/
index.html
154 lines (138 loc) · 8.1 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
---
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> Inference for Regression with Variables Generated from Unstructured Data </h5>
<div class="authors">
with Laura Battaglia, Tim Christensen, and Szymon Sacher</div>
<div class="summary">
<p>Plugging measures derived from unstructured data into regression models leads to biased inference. Our proposed solution is to jointly model informational retrieval and regression, which modern computational methods make possible.</p>
<a class="red-link" href="./pdf_files/reg_unstruct.pdf" target="_blank" rel="noopener noreferrer">
Paper</a>
</div>
</div>
<div class="paper" id="paper7">
<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="paper6">
<h5> Short and Variable Lags </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>Using novel daily measures of consumption, firm sales, and employment, we show that the economy reacts within days to monetary policy shocks. Time aggregation of the measures to quarterly frequency masks these short-run dynamics.</p>
<a class="red-link" href="./pdf_files/shortvariable_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="paper5">
<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="paper4">
<h5> Graphical Model Inference With External Network Data </h5>
<div class="authors">
with Jack Jewson, Li Li, Laura Battaglia, David Rossell, and Piotr Zweirnik
</div>
<div class="summary">
<p>We show how observed connections among variables in multiple networks can improve estimation of the precision matrix by targeting regularization and develop a Bayesian model for inferring pairwise correlations.</p>
<a class="red-link" href="./pdf_files/graphical_model_inference.pdf" target="_blank" rel="noopener noreferrer">
Paper
</a
><a class="green-link" href="https://github.com/llaurabat91/graphical-models-external-networks" target="_blank" rel="noopener noreferrer">
GitHub Repository
</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 -->