Conventional wisdom usually suggests that agents should use all the data they have to make the best possible prediction. In this paper, however, it is shown that agents may sometimes be able to make better predictions by throwing away old data. The optimality criterion agents adopt is the mean squared error criterion.mean squared error; prediction; optimality.
When an agent chooses between prospects, noise in information processing generates an effect akin to...
Learning is introduced into a sequence of large square endowment economies indexed by n, in which ag...
A "statistician" takes an action on behalf of an agent, based on the agent's self-reported personal ...
Conventional wisdom usually suggests that agents should use all the data they have to make the best ...
This dissertation presents three independent essays in microeconomic theory. Chapter 1 suggests an a...
Possibly, but more likely you are merely a victim of conventional wisdom. More data or better models...
The paper studies the way economic turmoils influence the lay agents’ predictions of macroeconomic f...
In this paper, we criticize the current adaptive or statistical learning literature. Instead of emph...
We study the framework of optimal decision making under uncertainty where the agents do not know the...
The paper studies the way economic turmoils influence the lay agents\u2019 predictions of macroecono...
Modern investors face a high-dimensional prediction problem: thousands of observable variables are p...
Different agents need to make a prediction. They observe identical data, but have different models: ...
This article questions the rather pessimistic conclusions of Allen et Carroll (2001) about the abili...
This thesis investigates optimality of heuristic forecasting. According to Goldstein a Gigerenzer (2...
Least square (LS) learning model is one of the most seminal models on how individuals can learn a ra...
When an agent chooses between prospects, noise in information processing generates an effect akin to...
Learning is introduced into a sequence of large square endowment economies indexed by n, in which ag...
A "statistician" takes an action on behalf of an agent, based on the agent's self-reported personal ...
Conventional wisdom usually suggests that agents should use all the data they have to make the best ...
This dissertation presents three independent essays in microeconomic theory. Chapter 1 suggests an a...
Possibly, but more likely you are merely a victim of conventional wisdom. More data or better models...
The paper studies the way economic turmoils influence the lay agents’ predictions of macroeconomic f...
In this paper, we criticize the current adaptive or statistical learning literature. Instead of emph...
We study the framework of optimal decision making under uncertainty where the agents do not know the...
The paper studies the way economic turmoils influence the lay agents\u2019 predictions of macroecono...
Modern investors face a high-dimensional prediction problem: thousands of observable variables are p...
Different agents need to make a prediction. They observe identical data, but have different models: ...
This article questions the rather pessimistic conclusions of Allen et Carroll (2001) about the abili...
This thesis investigates optimality of heuristic forecasting. According to Goldstein a Gigerenzer (2...
Least square (LS) learning model is one of the most seminal models on how individuals can learn a ra...
When an agent chooses between prospects, noise in information processing generates an effect akin to...
Learning is introduced into a sequence of large square endowment economies indexed by n, in which ag...
A "statistician" takes an action on behalf of an agent, based on the agent's self-reported personal ...