Conscientia Beam || conscientiabeam.com

Export to

Citations

Contact Us

For Marketing, Sales and Subscriptions Inquiries

2637 E Atlantic Blvd #43110
Pompano Beach, FL 33062

USA

Conference List

Journal of Social Economics Research

March 2017, Volume 4, 1, pp 9-21

Interfaces Between Road Infrastructure and Poverty in Africa: The Case of Malawi, 1994-2013

Abdi-Khalil Edriss

Cliff Chiunda

Abdi-Khalil Edriss¹

Cliff Chiunda²

Lilongwe University of Agriculture and Natural Resources (LUANAR) Bunda Campus, Lilongwe, Malawi ¹

Ministry of Economic Planning and Development, Lilongwe, Malawi ²

on Google Scholar

on PubMed

Pages: 9-21

DOI: 10.18488/journal.35.2017.41.9.21

Article History:

Received: 04 November, 2016
Revised: 10 February, 2017
Accepted: 08 March, 2017
Published: 24 April, 2017

View Citation

936Views

Create Citation Alert

Abstract:

Critical assessment on the correlation between public investment on road infrastructure and poverty was carried out, and therefore this research paper provides an in depth analyses of the linkage between road infrastructure and poverty, as well as, other relevant macro-economic variables used in the Malawi Growth and Development Strategy (MGDS) as target indicators. Using primary and secondary data from 1994-2013, dynamic time series models were applied in elaborating the various factors with thrust on road infrastructure that may influence poverty in Malawi. Noting poverty reduction as priority of Malawi Government’s development agenda since the early 1990s, MGDS provides the country’s socioeconomic growth and development platforms. According to the latest 2010 Integrated Household Survey (IHS3), the majority of Malawians (50.7 percent) are languishing in abysmal poverty; this level is remotely far from the MDGS target of 27 percent by end 2015. The country has a high inequality index (Gini 0.38) reflecting profound inequalities in access to assets, services and opportunities across the population. The distribution of the benefits of economic growth is also important for the alleviation of poverty. However, the distribution of income and wealth are highly skewed, with a majority of the population living in a state of absolute poverty. Based on NSO surveys (1998-2010), the poorest 20 percent of the population control only around 10 percent of national consumption implying inequality is not decreasing at all for long time. Hosts of factors explaining why poverty level continues to be rampant are: share of agricultural as a percent of GDP (proxy to agricultural production) and export as percent of GDP (proxy to exports). However, this paper findings show that there is significant (p=0.000<0.05) relationship between road network and poverty levels. Estimates from Granger Causality analysis indicate that for one percent increase in road network, a reduction of 7.2 percent in poverty level is perhaps achievable. Average inflation rate over the last 20 years stands at 22.41 percent, and this has an immense impact on poverty level since it dramatically reduces the purchasing power of the majority of the population. For a one percent increase in the inflation rate, there is a consequence of about 3.7 percent increase in the average poverty level. Average Gross Domestic Product (GDP) growth rate is 4.7 percent annually with a minimum of -4.9 percent and a maximum of 10.2 percent in the last 20 years. Poverty level appears to significantly respond to (GDP). There is a 4.27 percent reduction in poverty level if a one percent GDP increment takes place as shown in the dynamic time series analysis. In fact, the declining of agricultural production for export and the growing gap in balance of payment (average Malawi Kwacha -498.92 billion or approximately US$-1.1 billion) would immensely influence GDP negatively and therefore poverty becomes abysmal as GDP growth plummets. In a nutshell, the findings confirm that in the long run economic growth is the key to alleviation of extreme poverty since it creates the resources to raise incomes. Given the importance of agriculture in contributing towards GDP in Malawi, the positive impact that this sector has on poverty is evident. For agriculture to meaningfully impact economic growth, road infrastructure plays a great role. Other pro-poor variables such as development roads and other investment on infrastructure are vital for economic growth and hence poverty alleviation.

