Three essays in economics

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, September, 2020

Bibliographic Details
Main Author: Furukawa, Chishio.
Other Authors: Abhijit V. Banerjee and Stephen Morris.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2021
Subjects:
Online Access:https://hdl.handle.net/1721.1/129013
_version_ 1826197139915538432
author Furukawa, Chishio.
author2 Abhijit V. Banerjee and Stephen Morris.
author_facet Abhijit V. Banerjee and Stephen Morris.
Furukawa, Chishio.
author_sort Furukawa, Chishio.
collection MIT
description Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, September, 2020
first_indexed 2024-09-23T10:43:25Z
format Thesis
id mit-1721.1/129013
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T10:43:25Z
publishDate 2021
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/1290132021-01-06T03:56:24Z Three essays in economics Furukawa, Chishio. Abhijit V. Banerjee and Stephen Morris. Massachusetts Institute of Technology. Department of Economics. Massachusetts Institute of Technology. Department of Economics Economics. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, September, 2020 Cataloged from student-submitted PDF of thesis. Includes bibliographical references. This thesis consists of three essays on diverse topics but shared emphasis on statistical models with theory and empirics. The first and third essay examines the role of cognitive limitations in understanding biases in communication and learning. The second essay, joint with Masao Fukui, highlights the role of distributional assumptions of infection rates for epidemiological predictions, responding to the recent COVID-19 outbreak. The first chapter considers the effects of aggregation frictions on scientific communication and shows that publication bias emerges even when researchers are unbiased and communicate their findings optimally for readers. Specifically, when readers are cognitively constrained, they may only consider the binary conclusions rather than the estimates of the papers. Under such aggregation frictions of readers, researchers are shown to omit noisy null results and inflate marginal results. This chapter presents evidence consistent with this prediction, and develops a new bias correction method, called stem-based correction method, that is robust under the prediction of this and other models of publication selection processes. The second chapter examines the role of infection rate distributions for aggregate epidemiological dynamics in Susceptible-Infectious-Recovered (SIR) models. Specifically, we show that superspreading events (SSEs) of recent coronavirus outbreaks, including SARS, MERS, and COVID-19, follow a power law distribution with fat tails, or infinite variance. When embedding this distribution to stochastic SIR models, we find that idiosyncratic variations in SSEs generate important uncertainties in aggregate epidemiological dynamics. This result stands in contrast with the existing literature on stochastic SIR models that have assumed thin tailed distributions, and thus concluded that the idiosyncratic uncertainties are unimportant when the population is large. The third chapter considers the impact of imperfect recall on experimentation decisions and resulting inferences. When a Bayesian experimenter has an imperfect recall over past actions and information, her decisions depend not only on a confidence level but also on the expectation the future self will hold for today's action. This expectation arises from the persistent prior belief, and leads to the biases to conform to it. Meditation, to regulate one's attention with focus on the present, is shown to have an ameliorating effect: when the attention is focused, prior belief becomes essentially diffused so that the self-imposed expectation over behaviors becomes agnostic. by Chishio Furukawa. Ph. D. Ph.D. Massachusetts Institute of Technology, Department of Economics 2021-01-05T23:12:57Z 2021-01-05T23:12:57Z 2020 2020 Thesis https://hdl.handle.net/1721.1/129013 1227088268 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 197 pages application/pdf Massachusetts Institute of Technology
spellingShingle Economics.
Furukawa, Chishio.
Three essays in economics
title Three essays in economics
title_full Three essays in economics
title_fullStr Three essays in economics
title_full_unstemmed Three essays in economics
title_short Three essays in economics
title_sort three essays in economics
topic Economics.
url https://hdl.handle.net/1721.1/129013
work_keys_str_mv AT furukawachishio threeessaysineconomics