid-April, are likely to raise trade barriers both within and across the pre-2024 blocs, potentially reducing welfare.

Figure 1: World Trade / GDP Ratio

The Rise of Trade Blocs

The post-2016 era has been marked by significant policy shifts that potentially threaten international trade, such as the Brexit vote, the US-China trade war, and more recently, Russia’s invasion of Ukraine and subsequent sanctions. These events have sparked concerns about the possible unraveling of globalization.

However, an analysis of global trade data shows that trade relative to economic activity has not decreased since the onset of these shocks (Figure 1). In fact, the ratio of world trade to GDP has partially reversed the downward trend that started following the Global Financial Crisis.

What explains this resilience? As Antràs (2020) and Goldberg and Reed (2023) have documented, we are not experiencing deglobalization but rather fragmentation or decoupling – a reconfiguration of trade links across the globe. As countries involved in trade conflicts disengage from each other, they ramp up trade with other partners. Table 1 confirms this pattern: even as trade between the US and China fell, both economies increased trade with the rest of the world.

Table 1: Change in Trade (2015-2023)

Measuring Bloc Formation and Its Economic Impact

Our research employs a data-driven approach to identify which countries are aligning into which trade blocs. Using bilateral trade data from 2015 to 2023, we identify decoupling patterns and quantify their economic impacts.

We categorize countries into three groups: 1) The US bloc, consisting of countries that experienced reduced trade costs with the US and increased trade costs with China, 2) The China bloc, comprising countries with heightened trade costs with the US and decreased trade costs with China, and 3) Unaligned countries, where trade costs with both the US and China moved in the same direction[PT1] . We identify revealed trade costs from observed trade flows, by running a standard gravity equation. The residual of this equation is then revealed bilateral trade costs, up to the trade elasticity. Our approach, based on observed trade flows, contrasts to alternatives where the bloc structure is imposed on the data using observations like U.N voting patterns.

In our analysis of 187 countries, we find that roughly one-quarter of countries have aligned with the US, another quarter with China, and about half remain unaligned. Russia, Saudi Arabia, Israel, and Hong Kong are clearly aligned with China, while European countries, along with India, Korea, Japan, and Singapore, are part of the US bloc.

Surprising Consequences from Decoupling

Utilizing a quantitative multi-country, multi-sector global production network model, we evaluate the economic effects of observed changes in trade costs. Contrary to the widespread belief that fragmentation reduces welfare, our findings indicate that the median country experienced a marginal increase in real income from trade cost changes between 2015 and 2023, 0.6% respectively.

Thus, the process of decoupling has not yet diminished global GDP . As expected, nonaligned countries see larger income changes (0.8%) compared to those aligned with the US or China, since they do not consistently face increased trade costs with either bloc . However, even countries within the US and China blocs generally experience small gains in real income due to trade cost changes.

This finding stems from the fact that global trade remained quite stable relative to global activity from 2015 to 2023. Lower trade flows between some countries (such as the US and China) were more than compensated by higher trade flows between others. In other words, trade data reveal no significant rise in  trade costs on average, which explains the lack of a negative impact on average real GDP.

Are Countries in the “Right” Blocs?

According to the factual simulation above, most countries are not worse off in the fragmented world, as trade costs decreases within blocs more than offset trade cost increases across blocs. A natural question arises: are countries aligning with blocs based on the benefits arising from international trade? To answer this question, we conduct counterfactual exercises where we shift countries to different blocs and compare their outcomes to the baseline. Our counterfactual analysis examines whether countries would benefit economically from changing bloc alignment. Surprisingly, we find that economic self-interest does not fully account for current bloc formations. The median country in the US bloc would benefit from switching to the China bloc, and vice versa.

This suggests that geopolitical factors, rather than purely economic considerations, are influencing bloc alignment decisions. By investigating the determinants of trade changes, we find that geopolitical considerations indeed increased their role in international trade. After 2015, countries increased trade with their pre-2015 political allies (measured by UN voting patterns) at the expense of non-allies.

