Economics Department Seminar Schedule Spring 20142014 Economics Brownbag Seminars
Thursday, March 6
Place: SGMH 3333
Speaker: Justin Jarvis
Title: "Individual Determinants of Homelessness: A Revealed Preference Approach"
I will investigate how a homeless person’s intensity of homelessness is predicted by the individual’s discount rate and risk tolerances. I will construct a data set by interviewing all street homeless individuals in Costa Mesa, a population of approximately 180 people. During that interview, I will use a self-reported homeless history to construct a Homelessness Intensity Measure, a continuous variable from 0 to 1 in which 0 indicates someone who is not homeless and 1 indicates an individual who is intensely homeless (every single night is spent on the streets). I will have all individuals play two games: 1) A discount rate game in which they will be coded as either “patient” or “impatient” according to their decision to receive either a small payment now or a larger payment at a later date, and 2) A risk-tolerance game in which they are coded as being either “risk loving” or “risk averse” in accordance with their decision to play either a risky gamble or a safe gamble (both options will have the same expected payout but differing variances). Participants will get to keep the money used in these games. I posit that an increase in impatience, and an increase in riskiness are both associated with an increase in the individual’s Homelessness Intensity Measure. I will fit an econometric model that regresses the individual’s Homelessness Intensity Measure on the risk and discount dummies mentioned above, as well as on demographic and social controls, in order to test my hypothesis.
Friday, March 14
Place: SGMH 3333
Speaker: Daniel Cavagnaro
Title: “Optimal stimuli for testing behavioral choice models: An adaptive approach”
Collecting data to test models of decision making requires stimuli to be presented to decision makers. While models aim to predict choices across a wide range of stimuli, practical limitations force experimenters to select only a handful for actual testing. Some stimuli tend to be much more diagnostic than others, so the selection of optimal stimuli is crucial to the success of an experiment. In this talk, I will present an Adaptive Design Optimization approach to the selection of decision stimuli, which is very general in its application. The foundation of the approach is Bayesian, so it involves a precise statement about the value of information, and it adapts the stimulus in each experimental trial based on the results of preceding trials. I will provide a theoretical framework for the approach and demonstrate its application in empirical studies of risky choice and temporal discounting.
Friday, April 11
Place: SGMH 3333
Speaker: Gabriela Best
Title: “In what sense is monetary policy forward looking?”
This paper extends a standard New Keynesian model by introducing anticipated shocks to inflation, output, and interest rates, and by incorporating forward-looking monetary policy. The latter aspect is modeled through the presence of an expected future interest rate term in the Taylor rule that recent literature has found to be economically and statistically important in a variety of settings without anticipated shocks. Using Bayesian econometric methods, we find that the presence of anticipated shocks improves the model's fit to U.S. data but reduces the Fed's implied forecast-targeting horizon from about 2 quarters to 1 month or less. Our results suggests that, although communicating its intentions regarding future monetary policy conduct play an important role for the Fed, responding to its expectations of future macroeconomic conditions is not.