•  
  •  
 

Abstract

Poverty is a key issue in various developing countries, including Indonesia. One of the efforts to reduce poverty is building the infrastructure. Therefore, this study aims to determine the effect of infrastructure on the level of poverty by considering the spatial effect in the period 2011-2015. This study applies spatial panel data analysis with Spatial Autoregressive (SAR) model with fixed effect. The findings show that the infrastructure of electricity, health, sanitation, and building of senior high school has a significant negative impact on the percentage of the underprivileged people. Meanwhile, the building of elementary school has a significant positive impact on the percentage of the underprivileged people.

References

[1] Adams, RH 2003, ‘Economic growth, inequality, and poverty: Finding from a new data set’, Policy Research Working Paper 2972, Poverty Reduction and Economic Management Network, The World Bank. http://siteresources.worldbank.org/INTPGI/Resources/ 14021_WPS_2972_adams.pdf.

[2] ADB 2012, Infrastructure for supporting inclusive growth and poverty reduction in Asia, Asian Development Bank. https://www.adb.org/sites/default/files/publication/ 29823/infrastructure-supporting-inclusive-growth.pdf.

[3] Ali, I & Pernia, EM 2003, ‘Infrastructure and poverty reduction–What is the connection?’ ERD Policy Brief Series 13, Economics and Research Department, Asian Development Bank. https://www.adb.org/sites/default/files/ publication/28071/pb013.pdf.

[4] Anselin, L 1988, Spatial econometrics: Methods and models, Kluwer Academic Publisher, Dordrecht.

[5] Bappenas 2014, ‘Arah Kebijakan Penanggulangan Kemiskinan Jangka Menengah 2015-2019’, Direktorat Penanggulangan Kemiskinan, Kementerian Perencanaan Pembangunan Nasional/Badan Perencanaan Pembangunan Nasional (Bappenas).

[6] Bosch, C, Hommann, K, Rubio, G, Sadoff, C, & Travers, L 2001, ‘Water and Sanitation’, in J Klugman (Ed.) A sourcebook for poverty reduction strategies, Volume 2: Macroeconomic and sectoral approaches, pp. 371–404, World Bank, Washington, DC. http://documents.worldbank.org/curated/ en/681651468147315119/pdf/298000v-2.pdf.

[7] BPS 2008, Analisis dan penghitungan tingkat kemiskinan 2008, Central Bureau of Statistics, Jakarta.

[8] BPS 2011, Analisis dampak spasial pada peramalan perekonomian dan ketenagakerjaan provinsi, Central Bureau of Statistics, Jakarta.

[9] BPS 2013, Statistik Indonesia 2013, Central Bureau of Statistics, Jakarta.

[10] BPS 2015, Statistik Indonesia 2015, Central Bureau of Statistics, Jakarta.

[11] Dollar, D & Kraay, A 2002, ‘Growth is good for the poo’, Journal of Economic Growth, 7(3), pp.195-225. DOI: https://doi.org/10.1023/A:1020139631000.

[12] Elhorst, JP 2014, Spatial econometrics: from crosssectional data to spatials panel, Springer, Groningen.

[13] Estache, A, Foster, V & Wodon, Q 2002, Accounting for poverty in infrastructure reform: Learning from Latin America’s experience, WBI Development Studies, World Bank Institute, Washington, D.C. http://documents.worldbank.org/ curated/en/413901468758394547/pdf/multi0page.pdf.

[14] Haughton, J & Khandker, SR 2009, Handbook on poverty and inequality, The World Bank, Washington, DC. siteresources.worldbank.org/INTPA/Resources/ 429966-1259774805724/Poverty_Inequality_Handbook_ FrontMatter.pdf.

[15] Humantito, IJ 2009, ‘Analisis keterkaitan ketersediaan infrastruktur terhadap kemiskinan di Indonesia (Model regresi data panel 26 provinsi tahun 2001–2007)’, Tesis, Magister Perencanaan dan Kebijakan Publik Universitas Indonesia, Jakarta.

[16] Maryaningsih, N, Hermansyah, O & Savitri, M 2014, ‘Pengaruh infrastruktur terhadap pertumbuhan ekonomi Indonesia’, Buletin Ekonomi Moneter dan Perbankan, 17(1), pp.6298. DOI: https://doi.org/10.21098/bemp.v17i1.44.

[17] Nugraheni, D & Priyarsono, DS 2012, Kinerja keuangan daerah, infrastruktur, dan kemiskinan: Analisis kabupaten/kota di Indonesia 2006-2009’, Jurnal Ekonomi dan Pembangunan Indonesia, 12(2), pp.148–167. DOI: https://doi.org/10.21002/jepi.v12i2.495.

[18] OECD 2016, Survei Ekonomi OECD INDONESIA: Ikhtisar, Organisation for Economic Co- operation and Development, accessed on February 27, 2018 https://www.oecd.org/eco/surveys/ indonesia-2016-OECD-economic-survey-overview-bahasa. pdf.

[19] PT SMI 2017, SMI’s Insight 2017 - 4th Quarter, PT Sarana Multi Infrastruktur (Persero), accessed on March 23, 2018, https://www.ptsmi.co.id/wp-content/uploads/2018/03/ SMI_Insight_Q4_2017_ENG.pdf.

[20] Rahmawati, R, Safitri, D, & Fairuzdhiya, OU 2015, ‘Analisis spasial pengaruh tingkat pengangguran terhadap kemiskinan di Indonesia (Studi kasus Provinsi Jawa Tengah)’, Media Statistika, 8(1), pp.23–30. DOI: https://doi.org/10.14710/medstat.8.1.23-30.

[21] TNP2K 2011, Sensus infrastruktur, Tim Nasional Percepatan Penanggulangan Kemiskinan, Jakarta.

[22] UNDP 1997, Human development report 1997, United Nations Development Programme, New York, http://hdr.undp.org/sites/default/files/reports/258/hdr_ 1997_en_complete_nostats.pdf.

[23] UNDP 2016, Human development report 2016: Human development for everyone, United Nations Development Programme, New York. http://hdr.undp.org/sites/default/files/ 2016_human_development_report.pdf.

[24] World Bank 1994, World Development Report 1994: Infrastructure for Development, World Bank, New York. https://openknowledge.worldbank.org/bitstream/ handle/10986/5977/WDR%201994%20-%20English.pdf? sequence=2&isAllowed=y.

Bahasa Abstract

Kemiskinan merupakan salah satu masalah yang dihadapi oleh banyak negara berkembang, termasuk Indonesia. Salah satu upaya untuk mengatasi kemiskinan adalah dengan membangun infrastruktur. Dalam penelitian ini akan dilihat pengaruh infrastruktur terhadap tingkat kemiskinan di Indonesia dengan mempertimbangkan pengaruh spasial pada periode 2011–2015. Penelitian ini menggunakan metode analisis spasial data panel, yaitu model Spatial Autoregressive (SAR) dengan fixed effect. Hasil penelitian menunjukkan bahwa infrastruktur listrik, kesehatan, sanitasi, dan gedung SMA/SMK/MA berpengaruh signifikan dan negatif terhadap persentase penduduk miskin. Adapun gedung SD/MI berpengaruh signifikan dan positif terhadap persentase penduduk miskin.

Download

Share

COinS