| Literature DB >> 18197979 |
David Stuckler1, Christopher M Meissner, Lawrence P King.
Abstract
BACKGROUND: To assess whether a banking system crisis increases short-term population cardiovascular mortality rates.Entities:
Year: 2008 PMID: 18197979 PMCID: PMC2244604 DOI: 10.1186/1744-8603-4-1
Source DB: PubMed Journal: Global Health ISSN: 1744-8603 Impact factor: 4.185
Effect of a Banking Crisis on Log Heart Disease Mortality Rates by Income Level, 1960–2002
| Covariate | High Income Countries | Low Income Countries |
| Bank Crisis | 0.06** (0.02) | 0.26* (0.10) |
| Lag of GDP per capita change | -0.00 (0.00) | 0.01* (0.01) |
| Log Inflation Rate | -0.04** (0.02) | 0.10 (0.10) |
| Urbanization | 0.00 (0.01) | 0.00 (0.01) |
| Education Level | 0.03 (0.02) | 0.14 (0.09) |
| Dependency Ratio | 0.01 (0.00) | -0.00 (0.01) |
| Number of Observations | 729 | 157 |
| Number of Countries | 19 | 9 |
| R2 | 0.71 | 0.61 |
Note: Constant estimated but not reported; Robust standard errors in parentheses, clustered by country because observations are not independent. Models include dummy variables for each country and year. High Income countries include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Japan, Iceland, Italy, Netherlands, New Zealand, Norway, Spain, Sweden, Switzerland, United Kingdom and United States. Banking crisis is defined as a the first year of a systemic banking crisis in which all or most of a country's banking capital is used.1 Urbanization is percentage of population living in urban settings, Dependency ratio is number of elderly and infants as a percentage of total population, Education level is the population average total years of schooling, and the Inflation Rate is based on the change in the consumer price index. R2 value based on within-country variation. Data Sources: World Bank World Development Indicators 2005 edition, World Bank Systemic Banking Crises Data, and World Health Organization Global Mortality Database.
* – p < 0.05, ** – p < 0.01 (two-tailed tests).