Belief‐updating biases hinder the correction of inaccurate beliefs and lead to suboptimal decisions. We complement Rabin and Schrag's (1999) portable extension of the Bayesian model by including conservatism in addition to confirmatory bias. Additionally, we show how to identify these two...

This study applies the Technology Acceptance Model to examine user acceptance of emerging technologies - specifically LINE and Google Translate- -for language learning. A multimodal interactive teaching program, combining cooperative learning and problem-based learning, was implemented at a...

People often form mental models based on incomplete information, revising them as new relevant data becomes available. In this paper, we experimentally investigate how individuals update their models when data on predictive variables are gradually revealed. We find that people's models tend to...

Strategic learning self-efficacy reflects the confidence of managers in their ability to learn from the outcomes of past strategic decisions and apply that knowledge to new decisions. This research examines the relationship between strategic learning self-efficacy and a firm's industry-adjusted...

We study a duel game in which each player has incomplete knowledge of the game parameters. We present a simple, heuristically motivated and easily implemented algorithm by which, in the course of repeated plays, each player estimates the missing parameters and consequently learns his optimal...

Intensive care units (ICUs) operate with fixed capacities and face uncertainty such as demand variability, leading to demand-driven, early discharges to free up beds. These discharges can increase ICU readmission rates, negatively impacting patient outcomes and aggravating ICU bottleneck...

Betthäuser et al. (2023) examine the effects of the COVID-19 pandemic on the learning progress of school-aged children. They collect 291 estimates from 42 studies. Their meta-analysis-corrected estimate implies a substantial decline in students' learning (Cohen's d = −0.14, 95% confidence...

The global energy landscape is undergoing a major transformation, upending decades of economic thinking built around resource scarcity. Unlike fossil fuels – continuously extracted from finite, geographically fixed deposits – renewable energy revolves around manufacturing technology that...

In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In...

We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal...

We study the standard reputation model with a long-run (LR) player facing a sequence of short-run (SR) opponents, with one difference: the SR players are uncertain about the monitoring structure, while the LR player knows it. We construct examples where the standard reputation result breaks...

Intensive care units (ICUs) operate with fixed capacities and face uncertainty such as demand variability, leading to demand-driven, early discharges to free up beds. These discharges can increase readmission rates, negatively impacting patient outcomes and aggravating ICU bottleneck congestion....

We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal...

We develop a deep reinforcement learning (RL) framework for an optimal market-making (MM) trading problem, specifically focusing on price processes with semi-Markov and Hawkes Jump-Diffusion dynamics. We begin by discussing the basics of RL and the deep RL framework used; we deployed the...

Much research has examined the drivers of firms' R&D investments. However, many questions remain with respect to the role of R&D as a learning target and as a means of achieving legitimacy, particularly in the context of imitative R&D strategy. We develop a theory that integrates different...

Using a novel and unique panel dataset of individual-level professional forecasts at short, medium, and very-long horizons, we provide new stylized facts about survey forecasts. We present direct evidence that forecasters use multivariate models in an environment with imperfect information about...

The natural interest rate is the real rate that would prevail in the long-run. The standard view in macroeconomics is that the natural rate depends exclusively on structural factors such as productivity growth and demographics. This paper challenges this view by discussing three alternative, and...

This paper provides an overview of behaviors and learning of heterogeneous economic agents -whether individuals or firms- within complex evolving economies. It aims to explore the microfoundation of agency and learning, two fundamental aspects that constitutively contribute to the emergence of...

The World Bank Group considers itself a "Knowledge Bank." The Bank's knowledge work contributes to development outcomes both by informing clients in various policy and reform areas, and by informing staff and clients on the selection, design, and implementation of lending operations. This...