GROWTH EXTERNALITIES ON THE ENVIRONMENTAL QUALITY INDEX OF EAST JAVA INDONESIA, SPATIAL ECONOMETRICS MODEL OF STIRPAT

  • Rahma Fitriani Department of Statistics, University of Brawijaya, Indonesia
  • Herman Cahyo Diartho Department of Economics Development, University of Jember, Indonesia
  • Septya Hadiningrum Department of Statistics, University of Brawijaya, Indonesia
Keywords: environmental quality, externalities, spatial econometrics, STIRPAT

Abstract

East Java has shown strong economic growth, which negatively affects its environmental quality. Analysis of the functional relationship between economic growth and environmental quality is important to direct the growth without further deteriorate the environmental quality in this area. It is assumed that growth produces some externalities on environmental quality. The spread of technological information, economic productivity, population growth or investment, can be the source of the growth externalities. The objective of this study is to test the significance of the involved growth externalities on East Java’s environmental quality. Using spatial data, the externalities are accommodated in a spatial version of the STIRPAT model. It is estimated using per city/regency 2015 data. The analysis indicates that local density, local agricultural productivity, neighboring density, and neighboring mining activity significantly affect the local environmental quality. The latter two are the main sources of the growth externalities.

Downloads

Download data is not yet available.

References

Anselin, L. (2001). Spatial effects in econometric practice in environmental and resource economics. American Journal of Agricultural Economics, 83: 705–710.

Anselin, L. (2013). Spatial econometrics: methods and models. Springer Science & Business Media.

Arbia, G. (2014). A primer for spatial econometrics: with applications in R. Springer.

Bargaoui, S. A., Liouane, N., & Nouri, F. Z. (2014). Environmental impact determinants: An empirical analysis based on the STIRPAT model. Procedia-Social and Behavioral Sciences, 109(2): 449–458.

[BI] Bank Indonesia. (2017). Laporan Perekonomian Indonesia tahun 2017. Jakarta (ID): Bank Indonesia.

Bockstael, N. E. (1996). Modeling Economics and Ecology: The Importance of a Spatial Perspective. American Journal of Agricultural Economics, 78: 1168–1180.

[BPS] Badan Pusat Statistik. (2017). Produk Domestik Regional Bruto Provinsi Jawa Timur Menurut Lapangan Usaha 2012-2016. Jakarta (ID): Badan Pusat Statistik.

Ehrlich, P. R., & Holdren, J. P. (1971). Impact of population growth. Science, New Series, 171: 1212–1217.

Elhorst, J. P. (2014a). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Dordrecht. Springer Briefs in Regional Science.

Elhorst, J. P. (2014b). Spatial panel data models. In Spatial econometrics (pp. 37–93). Springer.

Ertur, C., & Koch, W. (2007). Growth, technological interdependence and spatial externalities: theory and evidence. Journal of Applied Econometrics, 22: 1033–1062.

Fingleton, B., & López-Bazo, E. (2006). Empirical growth models with spatial effects*. Papers in Regional Science, 85: 177–198.

Fitriani, R., & Syukrilla, W. (2017). Growth Externalities on the Environmental Quality Index of East Java Indonesia, Spatial Econometrics Model. Proceeding Regional Statistics Conference, 20–24. Denpasar (ID): International Statistical Institute.

Gujarati, D. N. (2003). Basic econometrics. Boston (US): McGraw Hill.

Hao, Y., Wu, Y., Wang, L., & Huang, J. (2018). Re-examine environmental Kuznets curve in China: Spatial estimations using environmental quality index. Sustainable Cities and Society, 42: 498–511.

[KLH] Kementerian Lingkungan Hidup dan Kehutanan. (2016). Indeks Kualitas Lingkungan Hidup Indonesia 2016. Jakarta (ID): Kementerian Lingkungan Hidup dan Kehutanan.

Lesage, J. P., & Pace, R. K. (2009). Introduction to spatial econometrics. Boca Raton (US): CRC Press.

Liddle, B. (2013). Population, affluence, and environmental impact across development: Evidence from panel cointegration modeling. Environmental Modelling & Software, 40: 255–266.

Liu, Y., Xiao, H., Zikhali, P., & Lv, Y. (2014). Carbon emissions in China: a spatial econometric analysis at the regional level. Sustainability, 6: 6005–6023.

Mankiw, N. G. (2014). Essentials of economics. Cengage learning.

Roberts, T. D. (2011). Applying the STIRPAT model in a post-Fordist landscape: Can a traditional econometric model work at the local level? Applied Geography, 31: 731–739.

Shahbaz, M., Loganathan, N., Sbia, R., & Afza, T. (2015). The effect of urbanization, affluence and trade openness on energy consumption: A time series analysis in Malaysia. Renewable and Sustainable Energy Reviews, 47: 683–693.

Tian, L., Wang, H. H., & Chen, Y. (2010). Spatial externalities in China regional economic growth. China Economic Review, 21.

Videras, J. (2014). Exploring spatial patterns of carbon emissions in the USA: a geographically weighted regression approach. Population and Environment, 36: 137–154.

Wang, S., Fang, C., & Wang, Y. (2016). Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data. Renewable and Sustainable Energy Reviews, 55: 505–515.

Wang, W., & Yu, J. (2015). Estimation of spatial panel data models with time varying spatial weights matrices. Economics Letters, 128: 95–99.

York, R., Rosa, E. A., & Dietz, T. (2003). STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecological Economics, 46: 351–365.

Zhu, Q., & Peng, X. (2012). The impacts of population change on carbon emissions in China during 1978-2008. Environmental Impact Assessment Review, 36: 1–8.

Published
2020-02-28
How to Cite
Fitriani, R., Diartho, H., & Hadiningrum, S. (2020). GROWTH EXTERNALITIES ON THE ENVIRONMENTAL QUALITY INDEX OF EAST JAVA INDONESIA, SPATIAL ECONOMETRICS MODEL OF STIRPAT. Indonesian Journal of Statistics and Its Applications, 4(1), 216-233. https://doi.org/10.29244/ijsa.v4i1.628
Section
Articles