Policy Implications

As the global economy continues to fragment, our findings have important implications. Firstly, fragmentation need not necessarily lead to economic losses. In fact, the reconfiguration of trade in the lead up to 2023 benefited marginally most countries by allowing them to redirect trade toward partners with lower costs. Secondly, regional trade integration may offset some negative effects of cross-bloc decoupling, as evidenced by declining trade costs within blocs. Thirdly, when economic and geopolitical incentives diverge, policymakers may face complex trade-offs. Our research shows that many countries are not part of the bloc that would be economically optimal for them.

Conclusion

The reorganization of global trade into blocs results in both winners and losers, but up until 2023, most countries have marginally benefited from the observed changes in trade costs. The increased integration within blocs has compensated for the negative impacts of fragmentation between blocs.

Our research suggests that factors beyond international trade are primarily driving these bloc alignments. This indicates that policymakers should aim to balance economic opportunities with geopolitical considerations in an increasingly divided world, strategically navigating geopolitical realities alongside economic prospects. That said, the 2025 trade war is already raising trade costs within the blocs that formed prior to 2023, and therefore might offset some of the marginal welfare gains this far.

References

Aiyar, Shekhar, Andrea Presbitero, and Michele Ruta. 2023. Geoeconomic Fragmentation: The Economic Risks from a Fractured World Economy. CEPR Press.

Antràs, Pol. 2020. “De-globalisation? Global value chains in the post-COVID-19 age.” NBER Working Paper No. 28115, National Bureau of Economic Research.

Bonadio, Barthélémy, Zhen Huo, Elliot Kang, Andrei A. Levchenko, Nitya Pandalai-Nayar, Hiroshi Toma, and Petia Topalova. 2024. “Playing with blocs: Quantifying decoupling.” Working Paper.

Clayton, Christopher, Matteo Maggiori, and Jesse Schreger. 2023. “A framework for geoeconomics.” NBER Working Paper No. 31852, National Bureau of Economic Research.

Goldberg, Pinelopi K and Tristan Reed. 2023. “Is the global economy deglobalizing? If so, why? And what is next?” Brookings Papers on Economic Activity 2023 (1):347–423.

Gopinath, Gita, Pierre-Olivier Gourinchas, Andrea Presbitero, and Petia Topalova. 2024. “Changing Global Linkages: A New Cold War?” IMF Working Paper 2024-076, International Monetary Fund.

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By Rodrigo Adão (Chicago Booth), Martin Beraja (UC Berkeley Haas), and Nitya Pandalai-Nayar (UT Austin)

As artificial intelligence reshapes the workplace, policymakers and business leaders are confronted with a pivotal question: how quickly will workers adapt to AI-driven changes? To understand what shapes these transition speeds, in a recent paper Adão et al. (2024), we examine two major technological revolutions of the past century: the manufacturing innovations of the early 1900s and the emergence of Information & Communications Technology (ICT) from the 1980s onward. We find that the skill requirements of new technologies critically determine how quickly economies adapt. The adjustment was faster for manufacturing because it required skills more similar to existing occupations, whereas the ICT revolution required different skill sets, resulting in a slower transition. While older workers found it challenging to transition into ICT-intensive occupations, younger generations gradually filled these roles.

Comparing Technological Shifts

Historically, innovations such as steam engines, electricity, and computers have led to fundamental shifts in economic activity. Looking to the future, artificial intelligence and robotics promise similar transformative impacts. When innovations favor specific skills, inequality may rise rapidly (Katz and Murphy, 1992). The reorganization of labor markets might take decades as workers shift roles and newer generations acquire necessary skills (Chari and Hopenhayn, 1991). But do economies adjust at different paces depending on technology? The literature mainly explains common patterns across adjustment episodes rather than examining how specific technologies shape them (Helpman, 1998; Herrendorf et al., 2014).