Contribution/ Originality
This study is one of the few studies which have analyzed the influences of road infrastructure on poverty in Malawi. It also demonstrates how road infrastructure development enhances economic growth, which is the engine of combating poverty in Malawi. It, in fact, investigated the links between various economic growth variables, road infrastructure development and alleviation of poverty in Malawi, as a whole.

Keywords:

Infrastructure, Vector autoregression, Granger causality, Public investment, Poverty, Malawi

Video:

Download Video

Download Audio

Reference:

Adikins, L. and R.C. Hill, 2011. Principles of econometrics. New York: John Wiley & Sons, Inc.

African Development Bank, 2013. Group Malawi Country Strategy Paper 2013-2017. Lilongwe, Malawi. Retrieved from www.mwnation.com/afdb-approves-new-strategy-for-malawi .

Ali, I. and E.M. Pernia, 2003. Infrastructure and poverty reduction. What is the connection? ERD policy brief. Asian Development Bank. ERD Policy Brief No. 13, Manila, Philipines.

Amisano, G. and C. Giannini, 1997. Topics in structural VAR econometrics. 2nd Edn., Berlin: Springer.

Arellano, M. and O. Bover, 1995. Another look at the instrumental variable estimation of. Error-components models. Journal of Econometrics, 1(68): 29-51. View at Google Scholar | View at Publisher

Datt, G. and M. Ravallion, 2002. Has India’s post-reform economic growth left the poor behind. Journal of Economic Perspectives, 16(3): 89-108. View at Google Scholar

Dufour, J.M. and E. Renault, 1998. Short run and long run causality in time series. Theory. Econometrica, 66(5): 1099–1125. View at Google Scholar | View at Publisher

Fan, S., P. Hazell and S. Thorat, 2000. Government spending, growth, and poverty in rural India. American Journal of Agricultural Economics, 82(4): 1038-1051.View at Google Scholar | View at Publisher

Fan, S., N. Rao and X. Zhang, 2004. Public expenditure, growth, and poverty reduction in rural Uganda. International Food Policy Research Institute, DSGD Discussion Paper No. 4.

Gachassin, M., B. Najman and G. Raballand, 2010. Roads impact on poverty reduction: A Cameroon case study. World Bank Poicy Working Paper Series, No. 5209.

Ghura, D., C. Leite and C.G. Tsangarides, 2002. Is growth enough? Macroeconomic policy and poverty reduction IMF Working Paper No. 02/118.

Gramlich, E.M., 1994. Infrastructure investment: A review essay. Journal of Economic Literature, 32(3): 1176–1196. View at Google Scholar

Granger, C.W.J., 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3): 424–438. View at Google Scholar | View at Publisher

Lütkepohl, H., 2005. New introduction to multiple time series analysis. Berlin: Springer.

Ministry of Economic Planning and Development (MEPD), 2007-2013. Annual Economic Reports. Government of Malawi, Lilongwe.

Munnell, A.H., 1992. Policy watch: Infrastructure investment and economic growth. Journal of Economic Perspectives, 6(4): 189-198. View at Google Scholar

Mustajab, M., 2009. Infrastructure investment in Indonesia: Process and impact. Unpublished PhD Thesis. Groningen, Netherlands.

National Roads Authority (NRA), 2011. Roads Authority Annual Report. Lilongwe, Malawi.

National Statistical Office, 2005. Malawi Demographic and Health Survey 2004. Zomba, Malawi. Retrieved from http://www.dhsprogram.com/ .

NSO, 1991. Malawi Demographic and Health Survey 1990. Zomba, Malawi.

NSO, 1999/2000. Malawi Demographic and Health Survey 1998. Zomba, Malawi.

NSO, 2012. Welfare Monitoring Survey 2011. Zomba, Malawi. Retrieved from www.nsomalawi/component/content/.../194-welfare-monitoring-survey2011 .

Ogun, T.P., 2010. Infrastructure and poverty reduction implications for urban development in Nigeria. Working Paper No. 2010/43.

Oraboune, S., 2008. Infrastructure (Rural Road) development and poverty alleviation I Lao PDR. National Economic Research Institute, Lao. Discussion paper No. 151, Institute of Development Economies, Chiba 261-8545, Japan: 2-75.

