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Journal Article

Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models

Available to Purchase
Rob J. Hyndman, Heather Booth, Farah Yasmeen
Demography (2013) 50 (1): 261–283.
DOI: https://doi.org/10.1007/s13524-012-0145-5
Published: 10 October 2012
... stationary time series models. The method is applied to sex-specific data for Sweden and state-specific data for Australia. Based on out-of-sample forecasts, the coherent forecasts are at least as accurate in overall terms as comparable independent forecasts, and forecast accuracy is homogenized across...
FIGURES | View All (10)
View articletitled, Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time <span class="search-highlight">Series</span> Models View PDF for article titled, Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time <span class="search-highlight">Series</span> Models
Journal Article

The end of rapid increase in the use of oral anovulants? Some problems in the interpretation of time series of oral use among married women

Available to Purchase
John D. Allingham, T. R. Balakrishnan, John F. Kantner
Demography (1970) 7 (1): 31–41.
DOI: https://doi.org/10.2307/2060020
Published: 01 February 1970
...John D. Allingham; T. R. Balakrishnan; John F. Kantner Abstract Several problems in the interpretation of time series of oral anovulant usage are discussed, among them the shifting marriage-duration distribution over time. Standardization fails to negate the conclusion that the rate of increase...
View articletitled, The end of rapid increase in the use of oral anovulants? Some problems in the interpretation of time <span class="search-highlight">series</span> of oral use among married women View PDF for article titled, The end of rapid increase in the use of oral anovulants? Some problems in the interpretation of time <span class="search-highlight">series</span> of oral use among married women
Journal Article

A Taylor series expansion for Lotka’s r

Available to Purchase
J. H. Pollard
Demography (1970) 7 (2): 151–154.
DOI: https://doi.org/10.2307/2060406
Published: 01 May 1970
...)) and derive a Taylor series for ro, the unique real solution. The series is no more advantageous from the calculation point of view than many previous solutions, but it may be useful in a theoretical context. The effects on the intrinsic rate of increase of the population due to changes in the cumulants...
View articletitled, A Taylor <span class="search-highlight">series</span> expansion for Lotka’s r View PDF for article titled, A Taylor <span class="search-highlight">series</span> expansion for Lotka’s r
Journal Article

A time series approach to forecasting Australian total live-births

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John McDonald
Demography (1979) 16 (4): 575–601.
DOI: https://doi.org/10.2307/2060937
Published: 01 November 1979
...John McDonald Abstract The relationship between classical demographic deterministic forecasting models, stochastic structural econometric models and time series models is discussed. Final equation autoregressive moving average (ARMA) models for Australian total live-births are constructed...
View articletitled, A time <span class="search-highlight">series</span> approach to forecasting Australian total live-births View PDF for article titled, A time <span class="search-highlight">series</span> approach to forecasting Australian total live-births
Journal Article

Modeling and Forecasting Populations by Time Series: The Swedish Case

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Joao L. M. Saboia
Demography (1974) 11 (3): 483–492.
DOI: https://doi.org/10.2307/2060440
Published: 01 August 1974
...Joao L. M. Saboia Abstract Time series analysis techniques are used to model and to forecast populations. An autoregressive (AR) and a moving average (MA) model, which seem to fit the population of Sweden very well, are found. Forecasts are calculated using both models and are compared...
View articletitled, Modeling and Forecasting Populations by Time <span class="search-highlight">Series</span>: The Swedish Case View PDF for article titled, Modeling and Forecasting Populations by Time <span class="search-highlight">Series</span>: The Swedish Case
Journal Article

Forecasting Mortality: A Parameterized Time Series Approach

Available to Purchase
Robert McNown, Andrei Rogers
Demography (1989) 26 (4): 645–660.
DOI: https://doi.org/10.2307/2061263
Published: 01 November 1989
...Robert McNown; Andrei Rogers Abstract This article links parameterized model mortality schedules with time series methods to develop forecasts of U.S. mortality to the year 2000. The use of model mortality schedules permits a relatively concise representation of the history of mortality by age...
View articletitled, Forecasting Mortality: A Parameterized Time <span class="search-highlight">Series</span> Approach View PDF for article titled, Forecasting Mortality: A Parameterized Time <span class="search-highlight">Series</span> Approach
Journal Article

