Note that InputOutput coefficients can only range between 0 and 1. Perhaps the most challenging task is to identify critical sectors that may be responsible for widespread spillover effects leading to substantial modifications in other sectors production input schemes. For the sector aggregate wholesale, retail trade, restaurants, and hotels, a one standard deviation increase in tropical cyclone damage cause a decrease of \(-\,1.16\) percentage points of the annual per capita growth rate. In total, the majority of all sectoral aggregates experience lagged negative growth effects due to tropical cyclones. One major effort of this paper is to generate a new meaningful sectoral damage variable on a country-year level. The main causal identification stems from the occurrence of tropical cyclones, which are unpredictable in time and location (NHC 2016) and vary randomly within geographic regions (Dell etal. About how did tropical cyclone eloise impact the economy. It has been shown that the damage of tropical cyclones increases non-linearly with wind speed and occurs only above a certain threshold. So unfortunately, WA can expect regular cyclone impacts even as the climate . The main causal identification stems from the exogenous nature of tropical cyclones, whose intensity and position are difficult to predict even 24h before they strike (NHC 2016). Additionally, tropical cyclone intensity is measured by remote sensing methods and other meteorological measurements. Int J Disaster Risk Sci 10(2):166178, Munich R (2018) NatCatSERVICERelevant natural loss events worldwide 19802018. Additionally, Cole etal. If the official data of the countries or regions are not available, the UNSD consults additional data sources. Ten mass-feeding kitchens were set up. Q J Econ 131(3):15431592, Berlemann M, Wenzel D (2018) Hurricanes, economic growth and transmission channels: empirical evidence for countries on differing levels of development. The analysis is conducted on a country-year level. The storm will likely damage homes. Other studies analyze the disasters impact on single sectors, such as the agricultural (Blanc and Strobl 2016; Mohan 2017) or the manufacturing sector (Bulte etal. The remaining variables are defined as in Eq. Sci Rep 9(1):20452322. Nonetheless, the results can provide general guidance for international disaster relief organizations that are active in various countries on how to direct their long-run disaster relief programs. 2014). I am grateful for comments made by Axel Dreher, Vera Eichenauer, Andreas Fuchs, Lennart Kaplan, Eric Strobl, and Christina Vonnahme. 16 in Appendix A.5. Out of 49 parameter estimates, only 12 are significantly different from zero.Footnote 26 As expected, the heavily damaged agriculture, hunting, forestry, and fishing sector aggregate experiences the most changes. Bakkensen LA, Park D-SR, Sarkar RSR (2018) Climate costs of tropical cyclone losses also depend on rain. Econometrica 55(3):703708, Newson R (1998) PARMEST: Stata module to create new data set with one observation per parameter of most recent model. Int J Remote Sens 38(21):59926006, Mohan PS, Spencer N, Strobl E (2019) Natural hazard-induced disasters and production efficiency: moving closer to or further from the frontier? Google Scholar, Albala-Bertrand J-M (1993) Natural disaster situations and growth: a macro-economic model for sudden disaster impacts. However, little is known about the empirical InputOutput effects across broader sectors after a natural disaster shock. For storm surge damage this is not possible, since there exists no global data set so far. The coefficients show the increase of the respective damage variable by one standard deviation. http://hdl.handle.net/10986/2512, Yang D (2008) Coping with disaster: the impact of hurricanes on international financial flows, 19702002. Color intensities indicate p values according to: \(p<0.01\), \(p<0.05\), \(p<0.1\). The growth literature predicts that some potential positive or negative impacts of natural disasters emerge only after a few years. WMO continues to monitor the "remarkable" tropical storm, which has cut a destructive path across . I decide to only examine changes in the InputOutput coefficients and not at indirect costs because it almost needs no assumptions. The agricultural sector relies heavily on environmental conditions as most of its production facilities lie outside of buildings and are hence more vulnerable to the destructiveness of tropical cyclones. 