Zeitschriften und Ausgaben

Volumen 38 (2022): Heft 3 (September 2022)

Volumen 38 (2022): Heft 2 (June 2022)

Volumen 38 (2022): Heft 1 (March 2022)
Special Heft on Price Indices in Official Statistics

Volumen 37 (2021): Heft 4 (December 2021)

Volumen 37 (2021): Heft 3 (September 2021)
Special Heft on Population Statistics for the 21st Century

Volumen 37 (2021): Heft 2 (June 2021)
Special Heft on New Techniques and Technologies for Statistics

Volumen 37 (2021): Heft 1 (March 2021)

Volumen 36 (2020): Heft 4 (December 2020)

Volumen 36 (2020): Heft 3 (September 2020)
Special Heft on Nonresponse

Volumen 36 (2020): Heft 2 (June 2020)

Volumen 36 (2020): Heft 1 (March 2020)

Volumen 35 (2019): Heft 4 (December 2019)
Special Heft on Measuring LGBT Populations

Volumen 35 (2019): Heft 3 (September 2019)

Volumen 35 (2019): Heft 2 (June 2019)

Volumen 35 (2019): Heft 1 (March 2019)

Volumen 34 (2018): Heft 4 (December 2018)

Volumen 34 (2018): Heft 3 (September 2018)
Special Section on Responsive and Adaptive Survey Design

Volumen 34 (2018): Heft 2 (June 2018)
Special Heft on Establishment Surveys (ICES-V)

Volumen 34 (2018): Heft 1 (March 2018)

Volumen 33 (2017): Heft 4 (December 2017)

Volumen 33 (2017): Heft 3 (September 2017)
Special Heft on Responsive and Adaptive Survey Design

Volumen 33 (2017): Heft 2 (June 2017)
Special Heft on Total Survey Error (TSE)

Volumen 33 (2017): Heft 1 (March 2017)

Volumen 32 (2016): Heft 4 (December 2016)
Special Section on The Role of official Statistics in Statistical Capacity Building

Volumen 32 (2016): Heft 3 (September 2016)

Volumen 32 (2016): Heft 2 (June 2016)

Volumen 32 (2016): Heft 1 (March 2016)

Volumen 31 (2015): Heft 4 (December 2015)

Volumen 31 (2015): Heft 3 (September 2015)
Special Heft on Coverage Problems in Administrative Sources

Volumen 31 (2015): Heft 2 (June 2015)
Special Heft on New Techniques and Technologies for Statistics

Volumen 31 (2015): Heft 1 (March 2015)

Volumen 30 (2014): Heft 4 (December 2014)
Special Heft on Establishment Surveys

Volumen 30 (2014): Heft 3 (September 2014)

Volumen 30 (2014): Heft 2 (June 2014)
Special Heft on Surveying the Hard-to-Reach

Volumen 30 (2014): Heft 1 (March 2014)

Volumen 29 (2013): Heft 4 (December 2013)

Volumen 29 (2013): Heft 3 (September 2013)

Volumen 29 (2013): Heft 2 (June 2013)

Volumen 29 (2013): Heft 1 (March 2013)

Zeitschriftendaten
Format
Zeitschrift
eISSN
2001-7367
Erstveröffentlichung
01 Oct 2013
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 37 (2021): Heft 3 (September 2021)
Special Heft on Population Statistics for the 21st Century

Zeitschriftendaten
Format
Zeitschrift
eISSN
2001-7367
Erstveröffentlichung
01 Oct 2013
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

12 Artikel
Uneingeschränkter Zugang

Preface

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 533 - 541

Zusammenfassung

Uneingeschränkter Zugang

Letter to the Editors

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 543 - 545

Zusammenfassung

Uneingeschränkter Zugang

Fertility Projections in a European Context: A Survey of Current Practices among Statistical Agencies

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 547 - 568

Zusammenfassung

Abstract

Projection studies have often focused on mortality and, more recently, migration. Fertility is less studied, although even small changes can have significant repercussions for the size and age structure of future populations. Across Europe, there is no consensus on how fertility is best projected. In this article, we identify different approaches used to project fertility among statistical agencies in Europe and provide an assessment of the different approaches according to the producers themselves.

Data were collected using a mixed-method approach. First, European statistical agencies answered a questionnaire regarding fertility projection practices. Second, an in-depth review of select countries was performed.

Most agencies combine formal models with expert opinion. While many attempt to maximise the use of relevant inputs, there is more variation in the detail of outputs, with some agencies unable to account for changing age patterns. In a context of limited resources, most are satisfied with their approaches, though some are assessing alternative methodologies to improve accuracy and increase transparency.

