metadata: authors: 0: author: Grover,Arti Goswami
1: author: Kahn,Matthew Edwin
count: World
docna: 0: docna: Firm Adaptation to Climate Risk in the
            Developing World
docty: Policy Research Working Paper
theme: Data production, accessibility and use,Entrepreneurship,Data Development and Capacity Building,Economic Policy,Green Growth,Economic Growth and Planning,Environment and Natural Resource Management,Enterprise Development,Private Sector Development,Public Sector Management,Climate change,Business Enabling Environment
abstracts: cdata!: How firms in the developing world adapt
            to changes in weather extremes will play a key role in
            determining their nation&#x2019;s economic growth. This
            survey of the recent microeconomics adaptation literature
            suggests that although firm competitiveness is negatively
            affected by weather events, firms may bounce back better
            under certain conditions. The adaptation and resilience of
            firms to climate change depend on their capabilities, the
            available information on risks, and the depth of insurance
            and financial markets. As real-time weather forecasting
            improves, firms are better informed about these risks and
            this affects their decisions regarding their location,
            production, and configuration of supply chains. A
            firm&#x2019;s resilience also depends on the quality of
            public investment in infrastructure and the social safety
            net. Understanding that market frictions can slow the pace
            of adaptation, the paper concludes with some insights on the
            options available to policy makers.
display_title: Firm Adaptation to Climate Risk in
            the Developing World
listing_relative_url: /research/2024/06/34338314/firm-adaptation-climate-risk-developing-world
topicv3: Economic Shocks and Vulnerability m1326506 702,Innovation, Technology and
            Entrepreneurship m1327691 376,Climate Change Adaptation m1327767 574,Firm Dynamics and Productivity Growth
            m1504195 2864
publishtoextweb_dt: 2024-06-10T00:00:00Z
dois: 10.1596/1813-9450-10797
no_of_pages: 35
author_keys: 0: author_key: 1066720
1: author_key: 1102566
model_extractions: Policy Research Working Paper 10797 Firm Adaptation to Climate Risk in the Developing World _Arti Grover Matthew E. Kahn_ International Finance Corporation June 2024
Policy Research Working Paper 10797

# **Abstract**

How firms in the developing world adapt to changes in weather extremes will play a key role in determining their nation’s economic growth. This survey of the recent microeconomics adaptation literature suggests that although firm competitiveness is negatively affected by weather events, firms may bounce back better under certain conditions. The adaptation and resilience of firms to climate change depend on their capabilities, the available information on risks, and the depth of insurance and financial markets.

As real-time weather forecasting improves, firms are better informed about these risks and this affects their decisions regarding their location, production, and configuration of supply chains. A firm’s resilience also depends on the quality of public investment in infrastructure and the social safety net. Understanding that market frictions can slow the pace of adaptation, the paper concludes with some insights on the options available to policy makers.

This paper is a product of the International Finance Corporation. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at agrover1@ifc.org and kahnme@usc.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Firm Adaptation to Climate Risk in the Developing World<sup>_†_</sup>

Arti Grover<sup>_‡_</sup> and Matthew E. Kahn<sup>§</sup>

**Keywords:** Climate Change; Firms; Resilience; Adaptation **JEL classification** D22, L25, 038, Q54

> _†_ The authors are immensely grateful to Arlan Brucal for his work in the early phases of this project. The authors also thank Yewon Choi for her research support and Somik Lall, Denis Medvedev and Forhad Shilpi for their thoughtful comments and suggestions. The views expressed in this paper are solely those of the author and do not necessarily reflect those of the World Bank, its Executive Directors, or the countries they represent.

> _‡_ The World Bank Group; Corresponding author, email: agrover1@ifc.org

> §University of Southern California; email: kahnme@usc.edu
# **1 Introduction**

Firms in developing nations face extreme weather including natural disasters, extreme heat, and drought. If climate change increases the likelihood and severity of these events, then firms have an increasing incentive to invest in various adaptation strategies. These strategies include – where a firm locates, how it configures its supply chains, and how much it invests in the physical workplace to harden it to withstand anticipated shocks. Each of these strategies feature costs that the firm or the nation will bear.

We survey the emerging microeconomics literature focused on firm adaptation to climate change. We explore the role of firm heterogeneity, weather dynamics and expectations about these dynamics, and government policy that together determine how different firms are affected by weather shocks. Climate change is costly for firms if it lowers their profits. Firms will anticipate this ”treatment effect” caused by climate change and will take proactive steps to offset this damage if the costs of adapting are lower than the expected present discounted value of benefits of making these offsetting investments. If firms can successfully adapt to rising weather risks, then this will raise overall productivity and help developing countries lower their poverty rates despite the harsher conditions these nations face going forward (Hallegatte, 2016; Hallegatte and Rozenberg, 2017).

Our survey melds several strands of literature. For example, the economic geography literature has emphasized the costs of “bad geography” for productivity and economic development Gallup et al. (1999). The weather risks that a firm faces are location specific. Many developing nations are located in regions that face greater _natural disaster_ risks such as typhoons and are exposed to _extreme_ heat and precipitation (Bakkensen and Barrage, 2018; Hsiang and Jina, 2014). The _risks and uncertainty_ posed by extreme weather to firms in the developing world are amplified by _weak governance_ capacity (Acemoglu and Robinson, 2013; Porta et al., 2008).

One important implication of weak governance is unreliable local infrastructure. If roads flood and if the electricity grid breaks down, then these firms will be even less productive as supply chains are immediately disrupted by shocks (Allcott et al., 2016; Chong et al., 2014). Developing countries have limited resources - both human and financial - to undertake investments in fixing such disruptions. We explore cases where private and public resilience _policies and investments_ are substitutes and cases where they are complements.

Figure 1 illustrates the key themes explored in our survey on firms in the context of climate change adaptation.

