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EMPIRICAL ESTIMATIONEmpirical ModelFollowing Figure 1, two equations were used for the estimation. The dependent variables were an individual''s choice of a usual source of care (a regular doctor, a regular site, or no usual source care), denoted by USC, and preventive service use, Y.Prob(USC) =f(predisposing, enabling, needs, error term I) (1)Y=g(predisposing, enabling, needs, USC, error term II) (2)An endogenous treatment effect model, an extension of a selection model, would be appropriate for analyzing the relationship between having a usual source of care and service use, as described above. Numerous analogies of the relationship between a usual source of care and service use can be found in the economics literature. Individuals purchase insurance because they foresee future use of medical care (Dowd et al. 1988). Workers join a union because they expect higher wages (Svejnar 1980). Consumers who purchase cars are those who travel frequently (Truong and Hensher 1985). Individuals who buy energy efficient appliances are those who use the appliances frequently (Revelt and Train 1997). In this study, a control function estimation was used to operationalize the endogenous treatment effect model.

Table 3 shows the selected parameter estimates from the second-stage estimation. As discussed, the adjusted Wald tests of whether the coefficients of the [lambda]''s were zero were the tests for the endogeneity of having a regular doctor or site. johnson The last column of Table 3 reports the result of the joint tests. The endogeneity of having a regular doctor or site was present for flu shots, blood pressure checkups, and cholesterol level checkups. No selection biases were found in the equations of pap smears or mammograms within the past two years.As described before, the effects of having a regular doctor ([I.sub.d]) and having a regular site ([I.sub.s]) conditional on the choice of a usual source of care are [gamma]1 + ([[alpha].sub.d][[lambda].sub.d] - [[alpha].sub.0][[lambda].sub.0]) and [gamma]2 + ([[alpha].sub.s][[lambda].sub.s] - [[alpha].sub.0][[lambda].sub.0]), respectively. These two effects are show in Table 4. Marginal effects of having a regular doctor and a regular site on the probabilities of receiving preventive services were reported. The [lambda]''s were calculated for each individual based on the predicted probabilities from the first-stage estimation. Because the [lambda]''s vary by individuals, the averages of the [lambda]''s were used in calculating the marginal effects.

Based on the conceptualization illustrated in Figure 1, this study focused on how having a regular doctor differs from having a regular site in affecting the use of five preventive services: mammograms, pap smears, blood pressure checkups, cholesterol level checkups, and flu shots. The probabilities of having a usual doctor, a regular site, and no usual source of care were analyzed first in the selection stage. It was followed by the examination of the impact of city having a regular doctor and having a regular site on the utilization of each above-mentioned preventive service, while incorporating individuals'' unobservable preferences in the selection stage.