il prices fell sharply in 2014 and have remained persistently low. While low oil prices may stimulate the U.S. economy overall, they can be disruptive to the domestic oil industry. A decline in prices may reduce oil firm revenues in the short run and increase uncertainty around future oil prices and earnings. These twin effects of oil-price uncertainty and lower potential earnings may, in turn, lower oil firms' creditworthiness, thereby reducing available financing for current operations and future investment. A firm's creditworthiness determines whether it can get financing and, if so, under what terms. Perhaps the most important term is the interest rate "spread," defined as the difference between the loan's interest rate and a benchmark rate. Banks typically require a higher spread for borrowers who are less creditworthy to compensate for the borrower's increased default risk. As a result, external factors that affect certain borrowers' profitability and creditworthiness-for example, a shock to the oil industry-should be reflected in price changes on new loans. In this article, we examine whether the relationship between creditworthiness and loan spreads for energy firms in the syndicated loan market changed after the 2014 oil-price shock. We use syndicated
ver the past 10 years, the U.S. energy sector has exerted substantial influence on overall U.S. business fixed investment. From 2010 to 2014, a time when energy production in the United States was expanding, investment in the energy sector was a boon to aggregate investment. However, following the sharp oil price decline in 2014, the energy sector was a drag on aggregate investment. These recent examples demonstrate that the energy sector can contribute both positively and negatively to overall investment activity in the United States. Assessing the energy sector's contribution to investment requires an understanding of the size of the energy sector relative to the overall economy, the contributions from individual segments of the energy sector, and how investment dynamics within these segments have changed over time. Energy sector technology advanced rapidly over the last decade, a period when U.S. energy activity and investment also expanded. These technological changes contributed to increased investment variability within some energy segments. Together, changing energy activity and shifting variability within segments of the energy sector can meaningfully alter both the level and variability of aggregate investment. In this article, I estimate how individual segments of the energy sector contribute to U.S. aggregate investment activity as well as how those contributions have shifted over time. I find that levels of investment Energy Investment Variability within the Macroeconomy
The rate of future global sea-level rise will likely increase due to elevated ocean temperatures and increases in land-ice melt. Nearly 40 percent of the U.S. population lives in coastal communities, and coastal properties are expected to become more prone to coastal flooding in the coming decades due to relative sea-level rise caused by both global and local factors. Understanding how this projected sea-level rise translates to lost economic value is critical to the decisions of insurance companies, banks, governments, investors, and regulatory agencies. We use probability distributions of local sea-level rise projections, National Oceanic and Atmospheric (NOAA) coastal digital elevation models, and CoreLogic housing data to estimate a range of housing market value impairments from future sea-level rise in 15 major U.S. coastal cities as well as the associated timing of those impairments. Our estimates include only residential properties with four or fewer units and thus provide a lower bound estimate of economic risk from sea-level rise. We estimate that within these 15 major U.S. coastal metros, sea-level rise will inundate between 2,000 and 28,000 properties by 2100 in a relatively low greenhouse gas concentration scenario and between 7,000 to 77,000 properties under an unlikely, extreme greenhouse gas concentration scenario.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.