We present new insights into how exposure to technological innovations affected employment and wages across different occupations in the U.S. during two eras: the manufacturing-enhancing technologies of the early 20th century and the ICT innovations later that century. The contrast between these historical episodes is striking. Panel A of Figure 1 shows that the relative employment growth in more exposed occupations was both faster and stronger overall following the manufacturing innovations of the early 1900s compared to the ICT innovations of the late twentieth century. When assembly lines and electrical machinery transformed manufacturing in the early 20th century, workers rapidly shifted into manufacturing-intensive occupations. Panel B indicates a quick surge in demand for ICT-intensive occupations between 1980 and 1990, with a corresponding labor supply response after 2000.

Figure 1

Panels C and D of Figure 1 depict the employment response for older and younger workers, respectively. The ICT expansion post-1980 was almost solely driven by younger workers, as older workers did not shift to ICT roles—the black dots in Panel C show negligible and statistically insignificant changes for seasoned workers. However, the black dots in Panel D illustrate a significant increase in young workers entering ICT roles over forty years. Overall, the data indicate that the labor supply adjustment to ICT innovations was limited and delayed due to the minimal reallocation of older generation.

The Role of Skill Specificity

What explains these contrasting patterns?  Our research shows that a key factor is how different the required skills are between old and new jobs – what we call “skill specificity.” When new technologies demand skills that differ from those used in existing jobs, the transition tends to be slower and more reliant on new generations entering the workforce.

Figure 2

To investigate this, we develop systematic measures of skill similarity between occupations. Figure 2 depicts two histograms, one for each episode, showing the task distance measure across occupations. The task distance distribution for ICT exposure in the latter episode has more mass on higher distance values than the distribution for manufacturing exposure in the earlier episode. For instance, the analytical and programming skills needed in software development had limited overlap with most existing jobs in 1980. This high skill specificity made it difficult for experienced workers to transition into ICT roles.  In contrast, manufacturing jobs in the early 1900s required skills more similar to existing occupations. A craftsman could more readily adapt his manual and technical abilities to operate new industrial machinery. This lower skill specificity enabled the faster reallocation of incumbent workers.

Dynamics of Adjustment

The degree of skill specificity shapes transition dynamics through two key channels: First, when skills are more specific, experienced workers find it harder to switch to new occupations, even when wages are higher. This creates a direct barrier to workforce reallocation. Second, this limited mobility of incumbent workers leads to higher wage premiums in new occupations. These wage increases provide strong incentives for young workers entering the labor force to invest in new skills. This explains why technological transitions with high skill specificity are driven primarily by new generations. We develop a theoretical model that formalizes these mechanisms and demonstrates how they can quantitatively account for the different adjustment patterns observed in the manufacturing and ICT transitions.

Implications for the AI Revolution

Our findings have important implications for how economies might adapt to artificial intelligence. Early evidence suggests that some AI applications, like large language models, may be relatively easy to use with existing skills. As discussed in Acemoglu et al. (2023), AI could augment rather than replace current capabilities, suggesting a potentially faster adaptation than during the ICT revolution. However, more advanced AI applications may require highly specific skills with limited transferability from existing occupations. If this proves true, the transition could be slow, primarily driven by new workers, similar to the ICT experience. This scenario could exacerbate generational inequality and slow down aggregate productivity gains.

Conclusion

The lessons from past technological revolutions highlight that while the nature of jobs might evolve, the fundamental challenge of equipping workers with relevant skills remains constant. As we face potentially one of history’s most significant technological shifts with the rise of AI, a proactive approach will be essential to ensure all segments of the workforce can benefit. Our findings provide valuable guidance in anticipating and addressing these challenges, enabling a smoother transition into an AI-driven future.

References

Acemoglu, D., Autor, D., & Johnson, S. (2023), “How AI can become pro-worker”, VoxEU.org, 4 October.

Adão, R., Beraja, M., & Pandalai-Nayar, N. (2024). Fast and slow technological transitions. Journal of Political Economy Macroeconomics, 2(2), 183-227.

Chari, V. V. and Hopenhayn, H. (1991). Vintage human capital, growth, and the diffusion of new technology. Journal of Political Economy, 99(6):1142–1165.

Helpman, E. (1998). General purpose technologies and economic growth. MIT press.

Herrendorf, B., Rogerson, R., and Valentinyi, Á. (2014). Growth and structural transformation.  Handbook of economic growth, 2, 855-941.

