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, Jain and Ching, Econometrica 77:1865-1899, 2009) (IJC). In the conventional nested fixed point algorithm, most of the...

We develop a Bayesian Markov chain Monte Carlo (MCMC) algorithm for estimating finite-horizon discrete choice dynamic programming (DDP) models. The proposed algorithm has the potential to reduce the computational burden significantly when some of the state variables are continuous. In a...

New product release preannouncement is a pre-release communication process for sending a message to target groups such as consumers, competitors, and/or stockholders. Despite its importance, little has been empirically investigated about the strategic role of its timing. In this paper, we focus...

Consumers commonly seek information from critic and consumer reviews when new product quality remains uncertain. However, consumer reviews are endogenous and may be subject to potential biases (e.g., self-selection). In this paper, we propose a new dynamic structural model where forward-looking...

This paper examines the role of software piracy in digital platforms where a platform provider makes a decision of how much software to produce in-house and how much to outsource from a third-party software provider. Using a vertical differentiation model, we theoretically investigate how piracy...

This paper provides a new and complementary explanation for a pricing puzzle for seasonal products, namely, counter-cyclical pricing, drawing on the category-expansion effects of price promotions. Our study emphasizes the seasonal fluctuation in promotion frequency rather than the change in...

The obesity rate has grown to epidemic proportions in the United States. Recent scientific studies suggest that excess intake of sugar-sweetened beverages (SSBs) is one of the primary contributors to weight gain. One option to address the growing obesity epidemic is to discourage SSB consumption...

This paper provides a step-by-step guide to estimating discrete choice dynamic programming (DDP) models using the Bayesian Dynamic Programming algorithm developed in Imai, Jain and Ching (2008) (IJC). The IJC method combines the DDP solution algorithm with the Bayesian Markov Chain Monte Carlo...