The Impact of Climate Change on Tourism Economies

Transcription

1 The Impact of Clmate Change on Toursm Economes Workng Paper Seres December 2011 Dng Du Assstant Professor of Economcs Northern Arzona Unversty The W. A. Franke College of Busness 20 McConnell Dr Flagstaff, AZ Pn Ng Professor of Economcs Northern Arzona Unversty The W. A. Franke College of Busness 20 McConnell Dr Flagstaff, AZ

2 The Impact of Clmate Change on Toursm Economes 1. Introducton Recreaton and toursm s one of the largest economc actvtes of the world, some even say t s the largest. (Bgano et al., 2007, p.147). For some economes such as Greece, Span and Turkey, toursm s consdered to be partcularly mportant for promotng economc growth (e.g. Gunduz and Hatem-J, 2005). Toursm s obvously hghly senstve to clmate change snce clmate defnes the length and qualty of toursm seasons, affects toursm operatons, and nfluences envronmental condtons that both attract and deter vstors (UNWTO, 2009, p.2). Therefore, wth mountng evdence n support of the noton of clmate change, 1 an mportant queston s: What s the mpact of clmate change on toursm economes such as Greece, Span and Turkey? One lne of extant research focuses on the mpact of clmate change on the toursm ndustry. For nstance, Ceron and Dubos (2000) show that mountanous parts of France, Italy and Span could become more popular because of ther relatve coolness. Hamlton et al. (2005) show that global warmng may have small mpact on global toursm. Taylor (2009) fnds that there s lkely to be ncreased domestc toursm as a result of clmate change. 2 Another lne of exstng research concentrates on the relatonshp between the toursm ndustry and economc growth, testng the toursm-led growth hypotheses. Researchers have found evdence suggestng that toursm can lead to economc growth (e.g. Balaguer and Cantavella-Jorda, 2002; Drtsaks, 2004; Lanza et al., 2003; Eugeno-Martn and Morales, 2004; Gunduza and Hatem-J, 2005; Proença and Soukazs, 2008; and Brda et al., 2010 among others). However, to the best of our knowledge, there s no research that combnes these two lnes of research and studes the mpact of clmate change on economc growth of toursm economes. Ths paper ntends to fll ths gap. In ths paper, we focus on the relatonshp between temperature (a proxy for clmate change) and GDP per capta (a proxy of economc growth) n a reduced-form framework. We could use a structural approach to model the mpact of clmate change on toursm economes. However, a major challenge of ths approach s ts complexty: UNWTO (2009) ponts out that the effects of clmate change on toursm are complex ncludng drect effects as well as ndrect effects; furthermore, how the toursm ndustry affects growth s also unsettled n terms of theory. 3 In contrast, the cross-sectonal relatonshp between temperature and GDP per capta motvates a smple reduced-form approach, and s ganng popularty n the area of clmate-change research. Two promnent examples of usng ths approach to estmate the mpact of clmate change are Horowtz (2009) and Ng and Zhao (2010). Emprcally, we adopt the model n Ng and Zhao (2011) to estmate the relatonshp between temperature and GDP per capta for toursm economes as well as for all countres n our sample, the G-7 countres and a group of developng countres. Based on the parameter estmates, we then calculate the economc mpacts of clmate change on dfferent types of economes. Our major fndng s that clmate change s negatve mpact on toursm economes s not smaller than ts mpact on other types of economes f temperature ncreases by more than 1 degree Celsus. Therefore, our fndngs suggest that toursm economes should also mplement aggressve clmate mtgaton polcy. The remander of the paper s organzed as follows: Secton 2 dscusses our data and model, Secton 3 reports our emprcal results and Secton 4 concludes the manuscrpt. 1 In ts most comprehensve scentfc assessment of clmate change, Intergovernmental Panel on Clmate Change (IPCC) concludes that Warmng of the clmate system s unequvocal (IPCC, 2007, Workng Group I Report Summary for Polcymakers, p. 5). 2 See also Agnew and Vner (2001), Elsasser and Burk (2002), Becken (2005) and Ceron and Dubos (2005). 3 Current research focuses on emprcally testng the toursm-led-growth hypothess. 1

