This study examines the relationship between time discounting, other sources of time preference, and intertemporal choices about smoking.Using a survey fielded for our analysis, we elicit rates of time discount from choices in financial and health domains.We also examine the relationship between other determinants of time preference and smoking status.We find very high rates of time discount in the financial realm for a horizon of one year, irrespective of smoking status.In the health domain, the implied rates of time discount decline with the length of the time delay (hyperbolic discounting) and the sign of the payoff (the "sign effect").We use a series of questions about the willingness to undergo a colonoscopy to elicit short-and long-run rates of discount in a quasi-hyperbolic discounting framework, finding no evidence that short-run and long-run rates of discount differ by smoking status.Using more general measures of time preference, i.e., impulsivity and length of financial planning horizon, smokers are more impatient.However, neither of these measures is significantly correlated with the measures of time discounting.Our results indicate that subjective rates of time discount revealed through committed choice scenarios are not related to differences in smoking behavior.Rather, a combination of more general measures of time preference and self-control, i.e., impulsivity and financial planning, are more closely related to the smoking decision.
In this paper, we investigate whether multimarket contact leads to collusive pricing in the retail lumber market and assess the effect of potential regulation on consumer welfare. In particular, we focus on the competition between Home Depot and Lowe's since they are the main players in retail lumber market. For our analysis, we assemble an original data set of prices and sales in the pressure treated lumber category. We first provide reduced form evidence for the effect of multimarket contact on collusion in pricing strategies by showing a positive and significant correlation between price and multimarket contact. Guided by this evidence we estimate a model, using the Berry, Levinsohn and Pakes (1995) equilibrium framework, that includes both the demand and supply side with conduct parameters which capture the degree of collusion in setting prices. We specify the conduct parameters as a function of multimarket contact, following the framework developed by Sudhir (2001) and Ciliberto and Williams (2014). We find that the conduct parameter for capturing the effect of multimarket contact on collusion is significant and positive, implying that multimarket contact leads to higher prices than those from a competitive Bertrand-Nash equilibrium. Using the model estimates, we conduct a counterfactual analysis to measure the consumer welfare impact due to collusive pricing. We find that consumer surplus in January, 2016 increases by $57.7k and this amounts to $692.4k in a year. To the best of our knowledge, this is the first paper that shows state-level multimarket contact facilitates collusive pricing with implications for consumer welfare. The finding has important policy implications that might suggest the need for monitoring prices in states where retail firms have a greater degree of multimarket contact.
Theoretical models predict asymmetric information in health insurance markets may generate inefficient outcomes due to adverse selection and moral hazard. However, previous empirical research has found it difficult to disentangle adverse selection from moral hazard in health care consumption. We propose a two‐step semiparametric estimation strategy to identify and estimate a canonical model of asymmetric information in health care markets. With this method, we can estimate a structural model of demand for health care. We illustrate this method using a claims‐level data set with confidential information from a large self‐insured employer. We find significant evidence of moral hazard and adverse selection.
This paper examines whether experience from entry in one market can potentially enhance profitability at a future market opportunity for a related product. We formulate and estimate a dynamic game of entry in which forward-looking firms make decisions not just based on present benefits of past entry but also anticipating potential future benefits of current entry. Dynamic spillovers of entry are incorporated through a firm-specific unobservable (to the researcher) cost that depends on past entry decisions. The unobserved costs may also be serially persistent. Thus, the model allows for firm-specific unobserved heterogeneity that evolves based on firm actions. The challenge of estimating a dynamic game with serially correlated unobserved state variables subject to endogenous feedback is overcome by embedding a particle filter-based technique in a nested fixed-point algorithm. Using an application to a stylized model of entry in the generic pharmaceutical industry, we underscore the motivation for the model specification and the methodology developed. Our estimates imply positive spillover effects of entry. Moreover, these spillovers suggest heterogeneity not just across firms but also within firms over time based on their history of entry decisions. Our results illustrate that entry may potentially provide firms with additional strategic advantage in later markets and that entry spillovers may be an important factor to consider in the equilibrium evolution of the generic drug industry. The web appendix is available at https://doi.org/10.1287/mnsc.2016.2648 . This paper was accepted by J. Miguel Villas-Boas, marketing.