1
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of weather-related risks and uncertainty are significant and, at times, larger than the actual event’s realization. Firms with greater exposure to climate risks have reduced valuation of assets such as plants and property and increased operating costs pertaining to insurance costs. They also face difficulty in accessing finance even at higher interest rates relative to firms with lower vulnerability. These effects are significantly greater for smaller firms, especially in high-risk sectors and countries and those with weaker capacity to adapt to and mitigate the consequences of climate change. Several market frictions, especially those pertaining to information, insurance markets, and distortions limiting reallocation of resources can affect adaptation and resilience to climate change.

_Finally_ , policymakers have access to a growing menu of strategies to encourage a firm’s adaptive investment. These include; (i) encouraging risk taking through development of insurance markets; (ii) improving information flows on risks and insurance; (iii) supporting upgrading of managerial capabilities; and (iv) financial support for rebuilding firms. Policymakers will be more likely to achieve their adaptation goals if they anticipate how optimizing firms will respond to the evolving ”rules of the game”.

The paper is organized as follows. In Section 2, we sketch out the microeconomics of how a profit maximizing firm would respond to expected changes in climate. If firms have perfect foresight concerning weather patterns, how would they configure their activities to maximize profits? We explore key aspects of firm heterogeneity in determining adaptive capacity. In Section 3 we then pivot and explore how weather risk and uncertainty affects the firm’s choices and outcomes. Section 4 explores the interplay between government policies and how firms respond to the implicit incentives they face and thereafter introduce a framework for evaluating the effectiveness of government interventions. This section also presents the options available to policymakers in the face of market frictions. Section 5 discusses empirical benchmarking of adaptation progress, while Section 6 ends with concluding remarks and directions for future research.

# **2 Adaptive Capacity in the Perfect Foresight Benchmark Case**

Firms can respond to climate change risks by making adjustments on three possible dimensions: sectoral, structural and spatial. _Sectoral_ adaptation includes diversifying into additional product lines within the same sector (Pelli et al., 2020), by investing in innovation (Gasbarro et al., 2016), labor saving technologies or by adopting of establishment-level 3
climate controls (Somanathan et al., 2021). _Structural_ shifts imply a drastic switch in the sector, for instance, by transitioning out of agribusiness sector to those that are less exposed to climate risks (Colmer, 2021) through (gradual or sudden) reallocation of factors of production (Zhang et al., 2018). _Spatial_ transformation takes place by physically relocating (Linnenluecke et al., 2011; Khanna et al., 2021) or diversifying production across locations (Pankratz and Schiller, 2021). Firms can also adapt by establishing financial links to other regions which can act as an effective spatial risk sharing tool (Albert et al., 2021).

# **2.1 Sectoral and Structural Dimensions of Adaptation**

Consider a firm that has already chosen a production location close to final consumers. Suppose that the firm has perfect foresight concerning weather shocks. This firm anticipates when it will be very hot and when it will be very rainy or polluted. The firm is endowed with a production function and the owner of the firm understands how the firm’s production is affected by each possible weather realization. Consider a case where the omniscient manager knows that over the next two weeks the weather will be awful. This firm can adapt by cancelling production during that time or by investing in protective gear to protect the production facility. The firm could undertake the less drastic approach to adaption through _within sector shifts_ and accelerate its production before the onset of terrible weather and store the production in a dry shed. In these cases, the marginal cost of adaptation to the firm is the cost of renting the shed and paying the workers overtime for their long days during the dry time. If the firm cancels work and does not pay the workers for those lost days, then these workers bear the cost of the weather induced downtime. For those families who do not have buffer savings, they can suffer large consumption drops if the earner’s income plummets due to horrible weather.

The perfect foresight case highlights the importance of adjustment costs. A shock is more costly when a firm is unprepared. A firm’s ability to make sectoral shifts, that is, pivot and substitute how it produces, when it produces plays a key role in determining the costs it suffers from extreme weather. The losses from a shock may differ at the firm level versus the industry level. If one firm fails to prepare for an anticipated weather event and cannot produce output that day then this creates an opportunity for a firm that is better prepared. In this sense, the industrial organization of a sector exposed to climate change plays a crucial role. A local monopolist will suffer a lower long term profit loss from a short run disruption in output because consumers have few alternatives to switch to.

Heterogeneous firms differ along a number of dimensions that determine their ability to 4
adapt to extreme weather events.

# **Firm attributes and adaptive capacity**

# _Firm size_

Consistent with the Schumpeterian ‘cleansing hypothesis’ (Schumpeter et al., 1939), evidence from the Hurricane Katrina, which hit the United States in 2005, reveals that firms with larger _initial size and productivity_ had a lower impact on their survival and revenue and also recovered more quickly (Basker and Miranda, 2018). Nevertheless, evidence also showed that the advantages offered by external firm attributes such as firm size dissipate over time.<sup>1</sup> Firm size proxies for access to capital markets, better management and technical capabilities and hence heightened productivity and profitability. For instance, a firm’s scale of operations will affect the profitability of adopting various adaptation strategies. Many adaptation strategies are lumpy such that they require bearing a fixed cost. Such lumpy investments feature scale economies so that larger firms will be more likely to adopt these measures Graff Zivin et al. (2018). Firms that do not have access to capital will be less likely to have access to lumpy adaptation strategies. Workers at these firms will face more risk and will demand to be paid higher wages.

# _Manager quality_

Larger and more productive firms have better financial and managerial capabilities Bloom et al. (2010). For instance, European firms with more _intangibles assets_ (e.g., patents and trademarks) experienced higher post-flooding employment growth and lower productivity decline (Leiter et al., 2009). The most vulnerable firms are less likely to engage in adaptation measures perhaps due to lack of _managerial capability_ to explore alternative business opportunities ( _structural adjustments_ ) or rational inattention of managers to productivityenhancing climate change ( _sectoral_ ) adaptations. In Uganda, firms with higher ability managers are more likely to adapt to pollution by protecting their workers through the provision of equipment and flexibility in work schedule, that is via _within sector adaptation_ mechanisms rather than avoiding locating in well-connected polluted areas ( _spatial adjustments_ ) (Bassi et al., 2021).

