AŞIRI HAVA KOŞULLARI VE TALEP: TÜRKİYE KLİMA PAZARI ÜZERİNE AMPİRİK BİR ÇALIŞMA

Yıl 2024, , 104 - 130, 03.10.2024

Mehmet Ali Soytas , Damla Durak Uşar

https://doi.org/10.11611/yead.1423671

Öz

Aşırı hava koşulları hem işletmeleri hem de tüketicileri önemli şekillerde etkileyebilir. Firmalar, üretim ve operasyonlardaki değişiklik ve kesintilerden etkilenebileceği gibi, tüketicilerin çeşitli mal ve hizmetlere olan talebinin aşırı hava koşulları nedeniyle değişmesi nedeniyle talep tepkisinden de etkilenebilir. Bu çalışmada Türkiye klima pazarı için aşırı sıcaklıklar ile klima talebi arasındaki karşılıklı bağımlılığın varlığı araştırılmaktadır. Türkiye'de klimalara olan talep hem demografik faktörler hem de kişi başına düşen GSYİH' deki hızlı artış nedeniyle son yıllarda artmaktadır. Ancak, büyümenin hızı tekdüze olmayıp, Türkiye'nin farklı bölgelerindeki farklı iklim ve sosyoekonomik koşulların varlığı nedeniyle büyük farklılıklar göstermektedir. Şehir düzeyindeki iklimsel ve sosyoekonomik farklılıkların yanı sıra zaman ve kesitsel farklılıkları da hesaba katmak için, dinamik bir sabit etki (DFE) modeli tahmin edilmiş ve aşırı hava koşullarının klima talebi üzerindeki kısa ve uzun vadeli etkilerini belirlemek için eş bütünleşme çerçevesi kullanılmıştır. Aşırı sıcak hava nedeniyle tüketici talebinin önemli ölçüde arttığı uzun vadeli denge etkisine dair güçlü kanıtlar bulunmuştur

Anahtar Kelimeler

ARDL Modeli, Aşırı Hava Koşulları, Dinamik Panel Veri Analizi, Talep

Etik Beyan

Çalışmamızda insan veya hayvan denek kullanılmamıştır. Bu sebeb ile deneysel araştırmalara ilişkin izin veya etik kurul onayına gereksinim duyulmamıştır.

EXTREME WEATHER AND DEMAND: AN EMPIRICAL STUDY OF TURKISH MARKET FOR AIR CONDITIONERS

Öz

Extreme weather can impact both businesses and consumers in significant ways. Firms can be affected through changes and disruptions in production and operations but can also be affected through the demand response as consumers’ demand for various goods and services changes due to extreme weather. We investigate the interdependence between the extreme temperatures and the AC demand. Demand for ACs in Turkey is growing in the last decades due to both demographic factors and an episode of rapid increase in the GDP per capita. However, the pace of the growth is not uniform and varies due to the existence of different climatic and socioeconomic conditions across different regions of Turkey. To reckon with time and cross-sectional variation as well as the city level climatic and socioeconomic differences, we estimate a dynamic fixed effect (DFE) model and use cointegration framework to identify short and long run effects of the extreme weather on the AC demand. We find strong evidence of a long run equilibrium effect where the consumer demand for ACs increases significantly due to extreme hot weather.

Anahtar Kelimeler

Auto regressive distributed lag model (ARDL), Demand, Dynamic Panel Estimation, Extreme Weather

