Sylvain Catherine

• Sylvain Catherine (2022), Keeping Options Open: What Motivates Entrepreneurs?, Journal of Financial Economics. Abstract

  Using French administrative data on job-creating entrepreneurs, I estimate a life-cycle model in which risk-averse individuals can start businesses and return to paid employment. Then, I use the dynamic model to value the option of returning to the labor market in case of failure. For new entrepreneurs, this option is worth 6.4 the average net wage in the country, which represented 136,000€ in 2018. This option value is explained by the unobserved heterogeneity in entrepreneurial abilities and the random-walk component of productivity. Estimated unobserved benefits of entrepreneurship represent 38.6% of the average net wage pre-tax per year (some 15% of profits), or 8,250€ in 2018. Unobserved benefits add up to 90,700€ over the average entrepreneurial spell. Together, unobserved benefits and the option value of returning to paid employment explain 42% of firm creations.

• Sylvain Catherine (2021), Countercyclical Income Risk and Portfolio Choices over the Life-Cycle, Review of Financial Studies. Abstract

  I structurally estimate a life-cycle model of portfolio choices that incorporates the relationship between stock market returns and the skewness of idiosyncratic income shocks. The cyclicality of skewness can explain (i) low stock market participation among young households with modest financial wealth and (ii) why the equity share of participants slightly increases until retirement. With an estimated relative risk aversion of 5 and yearly participation cost of $290, the model matches the evolution of wealth, of participation and of the conditional equity share over the life-cycle. Nonetheless, I find that cyclical skewness increases the equity premium by at most 0.5%.

• Sylvain Catherine, Maxwell Miller, Natasha Sarin (2020), Relaxing Household Liquidity Constraints through Social Security, Journal of Public Economics. Abstract

  More than a quarter of working-age households in the United States do not have sufficient savings to cover their expenditures after a month of unemployment. Recent proposals suggest giving workers early access to a small portion of their future Social Security benefits to finance their consumption during the COVID-19 pandemic. We empirically analyze their impact. Relying on data from the Survey of Consumer Finances, we build a measure of households’ expected time to cash shortfall based on the incidence of COVID-induced unemployment. We show that access to 1% of future benefits allows 75% of households to maintain their current consumption for three months in case of unemployment. We then compare the efficacy of access to Social Security benefits to already legislated approaches, including early access to retirement accounts, stimulus relief checks, and expanded unemployment insurance.
• Sylvain Catherine, Natasha Sarin, Max Miller, Social Security and Trends in Wealth Inequality. Abstract

  Recent influential work finds large increases in inequality in the U.S., based on measures of wealth concentration that notably exclude the value of social insurance programs. This paper revisits this conclusion by incorporating Social Security retirement benefits into measures of wealth inequality. Wealth inequality has not increased in the last three decades when Social Security is accounted for. When discounted at the risk-free rate, real Social Security wealth increased substantially from $5.6 trillion in 1989 to just over $42.0 trillion in 2016. When we adjust for systematic risk coming from the covariance of Social Security returns with the market portfolio, this increase remains sizable, growing from over $4.6 trillion in 1989 to $34.0 trillion in 2016. Consequently, by 2016, Social Security wealth represented 58% of the wealth of the bottom 90% of the wealth distribution. Redistribution through programs like Social Security increases the progressivity of the economy, and it is important that our estimates of wealth concentration reflect this.

• Sylvain Catherine (Work In Progress), Countercyclical Income Risk and Portfolio Choices: Evidence from Sweden. Abstract

  Using Swedish administrative panel data, we show that workers facing higher left-tail income risk when equity markets perform poorly are less likely to participate in the stock market and, conditional on participation, have lower equity shares. We call this measure of income risk “cyclical skewness” and show that it is a better predictor of equity holdings than other income risk measures such as variance, covariance, and countercyclical volatility. In line with theory, our findings are stronger at the beginning of the life-cycle, are not significant for individuals with substantial financial wealth, and are stronger when we focus on permanent income shocks. Finally, within their risky portfolio, workers put less weight on securities generating negative returns when their own income risk increases.