# _Firm ownership structure_

‘Footloose’ multinationals or foreign-owned plants are more likely to exit the market

> 1The authors studied 12,300 geocoded establishments in Mississippi from the Census Bureau’s Longitudinal Business Database (LBD), including over 1,500 businesses in four counties that experienced significant storm damage as determined by the Federal Emergency Management Administration (FEMA).

5
( _spatial adjustments_ ) after floods because these events destroy local suppliers and raise the cost of sourcing local inputs (Kato and Okubo, 2018). Nevertheless, these firms are also larger and better managed and hence, conceptually, they could be more resilient. There are not many studies that have considered this distinction in a systematic manner.

By comparison, single-person firms appear to be more resilient to crises. They are more likely to reopen in the first 3 months after the shock partly because (i) employment is flexible with family participating in business operations (ii) absence of other means of income opportunities for the owner and family members; and (iii) ability to react faster when making such decisions than larger firms. This was substantiated in a study of 673 Mississippi establishments that were tracked weekly in the year following Hurricane Katrina, (LeSage et al., 2011). Nevertheless, given that these firms are, by definition, small they are the hardest hit by the shock. This could be because the firms that disappear are not the same as those that emerge after the crisis.

# _Informality_

Poor people who run informal firms are the most likely to set up production in risky places because of the low demand for locating on such land parcels. Clear tradeoffs emerge between encouraging entrepreneurship while protecting people from engaging in excessive risk taking. Lowering the costs of entry for firms fosters competition and can contribute to achieving upward income mobility for those entrepreneurs who succeed. At the same time, informal production areas are most likely to emerge in areas exposed to flood risk and mudslide risk.

With the ever improving access to administrative data, we foresee that researchers in more and more developing countries will be able to recreate firm demographic longitudinal data to observe firms being born and closing. Empirical benchmarks of a failure to adapt include firm closings, new formal business formation, firm growth and a lower average product of labor in areas facing more weather shocks. Evidence from India using data on both formal and informal firms suggests that floods led to significant decline in employment in the formal sector, especially in the least productive establishments, and towards informal household-run enterprises (Hossain, 2020). This is consistent with the view that such reallocation results from survival strategy of workers who ended up unemployed and suffer from labor market contraction in the formal sector (Tybout, 2000; La Porta and Shleifer, 2014). Given the large productivity gap across formal and informal sectors, such climate-induced reallocation generates a significant reduction in aggregate productivity.

# **Industry dynamics and adaptive capacity**

6
## _Inherent disaster resilience_

Some sectors are more vulnerable to climate change than others. For instance, evidence on the impact of the 1959 Ise Bay Typhoon in Nagoya City, Japan suggests that firms in retail and wholesale have a lower probability of surviving typhoon-induced disruptions, compared to those involved in manufacturing and construction (Okubo and Strobl, 2021). This sectoral variation can stem from differences in disaster resilience. Retailers suffer due to broken production links and damaged storage facilities, while construction sector generally benefits from increased demand and new opportunities associated with the disaster recovery efforts. Uneven access to financial aid and assistance (e.g., manufacturing may receive more aid) and other government programs (including insurance payments) also explains why some firms replace old capital and invest in newer more productive capital (Noth and Rehbein, 2019) while others do not.

## _Reallocation across sectors_

The varying impact of climate-related disaster across industries and sectors yield an empirical prediction that labor and capital will flow to those sectors with a higher rate of return. In India, evidence from storms during the period 1995-2006 suggests that the impact on the formal and listed firms can be transmitted through reallocation within- and between-industries (Pelli et al., 2020) because capital destruction leads to a reallocation of sales towards better performing firms and industries. That is, shocks trigger reallocation _within sector, structural shifts or spatial_ adjustments. An optimistic twist on the creative destruction hypothesis is that firms that survive extreme events will ”build back better” (Leiter et al., 2009; Coelli and Manasse, 2014; Noth and Rehbein, 2019; Pelli et al., 2020).

# **2.2 Locational Choice as an Adaptation Response**

In the aftermath of major natural disasters, people move to places offering greater economic opportunities. Some examples include Hurricane Katrina’s impact on New Orleans and the 1930s Dust Bowl’s impact on Kansas where longitudinal research has documented that many people who were forced to move away from these shocked places prospered later on as they moved to more vibrant local labor markets (Deryugina et al., 2018; Hornbeck, 2012).

The economic geography literature emphasizes a type of ”chicken and egg” dynamic concerning whether people move to places where the jobs are available or do firms locate in places where people cluster. In choosing their location, firms tradeoff balancing the agglomeration benefits derived from sharing, matching and learning on the one hand, versus 7
the costs they must pay for land and labor and the risks they will face at a given location. Taking the hedonic land and labor market pricing gradients as given, firms will chose a profit maximizing location. New firms will take into account the competitive effects of whether they want to locate close to or far from incumbent firms.

Firms are not tied to any one location on the map. If certain areas experience repeated horrible weather, then rents of such land should decline and the most productive firms should be less likely to locate there (Rentschler et al., 2023). Such areas would likely be populated by less productive firms. In this sense, the equilibrium hedonic land price gradient sends signals about land quality.

Given that it is costly for a firm to migrate, firms have strong incentives to research the risks and challenges that each location faces. In the United States, there has been a growth in climate science information firms that provide location specific “climate report cards” for different geographic areas regarding their flood and fire risk. Such sufficient statistics are based on academic models and recent geocoded natural disaster realization data. In the short run, we expect that if such tailored risk report cards are introduced in the developing world this will accelerate the learning process and that geographic site selection will be better informed about the recent shocks and the expected future shocks (Burlig et al., 2024).