This study highlights the diversity of approaches used in fertility projections across Europe. Such knowledge may be useful to statistical agencies as they consider, test and implement different approaches, perhaps in collaboration with other agencies and the wider scientific community.

Schlüsselwörter

  • Europe
  • fertility
  • forecasts
  • methods
  • population projections
Uneingeschränkter Zugang

Modelling Frontier Mortality Using Bayesian Generalised Additive Models

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 569 - 589

Zusammenfassung

Abstract

Mortality rates differ across countries and years, and the country with the lowest observed mortality has changed over time. However, the classic Science paper by Oeppen and Vaupel (2002) identified a persistent linear trend over time in maximum national life expectancy. In this article, we look to exploit similar regularities in age-specific mortality by considering for any given year a hypothetical mortality ‘frontier’, which we define as the lower limit of the force of mortality at each age across all countries. Change in this frontier reflects incremental advances across the wide range of social, institutional and scientific dimensions that influence mortality. We jointly estimate frontier mortality as well as mortality rates for individual countries. Generalised additive models are used to estimate a smooth set of baseline frontier mortality rates and mortality improvements, and country-level mortality is modelled as a set of smooth, positive deviations from this, forcing the mortality estimates for individual countries to lie above the frontier. This model is fitted to data for a selection of countries from the Human Mortality Database (2019). The efficacy of the model in forecasting over a ten-year horizon is compared to a similar model fitted to each country separately.

Schlüsselwörter

  • Mortality
  • demography
  • Bayesian methods
  • population forecasting
Uneingeschränkter Zugang

Probabilistic Projection of Subnational Life Expectancy

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 591 - 610

Zusammenfassung

Abstract

Projecting mortality for subnational units, or regions, is of great interest to practicing demographers. We seek a probabilistic method for projecting subnational life expectancy that is based on the national Bayesian hierarchical model used by the United Nations, and at the same time is easy to use. We propose three methods of this kind. Two of them are variants of simple scaling methods. The third method models life expectancy for a region as equal to national life expectancy plus a region-specific stochastic process which is a heteroskedastic first-order autoregressive process (AR(1)), with a variance that declines to a constant as life expectancy increases. We apply our models to data from 29 countries. In an out-of-sample comparison, the proposed methods outperformed other comparative methods and were well calibrated for individual regions. The AR (1) method performed best in terms of crossover patterns between regions. Although the methods work well for individual regions, there are some limitations when evaluating within-country variation. We identified four countries for which the AR(1) method either underestimated or overestimated the predictive between-region within-country standard deviation. However, none of the competing methods work better in this regard than the AR(1) method. In addition to providing the full distribution of subnational life expectancy, the methods can be used to obtain probabilistic forecasts of age-specific mortality rates.

Uneingeschränkter Zugang

Spatio-Temporal Patterns in Portuguese Regional Fertility Rates: A Bayesian Approach for Spatial Clustering of Curves

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 611 - 653

Zusammenfassung

Abstract

It is important for demographic analyses and policy-making to obtain accurate models of spatial diffusion, so that policy experiments can reflect endogenous spatial spillovers appropriately. Likewise, it is important to obtain accurate estimates and forecasts of demographic variables such as age-specific fertility rates, by regions and over time, as well as the uncertainty associated with such estimation. Here, we consider Bayesian hierarchical models with separable spatio-temporal dependence structure that can be estimated by borrowing strength from neighbouring regions and all years. Further, we do not consider the adjacency structure as a given, but rather as an object of inference. For this purpose, we use the local similarity of temporal patterns by developing a spatial clustering model based on Bayesian nonparametric smoothing techniques. The Bayesian inference provides the uncertainty associated with the clustering configurations that is typically lacking in classical analyses of large data sets in which a unique clustering representation can be insufficient. The proposed model is applied to 16-year data on age-specific fertility rates observed over 28 regions in Portugal, and provides statistical inference on the number of clusters, and local scaling and shrinkage levels. The corresponding central clustering configuration is able to capture spatial diffusion that has key demographic interpretations. Importantly, the exercise aids identification of peripheral regions with poor demographic prospects and development of regional policy for such places.

