Knowledge that Transforms

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.

We develop a model that generates slowly unfolding disasters not only in the macroeconomy but also in financial markets. In our model, investors cannot exactly distinguish whether the economy is experiencing a mild/temporary downturn or is on the verge of a severe/prolonged disaster. Due to imperfect information, disaster periods are not fully identified by investors ex ante. Bayesian learning induces equity prices to gradually react to persistent consumption declines, which plays a critical role in explaining the VIX, variance risk premium, and put-protected portfolio returns. We show that our model can rationalize the market patterns of recent major crises, such as the dot-com bubble burst, Great Recession, and COVID-19 crisis, through investors' belief channel.

We study governance when shareholders vote and can also buy or sell shares. We find that voting for the policy that one believes is better for the firm maximizes portfolio value only when pivotal; otherwise, it is better to vote against one’s information, distort the market, and then trade at the distorted price. Equilibrium voting informativeness balances these forces and is demonstrably low. As the number of shareholders grows, the probability of making the correct decision becomes lower than the informational quality of just one shareholder’s private signal. Despite this, shareholders extract information rents from trading and thus obtain additional value from their private information. These effects are related to the level of direct information leakage in the market. The predicted patterns of trading and market volatility help reconcile several debates.

The option-implied oil price volatility is a strong negative predictor of economic growth beyond traditional uncertainty measures. A rise in oil volatility also predicts an increase in oil inventories and a reduction in oil consumption, in line with a propagation channel through the oil sector. We explain these findings within a macro-finance model featuring stochastic uncertainties and precautionary oil inventories: firms increase oil inventories when oil volatility rises, which curbs oil use for production and depresses economic activity. In the model and the data, aggregate equity prices fall at times of high oil volatility, with differential exposures across economic sectors.

We exploit a mortgage reform that differentially unlocked home equity across the Danish population and study how this impacted selection into entrepreneurship. We find that increased entry was concentrated among entrepreneurs whose firms were founded in industries where they had no prior work experience. Nevertheless, we find that marginal entrants benefiting from the reform had higher pre-entry earnings and a significant share of these entrants started longer-lasting firms. Our results are most consistent with a view that housing collateral enabled higher ability individuals with less-well-established track records to overcome credit rationing and start new firms, rather than only leading to ‘frivolous entry’ by those without prior industry experience.

Asset pricing predictions from the investment CAPM depend on the cross-sectional relation between investment and profitability. In samples of U.S. stocks featuring high cross-sectional investment-profitability correlation, both investment and profitability premiums are weak. Consistent with the conditional predictions from the investment CAPM, triple sorts on size, investment, and profitability as in Hou et al. (2015)’s q-factors resurrect the premiums in the high-correlation samples. We find similar results using cash-based profitability, consistent with the dynamic investment CAPM. Our work has important implications for constructing asset pricing factors and interpreting out-of-sample asset pricing test results, in particular the insignificance of historical investment and profitability premiums.

Between 2003 and 2006, the Federal Reserve raised rates by 4.25%. Yet it was precisely during this period that the housing boom accelerated, fueled by rapid growth in mortgage lending. There is deep disagreement about how, or even if, monetary policy impacted the boom. Using differences in exposure to the deposits channel of monetary policy, we show that Fed tightening induced a large reduction in banks’ deposit funding, which led banks to contract portfolio mortgage lending by 32%. However, this contraction was largely offset by substitution to privately-securitized (PLS) mortgages, led by nonbank originators. Fed tightening thus induced a shift in mortgage lending away from stable, insured deposit funding toward run-prone and fragile capital markets funding with little impact on overall lending. We find similar results during the most recent tightening cycle over 2014–2017 when PLS lending reemerged.

For-profit providers have become an important fixture of US higher education markets. Students who attend for-profit institutions take on more educational debt and are more likely to default on their student loans than those attending similarly-selective public schools. Because for-profits tend to serve students from more disadvantaged backgrounds, it is important to isolate the causal effect of for-profit enrollment on student debt and repayment outcomes as well as the educational and labor market mechanisms that drive any such effects. We approach this problem using a novel instrument combined with comprehensive institution-level data on student debt, default, educational attainment, and labor market outcomes. Our instrument leverages the interaction between changes in the demand for college due to labor demand shocks and the baseline supply of for-profit schools. We compare how enrollment and subsequent outcomes change across areas that experience similar labor demand shocks but that have different latent supply of for-profit institutions. The first-stage estimates show that students are much more likely to enroll in a for-profit institution for a given labor demand change when there is a higher supply of such schools in the base period. Among four-year students, for-profit enrollment leads to more loans, higher loan amounts, an increased likelihood of borrowing, and an increased risk of default. Two-year for-profit students also take out more loans, originate more student debt, and have higher default rates. We present evidence that these debt and default outcomes are driven by higher for-profit tuition and a negative effect of for-profit enrollment on labor market outcomes. Our results point to high costs and low returns to for-profit enrollment that generate worse student debt and repayment outcomes. These findings have important implications for public investments in higher education as well as for how students make postsecondary choices.

We use the COVID shock to study the direct and interactive effects of several forms of corporate flexibility on short- and long-term real business plans. We find that i) workplace flexibility, namely the ability for employees to work remotely, plays a central role in determining firms’ employment plans during the health crisis; ii) investment flexibility allows firms to increase or decrease capital spending based on their business prospects in the crisis, with effects shaped by workplace flexibility; and iii) financial flexibility contributes to stronger employment and investment, in particular when fixed costs are high. While the role of workplace flexibility is new to the COVID crisis, CFOs expect lasting effects for years to come: high workplace flexibility firms foresee continuation of remote work, stronger employment recovery, and shifting away from traditional capital investment, whereas low workplace flexibility firms rely more on automation to replace labor.

We add to the emerging literature on empirical asset pricing in the Chinese stock market by building and analyzing a comprehensive set of return prediction factors using various machine learning algorithms. Contrasting previous studies for the US market, liquidity emerges as the most important predictor, leading us to closely examine the impact of transaction costs. The retail investors’ dominating presence positively affects short-term predictability, particularly for small stocks. Another feature that distinguishes the Chinese market from the US market is the high predictability of large stocks and state-owned enterprises over longer horizons. The out-of-sample performance remains economically significant after transaction costs.