Limited memory capacity, retrieval constraints and anchoring are central to expectation formation processes. We develop a model of adaptive expectations where individuals are able to store only a finite number of past experiences of a stochastic state variable. Retrieval of these experiences is...

We experimentally investigate how price expectations are formed in a large asset market where subjects' only task is to forecast the future price of a risky asset. The realized prices depend on these expectations. We observe small (6 participants) and large markets (about 100 participants). In...

We develop a general framework for measuring biases in expectation formation. The method is based on the insight that biases can be inferred from the response of forecast errors to past news. Empirically, biases are measured by flexibly estimating the impulse response function of forecast...

We conduct an experiment to test whether the size of a loss and the time in a losing position affect investors’ adaptation to the loss situation and, subsequently, whether this adaptation affects future investment decisions. As investors adapt to losses, their neutral reference point shifts...

The recent macroeconomic literature stresses the importance of managing heterogeneous expectations in the formulation of monetary policy. We use a stylized macro model of Howitt (1992) to investigate inflation dynamics under alternative interest rate rules when agents have heterogeneous...

This experiment compares the price dynamics and bubble formation in an asset market with a price adjustment rule in three treatments where subjects (1) submit a price forecast only, (2) choose quantity to buy/sell and (3) perform both tasks. We find deviation of the market price from the...

Different theories of expectation formation and learning usually yield different outcomes for realized market prices in dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental environment. Subjects are asked to predict the next...