International Country Risk Guide (ICRG) Researchers Dataset

Main data files comprise 22 variables in three subcategories of risk (political, financial, and economic) for 146 countries for 1984-2018. Data are annual averages of the components of the ICRG Risk Ratings (Tables 3B, 4B, and 5B) published in the International Country Risk Guide. Indices include: political: government stability, socioeconomic conditions, investment profile, internal conflict, external conflict, corruption, military in politics, religion in politics, law and order, ethnic tensions, democratic accountability, and bureaucratic quality; financial: foreign debt, exchange rate stability, debt service, current account, international liquidity; and economic: inflation, GDP per head, GDP growth, budget balance, current account as % of GDP. Table 2B provides annual averages of the composite risk rating. Table 3Ba provides historical political risk subcomponents on a monthly basis from May 2001-March 2019. Also includes the IRIS-3 dataset by Steve Knack and Philip Keefer, which covers the period of 1982-1997 and computed scores for six additional political risk variables: corruption in government, rule of law, bureaucratic quality, ethnic tensions, repudiation of contracts by government, and risk of expropriation. Additional data files provide country risk ratings and databanks (economic and social indicators) for new emerging markets for 2000-2009.</p

Effects of Governance on Health: a Cross-National Analysis of 101 Countries

The importance of good governance for the health of populations has hardly been researched even though major donors and international financial institutions make their aid and loans increasingly conditional upon reforms that ensure 'good governance'. We analyse the role of governance in improving the health of individuals using a cross-sectional analysis for 101 countries over the period 2000-2005. Instead of focusing on one particular indicator of population health like most previous studies, we employ 18 indicators. Explorative Factor Analysis shows that these variables are individually all good but imperfect indicators of the latent construct population health. Similarly, we employ 6 indicators of government governance. Also these indicators are all good but imperfect indicators of the latent construct governance. Our hypothesis is that good governance has a positive impact on the health of individuals, be it directly and&sol;or indirectly through its impact on the health care sector or income. The selection of the control variables in our model is based on the general-to-specific approach. As both the dependent and some of the explanatory variables are latent variables, we use Structural Equation Modelling. Our results show that government governance is not directly related to the health of individuals once economic and demographic control variables are included. Indirectly, however, governance has influence on health via its positive impact on income and the quality of the health care sector. However, the significance of these indirect effects differs across country groups. In countries with a relatively healthy population, governance has a positive indirect effect through the quality of the health care sector, but not via income. In countries with poor health, governance has a positive indirect effect through income, but not via the quality of the health care sector. Copyright 2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd.

Green Havens and Pollution Havens

We test for pollution haven effects in outward foreign direct investment (FDI) for different sectors using a comprehensive and exhaustive data set for outward FDI from the Netherlands, one of the most environmentally stringent countries and a major source of global FDI. Our evidence suggests that in the sectors, natural resources extraction and refining, construction, retail, food processing, beverages and tobacco, and utilities, a less stringent environmental policy in the host country, significantly attract FDI. What is important for these pollution haven effects is not only regulation but also enforcement of environmental policy. In contrast to earlier results, it is not only footloose industries that display pollution haven effects, but also the traditional pollution-intensive industries. But for the machines, electronics and automotive and transportation and communication sectors, a more stringent and better enforced environmental policy attracts more FDI as this may help their reputation for sustainable management and CSR. These sectors display green haven effects. These findings have important implications for the sector distribution of FDI in destination countries