Addressing the Ethical Challenge of Market Inclusion in Base-of-the-Pyramid Markets: A Macromarketing Approach

Abstract

Making transformative services such as healthcare accessible to low-income consumers is an ethical challenge of vital importance to marketers. However, most low-income consumers across the world are excluded from the market for such transformative services because of financial constraints arising from poverty. In this paper, instead of focusing on the micro-interplay between firms and consumers, we examine the macro-interplay among firms, consumers, and public policy in addressing the ethical challenge of market inclusion at the base of the pyramid. Specifically, we examine how the Vietnam government used a policy of free and universal health insurance for children under the age of six as a means of lowering affordability barriers and fostering market inclusion in the healthcare market. Overnight in 2005, all children under the age of six living anywhere in Vietnam became eligible for free health insurance. Using this policy intervention as a natural experiment, we compare market inclusion outcomes of children under the age of six with older children who were ineligible before and after the program was implemented. We show that lowering affordability barriers through public policy (1) increases access to target services, (2) increases consumers’ overall out-of-pocket spending, and (3) increases access to complementary services. By adopting a macromarketing lens, this study makes a strong case for collaboration among firms, governments, and communities in addressing the ethical challenge of system-wide market inclusion in base-of-the-pyramid markets.

Appendix

Selection Criteria for HCFP Households

To determine the selecting households to exclude, we used the following estimation strategy:

$$Y_{\text{ht}} = \beta_{0} + \beta_{\text{k}} \times \, X_{\text{k}} + E_{\text{ht}} ,$$

(2)

where h is the household with children between the ages of one and 12 and t is the survey year (2002 and 2008). The outcome variable Y_ht is a binary variable that takes the value 1 (0 otherwise) if the households were reported as being a part of the bottom-income quintile in their respective provinces or if households belonged to the provinces of Thai Nguyen, Cao Bang, Bac Kan, Lao Kai, Ha Giang, Son La, Lai Chau, Dien Bien, Son La, Hoa Binh, Kon Tum, and Soc Trang (where more than 50% of the communes were selected for the 135 programs of the Vietnam government). The controls (X_k) included gender of head of household, education of the highest educated man and woman in the household, household size, whether the household is urban, and survey year, and province fixed effects. The regression is clustered at the level of the province and run as a probit model.

We use the results from the probit regression to estimate a predicted probability of being covered by the HCFP program after conditioning on covariates. In the main regression results, we consider children whose households received the cutoff of less than 40%. In Table 6, we provide the marginal effects of two models and their predicted probabilities to show how the chosen model works relative to others. Column 1 uses information from those who reported having HCFP or not as the outcome of interest. Column 2 is our preferred specification as it uses information from the program to construct the probability of being covered, thus avoiding any misreporting by households that were ineligible but received the program. We drop close to 20% of households (and thus children) by using this criterion in our main specification.

Table 6 Household selection criteria

See Tables 6, 7, 8, 9, 10, 11, and 12.

Table 7 Testing for parallel trends

Table 8 Testing sensitivity to children treated in the past

Table 9 Comparing different criteria for choosing non-HCFP children

Table 10 Robustness checks for private health center visits

Table 11 Results from multinomial regressions

Table 12 Other definitions for outcomes