We discuss the application of the GHK simulation method for maximum likelihood estimation of the multivariate probit regression model and describe and illustrate a Stata program mvprobit for this purpose.

https://journals.sagepub.com/doi/pdf/10.1177/1536867X0300300305

Multivariate probit regression using simulated maximum likelihood

An important aspect of marketing practice is the targeting of consumer segments for differential promotional activity. The premise of this activity is that there exist distinct segments of homogeneous consumers who can be identified by readily available demographic information. The increased availability of individual consumer panel data open the possibility of direct targeting of individual households. The goal of this paper is to assess the information content of various information sets available for direct marketing purposes. Information on the consumer is obtained from the current and past purchase history as well as demographic characteristics. We consider the situation in which the marketer may have access to a reasonably long purchase history which includes both the products purchased and information on the causal environment. Short of this complete purchase history, we also consider more limited information sets which consist of only the current purchase occasion or only information on past product choice without causal variables.

Proper evaluation of this information requires a flexible model of heterogeneity which can accommodate observable and unobservable heterogeneity as well as produce household level inferences for targeting purposes. We develop new econometric methods to implement a random coefficient choice model in which the heterogeneity distribution is related to observable demographics. We couple this approach to modeling heterogeneity with a target couponing problem in which coupons are customized to specific households on the basis of various information sets. The couponing problem allows us to place a monetary value on the information sets.

Our results indicate there exists a tremendous potential for improving the profitability of direct marketing efforts by more fully utilizing household purchase histories. Even rather short purchase histories can produce a net gain in revenue from target couponing which is 2.5 times the gain from blanket couponing. The most popular current electronic couponing trigger strategy uses only one observation to customize the delivery of coupons. Surprisingly, even the information contained in observing one purchase occasion boasts net couponing revenue by 50% more than that which would be gained by the blanket strategy. This result, coupled with increased competitive pressures, will force targeted marketing strategies to become much more prevalent in the future than they are today.

The Value of Purchase History Data in Target Marketing

Research on the Elderly: Economic Status, Retirement, and Consumption and Saving

An exact likelihood analysis of the multinomial probit model

Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models

This paper develops a general multiperiod-multinomial probit model for panel data to estimate the living arrangements of the elderly. The model has the following features: (a) In each period choices do not necessarily obey the assumption of independence of irrelevant alternatives. (b) Unobserved person-specific attributes are treated as random effects. These random effects may also be correlated across alternatives. (c) In addition, unobserved choice-specific utility components may persist over some time, creating an autoregressive and/or heteroscedastic error structure. The model is estimated by simulating the choice probabilities in the likelihood function. We examine several variants of the specification of the correlation structure and investigate the extent the biases created by ignoring intertemporal correlations.

/pdf/health-children-and-elderly-living-arrangements-a-1e9stzws5b.pdf

Health, children, and elderly living arrangements: a multiperiod-multinomial probit model with unobserved heterogeneity and autocorrelated errors

Perhaps no single statistic raises more concern about post War changes in the U.S. family than the proportion of the elderly living alone. Since 1940 the proportion of elderly living alone and in institutions has risen dramatically. While demographics appear to explain much of the change in the living arrangements of the elderly, the rising income of the elderly is viewed by many as the chief or at least a chief reason why the elderly live alone. The analyses underlying this view have not, however, considered the incomes and preferences of the children of the elderly. This paper presents a model of the joint living arrangement choice of parents and children. It then uses a new set of data to consider how the preferences and income positions of the elderly and their children influence the living arrangements of elderly parents. The findings suggest that the preferences and income levels of children may be important factors in explaining why so many of the elderly live alone.

/pdf/why-don-t-the-elderly-live-with-their-children-a-new-look-2q77co632m.pdf

John N. Morris

Papers

Health, children, and elderly living arrangements: a multiperiod-multinomial probit model with unobserved heterogeneity and autocorrelated errors

Why Don't the Elderly Live with Their Children? A New Look

Why Don't the Elderly Live With Their Children? A New Look

The Dynamics of Living Arrangements of the Elderly, Health and Family Support

Health, Children, and Elderly Living Arrangements: A Multiperiod-Multinomial Probit Model with Unobserved Heterogeneity and Autocorrelated Errors