Department of Economics
Texas Tech University
253 Holden Hall
Lubbock, TX 79409
My research focuses on how beliefs and predictions of people interact with the economy. I try to quantify the timing and accuracy of the information that people gather, and I aim to understand how the gathered information contributes to macro business cycles.
Identification of Rational Expectations Models Under Information Frictions
Identification of full information rational expectations (FIRE) models suffers from Manski’s (1993) reflection problem. I extend the standard rational expectations (RE) model to allow for a more general information structure and introduce a new framework to identify the generalized model with forecaster data. Identification is no longer subject to the reflection problem when two changes are made to the information structure: the addition of news shocks and imperfect information. News shocks provide additional variation in expectations about the future. Imperfect information provides changes in beliefs about past states, through which the feedback between expectations and decisions goes only in one direction. Expectations data are consistent with both. An application to Greenbook forecasts illustrates the importance of both news shocks and learning about the past. When I apply this framework to a Blanchard and Quah (1989) decomposition, I reach qualitatively new results. For example, expansionary supply shocks decrease unemployment. Supply shocks are also particularly subject to both news and information rigidities, so relaxing the information structure is key to correctly identifying these shocks.