We develop and estimate a dynamic game of strategic firm expansion and contraction decisions to study the role of firm size in future profitability and market dominance. Modeling firm size is important because retail chain dynamics are more richly driven by expansion and contraction than de novo entry or permanent exit. Additionally, anticipated size spillovers may influence the strategies of forward-looking firms, making it difficult to analyze the effects of size without explicitly accounting for these in the expectations and, hence, decisions of firms. Expansion may also be profitable for some firms while detrimental for others. Thus, we explicitly model and allow for heterogeneity in the dynamic link between firm size and profits as well as potential for persistent brand effects through firm-specific unobservable factors. As a methodological contribution, we surmount the hurdle of estimating the model by extending a two-step procedure that circumvents solving the game. The first stage combines semiparametric conditional choice probability estimation with a particle filter to eliminate the serially correlated unobservable components. The second stage uses a forward simulation approach to estimate the payoff parameters. Data on Canadian hamburger chains from their inception in 1970 to 2005 provide evidence of firm-specific heterogeneity in brand effects, size spillovers, and persistence in profitability. This heterogeneous dynamic linkage shows how McDonald’s becomes dominant and other chains falter as they evolve, thus affecting market structure and industry concentration. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2814 . This paper was accepted by J. Miguel Villas-Boas, marketing.
We estimate a dynamic oligopolistic entry model for the generic pharmaceutical industry that allows for dynamic spillovers from experience due to entry on future costs. Our paper contributes to both the estimation of oligopolistic dynamic games and the understanding of entry decisions in the pharmaceutical industry. Our dynamic model features unobserved firm production costs that are serially correlated over time. This introduces difficulty in the estimation of the dynamic game theoretic model which we overcome using sequential importance sampling methods. Our empirical findings show that the dynamic evolution of the production cost plays an important role in the equilibrium path of the pharmaceutical industry structure.
I develop a dynamic stochastic model of individual choices about health insurance, exercise, smoking, alcohol consumption and medical treatment. The primary objective is to estimate the parameters of the model to conduct counter-factual health policy experiments. The model is estimated through maximum likelihood using data on 3671 males from the Health and Retirement Study. A kernel smoothed probability simulator is developed to solve an initial conditions problem. Preliminary estimates show that the model does well in matching the means, frequencies and transitions in this sample for all the choices and states except for the insurance choices in the first half of the life cycle (ages 22 to 54). It needs to be emphasized however that the fit of the insurance choices is improving with the improvement of the estimates. The estimates are then used for two radically different counter-factual health policy experiments. In the first experiment that simulates the provision of comprehensive health insurance coverage, every individual is mandated to be on a health insurance plan that charges a premium of $1000.0 per annum (that is comparable in cost to the options in the data) but covers all out of pocket costs. The simulations suggest that the average health outcomes do not change much over the life cycle in the new regime. However the proportion of individuals smoking and consuming alcohol falls slightly, especially for those older than 60 years, with the decrease being as much as 0.8% in both instances. The proportion of individuals seeking medical treatment increases by as much as 49%. Average consumption of a composite commodity also rises by upto 7% providing partial evidence that the individuals are better off under the new policy. In another experiment that simulates the withdrawal of provision of subsidized medical care, all individuals are denied health insurance. Simulations reveal that the average health outcomes do not change much from the status quo. However the proportion of individuals smoking and consuming alcohol increases by as much as 3.2% and 0.5% respectively. The proportion of individuals seeking medical care falls by as much as 95%. The two experiments taken together suggest that provision of subsidized medical treatment tends to increase demand for medical care but fosters healthier behaviors. On the contrary withdrawal of subsidized treatment chokes demand for medical services but leads to increases in unhealthy behaviors. Of particular interest is the fact that the model provides no evidence of the existence of a moral hazard problem associated with the provision of subsidised medical care on habits like smoking and alcohol consumption.
