Research articles for the 2021-06-09

A Century of Economic Policy Uncertainty Through the French-Canadian Lens
David Ardia,Keven Bluteau,Alaa Kassem

A novel token-distance-based triple approach is proposed for identifying EPU mentions in textual documents. The method is applied to a corpus of French-language news to construct a century-long historical EPU index for the Canadian province of Quebec. The relevance of the index is shown in a macroeconomic nowcasting experiment.

A Mean-Field Game Approach to Equilibrium Pricing in Solar Renewable Energy Certificate Markets
Arvind Shrivats,Dena Firoozi,Sebastian Jaimungal

Solar Renewable Energy Certificate (SREC) markets are a market-based system that incentivizes solar energy generation. A regulatory body imposes a lower bound on the amount of energy each regulated firm must generate via solar means, providing them with a tradeable certificate for each MWh generated. Firms seek to navigate the market optimally by modulating their SREC generation and trading rates. As such, the SREC market can be viewed as a stochastic game, where agents interact through the SREC price. We study this stochastic game by solving the mean-field game (MFG) limit with sub-populations of heterogeneous agents. Market participants optimize costs accounting for trading frictions, cost of generation, non-linear non-compliance costs, and generation uncertainty. Moreover, we endogenize SREC price through market clearing. We characterize firms' optimal controls as the solution of McKean-Vlasov (MV) FBSDEs and determine the equilibrium SREC price. We establish the existence and uniqueness of a solution to this MV-FBSDE, and prove that the MFG strategies form an $\epsilon$-Nash equilibrium for the finite player game. Finally, we develop a numerical scheme for solving the MV-FBSDEs and conduct a simulation study.

Bitcoinmania: A Ticking Time Bomb Waiting to Explode
Taskinsoy, John
At the time of writing this article, the Bitcoin bomb has exploded; after peaking at $64,863 on 14 April 2021, the value of Bitcoin has plunged 45% to $31,276 on May 21, 2021; consequently, nearly $600 billion of value evaporated from Bitcoin’s market cap, i.e. from $1.182 trillion (April 2021) to less than $600 billion (May 2021). Bitcoin’s high price valuations coincides with its halving dates; aftermath of each halving event has led to a bubble formation within one year and a crash in the ensuing few months after a perceived peak has been achieved. The three previous halving events are a testimony to this fact; after the halving #1 on 28 November 2012 (block reward was reduced from 50 BTC to 25 BTC), price of each bitcoin increased from $76 on 9 July 2013 to a peak of $1,153 on 5 December 2013, an increase of 1,417% (but fell to $177 in January 2015). Following the halving #2 on 9 July 2016 (block reward was reduced from 25 BTC to 12.5 BTC), the price of bitcoin charted a remarkable ascent, from $963 on 2 January 2017 to $20,089 on December 17 in the same year (a surge of 1,986%, followed by a nosedive to $3,557 in January 2018). The halving #3 has been most unprecedented by any stretch of imagination, the value of each bitcoin has skyrocketed from $7,194 on 1 January 2020 to $64,863 on 14 April 2021; however in the subsequent month (May 2021), Bitcoin gave back half of the gain (price reduction of 20% or more could be considered as a major correction). It is important to mention that Blockchain is not confined to Bitcoin and its survival as a revolutionary technology does not depend on cryptocurrencies. Bitcoin and some altcoins may become obsolete, but blockchain will continue to forge ahead unabated as many life-changing inventions have done before.

ESG and the Pricing of IPOs: Does Sustainability Matter
Fenili, Alessandro,Raimondo, Carlo
The IPO process involves a large amount of information delivered to the public through different means. Information frictions may be what causes most of the underpricing. Socially conscious investors supposedly use the ESG criteria to check for potential investments. Thus, we argue that disclosing more ESG information in the S-1 prospectus diminishes the information asymmetry between the company and the investors, positively benefiting the companies’ financial performance, here in terms of lower underpricing and evaluation. Based on a sample of 783 U.S. IPOs we compute a text-based measure of ESG dislosure in IPOs. Our results show that (a) the amount of ESG disclosures in the S-1s is negatively associated with IPO’s underpricing and Tobin’s Q; (b) this effect is primarily driven for the underpricing by the ESG as a whole, as well as for the price revision. Our analyses show instead that when considering Tobin’s Q investors value at most the governance part of sustainability.

