Skip to main content

Advertisement

SpringerLink
Log in

Imperial Manila syndrome in poverty reduction: a province-level spatial distribution analysis

  • Article
  • Published:
Asia-Pacific Journal of Regional Science Aims and scope Submit manuscript

Abstract

The Philippines is an insular geography stretching nearly 2000 km from north to south, and has been beset with serious spatial poverty imbalances since its independence. This study comprehensively examined the provincial-level spatial poverty distribution for the years 2000–2018 by applying various spatial distribution analysis methods. Our conventional inequality measures showed an average significant poverty reduction and substantial inter-provincial poverty reduction gaps for the study period. The growth incidence curve revealed that the poverty gap increase was mainly attributable to the provinces with less (more) serious poverty, experiencing more (less) poverty reduction. Considering the island-province hierarchical regional structure, the one-stage Theil decomposition analysis indicated a substantial increase in inter-island components playing a major role in influencing the overall inter-provincial poverty gaps. This result differs from the findings of many existing regional income inequality studies that show the inter-group component plays a minor role. Our club convergence analysis identified six clubs and showed the provinces with higher poverty incidences are in the Mindanao Island, especially in the Autonomous Region of Muslim Mindanao. Whereas the lower poverty incidences are in the Luzon Island, especially Manila and its neighboring cities and provinces. This core–periphery structure infers capital city bias, referred to as the “Imperial Manila Syndrome” (IMS). We verified that the IMS structure became more serious during the study period. Therefore, region-specific government interventions and inter-governmental coordination are needed for balanced poverty reduction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

All data are available from the corresponding author on request.

Code availability

All codes are available from the corresponding author on request.

Notes

  1. Poverty headcount ratio is also called as poverty incidence.

  2. See Akita and Pagulayan (2014) for the summary of the existing studies about regional income inequality in the Philippines.

  3. The term “serious poverty” in this article means the higher poverty incidence.

  4. The nonlinear time-varying factor model is also called as the nonlinear dynamic factor model.

  5. See Mendez and Kataoka (2021) and Mendez (2020) for comprehensive discussions about club convergence.

  6. The phenomenon where no provinces are formed into any group may be termed as “no local convergence” or “divergence”.

  7. Given our province-level dataset (n = 81), the local convergence clubs can be formed, ranging between 0 and 40 clubs.

  8. The new name of ARMM is Bangsamoro Autonomous Region in Muslim Mindanao (BARMM).

  9. Tawi-Tawi is one of the richest fisheries in the Philippines, particularly in seaweed. Sharing the sea borders with Indonesia and Malaysia, the province is known as a “front door” to other ASEAN countries. Cross-border trading between Tawi-Tawi and Malaysia has taken place for centuries (International Alert 2006).

  10. The figure uses population density as a proxy for urbanization. The top-end presence like NCR could be observed in other developed countries and regions, such as London. See Brandily et al. (2022) for its role among OECD metro areas and NUTS3.

References

  • Aginta H, Gunawan AB, Mendez C (2020) Regional income disparities and convergence clubs in Indonesia: new district-level evidence. J Asian Pac Econ. https://doi.org/10.1080/13547860.2020.1868107

    Article  Google Scholar 

  • Akita T, Kataoka M (2022) Regional inequality and development: measurement and applications in Indonesia. Springer, Singapore

    Book  Google Scholar 

  • Akita T, Pagulayan MS (2014) Structural changes and interregional income inequality in the Philippines, 1975–2009. Rev Urb Reg Dev Stud 26(2):135–154

    Article  Google Scholar 

  • Albert JRG (2007) Household vulnerability to income poverty (No. PIDS No. 2007–05). Philippines Institute for Development Studies, Makati City, p 6

  • Almaden CRC (2015) Asset-based determinants of poverty intensity: a meso-level application in the Philippines. WSEAS Trans Bus Econ 12:88–98

    Google Scholar 

  • Asian Development Bank (2009) Poverty in the Philippines: causes, constraints, and opportunities. Asian Development Bank, Mandaluyong City, Philippines

  • Balisacan A (2011) What has really happened to poverty in the Philippines? New measures, evidence, and policy implications UPSE Discussion Paper: 2011–14

  • Balisacan AM, Fuwa N (2003) Growth, inequality and politics revisited: a developing-country case. Econ Lett 79(1):53–58. https://doi.org/10.1016/S0165-1765(02)00287-2

    Article  Google Scholar 

  • Balisacan AM, Fuwa N (2004a) Going beyond cross-country averages: growth, inequality and poverty reduction in the Philippines. World Dev 32(11):1891–1907. https://doi.org/10.1016/j.worlddev.2004.05.010