Katz, L. F. and Murphy, K. M. (1992). Changes in relative wages, 1963–1987: supply and demand factors. The Quarterly Journal of Economics, 107(1):35–78.

For more details, please see the associated working paper.

By Dimitris Georgarakos, Kwang Hwan Kim, Olivier Coibion, Myungkyu Shim, Myunghwan Andrew Lee, Yuriy Gorodnichenko, Geoff Kenny, Seowoo Han, and Michael Weber

Imagine a world where macroeconomic ups and downs don’t disrupt our lives. No recessions that put your job at greater risk, no skyrocketing prices, no financial crises, etc. Sounds ideal, right? But how much would you be willing to sacrifice to make that a reality?

To answer that question, we surveyed consumers across thirteen advanced economies to see how much individuals would trade in terms of their lifetime consumption to eliminate economic volatility (Georgarakos et al. 2025). Here’s what we found.

Key Findings:

• People are willing to give up 5-6% of their lifetime consumption to eliminate economic ups and downs.
• They are also willing to sacrifice around 5% of their lifetime consumption to achieve their preferred inflation levels.
• These figures are much higher than what traditional economic theories suggest.

In other words, while past research has suggested that stabilizing the economy wouldn’t make a big difference in terms of welfare, our study finds that real people think otherwise.

Why Do People Care So Much about Business Cycles?

We found that several factors are particularly important in determining how much people would be willing to pay to avoid business cycles, as illustrated in Figure 1 below.

1. Personal Experience with Macroeconomic Volatility
   • People in countries with historically volatile economies are willing to pay more. In our sample, Germany and the Netherlands are the two countries with the lowest macroeconomic volatility over the last thirty years, and consumers in those countries report that they would sacrifice around 3-4% of their consumption to eliminate business cycles. In the two most volatile countries in our sample, Spain and Greece, consumers would be prepared to sacrifice almost twice as much to eliminate business cycle risk.
2. Cyclicality of Consumption and Income
   • Individuals whose spending and income are more sensitive to changes in the state of the economy feel the effects of downturns more. As a result, we would expect them to be willing to sacrifice more to avoid instability. We find that this is indeed the case. Because of the different types of jobs and assets that people have, there is remarkable variation in the extent to which people are caused, either positively or negatively to business cycle fluctuations. The U.S., for example, is one of the countries in which people’s incomes are the most sensitive to business cycles, and U.S. consumers correspondingly report some of the highest WTP to achieve economic stability across countries.
3. Economic Uncertainty
   • Our willingness to pay to eliminate future business cycles should also depend on how big we think those future cycles are likely to be: those who foresee very little economic volatility in the future should not be willing to pay nearly as much as those who expect to see large swings. We find this to be one of the main determinants of people’s WTP to eliminate business cycles, as shown in the figure below.

Figure 1: Determinants of the Willingness to Pay to Eliminate Business Cycles

There are many other factors that matter as well, but quantitatively, we found these three explanations to be some of the most important when it comes to eliminating business cycles.

What about inflation?

For inflation, we wanted to know how much people would be willing to sacrifice to see inflation reach the ideal level for them. What inflation rate would that be? We found that people wanted to see prices fall overall, and by pretty large amounts. Part of this desire for falling prices was to offset the perceived price increases during the inflation surge: people living in countries where prices went up more following Covid generally wanted to see bigger price declines than those in countries who experienced more moderate inflation.

But just because someone would like to see prices fall doesn’t mean that they would be prepared to sacrifice much to achieve that outcome. So we asked survey participants how much they would be prepared to sacrifice to achieve their preferred inflation target. The answer was again close to 5% of their consumption, on average.

Why so high? One reason is that people want to see large changes in the inflation rate. As shown in the figure below, people living in countries where inflation has been low are willing to pay less to reduce inflation, because they perceive a smaller decline as being necessary.

Figure 2: Historical Inflation and the Willingness to Pay to Reduce Inflation

Another factor that helps explain a high WTP to reduce inflation is the fact that people associate higher inflation with more volatile inflation, and the volatility in inflation is itself perceived as costly as shown in Figure 2.