2014). http://www.nhc.noaa.gov/verification/verify5.shtml, Nickell SJ (1981) Biases in dynamic models with fixed effects. Consequently, for each grid point g, a wind speed S is calculated depending on the maximum sustained wind speed (M), the forward speed (T), the distance (D) from the storm center, and the radius of the maximum wind (R)Footnote 8: As a result, I generate hourly wind fields for each of the 7814 tropical cyclones in my sample period (19702015).Footnote 9 Figure 1 illustrates the resulting modeled wind fields for Hurricane Ike in 2008 on its way to the U.S. coast. Power cables and telephone lines come down, crops are ruined, and water and sewage supplies are affected. Last week, the East Coast prepared for Hurricane Florence, which roared through the Carolinas and Georgia. Bull Am Meteorol Soc 101(3):E303E322, Korty R (2013) Hurricane (typhoon, cyclone). Nevertheless, we can learn from this analysis the important role of those manufacturing sectors that are not directly affected. 4 and 6 with the population weighted damage for the agricultural sectoral aggregate. Excellent proofreading was provided by Jamie Parsons and Harrison Bardwell. 4 displays the average InputOutput coefficients for all countries for all available years (19902015). Future weather. Flooding could prove devastating. First, I add to the research area on the macroeconomic effects of disasters. Since the sample period is reduced to 19902015 due to data availability, I re-estimated the regression model of the main specification 2 for the reduced sample of model 6. This hypothesis is supported by empirical findings for a positive GDP growth effect for Latin American countries (Albala-Bertrand 1993), for high-income countries (Cuaresma etal. 2010). https://www.munichre.com/en/solutions/for-industry-clients/natcatservice.html, Newey WK, West KD (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. The data are collected every year for as many countries and regions as possible.Footnote 11 The sample used in my analysis covers the 19702015 period and includes a maximum of 205 countries.Footnote 12, To analyze potential sectoral shifts within the economy after a tropical cyclone, I take advantage of the InputOutput data of EORA26 (Lenzen etal. \end{array}\right. } This index is then multiplied by the cubed maximum wind speed \(S(max)_{g,t}^{3}\) in grid g and year t as calculated by Eq. Both variables are associated with the occurrence of tropical cyclones since they only form when water temperatures exceed 26 \(^{\circ }\)C and torrential rainfalls usually constitute part of them. About 12 hours before Hurricane Florence makes an appearance, both of Duke Energy's North Carolina plants will shut down. The radius of maximum wind (R, in km) is related to the latitude (L) of the respective raw data tropical cyclone position in the following way: Since the tropical cyclone data are available at global coverage since 1950, I will extend my database later for further specifications. To quantify the destructiveness of tropical cyclones, I construct a new damage measure based on meteorological data weighted by different exposure of the sectors. It comprises the logged per capita value added of the respective sector j to simulate a dynamic panel model, the population growth rate, a variable for openness (i.e., imports plus exports divided by GDP), and the growth rate of gross capital formation.Footnote 18 Including these socioeconomic control variables introduce some threats to causal inference. Read the InFocus blog post on climate change and flooding Generally speaking, the proposed models offer a simple but strong way for causal interpretation of the impact of tropical cyclones on sectoral growth. 2020). In the sample used, 70% of all grid-points are hit once by a tropical cyclone per year, whereas 20% are hit twice and 10% more than twice. This allows me to analyze whether any key sectors exist that, if damaged, result in direct damage of other sectors. B.E. How did the tropical cyclone impact the people communities? These regions include East Asia and Pacific, Europe and Central Asia, Latin America and Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. The error term \(\epsilon _{i,t}\) is clustered at the country level. In addition, in a recent working paper, Hsiang and Jina (2014) even demonstrate a long-term negative impact of tropical cyclones of up to 20 years. 2013). 2019). For example, Loayza etal. I show point coefficient estimates as well as accumulated effects and error statistics calculated via a linear combination of the lagged \(\beta _{t-L}\) coefficients.Footnote 17. Immediately after the disaster, the policy should concentrate on the agriculture, hunting, forestry, and fishing, and the wholesale, retail trade, restaurants, and hotels sector aggregates, as they are most vulnerable, and/or recovery measures have not been conducted efficiently in these sectors. The results can be found in Fig. Tropical cyclones are immensely powerful and can travel up to speeds of 65 km/h. Appendix A.5 presents further statistics: Figs. In consequence to tropical cyclone damage, less tourists visit affected countries (Hsiang 2010), since they perceive these destinations as too risky to travel to (Forster etal. After one year, we can also detect a positive effect in the construction sector, which is not surprising given the higher number of orders due to reconstruction efforts. 