This study presents the results of a rapid, low-cost survey that collected labor market data for individuals in the United States during the COVID-19 pandemic. The Yale Labor Survey (YLS) used an online panel from YouGov to replicate statistics from the Current Population Survey, the government’s main source of household labor market statistics. The YLS’s advantages include its timeliness, its low cost, and its ability to develop new questions quickly to study labor market patterns during the pandemic. The results of the YLS show that online surveys can be used to gather economic and demographic data with reasonable accuracy and at low cost. Such surveys can therefore be useful complements to less-frequent government surveys, particularly when the labor market is stressed and real-time data are especially valuable.

This study presents the design and results of a rapid-fire survey that collects labor market data for individuals in the United States. The purpose is to test online panels for their application to social, economic, and demographic information as well as to apply this approach to the U.S. labor market. The Yale Labor Survey (YLS) used an online panel from YouGov to replicate statistics from the Current Population Survey (CPS), the government’s official source of household labor market statistics. The YLS’s advantages included its timeliness, low cost, and ability to develop new questions quickly to study unusual labor market patterns during the COVID-19 pandemic. Results from the YLS track employment data closely from the CPS during the pandemic. Although YLS estimates of unemployment and participation rates mirrored the broad trends in CPS data, YLS estimates of those two rates were less accurate than for employment. The study demonstrates the power of carefully crafted online surveys to replicate expensive traditional methods quickly and inexpensively. 1 The authors of this report are Christopher Foote, senior economist and policy adviser, Federal Reserve Bank of Boston; Tyler Hounshell, Tobin Predoctoral Program, Yale University; William Nordhaus, Sterling Professor of Economics, Yale University; Douglas Rivers, Professor of Political Science, Stanford University, and Chief Scientist at YouGov; and Pamela Torola, Tobin Predoctoral Program, Yale University. We thank William Bannick of YouGov for outstanding assistance with this project. Alan Gerber, Matthew Shapiro, and Jason Faberman provided helpful suggestions in the design and execution of the project. (File is YLS-Report041521a-text.docx.) 2 Corresponding author is William Nordhaus (william.nordhaus@yale.edu). 3 The survey received initial Yale IRB approval on April 10, 2020 and has received further approvals as it has been revised. Foote, Hounshell, Nordhaus, and Torola declare no financial conflicts of interest with the research. Rivers has a conflict of interest as an employee and shareholder in YouGov. The views expressed in this study are those of the authors and do not indicate concurrence by the Federal Reserve Bank of Boston, the principals of the Board of Governors, the Federal Reserve System, or of any of the organizations with which the authors are affiliated. The initial surveys were conducted by YouGov for their own research purposes, and the ones after April 15 were financed by the Tobin Center at Yale University, the Cowles Foundation at Yale University, the MacMillan Center at Yale University, the Federal Reserve Bank of Boston, the Lounsbery Foundation, and the Sloan Foundation. The present paper draws upon a preliminary report in Foote et al. (2020).

In the future, the city of Knoxville, Tennessee will be impacted by climate warming due to anthropogenic climate change. Yet, the ecosystem services provided by urban tree canopy in Knoxville’s urban forest can help mitigate the effects of climate warming. In addition to improving air quality, regulating water flow, and reducing noise pollution, Knoxville’s urban forest serves as a carbon sink and sequesters carbon dioxide on an annual basis. Utilizing methods for calculating carbon sequestration by trees in urban and suburban settings developed by the U.S. Energy Information Administration, the sequestration potential and its uncertainty is calculated until the year 2050 for each individual tree. Present sequestration offsets about 1.24% of city-wide emissions, but offset potential more than doubles by 2050 with the urban forest estimated to offset about 2.94% of city-wide emissions. In addition to sequestration benefits, urban tree canopy lowers surface and air temperatures by providing shade and evaporative cooling as two additional ecosystem services. This reduction mitigates rising ambient air temperature for species inhabiting the understory and can be compared to species’ physiological sensitivities in order to estimate population responses to future climate warming. Mapping canopy cover also illustrates where wildlife corridors exist and areas where they need to be developed in order to maintain exchanges between populations fragmented by urban infrastructure. LiDAR data collected in 2016 is processed in GIS software to determine canopy density in Knoxville’s urban forest and other forest land within the city. A case study highlights one application of the canopy cover layer to determine areas of thermal refuge for an understory species, Tamias striatus (the eastern chipmunk). For both high-emissions and low-emissions scenarios, Tamias striatus is not affected by climate warming through 2025, but after that year, areas of refuge beneath canopy cover become critical for maintaining biological fitness.

Under private management and ownership, privately protected areas provide opportunities for in situ environmental conservation. These areas also provide ecosystem services and disservices for various stakeholders, but their impact on various stakeholders has not been comprehensively studied. To evaluate the economic impact of a privately protected area, a disaggregated cost-benefit analysis was conducted on SAI Sanctuary incorporating its ecosystem services and disservices on private, local, and global stakeholders over a 10-year period from 2010 to 2020. SAI Sanctuary is a privately protected area located in southern Kodagu, a district in the Western Ghats forests of Karnataka, India. To valuate costs and benefits, interviews were conducted with private and local stakeholders. A literature review integrating other valuation techniques was performed as well. Discount rates of 0% and 6% were selected, and sensitivity analysis yielded various tradeoffs born by each stakeholder group. Results indicate private stakeholders bear the greatest net costs, and local stakeholders gain the greatest net benefits largely due to pollination, a regulating service valued between $546,210 and $774,810 in the year 2020. Global stakeholders remained the least affected by SAI Sanctuary with net benefits ranging from $27,900 to $39,570 in 2020. Still, the results validate stakeholder predictions that SAI Sanctuary not only sequesters carbon dioxide, it provides a range of ecosystem services while harboring biodiversity and producing natural capital. The results also indicate that environmental conservation occasionally yields unintended tradeoffs with disproportionate costs and benefits. In sum, environmental conservation can have a multiplicity of outcomes, but it is vital to measure these outcomes and bring privately protected areas into strategies for global conservation.