Probabilistic population forecasting: Short to very long-term

Raftery, Adrian E.; Ševčíková, Hana

doi:10.1016/j.ijforecast.2021.09.001

Cited by 32 publications

(21 citation statements)

References 75 publications

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“…Water and land resources for agriculture may become limited globally in the near future because of the ever-increasing human population, requiring production of adequate food, − which can be affected by environmental stress that impairs food production. The anticipated depletion and, most significantly, the harmful effects of atmospheric variables on nonrenewable fossil fuels necessitate the utilization of alternative energy sources.…”

Section: Introductionmentioning

confidence: 99%

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

et al. 2022

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Sugar cane ( Saccharum spp. hybrids) is a major crop for sugar and renewable bioenergy worldwide, grown in arid and semiarid regions. China, the world’s fourth-largest sugar producer after Brazil, India, and the European Union, all share ∼80% of the global production, and the remaining ∼20% of sugar comes from sugar beets, mostly grown in the temperate regions of the Northern Hemisphere, also used as a raw material in production of bioethanol for renewable energy. In view of carboxylation strategies, sugar cane qualifies as one of the best C 4 crop. It has dual CO 2 concentrating mechanisms located in its unique Krantz anatomy, having dimorphic chloroplasts located in mesophylls and bundle sheath cells for integrated operation of C 4 and C 3 carbon fixation cycles, regulated by enzymes to upgrade/sustain an ability for improved carbon assimilation to acquire an optimum carbon economy by producing enhanced plant biomass along with sugar yield under elevated temperature and strong irradiance with improved water-use efficiency. These superior intrinsic physiological carbon metabolisms encouraged us to reveal and recollect the facts for moving ahead with the molecular approaches to reveal the expression of proteogenomics linked with plant productivity under abiotic stress during its cultivation in specific agrizones globally.

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Section: Introductionmentioning

confidence: 99%

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

et al. 2022

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“…Turning to the actual forecast, while a small population such as the Hopi presents difficulties in terms of forecasting, it has, fortunately, an important commonality with larger populations: inertia. Raftery and Ševčíková (2021) observe that because of inertia, it is possible to make reasonable long-term population forecasts. They further note that the effective time unit for population forecasting is the "generation," which is about 27 years.…”

Section: Discussionmentioning

confidence: 99%

Forecasting a Tribal Population Using the Cohort-Component Method: A Case Study of the Hopi

Swanson

2022

Popul Res Policy Rev

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Population forecasting is a difficult endeavor. When it involves a "small" population, forecasting becomes even more difficult because of the lack of adequate input data to appropriately implement a technique preferred by demographers, the cohortcomponent method (CCM). Small populations also are subject to high levels of stochastic uncertainty, which can lead to substantial temporal fluctuations in size as well as mortality, fertility, and migration rates over short periods of time. When the population is further defined in terms of characteristics such as tribal membership requirements, the acquisition of relevant age-sex and component data for the discrete population adds even more difficulty because the usual data sources may not have precise data for a given tribe, especially when there is a need for long-term forecasts as is the case in disputes over water allotments. In this case study of the Hopi tribal population, I show that these problems can be overcome, resulting in reasonably accurate forecasts over a long period of time. To do this, I identify three key input data sources: (1) an historic tribal census that serves as the basis for tribal membership; (2) the Social Security Administration's life tables, which are specific to cohorts by year of birth, staring in 1900; and (3) an accurate annual record of tribal membership record that covers a time period that can be used as a benchmark once the forecast is launched from the historic tribal census. For this case study. these three data sources allow me to launch an 80 year CCM forecast of the Hopi Tribal Population from its 1937 tribal census to 2017 and conduct an ex post facto assessment of the accuracy of the forecasted total population in five-year increments from 1992 to 2017 using the annual tribal membership roll for this period; the assessment finds that the forecast matches up well with the tribal membership roll. So without adjustments, the forecast is taken out 20 years more, from 2017 to 2037. The results suggest that accurate long-term forecasts are possible using the cohort-component method for the Hopi, which, in turn, suggests that this same CCM process could be used to develop reasonably accurate long-term population forecasts of other tribes for which a tribal census was conducted that is linked to current tribal membership rolls, especially when these forecasts are required in resolving disputes over water allotments.

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“…Instead, we extrapolate the life expectancies at birth and then adjust the baseline 2019 death rates so as to fit to the extrapolated life expectancies (graduation and adjustment procedures come from an earlier projection for Russia [ 27 ]). Our method is somewhat similar to the one employed by UN [ 30 , 31 ] who also extrapolate life expectancy first and then disaggregate it into age-specific rates. There are important differences, though.…”

Section: Methodsmentioning

confidence: 99%

COVID-19 and excess mortality in Russia: Regional estimates of life expectancy losses in 2020 and excess deaths in 2021

Scherbov

Gietel‐Basten²,

Ediev³

et al. 2022

PLoS ONE

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Accurately counting the human cost of the COVID-19 at both the national and regional level is a policy priority. The Russian Federation currently reports one of the higher COVID-19 mortality rates in the world; but estimates of mortality differ significantly. Using a statistical method accounting for changes in the population age structure, we present the first national and regional estimates of excess mortality for 2021; calculations of excess mortality by age, gender, and urban/rural status for 2020; and mean remaining years of life expectancy lost at the regional level. We estimate that there were 351,158 excess deaths in 2020 and 678,022 in 2021 in the Russian Federation; and, in 2020, around 2.0 years of life expectancy lost. While the Russian Federation exhibits very high levels of excess mortality compared to other countries, there is a wide degree of regional variation: in 2021, excess deaths expressed as a percentage of expected deaths at the regional level range from 27% to 52%. Life expectancy loss is generally greater for males; while excess mortality is greater in urban areas. For Russia as whole, an average person who died due to the pandemic in 2020 would have otherwise lived for a further 14 more years (and as high as 18 years in some regions), disproving the widely held view that excess mortality during the pandemic period was concentrated among those with few years of life remaining–especially for females. At a regional level, less densely populated, more remote regions, rural regions appear to have fared better regarding excess mortality and life expectancy loss–however, a part of this differential could be owing to measurement issues. The calculations demonstrate more clearly the true degree of the human cost of the pandemic in the Russian Federation.

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Probabilistic population forecasting: Short to very long-term

Cited by 32 publications

References 75 publications

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

Forecasting a Tribal Population Using the Cohort-Component Method: A Case Study of the Hopi

COVID-19 and excess mortality in Russia: Regional estimates of life expectancy losses in 2020 and excess deaths in 2021

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