Abstract
References
- Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS, (pp. 111–125). London, UK: Taylor&Francis
- Anselin, L. and Bera, A. (1998). Spatial Dependence in Linear Regression Models with An Introduction to Spatial Econometrics. In Ullah, A. and Giles,D. E., editors, Handbook of Applied Economic Statistics, 237–289. Marcel Dekker, New York
- Anselin L., Bera, AK., Florax, R., Yoon, M.J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26(1):77-104
- Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. London, UK: Pion.
- Darmofal, D. (2006). Spatial Econometrics and Political Science, In: Annual Meeting of Southern Political Science Association, Atlanta, GA, January:2006.
- Elhorst, J. P. (2011). Spatial Panel Data Models. In Handbook of Applied Spatial Analysis, edited by M. M. Fischer and A. Getis, pp. 377–407. Berlin, Germany: Springer
- Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques. Springer Science& Business Media
- Gumprecht, D. (2007). Spatial Methods in Econometrics: An Application to R&D Spillovers. WU Vienna University of Economics and Business, Doctoral Dissertation, (Online) http://epub. wu.ac.at/290/1/document.pdf
- Lesage, J. P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo, Ohio.
- Vega, Solmaria H., J. Paul ELHORST.(2013). “On Spatial Econometric Models, Spillover Effects, and W”, 53rd ERSA
- Congress, Palermo, Italy. http://www.sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA 2013_paper_00222.pdf (çevrimiçi)
- Wong, A. D., & Lee, J. (2005). Statistical analysis of geographic information with ArcView and ArcGIS. John Wiley&Sons, Inc Hoboken, NJ.
Abstract
References
- Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS, (pp. 111–125). London, UK: Taylor&Francis
- Anselin, L. and Bera, A. (1998). Spatial Dependence in Linear Regression Models with An Introduction to Spatial Econometrics. In Ullah, A. and Giles,D. E., editors, Handbook of Applied Economic Statistics, 237–289. Marcel Dekker, New York
- Anselin L., Bera, AK., Florax, R., Yoon, M.J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26(1):77-104
- Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. London, UK: Pion.
- Darmofal, D. (2006). Spatial Econometrics and Political Science, In: Annual Meeting of Southern Political Science Association, Atlanta, GA, January:2006.
- Elhorst, J. P. (2011). Spatial Panel Data Models. In Handbook of Applied Spatial Analysis, edited by M. M. Fischer and A. Getis, pp. 377–407. Berlin, Germany: Springer
- Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques. Springer Science& Business Media
- Gumprecht, D. (2007). Spatial Methods in Econometrics: An Application to R&D Spillovers. WU Vienna University of Economics and Business, Doctoral Dissertation, (Online) http://epub. wu.ac.at/290/1/document.pdf
- Lesage, J. P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo, Ohio.
- Vega, Solmaria H., J. Paul ELHORST.(2013). “On Spatial Econometric Models, Spillover Effects, and W”, 53rd ERSA
- Congress, Palermo, Italy. http://www.sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA 2013_paper_00222.pdf (çevrimiçi)
- Wong, A. D., & Lee, J. (2005). Statistical analysis of geographic information with ArcView and ArcGIS. John Wiley&Sons, Inc Hoboken, NJ.
Abstract
ABSTRACT
Climate change and global warming have been at the forefront of the world's agenda in recent years. The change, that could not be noticed, before has turned into a global phenomenon and has become visible. The global increase in surface temperatures has started to affect the socioeconomic life of people directly and indirectly, deteriorating the balance of the ecosystem, rising sea level, shrinking the areas of snow and ice cover by melting, and the rapid increase of epidemic diseases. Regardless of the level of development, this transformation process has brought serious economic costs on economies. This phenomenon, which puts pressure on the world economy in different dimensions, has led economies to create new environmental policies from an international perspective to a national one and even from local to regional in recent years. In this context, in this study, it is aimed to make a spatial analysis on the effect of environmental expenditures made by local governments and their work on hazardous substance disposal on air quality. The study was based on 2019 and the spatial distribution of the variables was aimed to be revealed with the help of LISA statistics. The study is based on 81 provinces. In addition, in the study, the effect of the variables on the air quality for 2019 with spatial data analysis was determined according to the appropriate model, so the effects of the expenditures and activities on the air quality were evaluated and the results were desired to be revealed.