912, while Tables 511 show the regression results. It is a unification of all best track data on tropical cyclones collected by weather agencies worldwide. Econ Disasters Clim Change 4(3):657698, Mohan P (2017) Impact of hurricanes on agriculture: Evidence from the Caribbean. Eastern North Carolina is prone to flooding associated with tropical cyclones (e.g., hurricanes Fran in 1996 and Matthew in 2016) and it is likely that an event similar to the Hurricane Florence . First, tropical cyclones frequently cause a surge in ocean waters causing sea levels to rise above normal. It remains unclear if there exists some key sector, which, if damaged, results in a negative shock for the other sectors. Nevertheless, it unveils the importance of the manufacturing sectors, as already demonstrated by their strong intersectoral connection in Fig. Mohan (2017) provides further evidence that in Caribbean countries agricultural crops are more severely affected by hurricanes compared to livestock. While some studies provide evidence of only a short-term economic impact of tropical cyclones (Bertinelli and Strobl 2013; Elliott etal. Based on a fine-gridded wind field model, I generate a new sector-specific damage measure weighted by either agricultural land use or population data. Table 21 in Appendix A.5 reveals that even with the smaller sample, all previously found effects can be identified again. 7. PLoS ONE 14(4):121, Strobl E (2011) The economic growth impact of hurricanes: Evidence from U.S. coastal counties. How did the tropical cyclone Florence impact the following ? The wind speed drops with distance to the center of the hurricane and as soon as it makes landfall. It is therefore important to examine their effects over time (Felbermayr and Grschl 2014; Hsiang and Jina 2014). The robustness tests that frequently fail are those with Conley-HAC and NeweyWest standard errors. They can best be summarized by three possible hypotheses: recovery to trend, build-back-better, and no recovery (Chhibber and Laajaj 2008). Most worryingly, the majority of all sectors experience delayed negative effects underpinning how far away the international community remains from a build-back better or recovery to trend situation for tropical cyclone-affected economies. Springer, Dordrecht, New York, pp 481494, Chapter It . 2018; Elliott etal. Evidence from India. For the sample average (0.88) of the regression of Column (1), this effect can be translated into a decrease of \(-298\)%, as displayed in Fig. Pictured: The East Coast of the U.S. and the Gulf of Mexico viewed by satellite as Hurricane Florence made landfall on September 14. https://doi.org/10.1007/s10640-021-00541-5, DOI: https://doi.org/10.1007/s10640-021-00541-5. It is evident from this analysis that many potential production changes are canceled out because of counteracting indirect effects. World Dev 40(7):13171336, Mendelsohn R, Emanuel K, Chonabayashi S, Bakkensen L (2012) The impact of climate change on global tropical cyclone damage. In coastal areas, storm surges can lead to flooding, the destruction of infrastructures and buildings, the erosion of shorelines, and the salinization of the vegetation (Terry 2007; Le Cozannet etal. I follow Emanuel (2011) by including the cube of wind speed above a cut-off wind speed of 92 km/h. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Originating from a tropical wave over West Africa, Florence quickly organized upon its emergence over the Atlantic Ocean. Hurricane Florence was a powerful and long-lived Cape Verde hurricane that caused catastrophic damage in the Carolinas in September 2018, primarily as a result of freshwater flooding due to torrential rain. Springer, New York, London, Toya H, Skidmore M (2007) Economic development and the impacts of natural disasters. Am Econ J Appl Econ 8(2):123153, Guha-Sapir D, CRED (2020) EM-DAT: the emergency events database. But those that do occur will be more intense and damaging. The red and green arrow colors represent significant negative and positive effects, whereas the color intensities denote different p-values. 2017). Further losses can occur if business continuity is lost through disrupted supply of intermediate inputs from, or distribution to, other businesses. For both variables, I use the year-by-year variation calculated from the Climatic Research Unit (CRU) version 4.01, which is available at a resolution of approximately 50km since 1901 (University of East Anglia Climatic Research Unit et al. 2012). Tropical Cyclone Eloise was the strongest tropical cyclone to impact the country of Mozambique since Cyclone Kenneth in 2019 and the second of three consecutive tropical cyclones to impact Mozambique in the 2020-21 South-West Indian Ocean cyclone season. In total, I exclude five country-year observations from my analysis: Dominican Republic 1979, Grenada 2004, Montserrat 1989, Myanmar 