I present evidence of systematically heterogeneous expectations, a violation of the Rational Expectations Hypothesis. I demonstrate that the expectations of different gender and wealth cohorts have different relative abilities to predict inflation, interest rates, unemployment, income, stock...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

A feature of GMM estimation--the use of a consistent estimate of the optimal weighting matrix rather than the joint estimation of the model parameters and the weighting matrix--can lead to the sensitivity of GMM estimation to the choice of parameter normalization. In many applications, including...

Lending standards are a direct measure of credit conditions. We use the micro data merged from three separate sources to construct this measure and document that an uncertain macroeconomic outlook, rather than banks' balance sheet positions, was an important reason that a majority of banks...

This paper specifies an estimable dynamic model of sequential discrete choices in a controlled jump-process framework. We study sufficient conditions under which the agent's optimal policy is stationary. We show that the observable event histories at the micro-level are sample paths of a...

In this paper, we discuss how to best exploit the information contained in spells that are in progress when an observation period begins, that is, left-censored and left-truncated duration data. We provide a survey of censoring and truncation mechanisms in event history models. We describe some...

We present the methodology for developing a predictive model for identifying homeless persons likely to have high future costs for public services. It was developed by linking administrative records from 2007 through 2012 for seven Santa Clara County agencies and identifying 38 demographic,...

Selectivity bias caused by protest responses in Contingent Valuation studies can be detected and corrected by means of sample selection models. This paper compares two methods: the Heckman 2-steps method and the full ML, applied to data on forest recreation - where WTP is elicited as a...