    Article  Google Scholar 

  • Balisacan A, Fuwa N (2004b) Changes in spatial income inequality in the Philippines. United Nations WIDER Research Paper: 2004b/34. UNU-WIDER, Helsinki, Finland

  • Balisacan A, Hill H, Piza S (2008) Regional development dynamics and decentralization in the Philippines: ten lessons from a ‘fast starter.’ ASEAN Econ Bull 25:293–315. https://doi.org/10.1355/ae25-3d

    Article  Google Scholar 

  • Brandily P, Distefano M, Donnat H, Overman HG, and Shah K (2022) Bridging the gap: What would it take to narrow the UK’s productivity disparities? The Economy 2030 Inquiry

  • Barrios MC, Jandrić M, Molnar D, Tanasković S (2021) Convergence clubs in different regions of Serbia. Appl Econ Lett 28(7):594–598. https://doi.org/10.1080/13504851.2020.1765960

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (1992) Convergence. J Polit Econ 100(2):223–251. https://doi.org/10.1086/261816

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (1995) Economic growth. McGraw Hill, New York, NY

    Google Scholar 

  • Capuno JJ (2017) Violent conflicts in ARMM: probing the factors related to local political, identity, and shadow-economy hostilities. UP School of Economics Discussion Papers 201707, University of the Philippines School of Economics

  • Clausen A (2010) Economic globalization and regional disparities in the Philippines. Singap J Trop Geogr 31:299–316. https://doi.org/10.1111/j.1467-9493.2010.00405.x

    Article  Google Scholar 

  • Du K (2017) Econometric convergence test and club clustering using Stata. Stata J 17(4):882–900. Retrieved from //<? echo(www) ?>.stata-journal.com/article.html?article=st0503

  • Federspiel, HM (1998) Islam and muslims in the southern territories of the Philippine islands during the American Colonial Period (1898–1946). J Southeast Asian Studies, 29(2): 340–356. http://www.jstor.org/stable/20072050

  • Fujii T (2017) Dynamic poverty decomposition analysis: an application to the Philippines. World Dev 100:69–84. https://doi.org/10.1016/j.worlddev.2017.07.031

    Article  Google Scholar 

  • Galor O (1996) Convergence? Inferences from theoretical models. Econ J 106(437):1056–1069. https://doi.org/10.2307/2235378

    Article  Google Scholar 

  • Gerson P (1998) Poverty, income distribution, and economic policy in the Philippines. IMF Working Paper, WP/98/20, Washington DC

  • Gozgor G, Lau CKM, Lu Z (2019) Convergence clustering in the Chinese provinces: new evidence from several macroeconomic indicators. Rev Dev Econ 23:1331–1346. https://doi.org/10.1111/rode.12590

    Article  Google Scholar 

  • Hirschman A (1959) The strategy of economic development. WW Norton & Company, New York

    Google Scholar 

  • International Alert (2006) Local business, local peace: the peacebuilding potential of the domestic private sector. https://www.international-alert.org/publications/local-business-local-peace/ Accessed 20 Aug 2022

  • Kireyev A (2017) Inclusive growth: decomposition, incidence, and policies-lessons for Asia. Asian Development Bank Institute. Retrieved from http://hdl.handle.net/11540/7622

  • Kurita K, Kurosaki T (2011) Dynamics of growth, poverty and inequality: a panel analysis of regional data from Thailand and the Philippines. Asian Econ J 25(1):3–33

    Article  Google Scholar 

  • Kurniawan H, de Groot HLF, Mulder P (2019) Are poor provinces catching-up the rich provinces in Indonesia? Reg Sci Policy Prac. https://doi.org/10.1111/rsp3.12160

    Article  Google Scholar 

  • Manasan RG, Mercado R (1999) Regional economic growth and convergence in the Philippines: 1975–1997. Discussion Paper Series 1999–13, Philippine Institute of Development Studies, Manila, Philippines

  • Mendez C (2020) Convergence clubs in labor productivity and its proximate sources: evidence from developed and developing countries. Springer, Singapore. https://doi.org/10.1007/978-981-15-8629-3

    Article  Google Scholar 

  • Mendez C, Kataoka M (2021) Disparities in regional productivity, capital accumulation, and efficiency across Indonesia: a club convergence approach. Rev Dev Econ 5(2):790–809. https://doi.org/10.1111/rode.12726