Finally, a third important reason why people are willing to pay so much to reduce inflation is that they seem to perceive higher inflation as happening when economic times are bad, so reducing inflation also serves to reduce business cycle volatility and vice-versa. Consistent with notion, we find that people who report that they are willing to pay more to eliminate business cycles are also willing to pay more to reduce inflation, as shown in Figure 3. Even though macroeconomists view the long-run level of inflation and economic volatility as largely separate things, this is not how consumers perceive them, leading to a strong correlation between their willingness to pay for either.

Figure 3: WTP to Eliminate Business Cycles vs WTP to Reduce Inflation

Implications for Policymakers

Traditional economic models often assume that people don’t worry much about business cycle volatility because they can “smooth” their consumption over time—saving in good times and spending in bad times. But our study challenges that idea.

Instead, it shows that people strongly prefer a stable economy and are willing to give up a significant portion of their potential income to achieve it. This insight suggests that macroeconomic policies should align more closely with what people actually value, not just what economic models predict.

At the end of the day, economic stability isn’t just an abstract concept—it’s something that affects real lives. Whether it’s job security, price stability, or financial peace of mind, people are willing to pay a surprising amount to avoid uncertainty.

For policymakers, that’s a message worth listening to.

References:

Georgarakos, Dimitris, Kwang Hwang Kim, Olivier Coibion, Myungkyu Kim, Myunghwang Lee, Yuriy Gorodnichenko, Geoff Kenny, Seowoo Han, and Michael Weber, 2025. “How Costly Are Business Cycle Volatility and Inflation? A Vox Populi Approach,” Manuscript.

By Nitya Pandalai-Nayar, Juanma Castro-Vincenzi, Gaurav Khanna, and Nicolas Morales

The views expressed are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Richmond and the Board of Governors.

As climate change intensifies, extreme weather events and unpredictable climate patterns pose growing threats to economies worldwide. The ongoing unseasonal fires in densely populated, economically important areas of Los Angeles highlight the risks faced to firms and workers from their location choices, given the growing prevalence of such climate shocks.[1] These risks are particularly acute for supply chains, where disruptions can ripple through entire industries, stalling production and raising costs. From floods to droughts and fires, localized climate shocks threaten to destabilize the links between firms and their suppliers. How do firms adapt to these challenges? And what are the broader economic implications of their responses? These questions lie at the heart of Castro-Vincenzi, Khanna, Morales and Pandalai-Nayar (2024).

Our paper focuses on India, a country that is highly exposed to climate risks and where regional disparities in climate vulnerability create a natural laboratory for studying firm behavior. By analyzing rich firm-to-firm transaction data alongside regional climate risk indicators, we uncover how businesses adapt their sourcing strategies to mitigate climate risks—and the trade-offs these adaptations entail.

The Challenge: Localized Risks in a Globalized World

Modern supply chains are highly interconnected and efficient, but they are also vulnerable to disruptions. A localized climate shock in one region—such as flooding or a severe drought—can have far-reaching consequences, especially if firms rely heavily on suppliers in the affected area. For firms, the stakes are high: a disrupted supply chain can lead to production delays, missed deadlines, and significant financial losses.

For policymakers, the problem is equally pressing. Climate-induced supply chain disruptions can destabilize local economies, depress wages, and widen regional inequalities. Understanding how firms adapt to these risks is essential for designing policies that foster resilience without exacerbating existing disparities.

Tackling the Problem: Data and Methods

To explore how firms respond to climate risk, we leverage a detailed dataset of firm-to-firm transactions from an Indian state. This dataset provides granular information on sourcing relationships—which suppliers each firm works with and where those suppliers are located. These data are paired with regional climate risk measures, such as the frequency and severity of extreme weather events.

Importantly, we develop a general equilibrium spatial model to simulate how firms make decisions about their supplier networks. The model accounts for key trade-offs:

• Risk Diversification: Firms can mitigate climate risks by diversifying their supplier base geographically, reducing reliance on any single region.
• Cost Trade-offs: Diversification often comes with higher costs, as sourcing from additional suppliers or more distant regions can increase logistical and operational expenses.
• Supplier Behavior: Suppliers in high-risk areas may lower their prices to compensate for the perceived risks, introducing further complexity to firms’ decision-making.

