A Machine Learning Analysis of the Recent Environmental and Resource Economics Literature

We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in different topics and the changing emphasis on topics in different journals. The most prevalent topics in environmental and resource economics research in this period are growth and sustainable development and theory and methodology. Topics on climate change and energy economics have emerged with the strongest upward trends. When we look at our results across journals, we see that journals have different topical profiles and that many topics mainly appear in one or a few selected journals. Further investigation reveal latent semantic structures across research themes that only the insider would be aware.

     

An efficient market? Going public in London, 1891–1911

There have been claims that British capital was not well deployed in Victorian Britain. There was, allegedly, a lack of support for new and dynamic companies in comparison to the situation in Germany and the US. We find no evidence to support these claims. The London Stock Exchange welcomed young, old, domestic, and foreign firms. It provided funds to firms in old, existing industries as well as patenting firms in ‘new‐tech’ industries at similar costs of capital. If investors did show a preference for older and foreign firms, it was because those firms offered investors better long‐run performance. In addition, we show some evidence that investors who worked in the same industry and lived close to the firm going public were allotted more shares in high‐quality initial public offerings.     

Foreign market portfolio concentration and performance

Using security holdings of 49,857 foreign investors on the Oslo Stock Exchange (OSE), I test whether concentrated investment strategies in international markets result in excess risk-adjusted returns. I find that investors with higher learning capacity increase returns, while investors with lower learning capacity decrease returns from the portfolio concentration. I measure learning capacity as institutional classification, geographical proximity to Norway, and cultural closeness to Norwegian investors (as based on the Hofstede cultural closeness measures). I conclude, consistent with the information advantage theory, that concentrated investment strategies in foreign markets can be optimal (disastrous) for investors with higher (lower) learning capacity.     

Laddering IPO shares

Regulators, investors, and the financial media argue that underwriters tie Initial Public Offering (IPO) allocations to investor post-listing purchases in the issuer shares. Using unique data from the Oslo Stock Exchange (OSE) I investigate if these tie-in agreements are driven by price stabilization (reducing price falls below the offer price) or laddering (inflating prices above the offer price). I find that both stabilizing and laddering investors are rewarded with increased allocations for their service. However, only laddering investors increase allocations in very oversubscribed future issues. Secondary investors also lose from falling returns following laddering. I conclude that underwriters use both price stabilization and laddering across different IPOs. However, the rewards for cooperating investors and the economic consequences for secondary investors are much greater following laddering.     

Rejected stock exchange applicants

We examine listing applications by firms to the London Stock Exchange between 1891 and 1911. The exchange rejected 82 (13.1%) of the 628 applicants to its main board. Accepted applicants were twice as likely to pay dividends (and to pay twice as much) and had longer firm lives than rejected applicants. Rejected applicants were more likely to file for liquidation than successful applicants. These results remain even after we control for the primary benefits of the listing itself: liquidity and future capital inflows. In this era, the London Stock Exchange could screen applicants for listing.