Schlüsselwörter

  • Spatio-temporal modeling
  • conditional autoregressive model
  • spatial clustering
  • bayesian wavelet smoothing
  • bayesian hierarchical model
  • age-specific fertility rates
Uneingeschränkter Zugang

Optimal Sampling for the Population Coverage Survey of the New Italian Register Based Census

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 655 - 671

Zusammenfassung

Abstract

For the first time in 2018 the Italian Institute of Statistics (Istat) implemented the annual Permanent Population Census which relies on the Population Base Register (PBR) and the Population Coverage Survey (PCS). This article provides a general overview of the PCS sampling design, which makes use of the PBR to correct population counts with the extended dual system estimator (Nirel and Glickman 2009). The sample allocation, proven optimal under a set of precision constraints, is based on preliminary estimates of individual probabilities of over-coverage and under-coverage. It defines the expected sample size in terms of individuals, and it oversamples the sub-populations subject to the risk of under/over coverage. Finally, the article introduces a sample selection method, which to the greatest extent possible satisfies the planned allocation of persons in terms of socio-demographic characteristics. Under acceptable assumptions, the article also shows that the sampling strategy enhances the precision of the estimates.

Schlüsselwörter

  • Population census
  • balanced area sample
  • capture-recapture estimator
  • administrative data
  • sample allocation
Uneingeschränkter Zugang

Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 673 - 697

Zusammenfassung

Abstract

Estimation of the unknown population size using capture-recapture techniques relies on the key assumption that the capture probabilities are homogeneous across individuals in the population. This is usually accomplished via post-stratification by some key covariates believed to influence individual catchability. Another issue that arises in population estimation from data collected from multiple sources is list dependence, where an individual’s catchability on one list is related to that of another list. The earlier models for population estimation heavily relied upon list independence. However, there are methods available that can adjust the population estimates to account for dependence among lists. In this article, we propose the use of latent class analysis through log-linear modelling to estimate the population size in the presence of both heterogeneity and list dependence. The proposed approach is illustrated using data from the 1988 US census dress rehearsal.

Schlüsselwörter

  • Capture-recapture
  • latent class analysis
  • log-linear models
Uneingeschränkter Zugang

A General Framework for Multiple-Recapture Estimation that Incorporates Linkage Error Correction

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 699 - 718

Zusammenfassung

Abstract

The size of a partly observed population is often estimated with the capture-recapture model. An important assumption of this chat model is that sources can be perfectly linked. This assumption is of relevance if the identification of records is not obtained by some perfect identifier (such as an id code) but by indirect identifiers (such as name and address). In that case, the perfect linkage assumption is often violated, which in general leads to biased population size estimates. Initial suggestions to solve this use record linkage probabilities to correct the capture-recapture model. In this article we provide a general framework, based on the standard log-linear modelling approach, that generalises this work towards the inclusion of additional sources and covariates. We show that the method performs well in a simulation study.

Schlüsselwörter

  • Population size estimation
  • capture-recapture
  • dual-system estimation
  • multiple-system estimation
  • record linkage
Uneingeschränkter Zugang

Exploratory Assessment of the Census of Pakistan Using Demographic Analysis

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 719 - 750

Zusammenfassung

Abstract

In 2017, Pakistan implemented a long-awaited population census since the last one conducted in 1998. However, several experts are contesting the validity of the census data at the sub-national level, particularly in the absence of a post-enumeration survey. We propose in this article to use demographic analysis to assess the results of the 2017 census at the sub-national level, using data from the 1998 census, from all available intercensal surveys, including three rounds of Demographic and Health Survey. Applying the cohort-component method of population projection, we subject each five first-level subnational entities to estimates regarding the level of fertility, mortality, international, and internal migration derived from the analysis of the existing data. We arrive at approximately similar results as the census at the national level: an estimated 210 million (95% CI: 203.4–218.9) compared to 207.8 million counted (1.1% difference). However, we found substantial sub-national variations. While there are too many uncertainties in the data used for the reconstruction to be fully confident about them, this analysis should prompt the national and the international community to ensure that a post-enumeration survey and demographic analysis are regular features of census operations of Pakistan in particular, and in developing countries with deficient data as a whole.

Schlüsselwörter

  • Census
  • population projections
  • reconstruction
  • Pakistan
  • Pakistan provinces
Uneingeschränkter Zugang

A Simulation Study of Diagnostics for Selection Bias

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 751 - 769

Zusammenfassung

Abstract

A non-probability sampling mechanism arising from nonresponse or non-selection is likely to bias estimates of parameters with respect to a target population of interest. This bias poses a unique challenge when selection is ‘non-ignorable’, that is, dependent on the unobserved outcome of interest, since it is then undetectable and thus cannot be ameliorated. We extend a simulation study by Nishimura et al. (2016) adding two recently published statistics: the ‘standardized measure of unadjusted bias’ (SMUB) and ‘standardized measure of adjusted bias’ (SMAB), which explicitly quantify the extent of bias (in the case of SMUB) or nonignorable bias (in the case of SMAB) under the assumption that a specified amount of nonignorable selection exists. Our findings suggest that this new sensitivity diagnostic is more correlated with, and more predictive of, the true, unknown extent of selection bias than other diagnostics, even when the underlying assumed level of non-ignorability is incorrect.