Our model is calibrated using data from 271 regions in India, capturing the interplay between climate risks, supply chain dynamics, and regional economic outcomes.

Key Empirical Findings: How Firms Adapt

Our analysis reveals clear patterns in how firms respond to climate risks. First, we argue that there is Supply Chain Diversification. Firms in regions exposed to high climate risk are more likely to diversify their supply chains, sourcing identical inputs from multiple suppliers spread across different areas. This strategy ensures that a disruption in one region does not halt production entirely.

Second, there are Price Adjustments by Suppliers. Suppliers located in climate-vulnerable areas often reduce their prices to retain buyers. These discounts act as a compensatory mechanism, encouraging firms to continue sourcing from high-risk regions despite the associated vulnerabilities.

Third, we highlight the Trade-offs in Wages and Costs. While diversification reduces the likelihood of supply chain disruptions, it also raises input costs for firms. Higher input costs, in turn, can suppress wage growth in supplier regions. Suppliers in high-risk areas often face lower wages, reflecting the economic consequences of climate vulnerability.

Fourth, we describe the Impact of Floods on Supply Chains. Event study analyses reveal that when suppliers are hit by floods, suppliers see a temporary fall in sales, and downstream buyers see a reduction in purchases. Yet, firms quickly adjust and recover, demonstrating the importance of preemptive resilience strategies.

Figure 1 illustrates the short-term sourcing shifts observed after a flood event, showing changes in supplier relationships over time.

Figure 1: Effects of floods on sales and downstream purchases.

Implications: Resilience and Inequality

Our findings have significant implications for firms, workers, and policymakers. First, when thinking about economic resilience, our results argue that supply chain diversification reduces the risk of large-scale disruptions, contributing to overall economic stability. By spreading risk across multiple regions, firms can better withstand localized shocks. On the other hand, this leads to regional disparities. That is, this adaptation strategy can deepen regional inequalities. Areas prone to frequent climate shocks face declining wages and reduced investment, while more resilient regions maintain or even improve their economic standing.

In the next 25 years, climate related disasters are expected to increase for some regions while dampen for others. In our project, we use the predicted change in flooding, rainfall, and heat levels by year 2050 to understand how different Indian regions will be affected as well as quantifying how much supply chains can amplify these effects. In panel a of Figure 2, we see that that the Gangetic Plain, the North East, and parts of Gujarat and Tamil Nadu, are expected to face more disruptions while parts of Andhra Pradesh are expected to have relatively lower climate risk. The increase in climate risk will have consequences on welfare (measured by real wages) across regions. Welfare on average decreases by 2.01%. There is wide spatial variation, with a range of 3.11pp, and some of the less risky regions see welfare gains. Supply chains contribute to amplify gains and losses created by climate change. Regions getting riskier will get the direct effect of climate change and are expected to face lower demand for their inputs, as demand moves to safer regions.

Figure 2: Expected changes in climate risk and their welfare consequences.

Together, these raise policy challenges. Policymakers must address the trade-offs inherent in these dynamics. For example, incentives to bolster infrastructure in high-risk areas could help reduce supplier vulnerabilities, while targeted wage subsidies might alleviate the economic burden on workers in these regions. Our findings underscore the need for proactive interventions to enhance supply chain resilience while minimizing negative economic consequences. Governments and firms can invest in infrastructure and technologies that reduce the vulnerability of suppliers in high-risk regions, such as flood-resistant facilities or advanced logistics systems. Furthermore, policy measures, such as tax incentives or subsidies for supply chain diversification, could help firms manage the higher costs associated with resilience strategies. Finally, policy makers must address wage inequalities, by targeting policies to support workers in climate-vulnerable regions. Such skill development programs, or income support could mitigate the adverse wage effects identified in our study.

