how did the tropical cyclone impact the economy of florence

Further details on the data on tropical cyclones can be found in Appendix A.1. 2.Economy 3.People /communities The meteorological history of Hurricane Florence spanned 22 days from its inception on August 28, 2018, to its dissipation on September 18. 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. The most interesting changes can be observed within the single sectors of the manufacturing (D) aggregate. 4. For the latitude and longitude the model takes a spline interpolation, whereas for intensity and time observations it uses a linear interpolation. With this paper, I close this research gap by using an InputOutput panel data set to analyze potential sectoral interactions after the occurrence of a tropical cyclone. The record-breaking rainfall from hurricanes such as Harvey and Florence can be attributed to three factors that have been linked to a warming climate. 16 in Appendix A.5. In total, I use two different aggregation methods. 2014). 2020). It asks for less input from the wholesale, retail trade, restaurants, hotels and mining and utilities sector aggregates, which results from a supply shock in the agricultural sector. Upon examining the underlying estimates in Tables 1213 in Appendix A.5, it is evident that the transport, storage, communication sectoral aggregate also turns negative, at least at the 90% confidence interval.Footnote 23. In comparison, in my analysis, I take meteorological data as input which is exogenous to the political and economic situation, contains all existing tropical cyclones, and has no quality fluctuations. Queensland has 20% of Australia's sugar cane production, but . The InputOutput analysis demonstrates that production processes are only slightly disturbed by tropical cyclones. Additionally, it has been shown, that low- and middle-income countries seem to be more vulnerable to the negative impacts of natural disasters than high-income countries (Felbermayr and Grschl 2014; Berlemann and Wenzel 2018). Ten mass-feeding kitchens were set up. For large weather systems, the circulation pattern is in a counterclockwise direction in the Northern Hemisphere and a clockwise direction in the Southern Hemisphere. 2008), and for a cross-section of 153 countries (Toya & Skidmore 2007). Taking all considerations together, I calculate the following tropical cyclone damage for each country i and year t: where \(w_{g,t-1}\) are the exposure weights, agricultural land, or population, in grid g in period \(t-1\). For example, Loayza etal. Some areas experience record rainfall with widespread flooding and predictions for it to get worse. Sept. 15: Florence is a 350-mile-wide tropical storm that is dumping massive amounts of rain throughout the Carolinas. Slider with three articles shown per slide. Fourth, to alleviate concerns of biased uncertainty measures (Hsiang 2016), I calculate different standard errors: NeweyWest standard errors with a lag length of 10 years and Conley-HAC standard errors, allowing for a spatial and temporal dependence within a radius of 1000km and within a time span of 10 years. The other proportional shares on total GDP are: Wholesale, retail trade, restaurants, hotels (15%); agriculture, hunting, forestry, fishing (14%); mining and utilities (10%); transport, storage, communication (8%). Economic impact of Hurricane Florence set to devastate US east coast J Mon Econ 45(1):69106, Hsiang SM (2010) Temperatures and cyclones strongly associated with economic production in the Caribbean and Central America. Within the agriculture, hunting, forestry, and fishing sectors, the negative effects become less pronounced with a zero effect being present after fouryears, while the wholesale, retail trade, restaurants, and hotels sectoral aggregate experiences a persistent negative growth even after 20years. They ask significantly less input from other sector aggregates, while, at the same time, sectors from other aggregates ask more input from the manufacturing sectors. The storm damaged and destroyed famand, vital infrastructure and thousands of homes, dealing another devastating blow to families still trying to put their lives together after. Therefore, I re-estimate the results of Eqs. Notes This figure shows the significant effects of a one standard deviation increase in tropical cyclone damage on the respective InputOutput coefficient. 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. (2012) use data from EM-DAT as main input for their explanatory variables. 2632). I tested my data extensively for outliers having a high influence on my results. 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. The manufacturing sectors use significantly less input from itself, which is not shown in Fig. Hurricane Florence Case Study - Internet Geography Evidence from developing countries. Storms that are strongest originate off the west coast of Africa because they have two weeks worth of warm water to build up over. 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. To allow for the possibility of multiple tropical cyclones per year and country, I conduct two robustness tests. Cyclone Ingrid - Wikipedia The findings can help them to identify the sectors for which they must reduce disaster risk. I follow Emanuel (2011) by including the cube of wind speed above a cut-off wind speed of 92 km/h. 6: The manufacturing sectors ask significantly less input from it. J Dev Econ 111:92106, Fetzer T (2020) Can workfare programs moderate conflict? To identify the causal effects of tropical cyclone intensity on sectoral per capita growth, I use the following set of regression equations, which constitutes my main specifications: where the dependent variable \(Growth_{i,t-1->t}^j\) is the annual value added per capita growth rate of sector j in country i. Notes This figure demonstrates the distribution of the tropical cyclone damage variable (in standard deviations) for exposed agricultural areas (a) and exposed population (b) from 1970 to 2015, Figure 3 shows the country-year observations of the tropical cyclone damage variable for (a) exposed agricultural land and (b) exposed population. 