Schlüsselwörter

  • Non-ignorable selection bias
  • survey nonresponse
  • multiple imputation
  • pattern mixture model
Uneingeschränkter Zugang

Fay-Herriot Model-Based Prediction Alternatives for Estimating Households with Emigrated Members

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 771 - 789

Zusammenfassung

Abstract

This article proposes a new methodology for estimating the proportions of households that had experience of international migration at the municipal level in Colombia. The Colombian National Statistical Office usually produces estimations of internal migration based on the results of population censuses, but there is a lack of disaggregated information about the main small areas of origin of the population that emigrates from Colombia. The proposed methodology uses frequentist and Bayesian approaches based on a Fay-Herriot model and is illustrated by one example with a dependent variable from the Demographic and Health Survey 2015 and covariables available from the population census 2005. The proposed alternative produces proportion estimates that are consistent with sample sizes and the main internal immigration trends in Colombia. Additionally, the estimated coefficients of variation are lower than 20% for municipalities for both frequentist and Bayesian approaches and large demographically-relevant capital cities and therefore estimates may be considered to be reliable. Finally, we illustrate how the proposed alternative leads to important reductions of the estimated coefficients of variations for the areas with very small sample sizes.

Schlüsselwörter

  • Small area estimation
  • international migration
  • Fay-Herriot model
  • coefficient of variation
  • direct estimator
  • model-based estimator
  • hierarchical Bayes prediction
12 Artikel
Uneingeschränkter Zugang

Preface

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 533 - 541

Zusammenfassung

Uneingeschränkter Zugang

Letter to the Editors

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 543 - 545

Zusammenfassung

Uneingeschränkter Zugang

Fertility Projections in a European Context: A Survey of Current Practices among Statistical Agencies

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 547 - 568

Zusammenfassung

Abstract

Projection studies have often focused on mortality and, more recently, migration. Fertility is less studied, although even small changes can have significant repercussions for the size and age structure of future populations. Across Europe, there is no consensus on how fertility is best projected. In this article, we identify different approaches used to project fertility among statistical agencies in Europe and provide an assessment of the different approaches according to the producers themselves.

Data were collected using a mixed-method approach. First, European statistical agencies answered a questionnaire regarding fertility projection practices. Second, an in-depth review of select countries was performed.

Most agencies combine formal models with expert opinion. While many attempt to maximise the use of relevant inputs, there is more variation in the detail of outputs, with some agencies unable to account for changing age patterns. In a context of limited resources, most are satisfied with their approaches, though some are assessing alternative methodologies to improve accuracy and increase transparency.

This study highlights the diversity of approaches used in fertility projections across Europe. Such knowledge may be useful to statistical agencies as they consider, test and implement different approaches, perhaps in collaboration with other agencies and the wider scientific community.

Schlüsselwörter

  • Europe
  • fertility
  • forecasts
  • methods
  • population projections
Uneingeschränkter Zugang

Modelling Frontier Mortality Using Bayesian Generalised Additive Models

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 569 - 589

Zusammenfassung

Abstract

Mortality rates differ across countries and years, and the country with the lowest observed mortality has changed over time. However, the classic Science paper by Oeppen and Vaupel (2002) identified a persistent linear trend over time in maximum national life expectancy. In this article, we look to exploit similar regularities in age-specific mortality by considering for any given year a hypothetical mortality ‘frontier’, which we define as the lower limit of the force of mortality at each age across all countries. Change in this frontier reflects incremental advances across the wide range of social, institutional and scientific dimensions that influence mortality. We jointly estimate frontier mortality as well as mortality rates for individual countries. Generalised additive models are used to estimate a smooth set of baseline frontier mortality rates and mortality improvements, and country-level mortality is modelled as a set of smooth, positive deviations from this, forcing the mortality estimates for individual countries to lie above the frontier. This model is fitted to data for a selection of countries from the Human Mortality Database (2019). The efficacy of the model in forecasting over a ten-year horizon is compared to a similar model fitted to each country separately.