Engineering-Economic Evaluation of Diffractive Non-Line-Of-Sight Backhaul (e3nb): A Techno-economic Model for 3D Wireless Backhaul Assessment
Edward J. Oughton,Erik Boch,Julius Kusuma

Developing ways to affordably deliver broadband connectivity is one of the major issues of our time. In challenging deployment locations with irregular terrain, fiber optic or traditional Clear-Line-Of-Sight (CLOS) wireless links can be uneconomical to deploy, resulting from the number of required towers making infrastructure deployment unviable. With the emergence of new research focusing on developing wireless diffractive backhaul technologies to provide diffractive Non-Line-Of-Sight (NLOS) links, this paper evaluates the engineering-economic implications of such approaches. To quantify different technology strategies, a Three-Dimensional (3D) techno-economic assessment framework is presented to help prioritize regions for future investment in broadband connectivity, utilizing a combination of remote sensing and viewshed geospatial techniques. Such a method is an essential evaluation step prior to beginning detailed Radio Frequency (RF) Quality of Service engineering but has hitherto received less research attention in the literature. This framework is applied to assess both Clear-Line-Of-Sight and diffractive Non-Line-Of-Sight strategies for deployment in Peru, as well as the islands of Kalimantan and Papua, in Indonesia. The results find that a hybrid strategy combining the use of Clear-Line-Of-Sight and diffractive Non-Line-Of-Sight links produces a 15-43 percent cost-efficiency saving, relative to only using traditional Clear-Line-Of-Sight wireless backhaul links. The codebase is released opensource via the Engineering-Economic Evaluation of Non-Line-of-Sight Backhaul (e3nb) repository.

Financing Experimentation
Liu, Tong
Leveraging the detailed project-level data on biotech startups and their IPO records, this paper studies how adverse selection in capital markets affects financing decisions of entrepreneurs and firm values. By structurally estimating a dynamic model that features strategic experimentation and volatile market valuation, I find that adverse selection is prevalent between early-stage startups and investors. The baseline estimates suggest that information frictions cause about 24% loss of ex-ante firm value, which is due to the distortion of market beliefs and higher financing costs in private markets. On average, asymmetric information induces startups to stay private for approximately 5 years longer, consistent with the sharp decline of IPOs observed in the last two decades. The effects of information frictions, however, are dampened among VC-backed startups, startups with more effective “patent fences”, and startups facing more stringent requirements on public disclosure of clinical trial results.

Optimal ESG Portfolios: Which ESG Ratings to Use?
Schmidt, Anatoly B.,Zhang, Xu
The idea behind the optimal ESG portfolio (OESGP) is to expand the mean variance theory by adding the portfolio ESG value (PESGV) multiplied by the ESG strength parameter γ (which is investor’s choice) to the minimizing objective function (Pederson et al., 2019; Schmidt, 2020). PESGV is assumed to be the sum of portfolio constituents’ weighted ESG ratings that are offered by several providers. In this work we analyze the sensitivity of the OESGP based on the constituents of the Dow Jones Index to the ESG ratings provided by MSCI, S&P Global, and Sustainalytics. We describe discrepancies among various ESG ratings for the same securities and their effects on the OESGP performance. We found that the OESGP diversity decreases with growing γ. The dependence of the ESG tilted Sharpe ratio on γ may have two maximums. The 1st maximum exists at moderate values of γ and yields a moderately diversified OESGP. The 2nd maximum at large γ corresponds to a highly concentrated OESGP. It appears if portfolio has one or two securities with lucky combinations of high returns and high ESG ratings.

Predicting cell phone adoption metrics using satellite imagery
Edward J. Oughton,Jatin Mathur

Approximately half of the global population does not have access to the internet, even though digital connectivity can reduce poverty by revolutionizing economic development opportunities. Due to a lack of data, Mobile Network Operators and governments struggle to effectively determine if infrastructure investments are viable, especially in greenfield areas where demand is unknown. This leads to a lack of investment in network infrastructure, resulting in a phenomenon commonly referred to as the `digital divide`. In this paper we present a machine learning method that uses publicly available satellite imagery to predict telecoms demand metrics, including cell phone adoption and spending on mobile services, and apply the method to Malawi and Ethiopia. Our predictive machine learning approach consistently outperforms baseline models which use population density or nightlight luminosity, with an improvement in data variance prediction of at least 40%. The method is a starting point for developing more sophisticated predictive models of infrastructure demand using machine learning and publicly available satellite imagery. The evidence produced can help to better inform infrastructure investment and policy decisions.