Green links: corporate networks and environmental performance
(with Hossein Asgharian, Zahra Hashemzadeh and Lu Liu)
Review of Finance, 2024, vol. 28, pp. 1027–1058. DOI: https://doi.org/10.1093/rof/rfad042
We investigate the propagation of environmental performance among competitors and in customer–supplier relationships. We find a significant causal effect among competitors, while the propagation from customers to suppliers and vice versa appears insignificant or does not survive identification tests. The effect is stronger among firms in highly concentrated competitor networks and toward firms with less market and bargaining power than their competitors. We also find significantly stronger propagation of environmental performance among competitors engaged in joint research and development activity. These results show that the propagation stems from both competitive pressure and technological spillover. Importantly, we find that propagation is strong when the competitor improves its environmental performance and when the firm’s own environmental performance is poor initially, alleviating concerns that improvements in performance are concentrated among firms, which are already green. Overall, network effects among competing firms are a significant force shaping environmental performance, and a force mostly for good.
Nonstandard Errors
(with Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Michael Kirchler, Sebastian Neususs, Michael Razen, Utz Weitzel et al.)
Journal of Finance, 2024, vol. 79, pp. 59–67. DOI: 10.1111/jofi.13337
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
The great margin call: The role of leverage in the 1929 Wall Street crash
(with Karol Jan Borowiecki and Alexander Tepper)
Economic History Review, 2023, vol. 76, pp. 807–826. DOI: 10.1111/ehr.13213
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Asymmetric Attention and Volatility Asymmetry
(with Marc Oliver Rieger and Tõnn Talpsepp)
Journal of Empirical Finance, 2018, vol. 45, pp. 59–67. DOI: 10.1016/j.jempfin.2017.09.010
Analyzing a large sample of U.S. firms, we show that the asymmetry of stock return volatility is positively related to investor attention and differences of opinion. Using the number of analysts following a given firm to capture attention and the dispersion in analyst forecasts as a common proxy for differences of opinion, we show that the two effects are complementary. Furthermore, the effect of attention is strongest among stocks with low institutional ownership and high idiosyncratic volatility. Our results are robust to the traditional “leverage effect” explanation of volatility asymmetry. The findings relate to the previously documented relationship between attention and volatility and suggest that volatility asymmetry is driven by asymmetric attention.
Measuring economic uncertainty and its impact on the stock market
Finance Research Letters, 2012, vol. 9(3), pp. 167–175. DOI: 10.1016/j.frl.2011.10.003
This paper proposes a novel measure of economic uncertainty based on the frequency of internet searches. The theoretical motivation is offered by findings in economic psychology that agents respond to increased uncertainty by intensifying their information search. The main advantages of using internet searches are broad reach, timeliness and the fact that they reflect actions, rather than words, which however are not directly related to the stock market. The search-based uncertainty measure compares well against a peer group of alternative indicators and is shown to have a significant relationship with aggregate stock returns and volatility.