Knowledge that Transforms

I show that prices impact analyst cash flow expectations and argue this impact can partially reconcile subjective beliefs data with asset pricing models in which investors have rational expectations and discount rate variation drives prices. Previous work argues that correlations of biased analyst cash flow expectations with prices and future returns contradict rational models and imply biased investor expectations distort prices. However, using two instrumental variables for price, I find increases in price unrelated to cash flow news raise analyst cash flow expectations. Based on this empirical finding, I propose a model with rational investors that matches key moments in beliefs data: analysts form biased cash flow expectations by learning from prices that contain discount rate variation. Thus, while stylized facts in beliefs data can be consistent with investors having biased expectations that distort prices, these facts can also be consistent with investors having rational expectations and analysts learning from prices.

We explore the extent to which aspirations – such as those forged in the course of social interactions – explain ‘puzzling’ behavioral patterns in investment decisions. We motivate an aspirational utility, reminiscent of Friedman and Savage (1948), where social considerations (e.g., status concerns) provide an economic foundation for aspirations. We show this utility can explain a range of observed investor behaviors, such as the demand for both right- and left-skewed assets; aspects of the disposition effect; and patterns in stock-market participation consistent with empirical observations. We corroborate our theoretical findings with two novel laboratory experimental studies, where we observed participants’ preference for skewness in risky lotteries shift as lab-induced aspirations shifted.

A central finding of the theoretical literature on bargaining is that parties’ attitudes towards delay influence bargaining outcomes. However, the ability to endure delays, resilience, is often private information and hard to measure in most real-world contexts. In the context of collective bargaining, we show firms actively attempt to become financially resilient in anticipation of labor negotiations. Firms adjust their financial resilience to respond to the passage of right-to-work laws (RWLs). Unions’ financial structure also responds to RWLs. Our findings suggest resilience is key to understanding the process through which collective bargaining determines wages.

After 1945, expected returns have started to dominate the variation in equity price movements, leaving little room for expected dividend growth. An increase in equity duration can help explain this change. Expected returns vary more for payouts further into the future. Furthermore, because expected returns are more persistent than growth rates, they are more important for longer-duration assets. We provide empirical support for this explanation across three datasets: dividend strips, the long time series for the aggregate market, and the cross-section of stocks. A simple present value model with time-varying duration can largely explain the post-1945 dominance of expected returns.

We demonstrate that off-exchange (wholesaler) executions provide significant cost savings to retail investors. Wholesaler concentration has raised regulatory concerns; however, we show that the largest wholesalers offer the lowest costs due to economies of scale. The entry of a new large wholesaler reduces incumbent scale economies, resulting in higher execution costs. Most retail brokers route to multiple wholesalers and actively monitor their performance, rewarding those offering lower execution costs with more volume. While retail investors benefit from the current landscape across all stocks, those trading small stocks benefit the most.

Using cross-country and German administrative data on robotization, we show that the impact of robots on firms and labor markets is limited. First, investment in robots is small and highly concentrated in a few industries, representing less than 0.3% of aggregate expenditures on equipment. Second, robotization does not grow as rapidly as Information Technology did in the past, and current growth is driven by gains in developing countries. Third, firms invest in robots when they face difficulties in finding workers and subsequently increase employment after the investment. The total employment effect in exposed industries and regions is negative but modest in magnitude. We discuss why the effects of robots are limited and demonstrate that other digital technologies have more potential for large economic impact.

Platform intermediation of goods and services has considerably transformed the U.S. economy. We use administrative data on U.S. tax returns to study the role of the gig economy on entrepreneurship. We find that gig workers are more likely to become entrepreneurs, particularly those who are lower income, younger, and benefit from flexibility. We track all newly created firms and show that gig workers start firms in similar industries as their gig experience, which are less likely to survive and demonstrate higher performance. Overall, our findings suggest on-the-job learning promotes entrepreneurial entry and shifts the types of firms started by entrepreneurs.

We study the impact of global volatility on the equity portfolio flows of institutional investors worldwide. Aggregate equity allocations of institutional investors decrease during periods of high volatility, both in developed and, even more strongly, in emerging markets. Our granular portfolio-level data allows us to uncover disaggregated investor responses that are an order of magnitude larger than aggregate estimates, and are dominated by discretionary (investor-driven) component of flows. We further show that periods of high volatility are associated with portfolio rebalancing by institutional investors from small-cap to large-cap stocks. Finally, institutional flows have significant impact on future firm stability, measured by their volatility and liquidity. Our findings are consistent with the economic mechanism in which investors with heterogeneous information capacity are learning about assets with different information rents.

We develop a novel recovery theorem based on no-arbitrage principles. To implement our Arbitrage-Based Recovery Theorem empirically, one needs to observe the Arrow–Debreu prices only for one single maturity. We perform several different density tests and mean prediction tests using more than 26 years of S&P 500 options data, and we find evidence that our method can correctly recover the probability distribution of the S&P 500 index return on a monthly horizon, despite the presence of a non-trivial permanent SDF component.

The literature has documented “reaching for yield”—the phenomenon of investing more in risky assets when interest rates drop—among institutional investors. We analyze detailed transaction data from a large brokerage firm to provide direct field evidence that individual investors also exhibit this behavior. Consistent with models of portfolio choice with labor income, reaching for yield is more pronounced among younger and less-wealthy individuals. Consistent with prospect theory, reaching for yield is more pronounced when investors are trading at a loss. Finally, we observe and discuss the phenomenon of “reverse reaching for yield.”