Migration in response to climate change induces reallocation of activity. For example, weather change induced migration of labor leads to reallocation of factors across space (Cai et al., 2016; Cattaneo and Peri, 2016; Mueller et al., 2014), as evidenced among localities in rural India that experienced higher-than-normal local rainfall. Such migration shifted labor towards non-agricultural non-tradable sectors (e.g., construction, retail, and education sectors) and consequentially increased productivity in the agricultural sector and led to an increased demand for non-tradables (Emerick, 2018). Higher temperature in India also led to reallocation of agricultural employment towards local manufacturing and services (Colmer, 2021). Such cross-sectoral labor movements are bounded within districts due to severe liquidity constraints (Cattaneo and Peri, 2016).

Firms differ with respect to where they locate their supply chains. If one firm chooses a set of suppliers who are located in riskier locations (because these areas are located in areas facing greater shocks), then this firm can benefit in the short run from having lower costs. When disasters strike in the risky areas, other firms who have ”played it safe” by sourcing their supply chains in safer areas have an edge. One recent study used a structural discrete choice model to study how car manufacturers respond to the risks posed by local natural disaster on supply chains (Castro-Vincenzi, 2022). Severe floods close to a car assembly site is associated with an economically significant reduction in subsequent production at that 8
plant. Multi-establishment firms respond to the shock by increasing their production at other establishments. Related recent research based on micro data from India shows that flood events disrupt local supply chains and firms respond by diversifying across locations which has significant distributional consequences (Castro-Vincenzi et al., 2024).

Production networks are formed through a complex web of contracts between firms and these firms use public infrastructure to trade goods. During times of extreme weather, public goods such as logistics infrastructure that facilitate production networks and trade in goods faces disruptions due to the “Tragedy of the Commons” problem. In addition to direct effects, firms in unaffected locations are indirectly impacted through production networks. For example, suppliers and buyers suffer from reduced revenues as a result of suppliers’ exposure to extreme heat and flooding incidents. In Tanzania, floods destroyed the fragile supply chain infrastructure and led to a disruption in the access of necessary inputs for firms even in unflooded areas. This caused 30-50% of all supply and delivery delays in the region and a drop in sales. Such disruptions in production networks transcends national borders as evidenced in a storm that affected not only Chinese plants’ performance but also reduced their foreign transactions (Elliott et al., 2019). Japanese affiliates in Thailand experienced a drop in sales following 2011 floods, while imports from China and Japan increased (Hayakawa et al., 2015). Hurricanes-induced job losses occurring within multiplant firms were propagated across undisturbed distant regions in the US (Seetharam, 2018). For every job loss of the firm in an affected county, 0.19-0.25 jobs are also lost across other sites in unaffected regions.

Firms that buy key inputs can adapt to climate change risk by diversifying away from weather-stricken suppliers (Pankratz and Schiller, 2021). Firms may also adapt by establishing financial links to other regions; viewed as an effective risk sharing and consumption smoothing tool (Albert et al., 2021). Such adjustments also occur in an international context, as illustrated in a study where the exports of poor countries to the United States decreased by 2.0-5.7 percentage points for each<sup>_◦_</sup> C rise in temperature (Jones and Olken, 2010).<sup>2</sup> In sum, the volatility in domestic production translates to greater variation in trade, with the effects being larger for poorer countries (Dell et al., 2009).

As more firms seek out ”climate resilient” supply chains, areas seeking to attract footloose firms will have a greater incentive to invest in local resilience infrastructure because this becomes an economic development strategy. Urban and regional economic studies of local agglomeration have documented how by attracting a major factory, a location can then

> 2In China, Li et al. (2015) suggest a negative effect of rising temperatures on exports ranging from 8.8% to 12.6%.

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attract other firms to co-locate nearby to reduce transportation costs in shipping (Greenstone et al., 2010). Developing world agglomerations are now taking root. They will be more likely _materialize_ if the location is _safer_ . The empirical question is whether safety is produced by exogenous features or can it be produced through strategic investments in urban planning and infrastructure. Infrastructure in developing countries are often more vulnerable to climate hazards, which, if destroyed, can delay recovery and increase coping costs (Rentschler et al., 2019). This may perhaps explain why firms in advanced economies of Europe experienced the _build back effects_ (Leiter et al., 2009; Coelli and Manasse, 2014; Noth and Rehbein, 2019) compared to those in developing countries such as India (Hossain, 2020) and Tanzania (Rentschler et al., 2021) where the impacts of similar natural hazards are devastating and persistent (Rentschler et al., 2021).

# **2.3 Adaptation to Sharp Climate Shocks versus Gradual Changes**

Not all climate-related hazards have immediate impacts. Gradual changes such as increased temperature and precipitation, and accelerated sea level rise, are not extreme weather changes by themselves, however, their cumulative impact overtime can be significant (Seneviratne et al., 2012).

Extreme events such as storms and induced floods can have large negative effects on firms’ output, employment, operational cost, demand and productivity. These consequences are more likely to take place if such shocks are unexpected or if the risks are known but firms do not have the managerial or financial capacity to self-protect against the anticipated shocks. Evidence from tropical storms in India during the period 1995-2006 show an immediate decline in sales and physical assets by 99% and 75%, respectively, among manufacturing firms, compared to their pre-shock levels (Pelli et al., 2020). In China, typhoons cost an annual damage of about US$3.2 billion (2017 prices) or about 1 percent of average turnover of Chinese plants (Elliott et al., 2019). In Viet Nam, the reduction in firm income per worker due to typhoons is around 33% (Vu and Noy, 2018). For gradual changes, evidence suggests that heat stress reduces firm output, efficiency and profits. The productivity of large garment manufacturers operating in Bangalore, India, starts to decline by as much as 2 efficiency points (i.e., realized output versus target output) for every<sup>_◦_</sup> C increase in temperature after reaching an equivalent outdoor temperature level of 27 _−_ 28<sup>_◦_</sup> C (Adhvaryu et al., 2020). In China, manufacturing plants experienced a reduction in output by 45% in days when temperature is above 32<sup>_◦_</sup> compared to days when temperature is between 10<sup>_◦_</sup> C and 15<sup>_◦_</sup> (Zhang et al., 2018). More frequent days with heat stress also resulted in significant 10
production losses in automobile industry in the US by as much as 8% (Cachon et al., 2012).