2018 Hurricane Florence: Facts, FAQs, and how to help Depending on the level of aggregation, I run 49 (7*7) or 676 (26*26) different regressions. In total, I extend this research area in three ways: First, I introduce a new objective damage measure that allows for sector specific exposure of tropical cyclones. 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. Section 5 concludes with a discussion of the results and highlights policy implications. Put in relation to the sample average per capita growth rate (2.53%), the effect translates to a decrease of \(-46\)%. Sept. 16: Some areas receive as much as 34 inches of rain from Sept. 13 to Sept. 16. Furthermore, only a minority of studies explicitly investigate the disasters influences on sectoral economic development. This paper examines the current, lagged, and indirect effects of tropical cyclones on annual sectoral growth worldwide. Furthermore, I cluster the standard errors at broader regional levels to account for the event that tropical cyclones can also affect neighboring countries within one region.Footnote 31 Additionally, I control for the yearly tropical cyclone frequency per year, I test a different damage variable (mean instead of maximum cubed wind speed per year), and include tropical cyclone basin fixed-effects in further robustness tests. It . Power cables and telephone lines come down, crops are ruined, and water and sewage supplies are affected. This cost could climb higher as many rivers have yet to crest and may yet cause additional flooding. Rev Environ Econ Policy 13(2):167188, Bulte E, Xu L, Zhang X (2018) Post-disaster aid and development of the manufacturing sector: lessons from a natural experiment in China. How did the tropical cyclone impact the people communities? Q J Econ 110(4):11271170, Klein Goldewijk K, Beusen A, Doelman J, Stehfest E (2017) Anthropogenic land use estimates for the holoceneHYDE 3.2. Additionally, tropical cyclone intensity is measured by remote sensing methods and other meteorological measurements. It is not empirically clear how long past tropical cyclones influence present economic growth rates. 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 finding clearly opposes the build-back-better hypothesis as well as the recovery to trend hypothesis. Additionally, within the agriculture, hunting, forestry, and fishing sectors, only the fishing sector experiences indirect negative effects. (2019) show that indirect impacts are nearly as high as direct impacts. Unraveling the Effects of Tropical Cyclones on Economic Sectors Worldwide: Direct and Indirect Impacts, $$\begin{aligned} S_{g} = {\left\{ \begin{array}{ll} \max (0, ((M - abs(T)) * \frac{R}{D}^\frac{3}{2} *e^{1-\frac{R}{D}^\frac{3}{2}})+T),&{} \text {if }D<10*R \text { from center to outer core} \\ 0, &{} \text {if }D>10*R \text { out of radius}. In: Bobrowsky PT (ed) Encyclopedia of natural hazards. Nat Hazards Earth Syst Sci 19(1):137151, Loayza NV, Olaberra E, Rigolini J, Christiaensen L (2012) Natural disasters and growth: going beyond the averages. 2013). The gray areas represent the respective 95% confidence intervals and the red line indicates the respective (connected) cumulative point estimates. Exposed countries are defined as having at least one positive damage observation over the sample period. Figure 7 illustrates the connections of significant changes of the InputOutput coefficient together with the effect size relative to the sample average of the respective InputOutput coefficients in parentheses (in %) resulting from model 6. It is evident from this analysis that many potential production changes are canceled out because of counteracting indirect effects. The result offers a better understanding of the finding of Hsiang & Jina (2014), who show that tropical cyclones have long-lasting negative impacts on GDP growth by demonstrating which sectors are responsible for the long-lasting GDP downturn that they identify. A study led by Kevin Reed, PhD, Assistant Professor in the School of Marine and Atmospheric Sciences (SoMAS) at Stony Brook University, and published in Science Advances, found that Hurricane. Ecol Econ 85:105115, Schreck CJ, Knapp KR, Kossin JP (2014) The impact of best track discrepancies on global tropical cyclone climatologies using IBTrACS. Sci Rep 9(1):20452322. There are two important points to note about this tropical cyclone damage variable. To the best of my knowledge, this is the first paper that analyzes global sectoral interactions after the occurrence of a tropical cyclone. 2012), and the higher exposure of people in large urban agglomerations near oceans (World Bank 2010), the overall damage and the number of people affected by tropical cyclones have been increasing since the 1970s (Guha-Sapir and CRED 2020). The results indicate that the policies should focus on the direct costs of tropical cyclones. This allows me to identify which of the competing hypothesesbuild-back-better, recovery to trend, or no recoveryis appropriate for which sector. 1.Environment . 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. This suggests that the production chains of the economy are only slightly disrupted by tropical storms, and indirect impacts are thus negligible. Furthermore, the results of the randomization test show that the \(H_0\) of no effect of tropical cyclone damage can be rejected at the 1% and 5% level of confidence for the agriculture, hunting, forestry, and fishing and wholesale, retail trade, restaurants, and hotels sectors, respectively.

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