Schlüsselwörter

  • Mortality
  • demography
  • Bayesian methods
  • population forecasting
Uneingeschränkter Zugang

Probabilistic Projection of Subnational Life Expectancy

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 591 - 610

Zusammenfassung

Abstract

Projecting mortality for subnational units, or regions, is of great interest to practicing demographers. We seek a probabilistic method for projecting subnational life expectancy that is based on the national Bayesian hierarchical model used by the United Nations, and at the same time is easy to use. We propose three methods of this kind. Two of them are variants of simple scaling methods. The third method models life expectancy for a region as equal to national life expectancy plus a region-specific stochastic process which is a heteroskedastic first-order autoregressive process (AR(1)), with a variance that declines to a constant as life expectancy increases. We apply our models to data from 29 countries. In an out-of-sample comparison, the proposed methods outperformed other comparative methods and were well calibrated for individual regions. The AR (1) method performed best in terms of crossover patterns between regions. Although the methods work well for individual regions, there are some limitations when evaluating within-country variation. We identified four countries for which the AR(1) method either underestimated or overestimated the predictive between-region within-country standard deviation. However, none of the competing methods work better in this regard than the AR(1) method. In addition to providing the full distribution of subnational life expectancy, the methods can be used to obtain probabilistic forecasts of age-specific mortality rates.

Uneingeschränkter Zugang

Spatio-Temporal Patterns in Portuguese Regional Fertility Rates: A Bayesian Approach for Spatial Clustering of Curves

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 611 - 653

Zusammenfassung

Abstract

It is important for demographic analyses and policy-making to obtain accurate models of spatial diffusion, so that policy experiments can reflect endogenous spatial spillovers appropriately. Likewise, it is important to obtain accurate estimates and forecasts of demographic variables such as age-specific fertility rates, by regions and over time, as well as the uncertainty associated with such estimation. Here, we consider Bayesian hierarchical models with separable spatio-temporal dependence structure that can be estimated by borrowing strength from neighbouring regions and all years. Further, we do not consider the adjacency structure as a given, but rather as an object of inference. For this purpose, we use the local similarity of temporal patterns by developing a spatial clustering model based on Bayesian nonparametric smoothing techniques. The Bayesian inference provides the uncertainty associated with the clustering configurations that is typically lacking in classical analyses of large data sets in which a unique clustering representation can be insufficient. The proposed model is applied to 16-year data on age-specific fertility rates observed over 28 regions in Portugal, and provides statistical inference on the number of clusters, and local scaling and shrinkage levels. The corresponding central clustering configuration is able to capture spatial diffusion that has key demographic interpretations. Importantly, the exercise aids identification of peripheral regions with poor demographic prospects and development of regional policy for such places.

Schlüsselwörter

  • Spatio-temporal modeling
  • conditional autoregressive model
  • spatial clustering
  • bayesian wavelet smoothing
  • bayesian hierarchical model
  • age-specific fertility rates
Uneingeschränkter Zugang

Optimal Sampling for the Population Coverage Survey of the New Italian Register Based Census

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 655 - 671

Zusammenfassung

Abstract

For the first time in 2018 the Italian Institute of Statistics (Istat) implemented the annual Permanent Population Census which relies on the Population Base Register (PBR) and the Population Coverage Survey (PCS). This article provides a general overview of the PCS sampling design, which makes use of the PBR to correct population counts with the extended dual system estimator (Nirel and Glickman 2009). The sample allocation, proven optimal under a set of precision constraints, is based on preliminary estimates of individual probabilities of over-coverage and under-coverage. It defines the expected sample size in terms of individuals, and it oversamples the sub-populations subject to the risk of under/over coverage. Finally, the article introduces a sample selection method, which to the greatest extent possible satisfies the planned allocation of persons in terms of socio-demographic characteristics. Under acceptable assumptions, the article also shows that the sampling strategy enhances the precision of the estimates.

Schlüsselwörter

  • Population census
  • balanced area sample
  • capture-recapture estimator
  • administrative data
  • sample allocation
Uneingeschränkter Zugang

Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 673 - 697

Zusammenfassung

Abstract

Estimation of the unknown population size using capture-recapture techniques relies on the key assumption that the capture probabilities are homogeneous across individuals in the population. This is usually accomplished via post-stratification by some key covariates believed to influence individual catchability. Another issue that arises in population estimation from data collected from multiple sources is list dependence, where an individual’s catchability on one list is related to that of another list. The earlier models for population estimation heavily relied upon list independence. However, there are methods available that can adjust the population estimates to account for dependence among lists. In this article, we propose the use of latent class analysis through log-linear modelling to estimate the population size in the presence of both heterogeneity and list dependence. The proposed approach is illustrated using data from the 1988 US census dress rehearsal.