A Time Series of Instrumental Fertility Variables

Available to Purchase
N. B. Ryder
Demography (1981) 18 (4): 487–509.
DOI: https://doi.org/10.2307/2060944
Published: 01 November 1981
.... : Princeton University Press . Westolf Charles F. ( 1977 ). The Predictive Validity of Reproductive Intentions . Demography , 14 , 431 – 453 . 10.2307/2060589 DEMOGRAPHY© Volume 18, Number 4 November 1981 A TIME SERIES OF INSTRUMENTAL FERTILITY VARIABLES N. B. Ryder Office of Population...
View articletitled, A Time <span class="search-highlight">Series</span> of Instrumental Fertility Variables View PDF for article titled, A Time <span class="search-highlight">Series</span> of Instrumental Fertility Variables
Journal Article

The Use of Mortality Time Series Data to Produce Hypothetical Morbidity Distributions and Project Mortality Trends

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Kenneth G. Manton, Eric Stallard
Demography (1982) 19 (2): 223–240.
DOI: https://doi.org/10.2307/2061192
Published: 01 May 1982
... morbidity distributions in the national population using auxiliary biomedical evidence and theory to estimate transitions to morbidity states from a cohort mortality time series. We present computational methods which employ these estimates of morbid state transitions to produce life table functions...
View articletitled, The Use of Mortality Time <span class="search-highlight">Series</span> Data to Produce Hypothetical Morbidity Distributions and Project Mortality Trends View PDF for article titled, The Use of Mortality Time <span class="search-highlight">Series</span> Data to Produce Hypothetical Morbidity Distributions and Project Mortality Trends
Journal Article

Environmental Inequality and Residential Sorting in Germany: A Spatial Time-Series Analysis of the Demographic Consequences of Industrial Sites

Open Access
Tobias Rüttenauer, Henning Best
Demography (2021) 58 (6): 2243–2263.
DOI: https://doi.org/10.1215/00703370-9563077
Published: 01 December 2021
FIGURES | View All (4)
View articletitled, Environmental Inequality and Residential Sorting in Germany: A Spatial Time-<span class="search-highlight">Series</span> Analysis of the Demographic Consequences of Industrial Sites View PDF for article titled, Environmental Inequality and Residential Sorting in Germany: A Spatial Time-<span class="search-highlight">Series</span> Analysis of the Demographic Consequences of Industrial Sites
Includes: Supplementary data
Image
Line plots of the total fertility rate, Human Life Indicator, Human Development Index, and life expectancy over the period 1969–2018.

Time series of fertility and the three development variables. The semitrans...

Open Access
in Revisiting the J-Shape: Human Development and Fertility in the United States > Demography
Published: 01 December 2024
Fig. 1 Time series of fertility and the three development variables. The semitransparent lines represent the data values for the states. The thick lines are the values of the indicator at the country level for the United States. TFR = total fertility rate. HLI = Human Life Indicator. HDI = Human More
Image
Time series (2010–2021) showing the remainder component of decomposed monthly standardized mortality rates in Brazil for various causes. Most show fluctuations around zero, with large deviations, positive and negative, post-2020. The vertical scales differ across panels.

Remainder component of the decomposition of time series of monthly standard...

Open Access
in Mortality by Cause of Death in Brazil: A Research Note on the Effects of the COVID-19 Pandemic and Contribution to Changes in Life Expectancy at Birth > Demography
Published: 01 April 2025
Fig. 2 Remainder component of the decomposition of time series of monthly standardized mortality rates by cause-of-death groups: Brazil, 2010–2021. The vertical scales differ across panels to uncover variations from each cause of death. More
Image
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources.

National time series trends for possible pathways. National trends in measu...

Open Access
in Growth in Suicide Rates Among Children During the Illicit Opioid Crisis > Demography
Published: 01 December 2023
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources. More
Image
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources.

National time series trends for possible pathways. National trends in measu...