Key Words: Global Warming, Climate Change, Local Governments, Spatial Analysis
JEL Classification: M31, Q20,Q30
References
- Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS, (pp. 111–125). London, UK: Taylor&Francis
- Anselin, L. and Bera, A. (1998). Spatial Dependence in Linear Regression Models with An Introduction to Spatial Econometrics. In Ullah, A. and Giles,D. E., editors, Handbook of Applied Economic Statistics, 237–289. Marcel Dekker, New York
- Anselin L., Bera, AK., Florax, R., Yoon, M.J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26(1):77-104
- Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. London, UK: Pion.
- Darmofal, D. (2006). Spatial Econometrics and Political Science, In: Annual Meeting of Southern Political Science Association, Atlanta, GA, January:2006.
- Elhorst, J. P. (2011). Spatial Panel Data Models. In Handbook of Applied Spatial Analysis, edited by M. M. Fischer and A. Getis, pp. 377–407. Berlin, Germany: Springer
- Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques. Springer Science& Business Media
- Gumprecht, D. (2007). Spatial Methods in Econometrics: An Application to R&D Spillovers. WU Vienna University of Economics and Business, Doctoral Dissertation, (Online) http://epub. wu.ac.at/290/1/document.pdf
- Lesage, J. P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo, Ohio.
- Vega, Solmaria H., J. Paul ELHORST.(2013). “On Spatial Econometric Models, Spillover Effects, and W”, 53rd ERSA
- Congress, Palermo, Italy. http://www.sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA 2013_paper_00222.pdf (çevrimiçi)
- Wong, A. D., & Lee, J. (2005). Statistical analysis of geographic information with ArcView and ArcGIS. John Wiley&Sons, Inc Hoboken, NJ.
Abstract
References
- Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS, (pp. 111–125). London, UK: Taylor&Francis
- Anselin, L. and Bera, A. (1998). Spatial Dependence in Linear Regression Models with An Introduction to Spatial Econometrics. In Ullah, A. and Giles,D. E., editors, Handbook of Applied Economic Statistics, 237–289. Marcel Dekker, New York
- Anselin L., Bera, AK., Florax, R., Yoon, M.J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26(1):77-104
- Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. London, UK: Pion.
- Darmofal, D. (2006). Spatial Econometrics and Political Science, In: Annual Meeting of Southern Political Science Association, Atlanta, GA, January:2006.
- Elhorst, J. P. (2011). Spatial Panel Data Models. In Handbook of Applied Spatial Analysis, edited by M. M. Fischer and A. Getis, pp. 377–407. Berlin, Germany: Springer
- Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques. Springer Science& Business Media
- Gumprecht, D. (2007). Spatial Methods in Econometrics: An Application to R&D Spillovers. WU Vienna University of Economics and Business, Doctoral Dissertation, (Online) http://epub. wu.ac.at/290/1/document.pdf
- Lesage, J. P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo, Ohio.
- Vega, Solmaria H., J. Paul ELHORST.(2013). “On Spatial Econometric Models, Spillover Effects, and W”, 53rd ERSA
- Congress, Palermo, Italy. http://www.sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA 2013_paper_00222.pdf (çevrimiçi)
- Wong, A. D., & Lee, J. (2005). Statistical analysis of geographic information with ArcView and ArcGIS. John Wiley&Sons, Inc Hoboken, NJ.
