Over one-fourth of US households experienced a power outage in 2023, with these interruptions costing on average US $150 Bn annually. Power outages negatively affect communities by removing an essential input for many sectors and creating health risks like food, water, and medical service shortages. In the US, more than 86% of outages are induced by natural hazards such as extreme weather. Consequently, considerable research and policy initiatives have studied simulating and measuring the macroeconomic impact of power network interruptions. However, a wide variety of different methods and approximations are utilized which deserve greater investigation. For example, analysis often focuses on lost output, intersectoral linkages, and supply-chain failures, with these insights potentially providing worthwhile policy recommendations to boost preparedness. We subsequently examine the macroeconomic effect of several large-scale natural hazard-induced power outages across the United States, evaluating the applicability and effectiveness of static Input-Output modeling for such purposes. This includes investigating three data parametrization techniques and three separate models based on the EORA MRIO database, producing estimates of macroeconomic losses from three case studies. We build off existing literature and contribute one of the first such analyses of IO modeling in the scope of natural hazards, which has been identified as an area of future work in several literature reviews.

More than one-fifth of the US population does not subscribe to a fixed broadband service despite broadband being a recognized merit good. For example, less than 4% of citizens earning more than US $70k annually do not have broadband, compared to 26% of those earning below US $20k annually. To address this, the federal government has undertaken one of the largest broadband investment programs ever via The Bipartisan Infrastructure Law, with the aim of addressing this disparity and expanding broadband connectivity to all citizens. We examine broadband availability, adoption, and need for each US state, and then construct an Input-Output model to explore the potential structural macroeconomic impacts of broadband spending on Gross Domestic Product (GDP) and supply chain linkages. In terms of macroeconomic impact, the total potential indirect contribution to US GDP by the program could be as high as US $84.8 billion, $32.7 billion, and $9.78 billion for the Broadband Equity, Access, and Deployment program, the Affordable Connectivity Program, and additional programs, respectively. Thus, overall, the broadband allocations could expand US GDP by up to US $127.3 billion (0.10% of annual US GDP over the next five years). Moreover, the broadband packages within the Bipartisan Infrastructure Law could create up to 230,000 jobs (0.14% labor market increase). We contribute one of the first economic impact assessments of the US Bipartisan Infrastructure Law to the literature

This project explores the trading behavior of a simple market with both explicit and implicit inflation. In both cases, both cost-pull and demand-push inflation are at play, but in one case, sellers are naturally responding to changes in cost and demand, and in the other, sellers are pushed towards the market equilibrium through a "media" warning them about impending inflation.