    Article  Google Scholar 

  • Mendoza RU, Ocampo J (2017) Caught between imperial manila and the provincial dynasties: towards a new fiscal federalism. SSRN Electron J. https://doi.org/10.2139/ssrn.2883981

    Article  Google Scholar 

  • Mendoza RU, Beja EL, Venida VS, Yap DB (2016) Political dynasties and poverty: measurement and evidence of linkages in the Philippines. Oxford Dev Stud 44:189–201

    Article  Google Scholar 

  • Mendoza RU, Olfindo R, Maala CR (2017) Spatial disparities and poverty: the case of three provinces in the Philippines. In: Batabyal A, Nijkamp P (eds) Regional growth and sustainable development in Asia. New frontiers in regional science: Asian perspectives, vol 7. Springer, Switzerland, pp 23–40

    Chapter  Google Scholar 

  • Myrdal G (1957) Rich lands and poor. Harper and Row, New York

    Google Scholar 

  • Philippines Statistical Authorly (PSA) (2020) Philippine statistical yearbook (PSY). Philippines, Manila

    Google Scholar 

  • Phillips PCB, Sul D (2007) Transition modeling and econometric convergence tests. Econometrica 75(6):1771–1855. https://doi.org/10.1111/j.1468-0262.2007.00811.x

    Article  Google Scholar 

  • Phillips PCB, Sul D (2009) Economic transition and growth. J App Econ 24(7):1153–1185. https://doi.org/10.1002/jae.1080

    Article  Google Scholar 

  • Ravallion M, Chen S (2003) Measuring pro-poor growth. Econ Lett 78(1):93–99. https://doi.org/10.1016/S0165-1765(02)00205-7

    Article  Google Scholar 

  • Salvacion AR (2020) Spatial pattern and determinants of village level poverty in Marinduque Island Philippines. Geo J 85(1):257–267. https://doi.org/10.1007/s10708-018-9944-6

    Article  Google Scholar 

  • Tusalem RF (2020) Imperial Manila: how institutions and political geography disadvantage Philippine provinces. Asian J Comp Politics 5(3):235–269

    Article  Google Scholar 

  • Vista BM, Murayama Y (2011) Spatial determinants of poverty using GIS-based mapping. In: Murayama Y, Thapa RB (eds) Spatial analysis and modeling in geographical transformation process: GIS-based applications. Springer, Dordrecht Heidelberg London New York, pp 275–296. https://doi.org/10.1007/978-94-007-0671-2_16

    Chapter  Google Scholar 

  • Wallerstein I (1974) The modern world system I: capitalist agriculture and the origins of the European world-economy in the sixteenth century. Academic Press, New York

    Google Scholar 

  • World Bank (2018) Making growth work for the poor: a poverty assessment for the Philippines. Manila

  • Zhang W, Xu W, Wang X (2019) Regional convergence clubs in China: identification and conditioning factors. Ann Reg Sci 62(2):327–350. https://doi.org/10.1007/s00168-019-00898-y

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by Grant-in-Aid for Scientific Research C (17K03723) from the Japan Society of the Promotion of Science. I gratefully acknowledge the critical review by anonymous referees. The author is solely responsible for any remaining errors.

Funding

Funding information that explains whether and by whom the research was supported. This work was partially supported by Grant-in-Aid for Scientific Research C (17K03723) from the Japan Society of the Promotion of Science.

Author information

Authors and Affiliations

  1. College of Business, Rikkyo University, 3-34-1 Nishiikebukuro, Toshima-ku, Tokyo, 171-8501, Japan

    Mitsuhiko Kataoka

  2. Bank Executive Officer, Development Bank of the Philippines, Makati, Philippines

    Al-Ikram Taupan Darangina

Authors
  1. Mitsuhiko Kataoka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Al-Ikram Taupan Darangina
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mitsuhiko Kataoka.

Ethics declarations

Conflict of interest

To the best of our knowledge, the named authors have no conflict of interest, financial or otherwise.

Research involving human participants and/or animals

This article does not contain any studies involving human participants and/or animals performed by any of the authors.

Informed consent

This article does not contain any studies involving human participants performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 4 Poverty incidence and local convergence clubs for 81 provinces
Full size table
Table 5 The provincial shares for each club by island
Full size table

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kataoka, M., Darangina, AI.T. Imperial Manila syndrome in poverty reduction: a province-level spatial distribution analysis. Asia-Pac J Reg Sci 7, 1–28 (2023). https://doi.org/10.1007/s41685-023-00275-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41685-023-00275-w

Keywords

JEL Classification

Search

Navigation