Shifrah Aron-Dine

PhD Candidate in Economics, Stanford

I am a PhD student in the Department of Economics at Stanford University. 

My research interests are in Macroeconomics, Finance,  and Environmental Economics.

Job Market Paper

"Rebuild or Relocate? Recovery after Natural Disasters"

Current US government policy after large natural disasters is to subsidize rebuilding what existed pre-disaster. While public rebuilding assistance may speed up the economic recovery after a shock, it distorts private relocation and rebuilding incentives. In this paper, I document new facts on household relocation and rebuilding decisions after hurricanes using detailed migration data and a survey of affected individuals. I find that migration is a widespread but costly form of ex-post insurance. Age, wealth, and housing tenure are all important determinants of household choices post-disaster. Motivated by these empirical findings, I propose a dynamic equilibrium model of migration, housing, and infrastructure, with rich household heterogeneity. I find that homeowners, especially those with less home equity at the time of the disaster are the biggest beneficiaries under current policy.

Working Papers

This paper studies sustainable investing using data from a representative survey of German households and a quantitative asset pricing model with heterogeneous investors. About a third of households have green investments worth 11% of household wealth.  Green investments are currently relatively risky, with equity as the main pathway, while green bank accounts are rare.  We find substantial heterogeneity in green taste for both safe and risky green assets throughout the wealth distribution, which can either increase or decrease demand for these assets. Model counterfactuals show that nonpecuniary benefits and hedging demands currently make green equity more expensive for firms.  Nevertheless, the rise of sustainable investing has introduced a greenium of about 1%, as investors who are now aware of green stocks bid up their prices. Many households desire green bank accounts which could substantially increase overall green finance. Feeding treatment effects from an RCT in the survey into our model suggests that greater awareness of climate finance could also lead to a further burst in green equity investment.


Spending Responses to High-Frequency Shifts in Payment Timing: Evidence from the Earned Income Tax Credit (with Aditya Aladangady David Cashin,  Wendy DunnLaura Feiveson,  Paul Lengermann, Katherine Richard, and Claudia Sahm) [Official Link, PDF],  AEJ: Economic Policy, 2023

This study explores the spending response to tax refunds for Earned Income Tax Credit recipients using a novel dataset combining transaction-based measures of retail spending with administrative IRS data on tax refunds. Our dataset allows us to exploit variation in the timing of EITC refunds, including changes related to the 2017 PATH Act, along with cross-state differences in refund magnitudes to identify spending responses. Results show EITC recipients spend about $0.30 per refund dollar ($1,150 for the average refund) within just two weeks of issuance, suggesting stimulus targeted at this population may provide a quick boost to aggregate demand.

Re-measuring Gentrification (with devin michelle bunten and Benjamin Preis) [Official Link, PDF], Urban Studies, 2023

We develop an expectations-based measure of gentrification. Property values today incorporate market participants’ expectations of the neighbourhood’s future. We contrast this with present-oriented variables like demographics. To operationalise the signal implicit in property values, we contrast the percentile rank of a neighbourhood’s average house price to that of its average income, relative to its metropolitan area. We take as our signal of gentrification the rise of a neighbourhood’s house value percentile above its income percentile. We show that a gap between the house value and income percentiles predicts future income growth. We further validate our metric against existing approaches to identify gentrification, finding that it aligns meaningfully with qualitative analyses built on local insight. Compared to existing quantitative approaches, we obtain similar results but usually observe them in earlier years and with more parsimonious data. Our approach has several advantages: conceptual simplicity, communicative flexibility with graphical and map forms and availability for small geographies on an annual basis with minimal lag.

From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending (with Aditya AladangadyWendy DunnLaura Feiveson,  Paul Lengermann, and Claudia Sahm).[Official Link, PDF]. NBER CRIW Volume: Big Data for 21st Century Economic Statistics, 2022, edited by Katharine G. Abraham, Ron S. Jarmin, Brian Moyer, and Matthew D. Shapiro

Timely access to information on consumer spending is important to economic policymakers. The Census Bureau's Monthly Retail Trade Survey is a primary source for monitoring spending nationally but publication delays and subsequent revisions diminish its usefulness for real-time analysis, and do not allow for analysis of localized or short-lived shocks. Expanding the survey to include higher frequencies or subnational detail would be costly and increase respondent burden. We develop new estimates of retail spending that are both timely and granular. We use anonymized transaction data from First Data (now Fiserv), an electronic payments technology company, to construct daily spending estimates at retailers and restaurants for detailed geographies. Our estimates are available a few days after the transactions occur, and span from 2010 to the present. When aggregated to the national level and monthly frequency, the time-series pattern of our estimates is similar to the official Census statistics. We present two applications of these new data. First, our estimates allowed the Federal Reserve to monitor spending in real time during the 2019 government shutdown, when Census data were delayed. Second, we leveraged the timely geographic detail to estimate the effects on spending of Hurricanes Harvey and Irma in 2017.

Other Publications

High-frequency Spending Responses to the Earned Income Tax Credit (with Aditya Aladangady David Cashin,  Wendy DunnLaura Feiveson,  Paul Lengermann, Katherine Richard, and Claudia Sahm). [Official Link]. FEDS Notes. Board of Governors of the Federal Reserve System. 2018.

The Effect of Sales-Tax Holidays on Consumer Spending (with Aditya AladangadyWendy DunnLaura Feiveson,  Paul Lengermann, and Claudia Sahm). [Official Link]. FEDS Notes. Board of Governors of the Federal Reserve System, 2017.

The Effect of Hurricane Matthew on Consumer Spending (with Aditya AladangadyWendy DunnLaura Feiveson,  Paul Lengermann, and Claudia Sahm). [Official Link]. FEDS Notes. Board of Governors of the Federal Reserve System, 2016.

Physics Publications

First-Principles Investigation of Structural and Magnetic Disorder in CuNiMnAl and CuNiMnSn Heusler Alloys. Shifrah Aron-Dine, Gregory S. Pomrehn, Aurora Pribram-Jones, Kevin J. Laws, and Lori Bassman.  [Official Link, PDF]. Physical Review B 95, 024108, 2017.

High Entropy Brasses and Bronzes - Microstructure, Phase Evolution and Properties. Kevin J. Laws, Cody Crosby, Aarthi Sridhar, Patrick Conway, Leah S. Koloadin, Mo Zhao, Shifrah Aron-Dine, and Lori Bassman. [Official Link] Journal of Alloys and Compounds 650, 949-961, 2015.

Coded Aperture Detector: an Image Sensor with sub 20-nm Pixel Resolution. Ryan Miyakawa, Rafael Mayer, Antoine Wojdyla, Nicolas Vannier, Ian Lesser, Shifrah Aron-Dine, and Patrick Naulleau. [Official Link]. Optics Express 22 16, 19803-19809, 2014 .