Kaynakça

• Aragon, V., James, P.A.B. And Gauthier, S. (2022) “The Influence of Weather on Heat Demand Profiles in UK Social Housing Tower Blocks”, Building and Environment, 219: 109101. Doi: 10.1016/J.Buildenv.2022.109101
• Bigerna, S. (2018) “Estimating Temperature Effects on the Italian Electricity Market”, Energy Policy, 118: 257-269. Doi: 10.1016/J.Enpol.2018.03.068
• Blake, D., Dawson, C., Loeillet, D. and Staver, C. (2018) “Can Global Climate Change Affect Prices in The World Banana Market?”, German Journal of Agricultural Economics, 67(1): 48-64. Doi: 10.22004/Ag.Econ.309949
• Calkins, M.M., Isaksen, T.B., Stubbs, B.A., Yost, M. G. and Fenske, R. A. (2016) “Impacts of Extreme Heat on Emergency Medical Service Calls in King County, Washington, 2007–2012: Relative Risk and Time Series Analyses of Basic and Advanced Life Support”, Environmental Health, 15:13.
• Capari, L., Wilfing, H., Exner, A., Höflehner, T. and Haluza, D. (2022) “Cooling the City? A Scientometric Study on Urban Green and Blue Infrastructure and Climate Change-Induced Public Health Effects”, Sustainability, 14: 4929. Doi:10.3390/Su14094929
• Castaño-Rosa, R., Barrella, R., Sánchez-Guevara, C., Barbosa, R., Kyprianou, I., Paschalidou, E., Thomaidis, N.S., Dokupilova, D., Gouveia, J.P., Kádár, J., Hamed, T.A. and Palma, P. (2021) “Cooling Degree Models and Future Energy Demand in the Residential Sector. A Seven-Country Case Study”, Sustainability, 13: 2987. Doi: 10.3390/Su13052987
• Conradt, S., Finger, R. And Bokusheva, R. (2015) “Tailored to the Extremes: Quantile Regression for Index-Based Insurance Contract Design”, Agricultural Economics, 46: 537-547. Doi: 10.1111/Agec.12180
• Corbett P. And Tan, A. (2020) “Demand Orientation in A World of Demand Inertia. Deloitte Australia Blog”, Link: Https://Www2.Deloitte.Com/Au/En/Blog/Strategy-Blog/2020/Demand-Orientation-In-World-Of-Demand-Inertia.Html, (09/27/2022)
• De Cian, E., Pavanello, F., Randazzo, T., Mistry, M. N. and Davide, N. (2019) “Households’ Adaptation in A Warming Climate. Air Conditioning and Thermal Insulation Choices”, Environmental Science & Policy, 100: 136-157. Doi: 10.1016/J.Envsci.2019.06.015.
• Di Lascio, F.M.L., Menapace, A. and Righetti, M. (2020) “Joint and Conditional Dependence Modelling of Peak District Heating Demand and Outdoor Temperature: A Copula-Based Approach”, Statistical Methods & Applications, 29: 373–395. Doi:10.1007/S10260-019-00488-4
• Dogru, T., Marchio, E. A., Bulut, U. and Suess, C. (2019) “Climate Change: Vulnerability and Resilience of Tourism and the Entire Economy”, Tourism Management, 72: 292–305. Doi: 10.1016/J.Tourman.2018.12.010
• Fu, K.S., Allen, M.R. and Archibald, R.K. (2015) “Evaluating the Relationship Between the Population Trends, Prices, Heat Waves, And the Demands Of Energy Consumption In Cities”, Sustainability, 7: 15284-15301. Doi:10.3390/Su71115284
• Furuya, J., Mar, S.S., Hirano, A. and Sakurai, T. (2021) “Optimum Insurance Contract of Flood Damage Index Insurance for Rice Farmers in Myanmar”, Paddy and Water Environment, 19: 319–330. Doi:10.1007/S10333-021-00859-2
• Garrido-Perez, J.M., Barriopedro, D., García-Herrera, R. and Ordóñez, C. (2021) “Impact of Climate Change on Spanish Electricity Demand”, Climatic Change, 165: 50. Doi:10.1007/S10584-021-03086-0
• Gómez-Martín, M.B., Armesto-López, X.A. and Martínez-Ibarra, E. (2014) “The Spanish Tourist Sector Facing Extreme Climate Events: A Case Study of Domestic Tourism in the Heat Wave Of 2003”, International Journal of Biometeorology, 58: 781–797. Doi:10.1007/S00484-013-0659-6
• Government of Pakistan, National Disaster Management Authority, 2022, Daily Weather & Flood Situation Report Dated 20th September 2022. Link: Http://Cms.Ndma.Gov.Pk/Storage/App/Public/Situation-Reports/September2022/2rjgbn4gtvjgzoznyly0.Pdf, (09/27/2022)