1977, and Saint Lucia 1980. Furthermore, a shortage in the labor force can lead to a wage increase, which can serve as an incentive for workers from other regions to migrate to the affected region, also leading to a positive effect (Hallegatte and Przyluski 2010). In light of this finding, one could question the reliability of the agricultural weighting scheme for the damage variable. Best track data are a postseason reanalysis from different available data sources, including satellites, ships, aviation, and surface measurements, that are used to describe the position and intensity of tropical cyclones (Kruk etal. However, we still can learn from this analysis of how certain direct effects evolve. When water changes from a liquid to a gas, it absorbs heat, and when it changes from a gas to a liquid, it releases heat. Freddy has finally been declared over by the French Meteorological service. Winds have lessened to 45 mph. Energy Econ 46:576592, Kruk MC, Knapp KR, Levinson DH (2010) A technique for combining global tropical cyclone best track data. In order to design effective mitigation and adaptation disaster policies to this threat, it is important to understand the economic impact of natural disasters. Kunze, S. Unraveling the Effects of Tropical Cyclones on Economic Sectors Worldwide: Direct and Indirect Impacts. Based on physical intensity data, Hsiang (2010) analyzes the effect of hurricanes on seven sectoral aggregates in a regional study for 26 Caribbean countries. As tropical cyclones are exogenous to sectoral economic growth, the greatest threat to causal identification could arise by omitting important climatic variables that are correlated with tropical cyclones (Auffhammer etal. 2020). It rather points to the presence of (delayed) negative effects of tropical cyclones from which the sectors cannot recover. Sven Kunze. The sample period hence reduces to 19712015. Panel (a) displays the percentage of agricultural land, whereas (b) shows the distribution of population in Australia in 2008. However, time-delayed effects must also be taken into account since some damage, such as supply-chain interruptions or demand-sided impacts, will only be visible after a certain time lag (Kousky 2014; Botzen etal. Across the Caribbean the economic costs of tropical cyclones amount to 2% of GDP annually since the 1950. Such data are positively correlated with GDP (Felbermayr and Grschl 2014) and prone to measurement errors (Kousky 2014). 2018). Open Access funding enabled and organized by Projekt DEAL. Asterisks and color intensities indicate p values according to: ***\(p<0.01\), **\(p<0.05\), *\(p<0.1\). The situation is completely different in the wholesale, retail trade, restaurants, and hotels sector aggregate, where a negative influence can be observed over almost the entire 20-year period. Economic sectors most vulnerable to direct capital destruction of tropical cyclones must be identified. \(Damage_{i,t}\) is the derived damage function for country i at year t from Eq. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. In general, this analysis reveals production scheme transformations that can result from both supply and demand changes of the sectors due to tropical cyclones. Appendix A.6 exhibits the resulting robustness tests for the direct and indirect sectoral effects.Footnote 33 For the direct sectoral effects, the significant results remain robust in all different specifications underlining their credibility for the empirical model used.Footnote 34 While the placebo test yields no significant coefficients, the coefficients and p-value remain relatively stable in all remaining robustness tests, as summarized in Fig. The sample is larger than the maximum size of recognized sovereign states as it also includes quasi-autonomous countries such as the Marshall Islands, if data are provided for them by the UNSD. First, I account for the economic exposure by weighting the maximum occurred wind speed per grid cell and year by the number of exposed people living in that grid cell relative to the total population of the country. To analyze the effect of tropical cyclones in the longer run, I introduced lags of the tropical cyclone damage variable to the main specification 4. (2018). I further thank seminar participants at Heidelberg University (2016), the AERE Summer Conference in Breckenridge (6/2016), the EAERE Meeting in Zurich (06/2016), the BBQ Workshop in Salzburg (07/2016), the Geospatial Analysis of Disasters: Measuring Welfare Impacts of Emergency Relief Workshop in Heidelberg (07/2016), the Oeschger Climate Summer School in Grindelwald (08/2016), the Conference on Econometric Models of Climate Change in Oxford (9/2017), the Impacts World Conference in Potsdam (10/2017), and the 8th Annual Interdisciplinary Ph.D. Workshop in Sustainable Development at Columbia University (04/2018). This allows me to identify which of the competing