Türkiye’de Çevre Harcamalarının İklim Değişikliği Üzerindeki Etkisinin Mekânsal Veri Analizi ile Modellenmesi
Abstract
ÖZ
Son yıllarda iklim değişikliği ve küresel ısınma dünya gündeminin ilk sıralarında yer alan konuların başında gelmektedir. Daha önceleri fark edilemeyen değişim küresel bir olguya dönüşerek gözle görülür bir hal almıştır. Yüzey sıcaklıkların küresel boyutta artış göstermesi ekosistemin dengesinin bozulmasına, deniz seviyesinin yükselmesine, kar ve buz örtüsünün eriyerek alanlarının daralmasına, salgın hastalıkların hızla artmasına doğrudan ve dolaylı olarak insanların sosyoekonomik yaşamını etkilemeye başlamıştır. Bu dönüşüm süreci gelişmişlik düzeyi ne olursa olsun, ekonomiler üzerinde ciddi maliyetleri de beraberinde getirmiştir. Dünya ekonomisine farklı boyutta baskı uygulayan bu olgu son yıllarda ekonomileri uluslararası perspektiften ulusal boyuta hatta yerelden bölgesele yeni çevre politikaları oluşturmasına yönlendirmiştir. Çalışmada Türkiye’de yerel yönetimler tarafından gerçekleştirilen çevre harcamalarının ve tehlikeli madde bertarafına yönelik yaptıkları çalışmaların hava kalitesi üzerinde nasıl bir etki oluşturduğu konusunda mekânsal bir analiz yapılmıştır. Çalışmada 2019 yılı esas alınmış ve değişkenlerin mekânsal dağılımı LİSA istatistiği yardımıyla ortaya koyulmuştur. Çalışma 81 ili esas alınmıştır. Ayrıca çalışmada mekânsal veri analizi ile değişkenlerin 2019 yılı için hava kalitesine etkisi uygun model belirlenmiştir. Elde edilen sonuçlara göre yerel yönetimler tarafından yapılan çevre harcamalarının hava kalitesini olumsuz yönde etkilediği, iklim değişikliği farkındalığının yüksek olmadığı sonucuna ulaşılmıştır.
Anahtar Kelimeler: Küresel Isınma, İklim Değişikliği, Yerel Yönetimler, Mekânsal Analiz
JEL Sınıflandırması: M31, Q20, Q30
Keywords
iKLİM DEĞİŞİKLİĞİ YEREL YÖNETİMLER MEKANSAL ANALİZ Global Warming Climate Change Local Governments Spatial Analysis
References
- Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS, (pp. 111–125). London, UK: Taylor&Francis
- Anselin, L. and Bera, A. (1998). Spatial Dependence in Linear Regression Models with An Introduction to Spatial Econometrics. In Ullah, A. and Giles,D. E., editors, Handbook of Applied Economic Statistics, 237–289. Marcel Dekker, New York
- Anselin L., Bera, AK., Florax, R., Yoon, M.J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26(1):77-104
- Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. London, UK: Pion.
- Darmofal, D. (2006). Spatial Econometrics and Political Science, In: Annual Meeting of Southern Political Science Association, Atlanta, GA, January:2006.
- Elhorst, J. P. (2011). Spatial Panel Data Models. In Handbook of Applied Spatial Analysis, edited by M. M. Fischer and A. Getis, pp. 377–407. Berlin, Germany: Springer
- Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques. Springer Science& Business Media
- Gumprecht, D. (2007). Spatial Methods in Econometrics: An Application to R&D Spillovers. WU Vienna University of Economics and Business, Doctoral Dissertation, (Online) http://epub. wu.ac.at/290/1/document.pdf
- Lesage, J. P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo, Ohio.
- Vega, Solmaria H., J. Paul ELHORST.(2013). “On Spatial Econometric Models, Spillover Effects, and W”, 53rd ERSA
- Congress, Palermo, Italy. http://www.sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA 2013_paper_00222.pdf (çevrimiçi)
- Wong, A. D., & Lee, J. (2005). Statistical analysis of geographic information with ArcView and ArcGIS. John Wiley&Sons, Inc Hoboken, NJ.
Details
| Primary Language | Turkish |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | December 29, 2022 |
| Published in Issue | Year 2022 Volume: 29 Issue: 4 |