A ”silver lining” caused by extreme events is to create the possibility of a type of Schumpeterian creative destruction (Schumpeter et al., 1939). If firms choose to rebuild after a disaster in the same location and if they now update their subjective assessment that the same type of disaster could occur again in the future, then they have stronger incentives to ”build back better” so that the future shock causes less damage to the firm. This optimistic adaptation hypothesis offers an empirical prediction that merits more research in the developing world.

Every firm faces a signal extraction problem as it tries to infer how the weather distribution it faces is changing over time. The 1970s rational expectations literature emphasized that “new news” influences investment decisions. If an event is anticipated, then forward looking decision makers will have already incorporated this expectation into their plans. Extreme weather such as a hurricanes during its season or extreme heat days during summer months are arguably much more difficult to anticipate than gradual changes in temperature.

Gradual changes in local weather induced by climate change also pose a threat to firms in the developing world. In India, the increased ambient temperature is not only associated with productivity declines but also with increases in _worker absenteeism_ (reduced labor supply) (Somanathan et al., 2021). Thermal stress can lead to workers’ degradation of both _cognitive and psychomotor task_ performance (Hancock et al., 2007), leading to reduced productivity (Niemel ̈a et al., 2002; Tham, 2004). Temperature changes affect firms in both developed and developing country-settings, reducing time allocated for work (Graff Zivin and Neidell, 2014; Garg et al., 2020; Neidell et al., 2021). These effects are generally nonlinear; that is, marginal changes in firm performance at lower levels of temperature but significant declines at high temperatures (Hancock et al., 2007; Zhang et al., 2018; Adhvaryu et al., 2020).

Changes in weather induces reallocation of activity due to greater demand for certain products (e.g., air conditioners, refrigerators) or in response to supply shortages. In India for example, a rise in temperature has been found to have reduced agricultural productivity, which also dampens demand for non-farm goods and services (Colmer, 2021). On the financial side, exposure to sea-level rise (SLR) is associated increased credit spread or exposure premium due to rising uncertainty (Goldsmith-Pinkham et al., 2021).

Overall, the effects of climate change, gradual or extreme, are heterogeneous as they depend on firm attributes such as; ownership structure, sector, spatial location and framework conditions. For example, some sectors such as health care and energy, oil, and gas did not experience a negative effect of increased temperature in the United States (Hugon and Law, 11
2019), “highly exposed sectors” were more affected partly due to reduced hours of work (Graff Zivin and Neidell, 2014; Garg et al., 2020; Neidell et al., 2021; Zhang et al., 2018).<sup>3</sup> Location is critical in understanding the effect of climate change which not only determines the risk and exposure but also the cost of securing finances due to exposure (Hauer et al., 2021). Sectors with greater linkages to agriculture (De Souza et al., 2015; Crick et al., 2018) are often more exposed to gradual changes in climate. This is not to understate the importance of sectoral attributes when it comes to recovery from extreme shocks and disaster resilience. For instance, retailers suffer due to broken production links and damaged storage facilities, while construction sector generally benefits from increased demand and new opportunities associated with the disaster recovery efforts. Uneven access to financial aid and assistance (e.g., manufacturing may receive more aid) and other government programs (including insurance payments) also explains why some firms replace old capital and invest in newer more productive capital (Noth and Rehbein, 2019) while others do not.

# **3 Climate Change Induced Uncertainty**

Climate change science remains an active field of inquiry with many unsettled issues pertaining to the timing and the possible extent of shifts in weather distributions. Put simply, what will be the empirical distribution of July temperature highs for each city around the world in the year 2060? Within India what will be the probability distribution of rainfall in the years 2030, 2035, 2040? Will there be another flood in Brazil or Dubai? This section describes firms’ responses and adaptation strategies in the face of such climate risks and the uncertainty in the changes in weather conditions.

## **3.1 Adapting to the ”Known” Risks of Climate Change**

Scientific progress plays a crucial role in shaping expert expectations about emerging risks. The social media platforms, non-profits and the news media educates the public about these emerging risks. The challenge here is the signal extraction problem. Given the considerable uncertainty associated with both climate science predictions concerning the timing and the severity of likely disaster risks, firm managers may have trouble forming updated beliefs about the short run risks they face. Information about emerging risks plays a central role in helping firms to adapt to expected shifts in the weather Burlig et al. (2024).

> 3The National Institute for Occupational Safety and Health (NIOSH) includes the following as highly exposed industries: agriculture, forestry, fishing, and hunting; construction; mining; and transportation and utilities; and manufacturing.

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Expectations concerning place-based climate risks influences economic geographic outcomes. For example, in the United States the risk of floods negatively affects firm entry, employment and output, and is associated with a reduction in aggregate output, of which only 20% is attributed to direct damages while the remaining 80% stems from expectation effects (Jia et al., 2022). In a recent study, Cevik and Miryugin (2022) document the impact of climate change vulnerability on corporate performance using a large panel dataset of more than 3.3 million non-financial firms from 24 developing countries over the period 1997–2019. Their results suggest that firms operating in countries with greater exposure to climate risks have difficulty in accessing debt financing even at higher interest rates, while being less productive and profitable relative to firms in countries with lower vulnerability. These effects are significantly greater for smaller firms, especially in high-risk sectors and countries, and those with weaker capacity to adapt to and mitigate the consequences of climate change. Their results are in line with previous findings suggesting the positive relationship between climate risks and cost of debt, which can result in a decline in firms’ leverage (Ginglinger and Moreau, 2019).

