dichotomous variable for “disability.” The model was estimated with ordinary least squares when the health variables were “number of days disabled in the last month”35 and “height.” When the health variables are “disability” and “number of days disabled in the last month,” the data are rural and urban for the year 1993. Age of the individual is specified as an exogenous endowment. 36 Considering that wealth might shift health outcomes positively (given that wealthier individuals have more resources to spend on health), non-labor income and a dummy to indicate the type of housing 37 were specified as individual private opportunities (O). Using data from CASEN and from other sources,38 a list of variables to describe the community-specific environment (P) were matched to sample clusters. The variables P are defined for 52 regions (approximately twice the number of “departamentos,” since most of the regions have rural and urban areas).39 At the municipality level, characteristics that were expected to be related to the health outcomes were climate,40 availability of health centers, enrollment in social security,41 transportation infrastructure, transportation time to reach hospitals, transportation time to reach schools, availability of water and electricity. Among those, few result in significant correlations and some of them have a counterintuitive sign. At the “departamental” level, the only significant variable was the number of yearly transfers from the central government to the “departamento” for health.42 Regional differences in Colombia are very important. Levels of earnings, formality of labor markets, levels of education and health are in general worse in coastal regions than in the interior. Particularly the Pacific coast is known to be the poorest region in the country. Although the variable altitude may capture some of these regional differences,43 there are cultural, racial and institutional differences that persist among these regions that go beyond the climate. In order to capture some differences due to these elements, two regional dummy variables were introduced, one for living in a “departamento” on the Pacific coast and one for living in a “departamento” on the Atlantic coast.44 When the health indicator is height, the data is only for the urban population in the year 1991.45 At the individual level the model controls for age,46 non-labor income, and a dummy to indicate owner-occupied housing. 47 The variables that capture environmental health risks (P ) are two indicators constructed at the city level, from the ENH-91. The first one measures availability of basic services in the households of the community where the person lives 48. The second one measures percentage of houses in the community that are not overcrowded. City and strata define the communities or sample clusters for urban areas. The estimation results are in Table 7. Age is an important factor that explains the three health indicators, with older individuals tending to have worse health. The coefficients of age and age squared are individually
35
Since the variable is truncated at zero and 30, Tobit models were also, but the results do not differ substantially from the OLS. Since older individuals tend to have lower levels of health, age and age squared were taken into account to capture possible diminishing returns. 37 The same variable “lives in house or apartment” defined in Section 4.2. 38 The Ministerio de Salud and the Instituto Geográfico Agustin Codazzi. 39 Some regions are only urban and others are only rural. 40 Altitude, temperature and yearly average rainfall in each municipality. 41 In 1993 approximately 25% of urban residents and 8% of rural residents were affiliated or beneficiary of the Social Security Institute for health services, 10% of the Colombian population used private health care, and 5% were covered by other services. 42 Other variables that were available but not included in this final model were: the number of primary and secondary schools, the number of hospital beds, average times to reach schools, average daily hours in schools. 43 Coastal regions are closer to the level of the sea. 44 The reference category was living in the interior. 45 It was impossible to find for 1991 the same information found for 1993 at the municipality level. 46 Age is more important for height than for the other health outcomes. 47 The same variable “owner-occupied housing” defined in Section 4.2. 48 The availability in the community of each basic service separately, was insignificant. The variable used here, that aggregates the availability of the three basic services (electricity, water and sewage) in the households, provided significant estimates. 36
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