• Gowdy, J. M. and Mayumi K. (2001) “Reformulating the Foundations of Consumer Choice Theory and Environmental Valuation”, Ecological Economics, 39 (2): 223-237. Doi:10.1016/S0921-8009(01)00197-5
• Gössling, S., Abegg, B. and Steiger, R. (2016) “It Was Raining All the Time! Ex Post Tourist Weather Perceptions”, Atmosphere, 7(1): 10. Doi:10.3390/Atmos7010010
• Guo, Y. (2017) “Hourly Associations Between Heat and Ambulance Calls”, Environmental Pollution, 220 (Pt B): 1424-1428. Doi: 10.1016/J.Envpol.2016.10.091
• Hadri, K. (2000) “Testing for Stationarity in Heterogeneous Panel Data”, Econometrics Journal, 3(2): 148-161. Doi: 10.1111/1368-423X.00043
• Hall, D. (2019) “Climate Explained: Why Some People Still Think Climate Change Isn’t Real”, Climate Explained, Link: Https://Theconversation.Com/Climate-Explained-Why-Some-People-Still-Think-Climate-Change-Isnt-Real-124763, (09/27/2022).
• Hands, D. W. (2010) “Economics, Psychology and the History of Consumer Choice Theory”, Cambridge Journal of Economics, 34(4): 633–648. Doi: 10.1093/CJE/BEP045
• Harish, S., Singh, N. and Tongia, R. (2020) “Impact of Temperature on Electricity Demand: Evidence from Delhi And Indian States”, Energy Policy, 140: 111445. Doi: 10.1016/J.Enpol.2020.111445
• Hasselqvist, H., Renström, S., Strömberg, H. and Håkansson, M. (2022) “Household Energy Resilience: Shifting Perspectives to Reveal Opportunities for Renewable Energy Futures in Affluent Contexts”, Energy Research & Social Science, 88: 102498. Doi: 10.1016/J.Erss.2022.102498
• Hübner, A. and Gössling, S. (2012) “Tourist Perceptions of Extreme Weather Events in Martinique”, Journal of Destination Marketing & Management, 1(1–2): 47-55. Doi: 10.1016/J.Jdmm.2012.09.0
• Kao, C. (1999) “Spurious Regression and Residual-Based Tests for Cointegration In Panel Data”, Journal of Econometrics, 90: 1-44. Doi: 10.1016/S0304-4076(98)00023-2
• Kayaga, S. M., Amankwaa, E. F., Gough, K. V., Wilby, R. L., Abarike, M. A., Codjoe, S. N. A., Kasei, R., Nabilse, C. K., Yankson, P. W. K., Mensah, P., Abdullah, K. and Griffiths, P. (2021) “Cities and Extreme Weather Events: Impacts Of Flooding And Extreme Heat On Water And Electricity Services In Ghana”, Environment And Urbanization, 33(1): 131–150. Doi:10.1177/0956247820952030
• Keleş, B., Gómez-Acevedo, P. and Shaikh, N. I. (2018) “The Impact of Systematic Changes in Weather on the Supply and Demand of Beverages”, International Journal of Production Economics, 195: 186-197. Doi: 10.1016/J.Ijpe.2017.08.002
• Komesaroff, P. and Kerridge, I. A. (2020) “Continent Aflame: Ethical Lessons from the Australian Bushfire Disaster”, Bioethical Inquiry, 17:11–14. Doi: 10.1007/S11673-020-09968-9
• Lam-González, Y.E., Galindo, C.G., Hernández, M.M.G. and León, C.J., (2021) “Understanding the Heterogeneity of Tourists’ Choices Under Climate Change Risks: A Segmentation Analysis”, Atmosphere, 12: 22. Doi:10.3390/Atmos12010022
• Lange, J. and Gillespie, J. (2022) “Bushfire, Prescribed Burning, and Non-Human Protection”, Geographical Research, 1– 24. Doi:10.1111/1745-5871.12558
• Lee, J. J., Gino, F. and Staats, B. R. (2014) “Rainmakers: Why Bad Weather Means Good Productivity”, Journal of Applied Psychology, 99 (3): 504-513. Doi:10.1037/A0035559
• Lee, J. (2022) “The Impact of Neglecting Climate Change and Variability on ERCOT’s Forecasts of Electricity Demand in Texas”, Weather, Climate, And Society, 14(2). Doi:10.1175/WCAS-D-21-0140.1
• Liu T-M. (2014) “Analysis of the Economic Impact of Meteorological Disasters on Tourism: The Case of Typhoon Morakot’s Impact on the Maolin National Scenic Area in Taiwan”, Tourism Economics, 20(1): 143-156. Doi:10.5367/Te.2013.0258
• Liu, X.-Q., Zhang, C., Zhou, Y. and Liao, H. (2021) “Temperature Change and Electricity Consumption of the Group Living: A Case Study of College Students”, Science of the Total Environment, 781: 146574.
