We experimentally study how people form expectations about correlated variables. Subjects forecast a time-series variable A. In the baseline treatment, subjects only observe past values of A. In the correlated treatment, they additionally observe an informative correlated variable B. Our novel...

We develop a framework for measuring biases in expectation formation. The basic insight is that under- and overreaction to new information is identified by the impulse response function of forecast errors. This insight leads to a simple and widely applicable measurement procedure. The procedure...

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...

Expectations affect economic decisions, and inaccurate expectations are costly. Expectations can be wrong due to either bias (systematic mistakes) or noise (unsystematic mistakes). We develop a framework for quantifying the level of noise in survey expectations. The method is based on the...