Dynamic Discrete Choice Model Research Articles

A Test of the Extreme Value Type I Assumption in the Bus Engine Replacement Model

Nearly every dynamic discrete choice model relies, for computational simplicity, on the assumption that underlying utility shocks are distributed extreme value type I. In this note we test this assumption in the context of the Rust (1987) classical model of bus engine replacement and find that, for most specifications tested, extreme value type I errors cannot be rejected. In a case where extreme value type I errors can be rejected, our more flexible estimation yields significantly different choice probabilities at some regions of the state space.

Dynamic Discrete Choice Model for Multiple Social Interactions

A dynamic discrete choice model for multiple social interactions was developed on the basis of retrospective panel data in the context of household vehicle-type choice. “Social interactions” refer to the influence of reference groups on household choice behavior. However, most studies in transportation have considered a household as a decision maker independent from the society to which it belongs. Social interactions have therefore not been well represented, especially if there were two or more types of reference groups, which may further vary over time. The model was built within the dynamic generalized extreme value framework, which included a set of dynamic elements, such as initial conditions, state dependence, and future expectation. This study defined three types of social interactions: diffusion rates of a vehicle type at the national level and at the neighborhood level and diffusion rate of households with the same income level. A survey was conducted in local Japanese cities in 2006. The survey focused on household vehicle ownership behavior over the 10 years from 1997 to 2006. Model estimation results confirmed that social interactions from reference groups of neighborhoods and households with the same income level were especially influential in decisions about household vehicle-type choice. On the contrary, social interaction from the whole society did not significantly influence the household choice. It was further found that effects of dynamic elements on the household choice were statistically significant.

The formal-informal labor market segmentation hypothesis revisited

Despite the existence of a large empirical literature, there is no conclusive answer to whether labor markets in developing countries are segmented. Moreover, a prior and perhaps more fundamental question remains largely unanswered, namely, whether the formal-informal segmentation hypothesis actually has empirical content. This paper tackles the latter question by developing a stochastic dynamic discrete choice model to analyze workers' choices between unemployment, formal and informal jobs. This general framework is then used to assess the empirical implications of dierent models of labor market functioning. As a complete taxonomy exercise is beyond the scope of this paper, I focus on the two most polar cases in the present context: the fully integrated and fully segmented labor markets. The nal goal is to analyze to which extent these two extreme benchmarks can generate implications that are empirically distinguishable and, more broadly, whether the ndings in the empirical literature can be supported by a single model or by a broad array of models. The analysis shows that both models can support the observed regularities regarding formal-informal wage gaps, transitions and job duration. Hence, it does not seem possible to identify the existence of segmentation from the moments typically analyzed in the empirical literature.

Duration Dependence and Timevarying Variables in Discrete Time Duration Models

This paper considers estimation of a dynamic discrete choice model with second order state dependence in the presence of strictly exogenous time-varying explanatory variables. We propose a new method for estimating such models, and a small Monte Carlo study suggests that the method performs well in practice. The method is used to test for duration dependence in labour market spells for young people in France. The novelty in the application is that we are able to control for time-varying explanatory variables. In a discrete time duration model, duration dependence will result in second order state dependence, and the paper therefore also adds to the literature on estimation of duration models with unobserved heterogeneity.

Continuity and differentiability of expected value functions in dynamic discrete choice models

This paper explores the properties of expected value functions in dynamic discrete choice models. The continuity with respect to state variables and parameters, and the differentiability with respect to state variables are established under fairly general conditions. The differentiability with respect to parameters is proved when some state variables do not affect the state transition probabilities and, thus, the expected value functions. It is shown that such variables are needed so as to apply the implicit function theorem used in the proof. The results are of particular relevance to estimable dynamic discrete choice models.

Identification of Models of the Labor Market

This chapter discusses identification of common selection models of the labor market. We start with the classic Roy model and show how it can be identified with exclusion restrictions. We then extend the argument to the generalized Roy model, treatment effect models, duration models, search models, and dynamic discrete choice models. In all cases, key ingredients for identification are exclusion restrictions and support conditions.

Understanding the Spanish Business Innovation Gap: The Role of Spillovers and Firms’ Absorptive Capacity

This paper investigates whether the existence of knowledge spillovers, differences in the capacity of firms to assimilate them and disparities in some human resource management practices are related with the decision to innovate of Spanish firms. In order to do this, we employ data from the “Central de Balances” database, which covers both manufacturing and services firms during the period 2003-2007, and use an estimator proposed by Wooldridge (2005) for dynamic random effects discrete choice models. The empirical exercise provides evidence on the positive link between spillovers and the innovative behaviour of companies, not just for the knowledge generated in the same industry, but also for that generated in the same region or by the public sector. Moreover, this link is stronger for those firms with a higher capacity to absorb those spillovers. This ability not only works through firms’ R&D capabilities, but also through such factors as the quality of the labour force, the share of temporary employment and the amount of resources spent in training. In addition to these factors, we find that innovation performance exhibits a high degree of inertia. Further, some other observed firm characteristics, such as size, sales growth, export behaviour, sector capital intensity or financial structure variables, are also found to be relevant determinants of the likelihood of innovation.