• Lucas, C.H., Booth, K.I. and Garcia, C. (2021) “Insuring Homes Against Extreme Weather Events: A Systematic Review of the Research”, Climatic Change, 165: 61. Doi:10.1007/S10584-021-03093-1
• Lybbert, T.J., Smith, A. and Sumner, D.A. (2014) “Weather Shocks and Inter-Hemispheric Supply Responses: Implications for Climate Change Effects on Global Food Markets”, Climate Change Economics, 05: 1450010.
• Mackay, A. and Remer, M. (2019) “Consumer Inertia and Market Power”, Harvard Business School, Working Paper 19-111. Doi: 10.2139/Ssrn.3380390
• Moradi-Sepahvand, M., Amraee, T. and Gougheri, S. S. (2022) “Deep Learning Based Hurricane Resilient Coplanning of Transmission Lines, Battery Energy Storages, and Wind Farms”, IEEE Transactions on Industrial Informatics, 18(3): 2120-2131. Doi: 10.1109/TII.2021.3074397
• Najafabadi, S., Hamidi, A., Allahviranloo, M. and Devineni, N. (2019) “Does Demand for Subway Ridership in Manhattan Depend on the Rainfall Events?”, Transport Policy, 74: 201-213. Doi: 10.1016/J.Tranpol.2018.11.019.
• Oğur, A. A. and Baycan, T. (2022) “Assessing Climate Change Impacts on Tourism Demand in Turkey”, Environment, Development and Sustainability. Doi:10.1007/S10668-022-02135-7
• Pedroni, P. (1999) “Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors”, Oxford Bulletin of Economics and Statistics, 61: 653-670. Doi: 10.1111/1468-0084.0610s1653
• Pedroni, P. (2004) “Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with An Application to The PPP Hypothesis”, Econometric Theory, 20 (3): 597-625. Doi:10.1017/S0266466604203073
• Pesaran, M.H. and Shin, Y. (1998) “An Autoregressive Distributed-Lag Modelling Approach to Cointegration Analysis”, Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium, 31: 371-413. Doi:10.1017/CCOL0521633230.011
• Pesaran, M. H., Shin, Y. and Smith, R. P. (1997) “Estimating Long-Run Relationships in Dynamic Heterogeneous Panels”, DAE Working Papers Amalgamated Series, 9721.
• Pesaran, M. H., Shin, Y. and Smith, R. P. (1999) “Pooled Mean Group Estimation of Dynamic Heterogeneous Panels”, Journal of the American Statistical Association, 94: 621-634. Doi: 10.2307/2670182
• Pesaran, M. H. and Smith, R. P. (1995) “Estimating Long-Run Relationships from Dynamic Heterogeneous Panels”, Journal of Econometrics, 68: 79-113. Doi: 10.1016/0304-4076(94)01644-F
• Phillips, P. C. B. and Moon, H. R. (2000) “Nonstationary Panel Data Analysis: An Overview of Some Recent Developments”, Econometric Reviews, 19: 263-286. Doi: 10.1080/07474930008800473
• Sabir, M., Van Ommeren, J. and Rietveld, P. (2013) “Weather to Travel to the Beach”, Transportation Research Part A: Policy and Practice, 58, 79-86. Doi: 10.1016/J.Tra.2013.10.003
• Salamanca, F., Georgescu, M., Mahalov, A., Moustaoui, M., Wang, M. and Svoma, B. M. (2013) “Assessing Summertime Urban Air Conditioning Consumption in A Semiarid Environment”, Environmental Research Letters, 8 (3): 034022. Doi: 10.1088/1748-9326/8/3/034022
• Silva, S., Soares, I. and Pinho, C. (2020) “Climate Change Impacts on Electricity Demand: The Case of a Southern European Country”, Utilities Policy, 67: 101115. Doi: 10.1016/J.Jup.2020.101115
• Soyiri, I.N., Reidpath, D.D. and Sarran, C. (2013) “Forecasting Peak Asthma Admissions in London: An Application of Quantile Regression Models”, International Journal of Biometeorology, 57: 569–578. Doi:10.1007/S00484-012-0584-0
• Stone, J. (1954) “Linear Expenditure Systems and Demand Analysis: An Application to the Pattern of British Demand”, Economic Journal, 64: 511–527.
• Susanto, J., Zheng, X., Liu, Y. and Wang, C. (2020) “The Impacts of Climate Variables and Climate-Related Extreme Events on Island Country’s Tourism: Evidence from Indonesia”, Journal of Cleaner Production, 276: 124204. Doi: 10.1016/J.JCLEPRO.2020.124204