Such exposure to climate risks are detrimental to the firm’s financial position. For instance, while actual climate changes negatively affects firms’ stock returns, earnings and equity valuations (Venturini, 2022; Bansal et al., 2016; Addoum et al., 2021; Hugon and Law, 2019; Pankratz et al., 2019), the risks of such events may lead to a reassessment of the value of a large range of firms’ assets (plants, property, and equipment) and to increased operating costs, such as relocation costs and insurance costs, resulting in lower profits and reduced repayment capacity. Greater physical climate risk led to lower leverage in the post Paris Agreement period, owing to both demand and supply side effects. On the demand side, firm’s optimal leverage reduced due to the larger expected distress costs, while on the supply side higher operating costs induced bankers and bondholders to increase the spreads when lending to riskier firms (Ginglinger and Moreau, 2019). It is therefore not surprising that firms exposed to climate change risk bear higher costs in financial markets when trying to access credit. In the United States one-standard-deviation increase in the risk of sea-level rise is associated with a loan spread that is 4.2 basis point higher (Jiang et al., 2019). The effects are larger on corporate bonds, reaching up to 7 basis points, especially for firms and industries vulnerable to extreme weather conditions (Allman, 2021).<sup>4</sup> When confronted with known unknowns, investors have an incentive to pursue an option

> 4Nevertheless, such climate-related financial risks are still mispriced and not fully reflected in asset valuations (Caselli and Figueira, 2020), although recently financial markets are increasingly recognizing such risks (Alsaifi et al., 2020) and firms are becoming more careful in embedding uncertainties in their overall risk management.

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value approach of delaying irreversible investment decisions when one knows that new information will arrive over time Dixit et al. (1994). The climate change adaptation challenge appears to be a prime example. Future research should explore how the value of holding a real option affects the timing of firm irreversible investments in location specific capital.

# **3.2 Adapting to the Uncertainty of Extreme Rare Events**

There are two components of extreme weather uncertainty: (a) the incidence of uncertainty: regarding where, when, and whether an extreme weather event will occur, and (b) the impact of uncertainty: how severe is the impact of the weather event’s effect conditional on an event occurring.

Business-related uncertainty is known to affect firms (Bernanke, 1983), however, the salience of such uncertainties in the context of climate change are only now being recognized (Fabrizio, 2012; Dorsey, 2019). Uncertainty about future climate shocks affect investments in innovation and technologies as well as decisions regarding other aspects of production such as input choice, location of firm and the sourcing of materials (Jia et al., 2022).

How firms and investors respond to uncertainty related to climate change also has implications for adaptation. Firms’ expectations about future weather events or shocks may influence their decisions concerning sector level innovation as well as the choice of inputs, spatial sourcing of material inputs, location of production and so on which in turn affects their productivity. Yet, these dimensions have been examined mostly in response to actual climate changes rather than uncertainty per say. One exception to this is a study by (Huang et al., 2018) that uses Global Climate Risk Index to capture likelihood of losses from natural hazards at the country level, which was found to be associated with firms’ lower and more volatile earnings and cash flows. These firms also tend to hold more cash and pay less cash dividends, suggesting that more exposed firms tend to hedge more against cash flow volatility and illiquidity due to higher climate risk. Increased climate uncertainty can also affect firms by increasing their insurance premiums. This can manifest through a decline in coverage agreements and, consequently, an increase in insurer exits because of limited revenue streams (Born and Viscusi, 2006), both will inevitably lead to higher insurance premiums.

Trading networks raises the possibility that a spatial shock to one area has a ripple effect that impacts non-treated areas. If a supply chain is not diversified and features a type of O-Ring such that a break in the chain shuts down production, then the whole network is sensitive to extreme disasters and weather events Carvalho et al. (2021). Access to geocoded micro data is creating new opportunities to study how firms adapt to extreme weather events.

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For example, geocoded microdata from Pakistan’s Federal Board of Revenue on the nearuniverse of formal firm-to-firm monthly sales transactions over ten years in combination with GPS tracking on trucks can help understand the spillover effects of floods through production network (Balboni et al., 2023). This research finds that firms affected by major floods relocate to less flood prone areas, diversify their supplier base, and shift the composition of their suppliers towards those located in less flood-prone regions and reached via less floodprone roads. Another recent study on India using new data on the universe of firm-to-firm transactions confirms that firms diversify sourcing locations, and that suppliers exposed to climate risk charge lower prices (Castro-Vincenzi et al., 2024). Such swift diversification of suppliers points to a forward-looking action that reduce future vulnerability to flood risk rather than direct effects of flooding are consistent with experience-based updating. It also supports the hypothesis that the impacts of climate change will be mediated as firms learn from the experience of increasingly frequent climate disasters.

# **3.3 Firm and Industry Attributes in Adapting to Risk and Uncertainty**

In the face of increasing climate change _risks_ , the heterogeneity in preparedness for climate change varies with firms and industry attributes, as is also the case of _actual_ shocks (described in Section 2.1). Some specific evidence of such variation driven by firm and industry attributes is presented below.

## **Firm attributes and climate risk**

In recent work, Lin et al. (2020) show that electricity providers increase investments in flexible power plants in response to long-term changes in local climate; (Li et al., 2020) document a negative effect of changes in long-term climate conditions on local employment; and Li et al. (2020) find that firms with high climate uncertainty increase their capital investments.

## _Firm size and supplier base_

Larger firms have lower exposure to risk as they can devote relatively more resources and have better abilities to sustain performance than smaller firms (Birkie et al., 2017). Firms that have a more _diverse supply base_ , both in terms of numbers and geographic dispersion, and hence may better manage climate risk by ensuring faster recovery in the event of unexpected climate shock (Tokui et al., 2017). Sophisticated supply chains can also increase exposure to climate-related disruptions due to potential ripple effect (Gouda and 15
Saranga, 2018) and managing such risk may require firms to have better capabilities.<sup>5</sup> **Industry attributes and climate risk**

### _Climate sensitivity_

Firms in sectors that rely on certain _seasonal and climate conditions_ (e.g., agriculture and related businesses), those that are vulnerable to the disruption of _infrastructure_ , and those _located in areas_ that are susceptible to physical climate change risks are particularly vulnerable (Weinhofer and Busch, 2013). Increased climate uncertainties can also increase price volatility in markets that have relatively higher dependence on moderate weather, such as agriculture and energy (including mining and oil extraction) (Fleming et al., 2006). The higher volatility of prices in these markets, which had been on the rise especially for agricultural products (Taghizadeh-Hesary et al., 2019), can deter investments and increase resource requirements for risk management that can be otherwise devoted to more productive activities. The exposure and the ability to mitigate climate risks vary by the sophistication of the sector.

