Social Finance

Kuchler, Theresa; Stroebel, Johannes

doi:10.3386/w27973

Cited by 13 publications

(5 citation statements)

References 50 publications

(62 reference statements)

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“…Other motivations to signal investment in Bitcoin may include self-satisfaction (Mandel (2009)), a bandwagon effect (Leibenstein (1950)), and insecurity about identity (Braun and Wicklund (1989)). Kuchler and Stroebel (2020) review the empirical literature on how social interactions influence retail investors' choices.…”

Section: Focus On $1200mentioning

confidence: 99%

Uncovering Retail Trading in Bitcoin: The Impact of COVID-19 Stimulus Checks

Divakaruni

Zimmerman

2024

Management Science

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In April 2020, the U.S. government sent economic impact payments (EIPs) directly to households as part of its measures to address the COVID-19 pandemic. We characterize these stimulus checks as a wealth shock for households and examine their effect on retail trading in Bitcoin. We find a significant increase in Bitcoin buy trades of size $1,200, which is the modal EIP amount. We find similar increases in trading for other countries that paid out stimulus checks. We estimate that the EIPs have a significant impact on the U.S. dollar–Bitcoin trading pair, increasing buy volume by 3.8% and the price by 0.6%. We also find that demand for Bitcoin is highly price inelastic compared with the demand for stocks. We suggest the demographic characteristics that make people more resilient to the COVID-19 economic shock—single, computer literate, and educated—are also characteristics of people who are more interested in Bitcoin. This paper was accepted by Bruno Biais, finance. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4790 .

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Section: Focus On $1200mentioning

confidence: 99%

Uncovering Retail Trading in Bitcoin: The Impact of COVID-19 Stimulus Checks

Divakaruni

Zimmerman

2024

Management Science

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“…Other novel applications of social media data in the context of firearms research are also possible. For example, economists at New York University recently developed a social-connectedness index drawing on social media data that has been used to analyze social behavior during COVID-19 and to study housing markets (Bailey, Cao, Kuchler, and Stroebel 2018; Bailey, Cao, Kuchler, Stroebel, et al 2018; Bailey et al 2019, 2020, 2021; Kuchler, Russel, and Stroebel 2020; Kuchler and Stroebel 2020). A natural question is whether we can use social media to construct a set of useful firearm-related indices to monitor the dynamics of firearm-related conversations.…”

Section: The Future Of Social Media Data and Firearms Researchmentioning

confidence: 99%

Social Media Data for Firearms Research: Promise and Perils

Singh¹,

Gresenz²

2022

The ANNALS of the American Academy of Political and Social Scie

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Firearms research has been hindered by a persistent lack of high-quality, reliable, and timely data. Using social media data in firearms research is, therefore, appealing: these data are large in scale, continuously provided, passively obtained, inexpensive in some cases, and easily combined with data from traditional sources. We consider how social media data have been used in firearms research to date and how they can be best used moving forward. Despite the many advantages of using social media data, there are key analytical and ethical considerations associated with their use, including understanding the underlying population, constructing valid and reliable measures from shared content, the possibility of false data and misinformation through fake accounts, and concerns having to do with the privacy and consent of social media users. Notwithstanding these drawbacks, we show that there is a compelling case for the continued development of these data for firearms research and suggest principles for their responsible use in this context.

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“…A large literature in economics and finance has examined the role of spillover or peer effects in behavioral interventions (e.g., see Beshears et al (2018) and Kuchler and Stroebel (2020) for reviews of this literature in household finance). Although this is not our main focus, our setting is well suited to examine such effects because one student per dormitory room was allocated to either the financial literacy or the self-control intervention.…”

Section: B Spillover Effectsmentioning

confidence: 99%

Cultivating Self-Control in FinTech: Evidence from a Field Experiment on Online Consumer Borrowing

Bu¹,

Hanspal

Liao³

et al. 2021

J. Financ. Quant. Anal.

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We report the results of a longitudinal intervention with students across 5 universities in China designed to reduce online consumer debt. We allocate participants to either a financial literacy treatment group, a self-control treatment group, or a zero-touch control group. Our self-control training intervention features detailed tracking of spending and borrowing, budgeting, and introspection about consumption choices. This intervention reduces online borrowing and delinquency charges, mainly driven by a reduction in entertainment-related spending and borrowing. In contrast, financial literacy interventions improve test scores but only marginally affect borrowing. Our results suggest that cultivating self-regulation and budgeting skills can improve borrowing behavior on e-commerce platforms.

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Social Finance

Cited by 13 publications

References 50 publications

Uncovering Retail Trading in Bitcoin: The Impact of COVID-19 Stimulus Checks

Uncovering Retail Trading in Bitcoin: The Impact of COVID-19 Stimulus Checks

Social Media Data for Firearms Research: Promise and Perils

Cultivating Self-Control in FinTech: Evidence from a Field Experiment on Online Consumer Borrowing

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