3 2. Data and Methodology Data We use a geophyscally-scaled economc data set (G-Econ) constructed by Nordhaus (2006). The G-Econ data compute varables at a 1-degree longtude by 1-degree lattude resoluton at a global scale. 4 As a result, we are able to perform cell-level analyss of the relatonshp between temperature and GDP per capta n contrast to a majorty of the other studes whch use country-level data. There are several advantages of usng cell-level data as compared to country-level data. Frst of all, cell-level data makes temperature measurement more meanngful as Nordhaus (2006) argues that for many countres, averages of most geographc varables (such as temperature or dstance from seacoast) cover such a huge area that they are vrtually meanngless, whereas for most grd cells the averages cover a reasonably small area. (Page 3511) Furthermore, usng cell-level data ncreases the number of useful observatons from around 100 countres to about 16,500 terrestral cells and, hence, allows us to captalze on the potentally hgher accuracy of the estmatons. Fnally, havng multple observatons per country enables us to control for factors that are unque to ndvdual countres, whch s mportant n our model specfcaton. The G-Econ data set contans measurement of GDP on grdded output, gross cell product (GCP), whch s smlar to the gross domestc product (GDP) as developed n the natonal ncome accounts, except that the geographc entty of the lattude-longtude grd cell s used nstead of poltcal boundares. The earth contans 64,800 such grd cells, of whch 27,445 observatons have reasonably complete data on clmate, populaton, and output for 248 countres. After removng cells wth zero GCP, area, populaton and data lower than the best qualty, we are left wth 174 countres and 16,511 observatons. The 1990 output of all countres usng natonal aggregates estmated by the World Bank s converted nto a common metrc usng market exchange rates based on 1995 U.S. dollars. A full descrpton of the data and methods can be found at the project web ste ( Table 1 contans summary statstcs of the varables used n ths paper. Methodology Ng and Zhao (2010) propose a theoretcal model of temperature and GDP per capta, whch takes nto account the hstorcal as well as contemporaneous effects of temperature on GDP per capta. For more detals on the hstorcal as well as contemporaneous effects of temperature on ncome, see Acemoglu et al. (2002), Easterly and Levne (2002), Rodrk et al. (2004), Gallup et al. (1998), Mellnger et al. (2000), Gallup and Sachs (2001), Sachs and Malaney (2002), and Sachs (2003). The model n Ng and Zhao (2011), whch s based on a Cobb-Douglas type producton functon, specfes output per capta as: Y 2 3 log( ) d at 1 a2t a3t blog( P) (1) P where Y s the total ncome (output), P represents populaton, T s the temperature, s the row vector of country coeffcents for the column vector of country dummy varables d, and captures the effects of all other varables. To model potental nonlnear effects of temperature on ncome emprcally, ther model ncludes a cubc polynomal n temperature. As explaned by Ng and Zhao (2010), the hstorcal effect of temperature on ncome s captured by the productvty of dfferent countres approxmated by the country dummy varables d, whle the contemporaneous effect of temperature s modeled drectly as a cubc polynomal n Equaton (1). It s ths contemporaneous effect that s of nterest to us, because t s relevant for assessng the mpact of clmate change (see Horowtz, 2009, Ng and Zhao, 2011). 4 The sze of a cell depends on ts lattude. In our sample, the average sze of a cell s about 6,206 km 2. 2

4 Varable 1990 GCP (bllons of 1995 US$) 1990 Populaton (persons) Temperature (C 0 ), average Varable 1990 GCP (bllons of 1995 US$) 1990 Populaton (persons) Temperature (C 0 ), average Varable 1990 GCP (bllons of 1995 US$) 1990 Populaton (persons) Temperature (C 0 ), average Varable 1990 GCP (bllons of 1995 US$) 1990 Populaton (persons) Temperature (C 0 ), average Table 1 Summary statstcs Panel A: Toursm Economes n = 198 Abbrevaton Mean Medan Std. Dev. Mn Max n G-Econ MER1990_ POPGPW_1990_34 488, , ,844 4,944,755 TEMPAV_ Panel B: World n=16,511 Abbrevaton Mean Medan Std. Dev. Mn Max n G-Econ MER1990_ POPGPW_1990_ e e e e+07 TEMPAV_ Panel C: G-7 Countres n = 2,382 Abbrevaton Mean Medan Std. Dev. Mn Max n G-Econ MER1990_ POPGPW_1990_ e e e e+07 TEMPAV_ Panel D: Emergng Countres n = 6,703 Abbrevaton Mean Medan Std. Dev. Mn Max n G-Econ MER1990_ POPGPW_1990_ e e e e+07 TEMPAV_ Table 1 contans summary statstcs of the varables used n ths paper.