• Thornton, H.E., Scaife, A.A., Hoskins, B.J., Brayshaw, D.J., Smith, D.M., Dunstone, N., Stringer, N. and Bett, P. E. (2019) “Skilful Seasonal Prediction of Winter Gas Demand”, Environmental Research Letters, 14 (2): 024009. Doi:10.1088/1748-9326/Aaf338
• UNDRR (2020) “Human Cost of Disasters: An Overview of the Last 20 Years 2000-2019”, United Nations Office for Disaster Risk Reduction, Geneva, Switzerland.
• United Nations Environmental Programme (2004) “Impacts of Summer 2003 Heat Wave in Europe”, Environment Alert Bulletin, 2, 1-4.
• Van Der Wiel, K., Bloomfield, H., Lee, R., Stoop, L., Blackport, R., Screen, J. Et Al. (2019) “The Influence of Weather Regimes on European Renewable Energy Production and Demand”, Environmental Research Letters, 14 (9): 094010. Doi:10.1088/1748-9326/Ab38d3
• Wang,Y., Liu, Y., Ye, D., Li, N., Bi, P., Tong, S., Wang, Y., Cheng, Y., Li, Y. and Yao, X. (2020) “High Temperatures and Emergency Department Visits in 18 Sites with Different Climatic Characteristics In China: Risk Assessment and Attributable Fraction Identification”, Environment International, 136: 105486.
• Westerlund, J. (2005) “New Simple Tests for Panel Cointegration”, Econometric Reviews, 24 (3): 297-316. Williams, A., Mcdonogh‐Wong, L. and Spengler, J. D. (2020) “The Influence of Extreme Heat on Police and Fire Department Services In 23 U.S. Cities”, Geohealth, 4. Doi:10.1029/2020GH000282
• World Meteorological Organization (WMO) (2021) “Weather-Related Disasters Increase Over Past 50 Years, Causing More Damage but Fewer Deaths”, Link: Https://Public.Wmo.Int/En/Media/Press-Release/Weather-Related-Disasters-Increase-Over-Past-50-Years-Causing-More-Damage-Fewer 09/27/2022.
• Wu, J. and Liao, H. (2020) “Weather, Travel Mode Choice, and Impacts on Subway Ridership in Beijing”, Transportation Research Part A: Policy and Practice, 135: 264-279. Doi: 10.1016/J.Tra.2020.03.020
• Xia, T. and Li, X. (2010) “Consumption Inertia and Asymmetric Price Transmission”, Journal of Agricultural and Resource Economics, 35 (2): 209–227. Doi: 10.22004/Ag.Econ.93210
• Xiao, Y. and Yao, J. (2019) “Double Trigger Agricultural Insurance Products with Weather Index and Yield Index.”, China Agricultural Economic Review, 11 (2): 99-316. Doi:10.1108/CAER-01-2018-0021
• Yang, X., Yue, X., Sun, H., Gao, Z. and Wang, W. (2021) “Impact of Weather on Freeway Origin-Destination Volume in China”, Transportation Research Part A: Policy and Practice, 143: 30-47. Doi: 10.1016/J.Tra.2020.11.007
• Yue, X., Yang, X., Song, D. and Yuan, Y. (2022) “The Interaction Effect of Severe Weather and Non-Weather Factors on Freeway Travel Volume”, Science of the Total Environment, 808: 152057, Doi: 10.1016/J.Scitotenv.2021.152057
• Zanni, A. M., Goulden, M., Ryley, T. and Dingwall, R. (2017) “Improving Scenario Methods in Infrastructure Planning: A Case Study of Long Distance Travel and Mobility in the UK Under Extreme Weather Uncertainty and a Changing Climate”, Technological Forecasting and Social Change, 115: 180-197. Doi: 10.1016/J.Techfore.2016.10.002
• Zhang, X.-B., Sun, J., Fei, Y. and Wei, C. (2020) “Cooler Rooms on a Hotter Planet? Household Coping Strategies, Climate Change, and Air Conditioning Usage in Rural China”, Energy Research & Social Science, 68: 101605. Doi: 10.1016/J.Erss.2020.101605
• Zhang, S., Guo, Q., Smyth, R. and Yao, Y. (2022) “Extreme Temperatures and Residential Electricity Consumption: Evidence from Chinese Households”, Energy Economics, 107: 105890. Doi: 10.1016/J.Eneco.2022.105890
• Zhao Et Al. (2021) “Global, Regional, And National Burden of Mortality Associated with Non-Optimal Ambient Temperatures From 2000 To 2019: A Three-Stage Modelling Study”, The Lancet Planetary Health, 5(7): E415-E425.