On the looting of nations

We develop a dynamic discrete choice model of an unchecked ruler making decisions regarding the development of a resource rich country. Resources serve as collateral and facilitate the acquisition of loans. The ruler chooses either to stay in power while facing the risk of being ousted, or loot the country’s riches by liquefying the resources through lending. We show that unstructured lending from international credit markets can create incentives to loot the country; and an enhanced likelihood of looting causes greater political instability, and diminishes growth. Using a treatment effects model, we find evidence that supports our predictions.

Estimation of Dynamic Discrete Choice Models in Continuous Time

This paper develops a dynamic model of retail competition and uses it to study the impact of the expansion of a new national competitor on the structure of urban markets. In order to accommodate substantial heterogeneity (both observed and unobserved) across agents and markets, the paper first develops a general framework for estimating and solving dynamic discrete choice models in continuous time that is computationally light and readily applicable to dynamic games. In the proposed framework, players face a standard dynamic discrete choice problem at decision times that occur stochastically. The resulting stochastic-sequential structure naturally admits the use of CCP methods for estimation and makes it possible to compute counterfactual simulations for relatively high-dimensional games. The model and method are applied to the retail grocery industry, into which Wal-Mart began rapidly expanding in the early 1990s, eventually attaining a dominant position. We find that Wal-Mart’s expansion into groceries came mostly at the expense of the large incumbent supermarket chains, rather than the single-store outlets that bore the brunt of its earlier conquest of the broader general merchandise sector. Instead, we find that independent grocers actually thrive when Wal-Mart enters, leading to an overall reduction in market concentration. These competitive effects are strongest in larger markets and those into which Wal-Mart expanded most rapidly, suggesting a diminishing role of scale and a greater emphasis on differentiation in this previously mature industry.

A Dynamic Model of User Behavior in a Social Network Site

This paper estimates a dynamic model of user behavior in a social network site using unique data on the daily login activity of a sample of members of MySpace.com. We view a social network as a stock of capital that yields a flow of utilities over time by creating interactions between the site user and her friends. This capital stock can be maintained and expanded by logging in to the site and communicating with other members. The user's login decision is thus a forward-looking one, which we model in the framework of a dynamic discrete-choice model. We allow for two sources of persistence in members' login decisions: state dependence and unobserved heterogeneity. We found two distinct types of consumers as regards utility, cost, and state transition. Across types, real-time chat and messaging, features of MySpace.com, positively affect the usage decision. We use our parameter estimates to perform counterfactual simulations with the goal of providing site managers with ways to enhance firm performance.

Semiparametric information bound of dynamic discrete choice models

We develop a simulation based approach that can determine whether the semiparametric efficiency bound of a dynamic discrete choice model with fixed effects is zero or not. We illustrate the usefulness of our approach by considering a simplified version of Keane and Wolpin's (1997) model, where we show that the semiparametric information is zero.

Heterogeneity in dynamic discrete choice models

Summary We consider dynamic discrete choice models with heterogeneity in both the levels parameter and the state dependence parameter. We first present an empirical analysis that motivates the theoretical analysis which follows. The theoretical analysis considers a simple two-state, first-order Markov chain model without covariates in which both transition probabilities are heterogeneous. Using such a model we are able to derive exact small sample results for bias and mean squared error (MSE). We discuss the maximum likelihood approach and derive two novel estimators. The first is a bias corrected version of the Maximum Likelihood Estimator (MLE) although the second, which we term MIMSE, minimizes the integrated mean square error. The MIMSE estimator is always well defined, has a closed-form expression and inherits the desirable large sample properties of the MLE. Our main finding is that in almost all short panel contexts the MIMSE significantly outperforms the other two estimators in terms of MSE. A final section extends the MIMSE estimator to allow for exogenous covariates.

THE ROLE OF SUNK COSTS IN THE DECISION TO INVEST IN R&D*

We present a dynamic empirical model of a firm's R&D decisions that is consistent with the existence of sunk R&D costs, taking into account that these costs may differ between small and large firms, and among different technological regimes. We estimate a multivariate dynamic discrete choice model using firm‐level data of Spanish manufacturing for 1990–2000. Conditional on firm heterogeneity and serially correlated unobservable factors, we find that R&D history matters. This true state dependence allows inferring the existence of sunk R&D costs associated with performing R&D. Sunk R&D costs are found to be higher for large, high‐tech firms.

Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

We estimate a dynamic structural model of sales force response to a bonus-based compensation plan. This paper provides substantive insight into how different elements of the compensation plan enhance productivity. We find evidence that (1) bonuses enhance productivity across all segments; (2) overachievement commissions help sustain the high productivity of the best performers, even after attaining quotas; and (3) quarterly bonuses help improve performance of the weak performers by serving as pacers to keep the sales force on track in achieving its annual sales quotas. The paper also introduces two main methodological innovations to the marketing literature: First, we implement empirically the method proposed by Arcidiacono and Miller [Arcidiacono P, Miller RA (2011) Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity. Econometrica 79(6):1823–1867] to accommodate unobserved latent-class heterogeneity using a computationally light two-step estimator. Second, we illustrate how discount factors can be estimated in a dynamic structural model using field data through a combination of (1) an exclusion restriction separating current and future payoff and (2) a finite-horizon model in which there is no forward-looking behavior in the last period.

Estimating the return to training and occupational experience: The case of female immigrants

We formulate a dynamic discrete choice model of training and employment to measure the personal and social benefits from government provided training for a sample of high-skilled female immigrants from the Former Soviet Union in Israel. We find that training has a significant impact on the mean offered wage in white-collar occupations, but not in blue-collar occupations. Training substantially increases the job-offer rates in both occupations. Counterfactual policy simulations show a substantial social gain from increasing the access to training programs, and the estimated model provides a good fit for within-sample, out-of-sample and aggregate trends using cross-sectional survey data.

Occupation and the labour market participation of women: why do some people trade down jobs when careers are interrupted?

A dynamic structural discrete choice model of labour market participation, schooling and occupational choice is applied to data for women drawn from the British Cohort Study. It is established that, for relatively highly educated workers, the return attached to childrearing is higher in the part-time non-managerial work regime than in the part-time managerial work regime. As a consequence, following childbirth, many female managers switch to occupations that underutilise their skills.

Labour adjustment costs: Estimation of a dynamic discrete choice model using panel data for Greek manufacturing firms

In this paper we estimate a dynamic structural model of employment at firm level. Our dataset consists of a balanced panel of 2790 Greek manufacturing firms. The empirical evidence of this dataset stresses three important stylized facts: (a) there are periods in which firms decide not to change their labour input, (b) there are periods of large employment changes (lumpy nature of labour adjustment) and (c) the commonality is employment spikes to be followed by smooth and low employment growth periods. Following Cooper and Haltiwanger [Cooper, R.W. and Haltiwanger, J. “On the Nature of Capital Adjustment Costs”, Review of Economic Studies, 2006; 73(3); 611–633], we consider a dynamic discrete choice model of a general specification of adjustment costs including convex, non-convex and “disruption of production” components. We use a method of simulated moments procedure to estimate the structural parameters. Our results indicate considerable fixed costs in the Greek employment adjustment.

Inference in Dynamic Discrete Choice Models With Serially Correlated Unobserved State Variables

This paper develops a method for inference in dynamic discrete choice models with serially correlated unobserved state variables. Estimation of these models involves computing high-dimensional integrals that are present in the solution to the dynamic program and in the likelihood function. First, the paper proposes a Bayesian Markov chain Monte Carlo estimation procedure that can handle the problem of multidimensional integration in the likelihood function. Second, the paper presents an efficient algorithm for solving the dynamic program suitable for use in conjunction with the proposed estimation procedure.

Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior

Two key issues in the literature on female labor supply are (i) whether persistence in employment status is due to unobserved heterogeneity or state dependence, and (ii) whether fertility is exogenous to labor supply. Until recently, the consensus was that unobserved heterogeneity is very important and fertility is endogenous. Hyslop (1999) challenged this. Using a dynamic panel probit model of female labor supply including heterogeneity and state dependence, he found that adding autoregressive errors led to a substantial diminution in the importance of heterogeneity. This, in turn, meant he could not reject that fertility is exogenous. Here, we extend Hyslop (1999) to allow classification error in employment status, using an estimation procedure developed by Keane and Wolpin (2001) and Keane and Sauer (2005). We find that a fairly small amount of classification error is enough to overturn Hyslop's conclusions, leading to overwhelming rejection of the hypothesis of exogenous fertility.

Bayesian Estimation of Dynamic Discrete Choice Models

We propose a new methodology for structural estimation of infinite horizon dynamic discrete choice models. We combine the dynamic programming (DP) solution algorithm with the Bayesian Markov chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters simultaneously. As a result, the computational burden of estimating a dynamic model becomes comparable to that of a static model. Another feature of our algorithm is that even though the number of grid points on the state variable is small per solution-estimation iteration, the number of effective grid points increases with the number of estimation iterations. This is how we help ease the “curse of dimensionality.” We simulate and estimate several versions of a simple model of entry and exit to illustrate our methodology. We also prove that under standard conditions, the parameters converge in probability to the true posterior distribution, regardless of the starting values.