We study investment and consumption decisions in a dynamic game under learning. To that end, we present a model in which agents not only extract a resource for consumption, but also invest in technology to improve the future stock. At the same time, the agents learn about the stochastic process...

To isolate the impact of the assumption of model-consistent expectations, this paper proposes a baseline case in which households are individually rational, have full information and learn using forecast rules specified as in the minimum state variable representation of the economy. Applying...

We introduce learning in a dynamic game of international pollution, with ecological uncertainty. We characterize and compare the feedback non-cooperative emissions strategies of players when the players do not know the distribution of ecological uncertainty but they gain information (learn)...

I develop an equilibrium model with collateral constraints in which rational agents are uncertain and learn about the equilibrium mapping between fundamentals and collateral prices. Bayesian updating of beliefs by agents can endogenously generate booms and busts in collateral prices and largely...

In an asset-pricing model, risk-averse agents need to forecast the conditional variance of a stock's return. A near-rational restricted perceptions equilibrium exists in which agents believe prices follow a random walk with a conditional variance that is self-fulfilling. When agents estimate...

The present paper draws on the main issues in the production of scientific knowledge based upon grounded theory in management accounting research. This piece of work is a bibliographic study confronting grounded theory practices with the expectations of its founders (Glaser et Strauss, 1967; Strauss...

We extend the persuasion game to bring it squarely into the economics of advertising. We model advertising as exciting consumer interest into learning more about the product, and determine a firm's equilibrium choice of advertising content over quality information, price information, and...

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the...