hypothesesbuild-back-better, recovery to trend, or no recoveryis appropriate for which sector. As tropical cyclones are highly correlated with higher temperature and precipitation (Auffhammer etal. First, I only use the damage fraction due to maximum wind speed of tropical cyclones. An exception forms the mean damage robustness test for the wholesale, retail trade, restaurants, and hotels sectors, where the coefficient turns slightly insignificant (\(p=0.12\)). Tropical Cyclone Eloise, which hit southeastern Africa in January 2021, caused widespread flooding and landslides, resulting in at least 21 deaths and. Notes The y-axis displays the cumulative coefficient of tropical cyclone damage on the respective per capita growth rates, and the x-axis shows the years since the tropical cyclone passed. Country-year observations above two standard deviations are labeled with the respective ISO3 code. \end{array}\right. } Eur Econ Rev 101:441458, Chhibber A, Laajaj R (2008) Disasters, climate change and economic development in Sub-Saharan Africa: lessons and directions. Section 5 concludes with a discussion of the results and highlights policy implications. This is an improvement in comparison to Hsiang (2010) who only focuses on 26 Caribbean countries, which are highly exposed but only account for 11% of global GDP in 2015 (United Nations Statistical Division 2015c). 2 contains a description of the data source, introduces the construction of the tropical cyclone damage measure, and presents descriptive statistics. http://data.un.org/Explorer.aspx?d=SNAAMA, University of East Anglia Climatic Research Unit, Harris IC, Jones PD (2017) CRU TS4.01: climatic research unit (CRU) time-series (TS) version 4.01 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901Dec. In the first test, I introduce a variable which counts the yearly frequency of tropical cyclones above 92 km/h per country (see Appendix Table 40 and Figs. Consequently, \(\beta ^j\) is the coefficient of main interest in this specification. Since the tropical cyclone data has global coverage since 1950, I am able to introduce lags of up to 20years without losing observations of my dependent variable, which ranges from 1971 to 2015. From a theoretical perspective, a natural disaster can have both positive and negative effects. 2014) remain. Since the EORA26 database also offers the data decomposed for 26 sectors, this section demonstrates the results of model 6 in more detail. After controlling for country and time specific effects, my estimation approaches allow for a causal identification of the direct and indirect responses to tropical cyclones damages with only little assumption needed (Dell etal. J Monet Econ 43(2):391409, Elliott RJ, Strobl E, Sun P (2015) The local impact of typhoons on economic activity in China: a view from outer space. This is because there are regions showing increases or . Put in relation to the sample average per capita growth rate (2.53%), the effect translates to a decrease of \(-46\)%. Before 2000, only decadal data are available. The variables are measured in constant 2005 USD. The sectoral GDP data originates from the United Nations Statistical Division (UNSD) (United Nations Statistical Division 2015b). The gray shaded area specifies the respective 95% confidence bands, and the red line depicts the connected estimates. Econ Inquiry 46(2):214226, de Mel S, McKenzie D, Woodruff C (2012) Enterprise recovery following natural disasters. The recovery to trend hypothesis characterizes a pattern where after a negative effect in the short run, the economy recovers to the previous growth path after some time. Distribution of tropical cyclone damage, 19702015. Cyclones also can bring torrential rains that lead to flooding. I take advantage of the International Best Track Archive for Climate Stewardship (IBTrACS) provided by the National Oceanic and Atmospheric Administration (Knapp etal. This behavior most likely speaks for an enduring risk adjustment of tourists. The start of the arrow shows the input, and the end denotes the respective output. Based on damage estimates from EM-DAT, the authors find a negative effect for the agricultural and a positive effect for the industrial sector. I also tested for lagged cumulative effects. This will provide further insights into whether production processes are seriously distorted by tropical cyclones. Notes The colored areas depict all significant coefficients between the sectors, with negative coefficients in red and positive in green. This finding clearly opposes the build-back-better hypothesis as well as the recovery to trend hypothesis. 2012, 2013). Figure 6 illustrates the cumulative point estimates of the past influence of tropical cyclone damage on the different sectoral growth variables.Footnote 22 The x-axis represents the lags of the damage variable, while the y-axis indicates the size of the cumulative coefficient \(\beta\) (in standard deviations).