Assessing the Importance of Infrastructure in Emerging Economies: A Cross-Country Study of Infrastructure and Income Inequality

Lead Author Major

Applied Economics

Format

Oral Presentation

Faculty Mentor Name

William Herrin

Faculty Mentor Department

Economics

Abstract/Artist Statement

Infrastructure is an integral aspect of a country’s development and may be used as an indicator of current and future economic success. In this paper, I investigate the relationship between the coverage of various equipment and structures that comprise a country’s infrastructure and GINI coefficients across countries. The GINI coefficient measures countries’ income inequality. My goal is to gauge if inequality can be explained by differences in infrastructure across countries. I use data from the World Bank, Infrastructure and Economy & Growth topics database. A multivariate regression analysis will be used to measure the relationship between GINI coefficients and infrastructure coverage across countries. I anticipate the findings to show a negative, linear relationship between the variables indicating as infrastructure coverage in a developing country increases, its GINI coefficient ought to decrease, showing movement towards a more equal dispersion of income. This result should occur as more individuals, especially rural residents, have access to structures and transportation which lead to additional income generating opportunities not available beforehand. Additionally, I will investigate the presence of non-linear relationships between infrastructure and GINI coefficients. Following the theory of immiserizing growth, or the theory that economic growth may hurt the developing countries rather than help, I will question if there is a point in emerging economies development where there may be too much infrastructure. If this occurs, I anticipate it to be much like a function of diminishing marginal returns, where additional infrastructure metrics may result in no change or an increase in the GINI coefficient as there may not be enough human capital available to allow it to impact the country’s dispersion of opportunities and income

Location

DeRosa University Center, Room 211

Start Date

30-4-2016 10:00 AM

End Date

30-4-2016 12:00 PM

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Apr 30th, 10:00 AM Apr 30th, 12:00 PM

Assessing the Importance of Infrastructure in Emerging Economies: A Cross-Country Study of Infrastructure and Income Inequality

DeRosa University Center, Room 211

Infrastructure is an integral aspect of a country’s development and may be used as an indicator of current and future economic success. In this paper, I investigate the relationship between the coverage of various equipment and structures that comprise a country’s infrastructure and GINI coefficients across countries. The GINI coefficient measures countries’ income inequality. My goal is to gauge if inequality can be explained by differences in infrastructure across countries. I use data from the World Bank, Infrastructure and Economy & Growth topics database. A multivariate regression analysis will be used to measure the relationship between GINI coefficients and infrastructure coverage across countries. I anticipate the findings to show a negative, linear relationship between the variables indicating as infrastructure coverage in a developing country increases, its GINI coefficient ought to decrease, showing movement towards a more equal dispersion of income. This result should occur as more individuals, especially rural residents, have access to structures and transportation which lead to additional income generating opportunities not available beforehand. Additionally, I will investigate the presence of non-linear relationships between infrastructure and GINI coefficients. Following the theory of immiserizing growth, or the theory that economic growth may hurt the developing countries rather than help, I will question if there is a point in emerging economies development where there may be too much infrastructure. If this occurs, I anticipate it to be much like a function of diminishing marginal returns, where additional infrastructure metrics may result in no change or an increase in the GINI coefficient as there may not be enough human capital available to allow it to impact the country’s dispersion of opportunities and income