Dataset Information

Spatiotemporal downscaling of global population and income scenarios for the United States.

ABSTRACT: Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscaled projections generated for the five Shared Socioeconomic Pathways used to support global scenario analysis generally show growth focused around relatively few centers especially in the southeast and western regions, with some areas in the Midwest and northeast experiencing population declines. Results are consistent with economic growth theory and with historical trends in population change and convergence of per capita personal income across US counties.

SUBMITTER: Wear DN

PROVIDER: S-EPMC6655633 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatiotemporal downscaling of global population and income scenarios for the United States.

Wear David N DN Prestemon Jeffrey P JP

PloS one 20190724 7

Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscale ...[more]

PMID: 31339927

Similar Datasets

Project description:BackgroundReports of high and rising maternal mortality ratios (MMR) in the United States have caused serious concern. We examined spatiotemporal patterns in cause-specific MMRs, in order to obtain insights into the cause for the increase.MethodsThe study included all maternal deaths recorded by the Centers for Disease Control and Prevention from 1999 to 2021. Changes in overall and cause-specific MMRs were quantified nationally; in low-vs high-MMR states (i.e., MMRs <20 vs ≥26 per 100,000 live births in 2018-2021); and in California vs Texas (populous states with low vs high MMRs). Cause-specific MMRs included those due to unambiguous causes (e.g., selected obstetric causes such as pre-eclampsia/eclampsia) and less-specific/potentially incidental causes (e.g., "other specified pregnancy-related conditions", chronic hypertension, and malignant neoplasms).FindingsMMRs increased from 9.60 (n = 1543) in 1999-2002 to 23.5 (n = 3478) per 100,000 live births in 2018-2021. The temporal increase in MMRs was smaller in low-MMR states (from 7.82 to 14.1 per 100,000 live births) compared with high-MMR states (from 11.1 to 31.4 per 100,000 live births). MMRs due to selected obstetric causes decreased to a similar extent in low-vs high-MMR states, whereas the increase in MMRs from less-specific/potentially incidental causes was smaller in low- vs high-MMR states (MMR ratio (RR) 5.57, 95% CI 4.28, 7.25 vs 7.07, 95% CI 5.91, 8.46), and in California vs Texas (RR 1.67, 95% CI 1.03, 2.69 vs 10.8, 95% CI 6.55, 17.7). The change in malignant neoplasm-associated MMRs was smaller in California vs Texas (RR 1.21, 95% CI 0.08, 19.3 vs 91.2, 95% CI 89.2, 94.8). MMRs from less-specific/potentially incidental causes increased in all race/ethnicity groups.InterpretationSpatiotemporal patterns of cause-specific MMRs, including similar reductions in unambiguous obstetric causes of death and variable increases in less-specific/potentially incidental causes, suggest misclassified maternal deaths and overestimated maternal mortality in some US states.FundingThis work received no funding.

Dataset Information

Spatiotemporal downscaling of global population and income scenarios for the United States.

Publications

Spatiotemporal downscaling of global population and income scenarios for the United States.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets