Abstract
Increasingly adverse climatic conditions have created greater systematic risk for companies throughout the global economy. Few studies have directly examined the consequences of climate-related risk on financing choices by publicly listed firms across the globe. We attempt to do so using the Global Climate Risk Index compiled and published by Germanwatch (Kreft & Eckstein, Global climate risk index 2014, Bonn: Germanwatch, 2014), which captures at the country level the extent of losses from extreme weather events. As expected, we find the likelihood of loss from major storms, flooding, heat waves, etc. to be associated with lower and more volatile earnings and cash flows. Consistent with policies that attempt to moderate such effects, we show that firms located in countries characterized by more severe weather are likelier to hold more cash so as to build financial slack and thereby organizational resilience to climatic threats. Those firms also tend to have less short-term debt but more long-term debt, and to be less likely to distribute cash dividends. In addition, we find that certain industries are less vulnerable to extreme weather and so face less climate-related risk. Our results are robust to using an instrumental variable approach, a propensity-score-matched sample, and path analysis, and remain unchanged when we consider an alternative measure of climate risk. Finally, our conclusions are invariant to the timing of financial crises that can affect different countries at different times.
Accepted by Gary Biddle, Area Editor, 14 October 2017. This article has been with the authors for three revisions.
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Notes
- 1.
According to United Nations International Strategy for Disaster Reduction (UNISDR, 2009), risk is the “combination of the probability [of occurrence] of a certain event and its negative consequences.”
- 2.
A large part of the economic damage emanating from extreme weather events is not insured, especially in the case of developing countries (Andersen, 2001; Bals et al., 2006). Catastrophic insurance usually covers only damage to the means of production (e.g., property), not indirect losses such as lost proceeds from property that is destroyed, not losses that other agents may suffer, e.g., loss of supplies from damaged property (Bals et al., 2006). Hence underlying our study is the assumption that firms cannot fully insure against climatic risk. To the extent that they can do so, we anticipate that our findings will be less significant.
- 3.
Bansal and Ochoa (2012) propose that equity returns in countries with higher temperatures (i.e., those closer to the Equator) have a positive temperature risk premium; they also show that increases in global temperature negatively affect the economic growth of countries closer to the Equator.
- 4.
Albouy et al. (2013) posit that US households prefer a certain temperature level and find a cost of living premium in areas with such levels.
- 5.
Concern about the effect of rising temperatures is growing. Pal and Eltahir (2016) predict that the temperature in Southwest Asia will rise beyond the habitable level if global warming is left unabated.
- 6.
Seasonal affective disorder refers to an extensively documented medical condition whereby the shortness of the daylight in fall and winter leads to greater depression and, in turn, heightened risk aversion.
- 7.
Prior literature tends to treat sunshine and temperature as two distinct weather variables. For example, Howarth and Hoffman (1984) show that skepticism is positively associated with temperature and negatively associated with the amount of sunshine.
- 8.
Interest in climate change has resulted in a recent strand of studies in this area including some that focus on the impact on firm valuation, as carbon dioxide emissions, hazardous chemicals, and other pollutants may result in onerous regulatory requirements, financial or reputational damage, or costly litigation. Konar and Cohen (2001) show that intangible asset valuation is negatively associated with levels of emitted toxic chemicals, Matsumura et al. (2014) that carbon emissions can negatively affect firm value, and Beatty and Shimshack (2010) that firms suffer from negative market returns when poorly rated on managing (i.e., measuring, reporting, and reducing) greenhouse gas emissions. Based on US evidence, Chava (2014) finds that investors charge firms with higher greenhouse emissions and hazardous chemical discharges more for equity and debt capital. Using a European sample, Tu (2014) finds that firms with better carbon management performance have better share performance. On the other hand, Anderson et al. (2016) document that carbon risk is currently underpriced by financial markets and investors can hedge against climate risks without losing any returns. Finally, Clapp et al. (2015) argue that climate science should play a crucial role in verifying that the “green projects” of firms are climate friendly. However, these studies do not directly study the impact of climate events (as opposed to concerns) on firm valuation and decision-making.
- 9.
Atta-Mensah (2016) suggests that countries and firms can issue weather-linked bonds to hedge against volatility due to weather-dependent assets.
- 10.
Firms in larger countries can possibly move from a country’s high-climate risk area to one where the risk is less. That possibility would tend to reduce the robustness of any findings. At the same time, many firms cannot relocate (e.g., some retailers and firms in communication and transportation).
- 11.
“Geological factors like earthquakes, volcanic eruptions and tsunamis, for which data is also available, are not included as they are not weather-related per se and therefore not climate change-related” (Kreft & Eckstein, 2014: 16).
- 12.
We were not able to obtain annual scores from the 2006 and 2007 editions.
- 13.
Economic losses comprise “all elementary loss events which have caused substantial damage to property or persons” or in other words, direct losses (Kreft & Eckstein, 2014: 16). Indirect losses, i.e., the losses that firms experience due to damaged assets and those of their customers, are not included. However, they are highly correlated to direct losses (Hallegatte, 2008; Kowalewski & Ujeyl, 2012).
- 14.
Because indicators 3 and 4, sum of losses in US$ at PPP and losses as a percent of GDP, are likely to be affected by the economic size and performance of a country, we control for level and change of GDP in our multivariate regression analysis. Also, according to Kreft and Eckstein (2014: 20), “the indicator ‘absolute losses in US$’ is identified by purchasing power parity (PPP), because using this figure better expresses how people are actually affected by the loss of one US$ than by using nominal exchange rates.”
- 15.
One limitation of this study is that we do not account for how a firm might be affected by climate risk associated with its material operations located overseas.
- 16.
We winsorized all the continuous variables at the 1 and 99% levels.
- 17.
To save space, we do not provide the annual CRI by countries where the results are similar.
- 18.
Results not reported here indicate that both annual and long-term climate risk scores are positively associated with firms having negative extraordinary items and discontinued items.
- 19.
Meyer et al. (2017) point out that it is important to discuss the confidence interval of the coefficient. To save space, we do not provide the confidence intervals in the tables.
- 20.
It is calculated as follows: (−25.17 − (−63.50)) × (−0.00047) = −0.0108.
- 21.
Effect size refers to the magnitude of the effects (Ferguson, 2009).
- 22.
It is calculated as follows: (−25.17 − (−63.50)) × (−0.0003) = −0.0115.
- 23.
- 24.
Rountree et al. (2008) argue that investors are mainly concerned about the cash flow (as opposed to accounting) component of earnings volatility. Moreover, illiquidity issues are usually caused by cash flow volatility, not earnings volatility.
- 25.
The results indicate that these firms have higher long-term debt and total debt, which is a sign of financial distress (Banerjee et al., 2008) and can be a result of poor earnings performance resulting from extreme weather events.
- 26.
It is calculated as follows: (−25.17 − (−63.5)) × (0.00364) = 0.1395.
- 27.
It is calculated as follows: (−25.17 − (−63.5)) × (−0.0002) = −0.0077.
- 28.
Our results are robust to controlling for whether a country’s company law or commercial code requires firms to distribute certain percentage of their income as dividends (La Porta et al., 1998).
- 29.
The results in Table 13.5 may be due to extreme weather or to volatility in higher earnings and cash holdings as suggested in Table 13.4. We use path analysis (e.g., Wright, 1934) to examine these potential dependencies where annual extreme weather is treated as the direct path and earnings volatility as the mediated (indirect) path. We find that both direct and mediated paths are significant and positive, indicating that the financing policies are affected by both organizational resilience and earnings volatility.
- 30.
We use the Fama–French Industry classification.
- 31.
Using propensity-score-matched sample is an effective method to address endogeneity issue in cross-country studies (e.g., Ghoul et al., 2017).
- 32.
Results are available from the authors.
- 33.
- 34.
For convenience, we use a definition of a recession commonly used in the business press involving a fall in GDP for two successive quarters. [Note that the NBER defines a recession more broadly as “a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales” (NBER, 2008)].
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Acknowledgements
We thank the valuable comments from the Editor-in-Chief Alain Verbeke, Editor Gary Biddle, the three anonymous reviewers, and the participants of workshop at the University of Kentucky and the Mid-year Conference of International Accounting Section of American Accounting Association. Chong Wang acknowledges the financial support from Hong Kong Polytechnic University Start-up Fund and the National Natural Science Foundation of China (Fund # 71332008).
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Huang, H.H., Kerstein, J., Wang, C. (2022). The Impact of Climate Risk on Firm Performance and Financing Choices: An International Comparison. In: Mithani, M.A., Narula, R., Surdu, I., Verbeke, A. (eds) Crises and Disruptions in International Business. JIBS Special Collections. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-80383-4_13
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