Time Series Models for Birth Forecasting.

Abstract

Autoregressive integrated moving average (ARIMA) models are developed for the birth time series, and their relationship with the classical models for population growth is investigated. Parsimonious versions of the ARIMA models are obtained which retain the most important pieces of information including the length of generation of the population. The technique is applied to human population data (Mexico and Norway) and forecasts are obtained. A causal model relating marriages to births is also developed and applied.

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1975
Accession Number
ADA010145

Entities

People

  • Joao L. M. Saboia

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Behavior And Behavior Mechanisms
  • Behavioral Disciplines And Activities
  • Behavioral Sciences
  • Collaborative Techniques
  • Delphi Method
  • Demographic Cohorts
  • Demography
  • Human Population
  • Interpersonal Relations
  • Management Engineering
  • Marriage

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Gender and Food Studies