Job market paper
Information frictions: Learning and Inattention in an Estimated New Keynesian Model
This paper considers a model with informational frictions and sticky prices in which agents form subjective expectations using an economic model and possibly out-of-date information. The proposed expectation formation mechanism is estimated via Bayesian methods and tested against rational expectations.
The paper yields three novel results. First, the data strongly prefers the model embedding inattention `a la Mankiw and Reis (2002) and subjective expectations under adaptive learning. Secondly, the degree of sticky information is susceptible to how the expectation formation process is modeled. In particular, the level of inattention is reduced considerably when I depart from the rational expectation assumption. Finally, this result remains unchanged when tested using real-time macroeconomic series and expectations data from the U.S. Survey of Professional Forecasters.
Do economic conditions matter for inflation expectations?
In this paper, I assess the role of economic conditions in inflation expectation formation using a Bayesian latent class ordinal model and survey data from the Michigan Survey of Consumers. On the contrary to most literature on inflation expectations, I use qualitative (ordinal) data on inflation expectations. This has the advantage of not demanding a point forecast from individuals that are not professional forecasters. Thus, the level of misunderstanding, uncertainty, and burden for the respondent decreases, helping to ensure the quality of the responses.
The results show evidence of inflation expectations been formed distinctly depending on the economic conditions faced by individuals. Moreover, the effect of demographic indicators, such as age, gender, education, and income, on inflation expectations varies with the level of distress of the economy. Overall, these findings give relevant insights for monetary policy.
Figure 1. Education effects on different inflation expectations (i.e. deflation, no inflation, and inflation) during Economic Distress (in red) and No Economic Distress (in blue).
Central bank transparency under adaptive learning
This paper uses Bayesian methods to estimate a baseline New Keynesian model with adaptive learning to assess the impact of central bank transparency on the evolution of agents’ expectations for the Mexican case.
The data prefer the scenario with the most realistic degree of transparency for the modern Mexican experience, partial transparency, where the central bank not only credibly communicates the inflation target but also discloses relevant information about its policy rule. Plus, the implied learning mechanism is able to match the empirical inflation expectations from the Survey on Expectations of Private Sector Specialists issued by the Mexican Central Bank. Moreover, the results suggest that higher degrees of transparency increase the effectiveness of monetary policy in stabilizing the economy.
Figure 2. IRF to a monetary policy shock under various degrees of central bank transparency.
Work in progress
Can Heterogeneous Expectations New Keynesian Models Match the Dispersion of Survey Forecasts (with Fabio Milani)
This paper explores the effectiveness of HENK models to match the level of dispersion observed in survey data on expectations.
The expectational channel of monetary policy
This paper studies the effect of central bank communication on survey expectations for the UK case.
© 2021 L. Carolina Acuña Armenta.