Conclusion

As climate risks such as the Los Angeles wildfires grow, firms are increasingly compelled to rethink their supply chain strategies. Our paper provides a detailed view of how businesses navigate these challenges, offering valuable insights for policymakers and industry leaders alike. While supply chain diversification enhances resilience, it also underscores the uneven economic consequences of climate adaptation.

Bibliography

Castro-Vincenzi, Juanma, Khanna, Gaurav, Morales, Nicolas and Nitya Pandalai-Nayar, 2024. “Weathering the Storm: Supply Chains and Climate Risk,” NBER working paper No. 32218, March.

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[1] Estimates of the losses from property damage due to these fires is upwards of $200 billion.

By Isabelle Salle, Olivier Coibion and Yuriy Gorodnichenko

Summary – The post-pandemic surge saw an entire generation live through its first episode of significant and persistent inflation. In this blog, the authors investigate how people’s memories of past inflation affect their beliefs about future inflation, using a survey and a lab experiment. They find that memories of past inflation can have long-lived effects on individuals’ inflation expectations. Since these expectations shape the tradeoff that policymakers face in trying to stabilize economic conditions, this suggests that the consequences of the recent inflation on policy-making may continue to be felt long after inflation has been tamed.

With inflation recently breaching 10% in many advanced economies for the first time in decades, an entire generation has lived through its first bout of significant and sustained price. How will this experience shape their beliefs in the future? Earlier evidence, surveyed in Malmendier and Wachter (2023), has shown that cataclysmic macroeconomic events can significantly shape the beliefs and economic decisions of a generation, from those Americans going through the Great Depression (Malmendier and Nagel 2016) to Germans who lived through the 1920s hyperinflation (Braggion et al. 2023). The recent inflation spike, however, is of an order of magnitude smaller than these catastrophes. Will its effects therefore rapidly fade, or will it be sufficient to have scarring effects on how people perceive inflation and monetary policy in the future? This is a pivotal question for central banks, considering the imperative to maintain inflation expectations of the public well anchored to their low inflation targets to forestall the entrenchment of higher inflation.

Our recent research (Salle et al. 2023) seeks to answer this question by using both a large-scale household survey of the Dutch population and a laboratory setting with students at the University of Amsterdam during the recent inflation peak in the Netherlands. Our results suggest that the recent rise of inflation may have long-lived effects on people’s inflation expectations, potentially complicating the central banks’ efforts to stabilize inflation for years ahead.

Individual memories are more diverse than common historical experiences

We first asked the lab participants and the survey respondents to describe up to two episodes of rising and decreasing inflation over their lifetime. They were invited to specify the time and location, recall the lowest and highest inflation rates, note the amplitude of the changes, rate their confidence in their memory, identify the perceived cause, and describe the impact on their personal finances. We find that individual memories differ greatly across individuals, even when they belong to the same generation. Panel A of Figure 1 plots the distribution over time of inflation surges and disinflations cited by survey respondents. Overall, participants are more likely to recall rising rather than decreasing inflation, with a large spike around 2021 and 2022, where around forty percent of survey participants recall an inflation surge. A second spike in both inflation and disinflation memories occurs around 2008-2010, when substantial changes in food and commodity prices occurred in the wake of the Great Financial Crisis. A smaller spike in recollections happens around 1980, when inflation in the Netherlands was high and volatile, leading households to recall both the inflation surge and the subsequent disinflation. Another example of this variation is the reported causes of these changes in inflation (see, respectively, Panels B and C of Figure 1). Episodes in the 1970s and from the 2010s were more likely to be attributed to input and energy cost changes than during the 80s-00s. Disinflation in the 1990s is attributed by many to currency changes, consistent with the large appreciation of the Dutch guilder around this time. For the 1980s, many do not remember the reason for the disinflation but about thirty-five percent of those who do attribute the disinflation to policy or lower demand for goods, with another fifteen percent emphasizing energy and input price changes. We also find a salient asymmetry when it comes to the effect of these episodes on household finance: while most respondents report that inflation surges made them worse off, there is little agreement about whether disinflations made them better off.

