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    The effect of openness to trade on the Gini index in the Philippine economy
    (2016-01) Abad, Francis Andrew Ong ; Pajaron, Marjorie C.
    According to Heckscher-Ohlin (HO) theor}', openness to trade decreases income inequality in developing countries like the Philippines. This paper aims to contribute to the existing literature that explores this relationship by testing four hypotheses based on HO theory using time series data (1950-2010) in the Philippines through ordinary least squares (OLS) and error correction models (ECM) in both the short and long run and by also incorporating consumption, government and investment share of GDP as controls across all the regression runs. The four hypotheses state that: (1) openness alone; (2) openness and national income; (3) openness and factor endowments; and (4) openness, foreign direct investment (FDI) and remittances determine income inequality in an economy. Four models are constructed to measure the effect of openness to trade on income inequality, which are measured using Gini and Market Gini, while controlling for GDP per capita, GDP per worker, land per worker, FDI net inflows and remittances. OLS and ECM reveal that the effect of openness on income inequality is ambiguous, which is consistent to previous studies of White and Anderson (2001), Lundberg and Squire (2003), Dollar and Kray (2002). Regional data within the Philippines needs to be obtained in order to increase the number of observations and the robustness of the results of this paper.
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    Does more inequality mean more crime?
    (2010-04) Lazo, Carlos Gerardo; Lim, Innah Samantha
    This paper investigates on the crime-inequality link in the Philippine setting. We study the correlation between Gini index and incidence of index crimes across provinces. We also examine the partial correlation by considering other socio-economic factors. The data combine cross-sectional data on 78 provinces and 2 time periods to produce a data set of 156 observations. Results show that income inequality has a positive and significant impact on crime, with an elasticity ranging from 1.2 to 1.4, even after controlling the effects of other potential determinants. Also, income, population density and unemployment have positive and significant effects on index crimes. By contrast, education and poverty have negative and significant effects on index crimes.