5 To estmate the mpact of clmate change, we follow Horowtz (2009) and Ng and Zhao (2011) and compute the effect of a temperature ncrease on the combned GCP of the relevant economes (holdng other relevant varables constant). More specfcally, based on the parameter estmates from Eq. (1), the estmated change n output per capta of a sngle cell observaton s computed usng the formula: aˆ1 T aˆ2 T1 T0 aˆ3 T1 T0 ˆ ˆ y y e 1 where log ˆ e y s the ftted value of log e Y P wth T 1 beng the new temperature, T 0 the current temperature and T T1 T0 the change n at T 0 n Eq. 1 temperature, and â 1, â 2 and â 3 are the estmated coeffcents of the polynomal n temperature. The total percentage change n output s then computed by yˆ P / yˆ P where the summaton s taken over all the cells of the relevant economes. We focus on three clmate change scenaros: a one, two or three-degree ncrease n temperature, because IPCC s best estmate for global average surface warmng at the end of the 21st century ranges from 1.8 C (wth 66 percent confdence nterval from 1.1 C to 2.9 C) to 4.0 C (wth 66 percent confdence nterval from 2.4 C to 6.4 C). 3. Emprcal Results Man results Emprcally, we focus on three major toursm economes: Greece, Span and Turkey (see Gunduz and Hatem-J, 2005). We estmate Eq. (1) usng the ordnary least-squares regresson for the three major toursm economes. For comparson, we also perform estmaton for all countres n our sample, the developed G-7 countres and a group of developng countres 5. The results are reported n panels A through D n Table 2. Based on the parameter estmates n Table 2, we calculate the economc mpacts of clmate change on dfferent types of economes. The estmated mpacts are reported n Table 3 as well as n Panels A through D n Fgure 1. In Fgures 1, the three horzontal lnes represent the mpacts of the onedegree (sold red horzontal lne), two-degree (dash red horzontal lne) and three-degree (dotted red horzontal lne) Celsus ncrease n temperature on combned GDP of dfferent types of economes (.e. toursm economes, all countres, the G7 countres and the emergng countres, respectvely). As we can see, the average mpact of a one degree Celsus ncrease n temperature on the three major toursm economes s slghtly smaller than that on other types of economes. However, the lower estmate of global warmng at the end of the 21st century of IPCC s 1.8 C. Therefore, t wll be more nformatve to focus on the mpacts when temperature ncreases by more than 1 C. As we can see from Table 3 as well as Fgure 1, f temperature ncreases by more than 1 C, the estmated mpacts of clmate change on toursm economes are not smaller than ts mpacts on other types of economes. Ths s the central fndng of the paper, whch suggests that toursm economes should also mplement aggressve clmate mtgaton polcy. 5 Russa, Czech Republc, Poland, Chle, Hungary, South Korea, Turkey, Chna, Peru, Mexco, Morocco, South Afrca, Brazl, Egypt, Colomba, Indonesa, Inda, Malaysa, Phlppnes and Thaland. 4

6 Fgure 1 Estmates of The Global Warmng Impact on Total Output for Greece, Span and Turkey. Panel A: Greece, Span and Turkey Panel B: All Countres Panel C: G-7 Countres Panel D: Developng Countres Panel E: Top 19 Toursm Countres Fgure 1 shows the estmated mpacts of one-, two- and three-degree ncreases n temperature on the total GCP of relevant economes. The horzontal lnes are the ordnary least-squares estmated mpacts, whle the curves are the quantle regresson estmated mpact on the -th quantle of the total GCP of relevant economes. 5

