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---
layout: default
title: Stephen Hansen - Economics Professor
---
<div class="bio">
<h1>Stephen Hansen</h1>
<img src="my_photo_web.jpg" alt="Stephen Hansen Photo">
<h3> About Me </h3>
<p>I am a Professor of Economics at <a href="https://www.ucl.ac.uk/economics/ucl-department-economics"
target="_blank" rel="noopener noreferrer">University College London</a>. My current research uses
unstructured data to build new
measures of economic activity and behavior across a variety of applications, most often related to
organizational
economics and monetary policy. I maintain a <a href="https://github.com/sekhansen" target="_blank"
rel="noopener noreferrer">Github page</a> where I share code and lecture slides related to methodologies for
the
analysis of unstructured and high-dimensional data. I co-organize the monthly <a
href="https://sites.google.com/view/amleds/home" target="_blank" rel="noopener noreferrer">AMLEDS</a>
webinar
that explores economic applications of machine learning. My research is supported by an ERC Conslidator Grant.
</p>
</div>
<div class="blurb">
<hr>
<h3> Current Working Papers </h3>
<div class="hover-to-expand-msg">
(Hover on a paper to expand. On mobile, tap to expand.)
</div>
<!-- Use '>' on next line to end closing tag of one link right before start of another. Prevents unwanted extra whitespace between links. -->
<div class="paper" id="paper8">
<h5> Initial Match and Career Outcomes: Evidence from the NFL Draft </h5>
<div class="authors">
with Pablo Casas-Arce, Miguel Martinez-Carrasco, and Asis Martinez-Jerez</div>
<div class="summary">
<p>NFL draft rules randomly allocate players of similar quality to teams of different quality. But there is
no effect of initial match on long-term performance, suggesting that firms do not contribute to
long-term inequality in sufficiently competitive markets.</p>
<a class="red-link" href="./pdf_files/NFL.pdf" target="_blank" rel="noopener noreferrer">
Paper</a>
</div>
</div>
<div class="paper" id="paper7">
<h5> Inference for Regression with Variables Generated by AI or Machine Learning </h5>
<div class="authors">
with Laura Battaglia, Tim Christensen, and Szymon Sacher</div>
<div class="summary">
<p>Plugging measures derived from AI/ML algorithms into regressions leads to biased estimation but does not
distort confidence intervals. Valid inference can be performed with a bias correction or maximum
likelihood estimation.</p>
<a class="red-link" href="./pdf_files/reg_unstruct.pdf" target="_blank" rel="noopener noreferrer">
Paper</a>
</div>
</div>
<div class="paper" id="paper6">
<h5> Policymakers' Uncertainty </h5>
<div class="authors">
with Anna Cieslak, Michael McMahon, and Song Xiao
</div>
<div class="summary">
<p>Inflation uncertainty leads to more hawkish policy stances on the Federal Open Market Committee. This
appears to arise from concerns for tail risk than model parameter uncertainty. </p>
<a class="red-link" href="./pdf_files/mp_uncertainty.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a>
</div>
</div>
<div class="paper" id="paper5">
<h5> The Short Lags of Monetary Policy </h5>
<div class="authors">
with Gergely Buda, Vasco Carvalho, Giancarlo Corsetti, Joao Duarte, Afonso Moura, Alvaro Ortiz, Tomasa
Rodrigo, Sevi Rodriguez Mora, and Guilherme Alves da Silva
</div>
<div class="summary">
<p> We build a unique dataset of daily measures of consumption, investment, output, and employment to study
the transmission of monetary policy shocks. Consumption and downstream sectors react quickly to shocks,
which then more slowly propagate to the rest of the economy. </p>
<a class="red-link" href="./pdf_files/short_lags.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a><a class="blue-link" href=https://cepr.org/voxeu/columns/monetary-policy-also-has-short-run-effects
target="_blank" rel="noopener noreferrer">
VoxEU Column
</a>
</div>
</div>
<div class="paper" id="paper4">
<h5> Remote Work across Jobs, Companies, and Space </h5>
<div class="authors">
with Peter Lambert, Nick Bloom, Steven Davis, Raffaella Sadun, and Bledi Taska
</div>
<div class="summary">
<p>We use a large language model trained on tens of thousands of human labels to measure remote and hybrid
work adoption with unprecedented granularity. We document large heterogeneity in adoption across narrow
occupation categories, cities, and firms.</p>
<a class="red-link" href="./pdf_files/wham.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a><a class="blue-link" href=https://cepr.org/voxeu/columns/using-job-postings-quantify-remote-work
target="_blank" rel="noopener noreferrer">
VoxEU Column
</a><a class="green-link" href="https://wfhmap.com/" target="_blank" rel="noopener noreferrer">
Website
</a>
</div>
</div>
<div class="paper" id="paper3">
<h5> National Accounts in a World of Naturally Occurring Data: A Proof of Concept for Consumption </h5>
<div class="authors">
with Gergely Buda, Vasco Carvalho, Alvaro Ortiz, Tomasa Rodrigo, and Sevi Rodriguez Mora
</div>
<div class="summary">
<p>We use comprehensive financial transactions from one of Europe's largest banks to build a large-scale
consumption survey using national accounting principles. We use this to build aggregate and
distributional accounts for consumption, as well as a detailed individual consumption panel. </p>
<a class="red-link" href="./pdf_files/consumption_measure.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a>
</div>
</div>
<div class="paper" id="paper2">
<h5> The Demand for Executive Skills </h5>
<div class="authors">
with Tejas Ramdas, Raffaella Sadun, and Joseph Fuller
</div>
<div class="summary">
<p>We measure the demand for executive skills aross firms using a unique, large-scale corpus of job
specifications. The importance of social skills is growing over time and is related to firm size, firm
scope, and the information intensity of worker skills. </p>
<a class="red-link" href="./pdf_files/c_suite_skill_demand.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a><a class="blue-link" href="https://hbr.org/2022/07/the-c-suite-skills-that-matter-most" target="_blank"
rel="noopener noreferrer">
HBR Article
</a>
</div>
</div>
<div class="paper" id="paper1">
<h5> Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19 </h5>
<div class="authors">
with Steven Davis and Cristhian Seminario-Amez
</div>
<div class="summary">
<p>We combine elements of supervised machine learning and dictionary methods to uncover narrow,
interpretable risk exposures from 10-K filings that account for firm-level reactions to aggregate
shocks. We apply this idea to study equity returns during the COVID-19 pandemic. </p>
<a class="red-link" href="./pdf_files/risk_exposures.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a><a class="blue-link" href=https://cepr.org/voxeu/columns/firm-level-stock-price-reactions-pandemic-news
target="_blank" rel="noopener noreferrer">
VoxEU Column
</a>
</div>
</div>
</div>
<!-- /.blurb -->