# **4 The Strategic Interactions between Firm Investment and Government Policy**

We now focus on the government’s role in providing an enabling environment, place-based infrastructure, public insurance and direct firm support (e.g., cash grants, training, information etc.) in facilitating adaptation. We devote special attention to intended and unintended consequences of government investments and possible options available to policymakers to help firms prepare for and respond to climate change.

## **4.1 Government Infrastructure Investment**

Over the next few decades, enormous investments will be made in durable infrastructure investment in the developing world. Nations will build new roads, sea walls, bridges, water treatment facilities, power generation plants, airports and many other pieces of location specific sunk capital. Such capital will last for decades and will be costly to retrofit. The siting of this infrastructure will determine where many firms locate because of the complementarities

> 5A number of factors such as size, customer base, firms’ organizational setup, the breadth of the supply chain network, and diversification of product portfolio, are all sources of supply chain complexity (Birkie et al., 2017).

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between public and private investment.

No government has the sole goal of maximizing a nation’s climate resilience. Instead, many government officials are pursuing policies to increase national economic growth. Such pro-growth policies raise the likelihood that officials will stay in power and enhances their own reputations and influence. In pursuing economic growth goals, governments often make lumpy investments in infrastructure such as building roads, airports, and sewer systems. Once these investments are sunk, they become irreversible investments. An open empirical question is whether building durable capital in areas unintentionally increases the climate risk that local firms and people face. For instance, Hsiao et al. (2021) argues that sea wall investment in Jakarta that is financed by the nation as a whole is attracting too many people to live in this mega-city, implying that more people and firms face climate risks relative to a counter-factual where spatial sunk investment in sea walls had not taken place.

Government investment in protective infrastructure can crowd out private investment in self-protection if the two are substitutes (Ehrlich and Becker, 1972). Public investment in place-based infrastructure (such as Sea Walls) could possibly be crowding out private selfprotection as firms move to the risky area because it is a more productive area. If firms and their workers overestimate the safety protection provided by the seawalls then a type of moral hazard effect takes place. Infrastructure is long lived and this creates ”lock in” effects such that if it is built in places that turn out to be risky then road infrastructure investments can simultaneously increase a firm’s productivity (because it can ship goods at lower costs) while raising its short term climate risk exposure (Balboni, 2019). International financing agencies have an incentive to anticipate this dynamic and to take into account the growth complementarities that will be caused by building the new infrastructure (Hsiao, 2023; Avner et al., 2021).

# **4.2 Policies to Prepare for and Respond to Climate Change**

Given the shifts in climatic and weather conditions that impose substantial economic burden on firms, adaptation and strategies for developing resilience to climate change are necessary to minimize losses (Mendelsohn, 2000; Carleton and Hsiang, 2016). As described in previous sections, in an unconstrained environment, firms can potentially respond to climate changes by making adjustments on three possible dimensions: sectoral, structural and spatial. Yet, market response to the risk of climate shocks ranges from non-reaction, or a ”wait and watch” strategy even in sophisticated financial markets such as the US (Alesch et al., 2001) to high-levels of risk aversion such that firms hold more cash; resort to a portfolio with 17
more long-term debt; and lower probability of distributing cash dividends (Huang et al., 2018) because of their expected (in)ability to repay their creditors. Select insights from the literature on possible policy action is explained below.

# **Encourage risk taking through the development of insurance markets**

Insurance markets play a key role in pooling risks. Even in advanced countries such as the United States, businesses’ losses from hurricanes are not covered by insurance (Battisto et al., 2017; Swiss Re, 2018; Collier et al., 2020). Disasters can cause spatially concentrated loan defaults in the absence of insurance (Collier and Babich, 2019; Collier, 2020) and a reduction in the credit supply after the disaster that further delays the recovery of affected firms (Del Ninno et al., 2003). In developed and developing countries alike, getting businesses to insure remains a formidable challenge. The progress on expanding insurance coverage to SMEs in developing markets has been slow (Binswanger-Mkhize, 2012) due to (i) differences in perception of risks (Wagner, 2020); (ii) liquidity constraints; and (iii) presence of other types of risks (Cole et al., 2013) that may be more prevalent in developing countries (Collier, 2020). For instance, other risks that cannot be insured can affect the demand for insurance (e.g., Doherty and Schlesinger, 1983; Courbage et al., 2017; Hoffmann et al., 2009) because the burden of insurance premiums reduce the wealth of policyholders and hence increase their susceptibility to other shocks (Collier, 2020). Policymakers can assist in establishing new insurance arrangements for natural disasters or improve existing ones, possibly even being an insurer of last resort (Bruggeman et al., 2010).

# **Reducing Information Frictions that Limit Insurance Market Growth**

Informational issues also affect the use of insurance. Firms tend to under-insure through markets not only due to ignorance about their risk, but also because of the complexity of coverage under different insurance products, and the strategic behavior that balances market insurance with mitigation and self-insurance (Kousky, 2019). For example, behavioral economists posit that economic agents tend to underestimate the probability of a climate risk if they have not recently experienced it (“availability bias”), which in turn discourages investments in crises preparation or insurance (Bin and Polasky, 2004; Kousky, 2010; Atreya et al., 2013; Bin and Landry, 2013).

# **Financial support for rebuilding firms**

A number of instruments can be implemented to support firms in responding to climate shocks. For instance, grants or financial aid, which had been effective in the case of microenterprises in Sri Lanka post 2004 Tsunami (De Mel et al., 2008). Real profits among treated firms increased due to cash and in-kind grants compared to the control groups. The “build18
back-better” experienced by firms in Germany after a major flood in 2013 was also partially attributed to the availability of government aid, and banks’ willingness to fund re-investments (Noth and Rehbein, 2019). Manufacturing firms, which received the _most financial aid_ post 1959 Ise Bay Typhoon in Nagoya City, Japan, had higher chances of remaining viable as opposed to those in retail and wholesale sectors (Okubo and Strobl, 2021).