This range of recalled memories clearly indicates that individual experiences cannot be reduced to the past economic events that they have lived through together. How do these personal memories affect people’s beliefs and attitude towards inflation beyond their common historical experience?

Individual memories affect beliefs beyond common historical experiences

After their inflation memories, we elicited the respondents’ views about inflation up to 2025 along with a range of other personal opinions and preferences. We employed econometric techniques to link detailed lifetime memories with inflation outlooks and particularly policy-relevant beliefs, including trust in the central bank and awareness of its primary goal. Our comprehensive questionnaire controls for numerous potential confounders, and we incorporate historical inflation data to separate the influence of personal memories from collective experience.

We find that inflation and disinflation memories are correlated with inflation forecasts. Recalling past inflationary episodes is associated with a higher inflation outlook and more confidence in these outlooks. By contrast, the larger are the disinflations recalled, the lower are the inflation expectations. Interestingly, the largest effect on expectations is observed for disinflations that people attribute to policy. Recalling past disinflations is also associated with more uncertainty regarding future inflation, reflecting the fact that these people envision a broader set of possible future inflation outcomes. Additionally, we report clear evidence that inflation memories are closely tied to trust in the ECB. Recalling past increases in inflation is associated with less trust while recalling disinflationary episodes with more trust. We also find that memories of both inflation surges and disinflations are associated with a deeper knowledge about instruments and objectives of monetary policy.

An important policy-relevant take-away from this analysis is that those who remember prior disinflations are more open to the possibility of future inflation declining sharply, such that they have lower inflation forecasts on average, consistent with more trust that the ECB will be successful in bringing inflation back to its target. Is it merely an association or do various inflation memories cause different inflation expectations?  If so, can we artificially recreate lifetime memories of inflation that can also shift people’s expectations?

Creating pseudo-life experiences through games treatments

After eliciting their inflation expectations, some survey and lab participants were randomly chosen to play a game that consisted in repeatedly predicting next year’s inflation while incrementally observing inflation in the previous years. These “treated” individuals played either with data from a rising inflation episode (over 1967-1975), a decreasing inflation episode (over 1980-1988) or a flat inflation episode (over 2006-2014), while the rest of the respondents skipped the game as they constitute the “control” group. We then elicited once more inflation expectations to explore how the game treatments may have affected these expectations, while accounting for their inflation priors and retrieved memories.

We find that playing the forecasting games can have powerful effects on expectations, both in the lab and in the survey, and these effects largely mirror those of inflation memories: playing through a period of rising inflation raises inflation expectations, whereas playing through an episode of flat or falling inflation tends to reduce inflation expectations. This latter treatment effect is larger for respondents who did not report any inflation memory or who declared relatively higher prior beliefs about inflation. Interestingly, in a follow-up survey conducted months later, individuals were more likely to recall both inflation surges and disinflations if they had played a game with decreasing inflation in the first wave, with the effect of disinflations being particularly strong for young survey participants. Furthermore, consistent with the idea that forecasting games create new memories, we find that the effects of the game experience on inflation expectations persist in the follow-up survey, even after accounting for individuals’ prior memories.

Conclusion

Our results suggest that inflation memories at least partly cause inflation expectations. Therefore, the recent inflation surge could persistently affect household inflation expectations. How it does so, however, will depend on whether individuals’ memories focus more on the inflation increase or the ongoing disinflation, as the two affect expectations quite differently. Policy communication could play a role in shaping the future narrative that individuals will recall about the current inflation dynamics. Delving further into how memories are formed and persist would allow for a better understanding of how a specific episode like the recent inflation surge is likely to affect economic expectations and the conduct of monetary policy in subsequent years. Graeber, Roth and Zimmermann (2023) provide novel evidence on the formation of memories, for example.

Our work also helps bridge the gap between the survey and the lab experimental literature: while lab subjects are young college students and do not share the much longer life experiences of the broader population, our results suggest that game experience can partially recreate that life experience and help make them more representative of the broader population. Because laboratory experiments have many advantages in other respects, the ability to make their participants more diverse could help expand the scope of questions that can be fruitfully addressed in the lab.    

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