• Sylvain Catherine (Working), Labor Market Risk and the Private Value of Social Security.
• Sylvain Catherine, Thomas Chaney, David Thesmar, David Sraer, Zongbo Huang (Under Revision), Quantifying Reduced-Form Evidence on Collateral Constraints (accepted Journal of Finance). Abstract

  While a mature literature shows that credit constraints causally affect firm-level investment, this literature provides little guidance to quantify the economic effects implied by these findings. Our paper attempts to fill this gap in two ways. First, we use a structural model of firm dynamics with collateral constraints, and estimate the model to match the firm-level sensitivity of investment to collateral values. We estimate that firms can only pledge about 19% of their collateral value. Second, we embed this model in a general equilibrium framework and estimate that, relative to first-best, collateral constraints are responsible for 11% output losses.

Current Courses

• FNCE2500 - Venture Capital And The Finance Of Innovation

  This course covers the finance of technological innovation, with a focus on the valuation tools useful in the venture capital industry. These tools include the "venture capital method," comparables analysis, discounted cash flow analysis, contingent-claims analysis. The primary audience for this course is finance majors interested in careers in venture capital or in R&D-intensive companies in health care or information technology.

  FNCE2500001 ( Syllabus )

  FNCE2500002 ( Syllabus )

• FNCE9260 - Empirical Methods In Corporate Finance

  The course will cover a variety of micro-econometric models and methods including panel data models, program evaluation methods e.g. difference in differences, matching techniques, regression discontinuity design, instrumental variables, duration models, structural estimation, simulated methods of moments. The structure of the course consists of lectures, student presentations, and empirical exercises. Published studies will be utilized in a variety of fields such as corporate finance, labor economics, and industrial organization to illustrate the various techniques. The goal of the course is to provide students with a working knowledge of various econometric techniques that they can apply in their own research. As such, the emphasis of the course is on applications, not theory. Students are required to have taken a graduate sequence in Econometrics, you should be comfortable with econometrics at the level of William Green's "Econometric Analysis of Cross-Section and Panel Data".

  FNCE9260001 ( Syllabus )

Past Courses

• FNCE2500 - Vent Cap & Fnce of Innovation

  This course covers the finance of technological innovation, with a focus on the valuation tools useful in the venture capital industry. These tools include the "venture capital method," comparables analysis, discounted cash flow analysis, contingent-claims analysis. The primary audience for this course is finance majors interested in careers in venture capital or in R&D-intensive companies in health care or information technology.

• FNCE3990 - Independent Study

  Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.

• FNCE7500 - Vent Cap & Fnce Innovat

  This course covers the finance of technological innovation, with a focus on the valuation tools useful in the venture capital industry. These tools include the "venture capital method," comparables analysis, discounted cash flow analysis, contingent-claims analysis. The primary audience for this course is finance majors interested in careers in venture capital or in R&D-intensive companies in health care or information technology.

• FNCE9260 - Empirical Meth Corp Fn

  The course will cover a variety of micro-econometric models and methods including panel data models, program evaluation methods e.g. difference in differences, matching techniques, regression discontinuity design, instrumental variables, duration models, structural estimation, simulated methods of moments. The structure of the course consists of lectures, student presentations, and empirical exercises. Published studies will be utilized in a variety of fields such as corporate finance, labor economics, and industrial organization to illustrate the various techniques. The goal of the course is to provide students with a working knowledge of various econometric techniques that they can apply in their own research. As such, the emphasis of the course is on applications, not theory. Students are required to have taken a graduate sequence in Econometrics, you should be comfortable with econometrics at the level of William Green's "Econometric Analysis of Cross-Section and Panel Data".

Knowledge @ Wharton

• College Football Playoffs with Bill Connelly, Knowledge @ Wharton - 01/08/2025
• The Real Estate Market Survived Until 2025. What’s Next?, Knowledge @ Wharton - 01/07/2025
• AI in 2025: What Challenges Lie Ahead?, Knowledge @ Wharton - 01/07/2025
• Jeremy Siegel: 2025 Outlook for Stocks and the Economy, Knowledge @ Wharton - 01/07/2025
• What’s Ahead for Real Estate in 2025?, Knowledge @ Wharton - 01/07/2025
• Confidence in Cryptocurrency | David Reibstein and John Zhang (Part 1), Knowledge @ Wharton - 01/07/2025
• What’s Ahead for the Economy in 2025, Knowledge @ Wharton - 01/06/2025
• How Did AI Grow in 2024 and What’s in Store for 2025?, Knowledge @ Wharton - 01/02/2025
• NFL Data Science with Tom Bliss, Knowledge @ Wharton - 12/25/2024
• Overwhelmed by Too Many Choices When Shopping? Wharton Retail Expert Weighs In, Knowledge @ Wharton - 12/19/2024