Literature DB >> 30140176

Population projection accuracy: The impacts of sociodemographics, accessibility, land use, and neighbour characteristics.

Guangqing Chi1, Donghui Wang1.   

Abstract

Population projection is essential to governments, businesses, and research communities for many purposes. Although projection performance is often evaluated, we know very little about what factors affect projection accuracy. It is important to understand these factors in order to utilize the projections knowledgeably. This study fills this gap in the literature by comprehensively investigating the possible factors associated with population projection accuracy in 2010 for the continental US counties. The results indicate that the counties whose populations are more predictable tend to be desirable places-places with abundant employment opportunities, reliable public transportation infrastructure, easy access to work, and/or high land development potential; their neighboring counties tend to have a well-educated population and a higher income level. Also, projection accuracy is highly spatially associated. The findings provide important insights for population projection users to understand the characteristics of counties and their neighboring counties associated with their projection accuracy.

Entities:  

Keywords:  bias; driving factors; neighboring counties’ characteristics; population projection; precision; projection accuracy

Year:  2017        PMID: 30140176      PMCID: PMC6100728          DOI: 10.1002/psp.2129

Source DB:  PubMed          Journal:  Popul Space Place        ISSN: 1544-8444


  12 in total

1.  An evaluation of population projections by age.

Authors:  Stanley K Smith; Jeff Tayman
Journal:  Demography       Date:  2003-11

2.  Tests of forecast accuracy and bias for county population projections.

Authors:  S K Smith
Journal:  J Am Stat Assoc       Date:  1987-12       Impact factor: 5.033

3.  A surface model approach to small area population estimation.

Authors:  I Bracken
Journal:  Town Plan Rev       Date:  1991-04

4.  An analysis of population and social change in London wards in the 1980s.

Authors:  P Congdon
Journal:  Trans Inst Br Geogr       Date:  1989

5.  A comparison of population estimation methods: housing unit versus component II, ratio correlation, and administrative records.

Authors:  S K Smith; M Mandell
Journal:  J Am Stat Assoc       Date:  1984-06       Impact factor: 5.033

6.  Updating small area population estimates in England and Wales.

Authors:  S Simpson; I Diamond; P Tonkin; R Tye
Journal:  J R Stat Soc Ser A Stat Soc       Date:  1996       Impact factor: 2.483

7.  Can knowledge improve population forecasts at subcounty levels?

Authors:  Guangqing Chi
Journal:  Demography       Date:  2009-05

8.  Spatial Variation in the Quality of American Community Survey Estimates.

Authors:  David C Folch; Daniel Arribas-Bel; Julia Koschinsky; Seth E Spielman
Journal:  Demography       Date:  2016-10

9.  Putting people into place.

Authors:  Barbara Entwisle
Journal:  Demography       Date:  2007-11

10.  Evaluating Population Forecast Accuracy: A Regression Approach Using County Data.

Authors:  Jeff Tayman; Stanley K Smith; Stefan Rayer
Journal:  Popul Res Policy Rev       Date:  2010-06-16
View more
  2 in total

1.  A novel approach of creating sustainable urban planning solutions that optimise the local air quality and environmental equity in Helsinki, Finland: The CouSCOUS study protocol.

Authors:  Joanne C Demmler; Ákos Gosztonyi; Yaxing Du; Matti Leinonen; Laura Ruotsalainen; Leena Järvi; Sanna Ala-Mantila
Journal:  PLoS One       Date:  2021-12-02       Impact factor: 3.240

2.  Evaluation and analysis of the projected population of China.

Authors:  Kaixuan Dai; Shi Shen; Changxiu Cheng
Journal:  Sci Rep       Date:  2022-03-07       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.