Abed, G.T., 1998. Governance issues and transition economies. IMF, May 27-28, Challenges to Economies in Transition: Stabilization, Growth, and Governance” Bishkek, Kyrgyz Republic May 27–28, 1998.
Acemoğlu, D. and J.A. Robinson, 2012. Why nations fail: The origins of power. 1st Edn., London: Crown Publishers.
Andrijauskas, K., 2013. Chinaʼs economic penetration into post-soviet central Asia and Eastern Europe. Lithuanian Foreign Policy Review, 30: 113-131. Retrieved from http://lfpr.lt/wp-content/uploads/2015/09/LFPR-30-Andrijauskas.pdf.
Cihangir, D., 2011. AB Aday ve Potansiyel Aday Ülkelerinin 2011 İlerleme Raporları Hakkında Değerlendirme. İktisadi Kalkınma Vakfı. Retrieved from www.ikv.org.tr.
Eurasıan, 2016. Retrieved from http://www.eurasiancommssion.org/.
Freedom House, 2014. Freedom house in the world 2014. Retrieved from https://freedomhouse.org/sites/default/files/Eurasia%20Fact%20Sheet.pdf.
Hair, J.F., W.C. Black, B.J. Babin and R.E. Anderson, 2009. Multivariate data analysis. 7th Edn., London, UK: Prentice Hall.
Johnson, C., 2002. Democratic transition in the Balkans: Romania's Hungarian and Bulgaria's Turkish minority (1989–99). Nationalism and Ethnic Politics, 8(1): 1-28. View at Google Scholar | View at Publisher
Kooiman, J., 1993. Modern governance: New government-society interactions. London: Sage.
Maldona, N., 2010. The world bank's evolving concept of good governance and its impact on human rights. Doctoral Workshop on Development and International Organizations, Stockholm, Sweden.
Mikheev, S., 2006. Post-soviet space: Elites are against integration. Postsovetskoje Prostranstvo: Elity Protiv Integracii.
Mikhnovets, I., 2015. Moldova, Ukraine and Georgia: What has been done after the decisive Eastern partnership summit in vilnius in 2013. Austria Institut für Europa- Und Sıcherheitspolitik. Retrieved from https://www.aies.at/download/2015/AIES-Fokus-2015-04.pdf.
Mukhamedzhanova, D., 2007. Economic preconditions of regional integration in the post-soviet space. Journal of Kazakhstan in the Global Processes, 4: 138-149. View at Google Scholar
North, D., 1990. Institutions, institutional change and economic performance. 2nd Edn., Cambridge: Cambridge University Press.
Rodrik, D., 2007. One economics, many recipes: Globalization, institutions, and economic growth. 1st Edn., United Kingdom: Princeton University Press.
Unlukaplan, I., 2011. Multivariate investigation of governance indicators in European Union. Journal of US-China Public Administration, 8(1): 66-76.
Unlukaplan, I. and E. Canıkalp, 2015. Determination of Turkey's quality of governance position by world bank governance indicators: Cluster analysis. Marmara University Journal of Economic & Administrative Sciences, 37(2): 409-427.
Yuksel, M., 2000. Yönetişim Kavramı Üzerine. Ankara Barosu Dergisi, 58(3): 145-159. View at Google Scholar
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(2017). Specifying Quality of Governance in Transition Economies with Cluster Analysis. Journal of Social Economics Research, 4(1): 1-8. DOI: 10.18488/journal.35.2017.41.1.8
With the collapse of Soviet Russia, transition of communist countries towards the market economy not only caused an economic transformation but also formal and informal constraints, institutional structures and legal norms in society were changed. IMF's and World Bank’s reports and governance concept containing neoliberal policies that took place in World Bank’s publications were important factors behind this transition. In this study, it is aimed to analyze quality of governance in transition economies by the year 2014. With this framework, Cluster analysis is performed by Ward (1963) Minimum Variance Method by using World Bank Governance and Freedom House dataset.
This paper contributes to the literature by determination of transition economies’ position in terms of their governance scores in a multivariate framework. The results of Cluster analysis indicate that countries in the process of integration with the EU have better governance scores with respect to other transition economies.
Interfaces Between Road Infrastructure and Poverty in Africa: The Case of Malawi, 1994-2013
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
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.
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
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., 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
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.
(2017). Interfaces Between Road Infrastructure and Poverty in Africa: The Case of Malawi, 1994-2013. Journal of Social Economics Research, 4(1): 9-21. DOI: 10.18488/journal.35.2017.41.9.21
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.
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.