# **5 Empirical Benchmarking of Firm Adaptation Progress**

Given the high dimensionality of the adaptation strategy set, how can a researcher using observational data actually detect whether firms are becoming resilient to climate shocks over time? The economic definition of firm level ‘adaptation progress” is that a firm’s willingness to pay to not face a weather shock is declining over time. The ideal measure would be a firm’s willingness to pay to not face a weather shock. The firm’s willingness to pay would reflect the difference between its profits with and without the shock.

Empirical researchers have access to better data. With the rise of nation level geocoded administrative data sets such as the Census of Manufacturers and the Census of Services, there is an increased capacity to track the economic performance of firms over time. By merging in data on the location specific weather events that have taken place, observational econometrics approaches can used to estimate ”climate damage functions”. These are reduced form regressions such as the one presented below.

In this regression, the unit of observation is firm i in sector j located in city l at time t. The dependent variable is a measure of the flow damage (measured in dollars) suffered by a firm. Controlling for firm attributes, the key explanatory variables are measures of the firm’s recent exposure to extreme weather and the firm’s expectations of future weather conditions. Most empirical studies do not include this second term. Assuming that the error term is uncorrelated with the weather realization, this regression yields an estimate of the average effect of a weather shock on a firm specific outcome variable. It is important to note that this approach does not explicitly model the general equilibrium effects of how the weather shock affects market prices for output or labor. In these empirical studies, the prices are taken as given.

Estimates of this equation are useful but up until now they have not explicitly modeled 19
the firm site selection issue. Imagine a case where firms update their beliefs about location j’s future weather shocks as the climate scientists are predicting that location j faces medium term extreme weather risk. Forward looking firms will start to migrate to relatively safer locations over time. In this case, an econometrician who estimates equation (1) should be concerned that the firms who continue to locate in location j are not a representative sample of firms. One selection hypothesis would be to posit that better managers might locate in such areas if they have a risk adaptation edge. In this case, they can rent cheap land and still be productive. Another selection hypothesis would posit that worse managers will choose to locate in the riskiest areas because avoiding risk is a normal good.

In estimating equation (1), the researcher does not observe the costs that the firm has incurred to offset extreme weather. Such a regression does estimate the marginal cost to the firm of being exposed to extreme weather. If the firm has incurred upfront costs to adapt, then the econometrician is likely to estimate smaller marginal coefficients in equation (1). In an economy where firms are anticipating more extreme weather, firms will invest more in adaptation and the econometrician will actually estimate a smaller marginal damage coefficient over time.

The climate damage estimate literature relies on observational data as extreme weather provides the variation. Adaptation scholars can rarely implement field experiments here. A field experiment might consist of randomly distributing risk report cards to firms to educate them about the risks their geographic location faces. If firms trust the information source and were unaware of the risk, then this “new news” may affect their adaptation investment. Survey research and observational data on subsequent output can be used to study whether such an information nudge accelerates adaptation investment and lowers the marginal damage (B1 in equation 1) for the treated firms. Another field experiment research design would be to randomly assign different subsidies to firms for purchasing adaptation products. This price variation would trace out the demand curve for adaptation goods and this random variation could again be used to test whether the climate damage is less sensitive to extreme weather when firms have been induced (at random) to invest more in adaptation. As more firms seek to buy adaptation enhancing products, this provides an incentive for entrepreneurs to design these products. This dynamic innovation process will lead to higher quality products that sell for lower prices and this accelerates the global adaptation process Acemoglu and Linn (2004).

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# **6 Conclusion**

Global carbon dioxide emissions continue to rise. While the annual International Conference of the Parties (COP) meetings have helped nations to co-ordinate decarbonization activities, the global growth in population and per capita income raises greenhouse gas emissions. A fundamental global free rider problem lurks as developing nations are prioritizing economic growth over decarbonization. Every nation is hoping that every other nation bears the costs of decarbonization. As global fossil fuel consumption continues to rise, developing country nations face greater risks from climate change. Facing this reality, climate change adaptation takes on a prime importance especially in developing countries.

In this survey, we have presented a “bottom-up” microeconomic approach that focused on the challenges that extreme weather poses for firms in the developing world. We surveyed an emerging literature that studies the role of markets, information, and expectations in determining the pace of adaptation. The expectation that firms will lose profit if they fail to adapt motivates them to consider adopting adaptation strategies. In this paper, we have not solved a Pareto problem of balancing the global economy’s optimal investment in carbon mitigation versus climate change adaptation. Instead, we have focused on firms. No individual firm causes climate change through its carbon emissions. Each has a private incentive to free ride but at the same time each has a private incentive to invest in adaptation.

Private actors rely on government infrastructure to achieve their daily goals. Our careful attention to the interplay between private investments and local public goods in determining the economic geography of production suggests that efficient government policy hinges on the diagnosis of the market failures at play in climate change adaptation. For example, if firms do not adapt due to poor information systems, then efficient government action is to fix the information gaps rather than invest in resilient infrastructure. By comparison, if firms do not adapt due to poor capabilities, providing some direct support and training to firms may be warranted. At the very least, however, perverse incentives and distortions that inhibit firms’ _sectoral_ , _structural_ and _spatial_ shifts required for adaptation to climate change can be minimized.

All over the world, firms demand products to help them to adapt to extreme weather. This creates a profit motive to seek new solutions for mitigating the consequences of extreme heat, air pollution and flood risk. As endogenous adaptation innovation takes place, the diffusion of these products and strategies to the developing world will increase their adaptation menu (Acemoglu and Linn, 2004). An empirical implication of the endogenous adaptation innovation hypothesis is that the productivity losses associated with extreme weather events 21
may decrease over time. Adaptation innovation raises the possibility that the cost of offsetting the physical risks of climate change could decline over time. Future research should test this hypothesis.

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