Perron, P., 1990. Testing for a unit root in a time series with a changing mean. Journal of Business & Economic Statistics, 8(2): 153–162. View at Google Scholar | View at Publisher

Ramirez, M.D., 2004. Is public infrastructure spending productive in the mexican case? A vector error correction analysis. Journal of International Trade and Economic Development, 13(2): 159–178. View at Google Scholar | View at Publisher

Ravallion, M. and G. Datt, 1996. How important to India’s poor Is the sectoral composition of economic growth? World Bank Economic Review, 10(1): 1-25.View at Google Scholar | View at Publisher

Romp, W. and J. De-Haan, 2005. Public capital and economic growth: A critical survey. EIB Papers, 10(1): 40–93. View at Google Scholar

Saikkonen, P. and H. Lütkepohl, 2002. Testing for a unit root in a time series with a level shift at unknown time. Econometric Theory 18(2): 313–348.View at Google Scholar | View at Publisher

Sarte, P.G., 1997. On the identification of structural vector autoregressions. Federal Reserve Bank of Richmond Economic Quarterly, 83/3.

Seeanah, Ramessur and Rojid, 2009. Does infrastructure alleviate poverty in developing countries? International Journal of Applied Econometrics and Quantitative Studies, 6(2): 31-36. View at Google Scholar

Seetanah, B., 2012. Transport investment and poverty reduction: The African experience using dynamic panel data estimates. International Journal of Innovations in Business, 1(1): 60. View at Google Scholar

Sims, C.A., 1980a. Macroeconomics and reality. Econometrica, 48(1): 1-48. View at Google Scholar

Sims, C.A., 1980b. Comparison of interwar and postwar business cycles: Monetarism reconsidered. American Economic Review, 70(2): 250-257. View at Google Scholar

Sturm, J.E., G.H. Kuper and J. De-Haan, 1998. Modelling government investment and economic growth on a macro level: A review. In S. Brakman, H. van Ees & S. K. Kuipers (Eds.), Market Behaviour and Macroeconomic Modelling. London: Macmillan Press Ltd.

Toda, H.Y. and P.C.B. Phillips, 1993. Vector autoregression and causality. Econometrica, 61(6): 1367–1393. View at Google Scholar

Toda, H.Y. and P.C.B. Phillips, 1994. Vector autoregression and causality: A theoretical overview and simulation study. Econometric Review, 13(2): 259–285. View at Google Scholar | View at Publisher

UN Habitat, 2011. Infrastructure for economic development and poverty reduction in Africa. Nairobi: United Nations Human Settlements Programme.

Wooldridge, J.M., 2002. Econometric analysis of cross section and panel data. Cambridge: The MIT Press.

World Bank, 2006. Malawi country assistance evaluation. Report No. 36862. Independent Evaluation Group. Washington, D. C.

World Bank, 2006. Malawi country assistance evaluation. Report No. 36862. Washington, D. C.

World Bank, 2010. Africa Infrastructure Country Diagnostic (AICD); Malawi’s Infrastructure: A Continental Perspective. Washington, D.C. Retrieved from documents.worldbank.org/curated/en/.../malawi-infrustructure-a-continental-perspective.

World Bank, 2013. Implementation completion and result report. Report No. ICR2467, Infrastructure Services Project, Urban Development and Services Practice, Country Department, Africa Region.

Statistics:

Search :

Funding:

The study was funded by German Development Cooperation (GIZ) on behalf of Malawi Government under PFEM project. The preparations of the final report and finally this extraction of this article would not have been possible without the support and valuable contributions of several individuals, panel of experts and organizations.

Competing Interests:

The authors declare that they have no competing interests.

Acknowledgement:

The author would like to thank significantly the nucleus team from GIZ, Mrs Sook-Jung Dofel (PFEM Team Leader), Dr. Alfred Nyasulu (Deputy Advisor) and Mr. Daniel Schmidt (Junior Advisor) for their significant role, relentless support and advices in the co