Forecasting State and Local Population Growth with Limited Data: The Use of Employment—Migration Relationships and Trends in Vital Rates

M J Greenwood and G L Hunt
Additional contact information
M J Greenwood: Department of Economics and Center for Economic Analysis, University of Colorado at Boulder, Boulder, CO 80309, USA
G L Hunt: Department of Economics, East Carolina University, Greenville, NC 27858, USA

Environment and Planning A, 1991, vol. 23, issue 7, 987-1005

Abstract: Long-term forecasts of state and local population are required for a variety of reasons, but frequently these forecasts or projections are not tied to economic activity, and the migration component of population change is commonly treated in an unsatisfactory fashion. In this paper, growth of state and local population is related to the area's net natural increase and to its net migration, which must be inferred because of lack of data. In turn, net migration is related to the growth of national employment and to the growth of regional civilian and military employment. The model is estimated for two regions, the El Paso, TX, standard metropolitan statistical area (SMSA) and the State of New Mexico. Several statistical problems arise because of the limited number of available time-series observations. Fully dynamic historical simulations track the population quite closely, in one case never differing from the actual value by more than 1.17% and in the other never differing by more than 1.36%.

Date: 1991
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1068/a230987 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:23:y:1991:i:7:p:987-1005

DOI: 10.1068/a230987

Access Statistics for this article

More articles in Environment and Planning A
Bibliographic data for series maintained by SAGE Publications ().