7 Table 2 Ordnary Least-squares Estmates of the Temperature-Income Relaton Panel A: Greece, Span, Turkey (-0.89%) T T 2 T 3 Log(P) R 2 Coeffcent t-statstcs Panel B: World T T 2 T 3 Log(P) R 2 Coeffcent t-statstcs Panel C: G-7 Countres T T 2 T 3 Log(P) R 2 Coeffcent t-statstcs Panel D: Emergng Countres T T 2 T 3 Log(P) R 2 Coeffcent t-statstcs Panel E: Top 19 Toursm Economes T T 2 T 3 Log(P) R 2 Coeffcent t-statstcs Table 3 Global warmng mpact estmates 1 degree 2 degrees 3 degrees Greece, Span, Turkey -0.89% -2.82% -5.37% World -1.29% -2.46% -3.51% G-7 countres -1.50% -2.61% -3.32% Emergng countres -1.40% -2.72% -3.95% Top 19 toursm economes -0.88% -2.01% -3.38% Robustness check If Eq. (1) has mssng varables or our data have outlers or exhbt heteroskedastcty, the ordnary least-squares estmates n Table 2 would not be relable. The p-value of the Breusch-Pagan test for heteroskedastcty for the three major toursm economes, all the countres, the G7 countres and the emergng countres are essentally zero. Hence, there s strong evdence of volaton of the assumpton of homoskedastc varance n the classcal lnear regresson model. We, therefore, utlze the quantle regresson nvented by Koenker and Bassett (1978) to re-estmate Eq. (1). The quantle regresson along wth the ordnary least-squares regresson estmates of the slope coeffcents for log P and the three temperature polynomal coeffcents are presented n Fgures 2 through 5 for the three major toursm economes, all countres, the G7 countres and the emergng countres, respectvely. As we can see, there s strong evdence of heteroskedastcty n the regresson quantle coeffcents. 6

8 Fgure 2 Quantle Regresson and Ordnary Least-squares Regresson Estmates of the Slope Coeffcents for log P and the Temperature Polynomal for Greece, Span and Turkey. 7

9 Fgure 3 Quantle Regresson and Ordnary Least-squares Regresson Estmates of the Slope Coeffcents for log P and the Temperature Polynomal for All Countres. 8

10 Fgure 4 Quantle Regresson and Ordnary Least-squares Regresson Estmates of the Slope Coeffcents for log P and the Temperature Polynomal for the G7 Countres. 9

11 Fgure 5 Quantle Regresson and Ordnary Least-squares Regresson Estmates of the Slope Coeffcents for log P and the Temperature Polynomal for the Emergng Countres. 10

12 Based on our quantle regresson estmated coeffcents, we calculate and report the mpacts of the one-degree (sold black curve), two-degree (dash black curve) and three-degree (dotted black curve) Celsus ncrease n temperature on the -th quantle of the GCP for 0.1,0.9 n 0.1 ncrements n Fgure 1. Although there s clear quantle effect on the estmated changes n GCP over the dfferent quantles, the general pattern s consstent wth the OLS results. That s, n general, clmate change s mpact on toursm economes s not smaller than ts mpact on other types of economes f temperature ncreases by more than 1 degree Celsus. Therefore, our fndngs suggest that toursm economes should also mplement aggressve clmate mtgaton polcy. Turkey, Greece and Span may not be representatve of toursm economes, snce toursm as a percentage of GDP s stll relatvely small for these three economes. We, therefore, also look at a sample of the top 19 toursm economes 6 that have the hghest nternatonal toursm recept as a percentage of GDP as reported at NatonMaster.com (2011). The regresson result s reported n Panel E of Table 2, whle the mpact estmates are presented n Table 3 as well as n Panel E of Fgure 1. We can see, n general, temperature ncrease also has sgnfcantly negatve mpacts on these economes. Therefore, our man fndngs n Tables 2 and 3 are robust. Concluson Some economes such as Greece, Span and Turkey depend partcularly on toursm for promotng economc growth (e.g. Gunduz and Hatem-J, 2005). Toursm s obvously hghly senstve to clmate change. Therefore, wth mountng evdence n support of the noton of clmate change, an mportant queston s: What s the mpact of clmate change on toursm economes such as Greece, Span and Turkey? Prevous studes focus on ether the mpact of clmate change on the toursm ndustry or the mpact of the toursm ndustry on economc growth. To the best of our knowledge, no research has combned these two lnes of research and looks at the mpact of clmate change on economc growth of toursm economes. Ths paper ntends to fll ths gap. We use a model n Ng and Zhao (2011) to estmate the economc mpacts of clmate change on dfferent types of economes. Our man fndng s that clmate change s mpact on toursm economes s not smaller than ts mpact on other types of economes f temperature ncreases by more than 1 degree Celsus. Therefore, our fndngs suggest that toursm economes should also mplement aggressve clmate mtgaton polcy. 6 Only 19 of the top 29 natons lsted at NatonMaster.com have qualty GEcon data for the varables n Equaton (1) and they are Albana, Bahamas, Belze, Bulgara, Camboda, Cape Verde, Croata, Fj, French Polynesa, Gamba, Jamaca, Jordan, Lebanon, Luxembourg, Maurtus, Mongola, Morocco, Samoa, and Vanuatu. 11

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