Data fusion, hedonic pricing, and blockchains: Lowering investment barriers for sustainable infrastructure

The United Nations Environment Program Finance Initiative as well as the National Academies of Science, Engineering, and Medicine recognize the need for financial innovations to facilitate transitioning to a sustainable society. To ignore financial solutions is to risk increasing environmental and social cost and the window to limit global warming under 1.5ﹾC. Under-investment in infrastructure has resulted in significant deterioration in functionality and deficiencies in society’s ability to meet present needs without compromising future generation needs from an environmental, social, and economic perspective. The American Society of Civil Engineers estimated that $5.9 trillion USD would be required to bring infrastructure to an adequate state and currently only 56 percent has been committed. This translates to an annual deficit of $259 billion USD from 2020 to 2029. Aside from the built environment, investment deficits are found in incentivizing sustainable practices in agriculture as well. Yet, while government subsidies have attempted to guide these operations towards sustainable outcomes, the capital market instruments have not been executed in farming due to market and definitional frictions. This dissertation sought to achieve three goals: (1) to understand the economic value and environmental cost of unsustainable practices; (2) to explore the potential for technology-based financing models such as blockchain to facilitate sustainability-linked financing mechanisms; and (3) to demonstrate a proof-of-concept to operationalize agricultural outcomes-based financing using blockchain. The regional use case focused on agriculture in the sub-watersheds of the Great Lakes drainage area. The work presented here leverages a number of methodologies to achieve these goals, including novel data fusion approaches, application of econometric theories, as well as blockchain-enabled funding and financing mechanisms. My initial approach applies data fusion and hedonic pricing to quantify the contribution of nitrogen and phosphorus loading on farmland sales transactions. The data sources and fusion process were derived from AcreValue, the United States Department of Agriculture's Gridded Soil Survey Geographic database and the United States Geological Survey's Spatially Referenced Regression on Watershed Attributes database. The results suggest that nutrient loading has significant positive influence on farmland prices such that prices increase with contamination and re-valuations of contaminating farmlands is required. The following chapters leverage technology-based financing using blockchains and decentralized oracle networks to reduce investment barriers for sustainable systems. A framework is presented where trusted data from internet-of-things of infrastructure can inform financial transactions on-chain in an efficient manner. This section employs the Model method to justify and predict how blockchains and oracles can use infrastructure internet-of-things data to streamline performance-based financing mechanisms by creating trust and automation. A performance-based proof-of-concept to incentivize regenerative agriculture practices is then implemented on the Ethereum blockchain. This research element highlights the benefits of implementing performance-based incentives on a blockchain via Transaction Cost Economics (TCE) analysis. The combination of blockchain-based platforms and decentralized oracle networks not only show that payment processes are automated, reducing transaction costs, but also that multiple transaction steps in a typical pay-for outcomes program can be executed using a smart contract. This work reveals the value of leveraging data streams, where insights are generated to understand the boundary conditions for the future design of sustainable infrastructure and practices. The findings of this study serve as a key input for technology-enabled financing models that can lower transaction costs and unlock new capital resources.