Open Access
in Growth in Suicide Rates Among Children During the Illicit Opioid Crisis > Demography
Published: 01 December 2023
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources. More
Image
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources.

National time series trends for possible pathways. National trends in measu...

Open Access
in Growth in Suicide Rates Among Children During the Illicit Opioid Crisis > Demography
Published: 01 December 2023
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources. More
Image
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources.

National time series trends for possible pathways. National trends in measu...

Open Access
in Growth in Suicide Rates Among Children During the Illicit Opioid Crisis > Demography
Published: 01 December 2023
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources. More
Image
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources.

National time series trends for possible pathways. National trends in measu...

Open Access
in Growth in Suicide Rates Among Children During the Illicit Opioid Crisis > Demography
Published: 01 December 2023
Fig. 5 National time series trends for possible pathways. National trends in measures were impacted by reformulation. OxyContin reformulation is indicated by a vertical line in 2010. See text for discussion of data sources. More
Image
Time series (2010–2021) showing monthly standardized mortality rates in Brazil for various causes, including septicemia, obesity, and heart disease and stroke (which were relatively stable); notable spikes are seen for COVID-19 and total deaths from 2020. The vertical scales differ across panels.

Time series of monthly standardized mortality rates by cause-of-death group...

Open Access
in Mortality by Cause of Death in Brazil: A Research Note on the Effects of the COVID-19 Pandemic and Contribution to Changes in Life Expectancy at Birth > Demography
Published: 01 April 2025
Fig. 1 Time series of monthly standardized mortality rates by cause-of-death groups: Brazil, 2010–2021. The vertical scales differ across panels to uncover variations from each cause of death. More
Image
Fig. 4 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among all persons giving birth in California from March 2020 to November 2021. Symbols indicate parameter estimates, and vertical lines depict 95% confidence intervals. Parameter estimates represent risk differences between the observed preterm birth rate and the rate expected as a function of autocorrelation from January 2014 to February 2020 (the prepandemic period). Model 2 includes the following covariates: mother's age, age squared, birth parity, education, race/ethnicity, foreign-born status, and ZIP code of residence socioeconomic quartile. Model 3 adds controls for cesarean section and labor induction.

Time-series ARIMA analysis predicting changes in the preterm birth rate aft...

Open Access
in The Unequal Impact of the COVID-19 Pandemic on Infant Health > Demography
Published: 01 December 2022
Fig. 4 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among all persons giving birth in California from March 2020 to November 2021. Symbols indicate parameter estimates, and vertical lines depict 95% confidence intervals. Parameter estimates More
Image
Fig. 5 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among all persons giving birth and persons giving birth without a COVID infection at the time of delivery in California from March 2020 to November 2021. Symbols indicate parameter estimates, and vertical lines depict 95% confidence intervals. Parameter estimates represent risk differences between the observed preterm birth rate and the rate expected as a function of autocorrelation from January 2014 to February 2020 (the prepandemic period).

Time-series ARIMA analysis predicting changes in the preterm birth rate aft...

Open Access
in The Unequal Impact of the COVID-19 Pandemic on Infant Health > Demography
Published: 01 December 2022
Fig. 5 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among all persons giving birth and persons giving birth without a COVID infection at the time of delivery in California from March 2020 to November 2021. Symbols indicate parameter estimates More
Image
Fig. 6 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among subgroups of persons giving birth, by educational attainment, in California from March 2020 to November 2021. Symbols indicate parameter estimates, and vertical lines depict 95% confidence intervals. Parameter estimates represent risk differences between the observed preterm birth rate and the rate expected as a function of autocorrelation from January 2014 to February 2020 (the prepandemic period). HS = high school. BA = bachelor's degree.

Time-series ARIMA analysis predicting changes in the preterm birth rate aft...

Open Access
in The Unequal Impact of the COVID-19 Pandemic on Infant Health > Demography
Published: 01 December 2022
Fig. 6 Time-series ARIMA analysis predicting changes in the preterm birth rate after the pandemic onset among subgroups of persons giving birth, by educational attainment, in California from March 2020 to November 2021. Symbols indicate parameter estimates, and vertical lines depict 95 More