Urban Geographical Economics and per Capita GDP Growth in Romania

Conflicts in the form of civil war, ethnic tensions and political discord are of enduring concern and a major bottleneck to economic development in Sri Lanka. Three decades of civil war and unethical political culture have caused severe economic problems for the country, including slower rate of growth and a huge defence expenditure. The aim of this study is to examine the effect of military expenditure and conflict on per capita GDP growth rate in Sri Lanka from 1973 to 2014 using the Solow growth model and ARDL bounds test approach. The results of the bounds test are highly significant and lead to cointegration. The negative and significant coefficients of the error correction term illustrate the expected convergence process in the long-run dynamic of per capita GDP. The estimated empirical results show that, the coefficients of military expenditure and conflict are negative and statistically significant in the short-run as well as in the long-run in determining per capita GDP growth rate in Sri Lanka. Hence, it is critically important to take necessary action to decrease military expenditure and provide an efficient political solution to the problem of minorities, specifically in the post-war period.

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The Impact of Infrastructure on Growth in Developing Countries

Advances in Finance, Accounting, and Economics - Handbook of Research on Economic, Financial, and Industrial Impacts on Infrastructure Development ◽

10.4018/978-1-5225-2361-1.ch003 ◽

2017 ◽

pp. 40-68 ◽

Cited By ~ 2

Author(s):

Derya Yılmaz ◽

Işın Çetin

Keyword(s):

Developing Countries ◽

Instrumental Variables ◽

Dynamic Panel Data ◽

Gdp Growth ◽

Per Capita Gdp ◽

Gdp Growth Rate ◽

Generating Capacity ◽

Catch Up ◽

Per Capita ◽

The Impact

Infrastructure and growth nexus has been debated in the literature since 1980s. This debate has a vital importance for the sake of developing countries. These countries need to grow faster in order to catch-up their advanced counterparts. Thus, it is important to detect the effect of infrastructure on growth. Bearing in mind this fact, we develop a standard growth regression in this present chapter using per capita GDP growth rate as a dependent variable. Infrastructure is added to the model as an index constructed from the indicators of infrastructure: total electric generating capacity, total telephone lines and the length of road network. We also employ set of instrumental variables comprising 29 developing countries between 1990 and 2014. In order to estimate our dynamic panel data we prefer GMM estimators. According to our empirical analysis, we can claim that infrastructure has a positive and significant impact on growth. But this impact is smaller than the earlier studies predict.

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