Abstract
The combined analysis of revealed preference and qualitative choice data offer complementary features in addressing data shortages and reliability constraints faced in many low-middle income countries. The lack of data for rural north India’s primary health care market provides a context in which this joint modelling is advantageous. This paper specifically highlights the benefits of jointly modelling data to help overcome a lack of price data for non-utilised health care providers. The flexibility of the Mixed Multinomial Logit error component model to apply random draws from non-normal distributions and account for data set specific scaling is compelling.
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