A practitioner's guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865–1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer “frequent-buyer” type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1

Heterogeneity and the dynamics of technology adoption

We estimate the demand for a videocalling technology in the presence of both network effects and heterogeneity. Using a unique dataset from a large multinational firm, we pose and estimate a fully dynamic model of technology adoption. We propose a novel identification strategy based on post-adoption technology usage to disentangle equilibrium beliefs concerning the evolution of the network from observed and unobserved heterogeneity in technology adoption costs and use benefits. We find that employees have significant heterogeneity in both adoption costs and network benefits, and have preferences for diverse networks. Using our estimates, we evaluate a number of counterfactual adoption policies, and find that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption

Firm turnover and productivity differentials in Ethiopian manufacturing

Entry and exit, Productivity, Manufacturing, Africa, D24, L25, L60, O55,

Moral hazard and sorting in a market for partnerships

We examine how equilibrium sorting patterns in a matching market for partnerships are impacted by the presence of bilateral moral hazard in a repeated production setting. We find that this impact depends on how the cost of moral hazard manifests itself—whether efficient effort is not feasible or desirable from the beginning, or whether inefficient effort is resorted to only as a punishment equilibrium. Which of these is the case depends on both the details of the technology and the contractual environment. In the former case, the presence of moral hazard moves the market away from positive sorting. In the latter case, whether moral hazard favors positive or negative sorting depends on how the power of incentives needed to implement effort varies with the observable types of the agents

Endogenous matching in a market with heterogeneous principals and agents

Risk sharing, Endogenous matching, Assignment Game, C78, D81,

Does access to finance improve productivity? The case of Italian manufacturing

Many contributions have analyzed the implications of underdeveloped financial markets for economic growth and efficiency of production, emphasizing their role as a source of misallocation and highlighting their negative impact on firm dynamics and innovation. The phenomenon is particularly severe in economies characterized by high reliance on debt financing, asymmetric information and imperfect capital markets. This paper reviews the literature on the link between finance and total factor productivity (TFP) and presents some microeconomic empirical evidence in support of a negative relationship between a firm’s ability to access external funding and its productivity. We exploit financial accounts data from ORBIS and AMADEUS and focus on a sample of Italian manufacturing firms during the period 2005-2015. Our findings show that financing constraints negatively affect firms’ productivity, with important implications at the aggregate level. We also document that the sensitivity of TFP to credit constraints increased significantly as a result of the Great Recession, possibly explaining the stalling post-crisis Italian recovery

The effects of detailing on prescribing decisions under quality uncertainty

Detailing, Prescription drugs, Decisions under uncertainty, Representative opinion leader, Diffusion, D83, I11, I18, M31, M37, M38,