Saleh Mamun

National governments and multilateral institutions face difficult challenges reconciling biodiversity, climate, and economic development goals. We integrated spatial biophysical and economic data with optimization methods to develop sustainable landscape efficiency frontiers that show maximally feasible combinations of biodiversity conservation, land-based climate mitigation, and net economic value from agricultural crops, livestock, and forestry production. We applied this approach in 146 countries and found large potential gains in biodiversity, climate, and economic development from improved land use and land management. Summing national-level results shows the potential to increase climate mitigation by more than 200 billion metric tons of CO ₂ equivalents (>20% increase) or net economic value by more than US$350 billion (>80% increase), without loss in other objectives.

We used the quasi-experimental difference-in-differences method to estimate the impact that the Endangered Species Act’s (ESA’s) critical-habitat (CH) regulation had on developed and undeveloped parcel prices throughout the United States between 2000 and 2019. At the national level we find that, on average, the prices of parcels in CH areas were not statistically different from the prices of similar nearby parcels not in CH. However, limiting our analysis to specific subsets of CH areas, we find mixed results. Previous empirical estimates have consistently found that the regulation reduces parcel prices. We offer several potential explanations for our contradictory results.

This study uses Zillow’s Transaction and Assessment Database to investigate variation in hedonic price effects of water clarity on single-family houses throughout the United States. We consider five spatial scales and estimate models using different sample selection criteria and model specifications. The results indicate considerable spatial heterogeneity within and across the four U.S. census regions. However, we also find heterogeneity resulting from different types of investigator decisions, including sample selection and modeling choices. Thus, it is necessary to use practical knowledge to consider the limits of market areas and to investigate the robustness of estimation results to investigator choices.

We discuss data quality and modeling issues inherent in the use of nationwide property data to value environmental amenities. By example of ZTRAX, a U.S.-wide real estate database, we identify challenges and propose guidance for: (1) the identification of arm’s-length sales, (2) the geo-location of parcels and buildings, (3) temporal linkages between transaction, assessor, and parcel data, (4) the identification of property types, such as single-family homes and vacant lands, and (5) dealing with missing or mismeasured data for standard housing attributes. We review current practice and show that how researchers address these issues can meaningfully influence research findings.

High-quality water resources provide a wide range of benefits, but the value of water quality is often not fully represented in environmental policy decisions, due in large part to an absence of water quality valuation estimates at large, policy relevant scales. Using data on property values with nationwide coverage across the contiguous United States, we estimate the benefits of lake water quality as measured through capitalization in housing markets. We find compelling evidence that homeowners place a premium on improved water quality. This premium is largest for lakefront property and decays with distance from the waterbody. In aggregate, we estimate that 10% improvement of water quality for the contiguous United States has a value of $6 to 9 billion to property owners. This study provides credible evidence for policymakers to incorporate lake water quality value estimates in environmental decision-making.

Life cycle assessment (LCA) is a well-established tool for measuring environmental effects of existing technology. While the most recent LCA research has focused on future environmental impacts, in particular the effects of climate change. And there is growing interest in how LCA can be used prospectively. A 2019 workshop in Duluth, Minnesota sought to define the needs and

Compared with the rest of the world, the US prison system is characterized by high incarceration rates, high recidivism, and substantial incarceration costs. The US has increasingly turned to private prisons, resulting in a debate concerning the efficacy of these private prisons. While the private system may produce cost savings it may have also have negative consequences including increased recidivism. Although numerous studies have investigated the cost savings associated with private prisons and their effect on recidivism, to our knowledge no work has evaluated the joint impact. In this paper we evaluate these impacts jointly within a dynamic system model, utilizing cost, incarceration and recidivism estimates from the literature. Overall, considering the tradeoff between cost efficiency and recidivism rates, we find that public prisons are less costly in the long term than private prisons. Considering a 25-year time horizon, we find that total inflation-adjusted costs are approximately 1.5% higher for private prisons than public prisons. Considering a 40-year time horizon, we find that private prisons are 3% more costly than public prisons. Thus, results suggest that estimated short-term cost efficiency provided by private prisons may not be worth the long-term consequences of potential increases in recidivism.

Background: The US has the highest incarceration rate in the world and spends $40–$80 billion to house inmates per year. It is well-known that a significant correlation is present between substance use and crime, especially over recent years as opioid use disorder (OUD) has grown exponentially. To mitigate OUD, methadone maintenance treatment (MMT) has demonstrated effectiveness in numerous randomized and quasi-experimental studies. A potentially fruitful environment for MMT is correctional facilities, particularly short-term facilities, such as city and county jails. However, little is known about the economic implications of MMT within correctional facilities. Objective: The aim of the present study was to estimate the economic costs of jail-based MMT using data from a novel, established MMT program located within a large urban jail in New Mexico. Methods: Data were collected using administrative records and by interviewing program administrators using a modified version of the Drug Abuse Treatment Cost Analysis Program (DATCAP). Both sensitivity analysis and cost-structure analysis were conducted to gauge the robustness of the findings. Results: The average (per patient) weekly cost of MMT is $115 and the total treatment cost for an average treatment episode is $689. These costs are generally in-line with non-jail-based MMT programs of similar size. Weekly cost estimates range from $86 to $185 depending on the size of the treatment facility, with larger programs exhibiting lower per-patient costs. Conclusion: Results provide a valuable economic benchmark to policy makers, criminal justice officials, and program administrators considering establishing and/or expanding MMT in jail settings.