Chenyu Hou

PhD Job Market Candidate

My research interest is in Macroeconomics and Monetary Economics, with specific focus on expectation formation and information acquisition.

My job market paper examines how households utilize rich sources of information to form macroeconomic expectations, using an innovative non-parametric method that maintains the dynamic structure of most learning models: Recurrent Neural Network.

In another paper with Franck Portier and Paul Beaudry, we highlight the presence of a cost-channel of monetary policy and discuss its implication on inflation and relevant policy rules.

I will be available for interviews at the 2020 EEA meeting and the 2020 ASSA/AEA meeting. I expect to graduate in 2021.

 

 

 

JOB MARKET PAPER

In this paper, I propose a flexible non-parametric method using Recurrent Neural Networks (RNN) to estimate the dynamic structure of most expectation formation models in macroeconomics. This approach does not rely on restrictive assumptions of functional forms and parametric methods but nests the standard approaches of empirical studies on expectation formation. Applying this approach to data on macroeconomic expectations from the Michigan Survey of Consumers (MSC) and a rich set of signals available to U.S. households, I find qualitatively new results: (1) agents' expectations about the future economic condition have asymmetric and non-linear responses to signals; (2) agents' attentions shift from signals about the current state to signals about future: they behave as if they were adaptive learners in ordinary periods and become forward-looking as the state of economy gets worse; (3) the content of signals on economic condition, rather than the volume of these signals, plays the most important role in creating the attention-shift. My method also allows me to apply the Double Machine Learning method to assess the statistical significance of these empirical findings. Finally, I show these stylized facts can be generated by a model with rational inattention, in which information endogenously becomes more valuable when economic status gets worse.[GO TO PAPER]

WORKING PAPER

This papers begins by highlighting how the presence of a cost channel of monetary policy can offer new insights into the behavior of inflation when the Phillips curve is locally quite flat. For instance, we highlight a key condition whereby lax monetary policy can push the economy in a low inflation trap and we discuss how, under the same condition, standard policy rules for targeting inflation may need to be modified.  In the second part of the paper we explore the empirical relevance of the conditions that give rise to these observations using US data.  To this end, we present both (i) a wide set of estimates derived from single-equation estimation of the Phillips curve and (ii) estimates based on structural estimation of a full model. The results from both sets of empirical exercises strongly support the key condition we derived.[GO TO PAPER]

Expectations about different macroeconomic aspects correlate with each other. I perform a structural test in framework of noisy information model and show that individual forms their expectations on multiple macroeconomic variables jointly rather than independently, thus causing these expectations to be correlated with each other. In particular, they have a subjective model about the economy. They believe economic conditions will be worse during episode with extensive inflation news, even if there's only mild inflation, causing their average expectation on inflation to co-move with that of unemployment and business condition. To alleviate the concern of possible mis-specification of linear noisy information model, I then propose an innovative generic learning model that can cover a large class of expectation formation models, including those are standard in the literature. The effect of signals on expectational variables is estimated with Recurrent Neural Network. I found again realized inflation increase household's perceived future unemployment rate change whereas actual unemployment rate hike will lower their expected inflation. The pessimistic effect of inflation is not because of household's belief on interest rate and is particularly strong after late 1990s. These patterns call for explanations on how agents form beliefs on interactions between macroeconomic variables that are different from the actual structure of data. They also suggest Central Bank should use inflation-related expectation management policy with cautious, as such policy may induce pessimistic responses among households.[GO TO PAPER]

WORK IN PROGRESS

India has witnessed a remarkable catch-up since 1983 by the historically discriminated against scheduled castes and tribes (SC/STs) towards non-SC/ST levels in their education attainment levels, occupation choices as well as wages. This period has also been characterized by a sharp rise in aggregate economic growth and a structural transformation of the Indian economy. We develop a multi-sector model with two types of agents to show that productivity growth during this period can explain 3/4 of the observed convergence between the groups. The key to our result is the existence of an initial affirmative action policy in education and/or jobs for the relatively disadvantaged group. We show some indirect evidence in support of this channel by examining the convergence patterns of Muslims who were not covered by such affirmative action policies.

Uncertainty about the fundamental aspects of the evolution of infections in the population (e.g. the infection rate and the fraction of infected population) is a prominent feature of newly discovered viruses. This paper studies the role of early testing as a tool on the hands of the policy maker for learning about the structural parameters underlying the evaluation of a pandemic. The paper analyses the informational content of testing at the different stages of a pandemic and how learning through testing interacts with other instruments in the definition of the optimal policy.

In this paper I document new data patterns for US economy since 1950 to describe the volatility change usually referred as ”Great Moderation”. I argue the conventional approach using first difference data is a particular way of data transformation and has lost some important features in a way that is in favor of the existing explanations on Great Moderation. I then want to explore plausible causes for Great Moderation that is consistent with both the conventional and the new patterns of data.

 

TEACHER ASSISTANT

  • ECON 626 Econometrics Theory I (Phd) 2016
  • ECON 302 Intermediate Macroeconomics (Undergrad) 2017, 2018
  • ECON  502 Advanced Macroeconomics (Masters) 2017-2019
  • ECON 546 Monetary Economics (Masters) 2018
  • ECON 556 International Finance (Masters) 2019
  • ECON  323 Quantitative Economics Modeling with Data Science Applications (Undergrad) 2020

GUEST LECTURER

  • ECON  307 Honours Intermediate Macroeconomics II
  • Lecture on “Rational and Adaptive Expectation”