Schlüsselwörter

  • Capture-recapture
  • latent class analysis
  • log-linear models
Uneingeschränkter Zugang

A General Framework for Multiple-Recapture Estimation that Incorporates Linkage Error Correction

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 699 - 718

Zusammenfassung

Abstract

The size of a partly observed population is often estimated with the capture-recapture model. An important assumption of this chat model is that sources can be perfectly linked. This assumption is of relevance if the identification of records is not obtained by some perfect identifier (such as an id code) but by indirect identifiers (such as name and address). In that case, the perfect linkage assumption is often violated, which in general leads to biased population size estimates. Initial suggestions to solve this use record linkage probabilities to correct the capture-recapture model. In this article we provide a general framework, based on the standard log-linear modelling approach, that generalises this work towards the inclusion of additional sources and covariates. We show that the method performs well in a simulation study.

Schlüsselwörter

  • Population size estimation
  • capture-recapture
  • dual-system estimation
  • multiple-system estimation
  • record linkage
Uneingeschränkter Zugang

Exploratory Assessment of the Census of Pakistan Using Demographic Analysis

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 719 - 750

Zusammenfassung

Abstract

In 2017, Pakistan implemented a long-awaited population census since the last one conducted in 1998. However, several experts are contesting the validity of the census data at the sub-national level, particularly in the absence of a post-enumeration survey. We propose in this article to use demographic analysis to assess the results of the 2017 census at the sub-national level, using data from the 1998 census, from all available intercensal surveys, including three rounds of Demographic and Health Survey. Applying the cohort-component method of population projection, we subject each five first-level subnational entities to estimates regarding the level of fertility, mortality, international, and internal migration derived from the analysis of the existing data. We arrive at approximately similar results as the census at the national level: an estimated 210 million (95% CI: 203.4–218.9) compared to 207.8 million counted (1.1% difference). However, we found substantial sub-national variations. While there are too many uncertainties in the data used for the reconstruction to be fully confident about them, this analysis should prompt the national and the international community to ensure that a post-enumeration survey and demographic analysis are regular features of census operations of Pakistan in particular, and in developing countries with deficient data as a whole.

Schlüsselwörter

  • Census
  • population projections
  • reconstruction
  • Pakistan
  • Pakistan provinces
Uneingeschränkter Zugang

A Simulation Study of Diagnostics for Selection Bias

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 751 - 769

Zusammenfassung

Abstract

A non-probability sampling mechanism arising from nonresponse or non-selection is likely to bias estimates of parameters with respect to a target population of interest. This bias poses a unique challenge when selection is ‘non-ignorable’, that is, dependent on the unobserved outcome of interest, since it is then undetectable and thus cannot be ameliorated. We extend a simulation study by Nishimura et al. (2016) adding two recently published statistics: the ‘standardized measure of unadjusted bias’ (SMUB) and ‘standardized measure of adjusted bias’ (SMAB), which explicitly quantify the extent of bias (in the case of SMUB) or nonignorable bias (in the case of SMAB) under the assumption that a specified amount of nonignorable selection exists. Our findings suggest that this new sensitivity diagnostic is more correlated with, and more predictive of, the true, unknown extent of selection bias than other diagnostics, even when the underlying assumed level of non-ignorability is incorrect.

Schlüsselwörter

  • Non-ignorable selection bias
  • survey nonresponse
  • multiple imputation
  • pattern mixture model
Uneingeschränkter Zugang

Fay-Herriot Model-Based Prediction Alternatives for Estimating Households with Emigrated Members

Online veröffentlicht: 13 Sep 2021
Seitenbereich: 771 - 789

Zusammenfassung

Abstract

This article proposes a new methodology for estimating the proportions of households that had experience of international migration at the municipal level in Colombia. The Colombian National Statistical Office usually produces estimations of internal migration based on the results of population censuses, but there is a lack of disaggregated information about the main small areas of origin of the population that emigrates from Colombia. The proposed methodology uses frequentist and Bayesian approaches based on a Fay-Herriot model and is illustrated by one example with a dependent variable from the Demographic and Health Survey 2015 and covariables available from the population census 2005. The proposed alternative produces proportion estimates that are consistent with sample sizes and the main internal immigration trends in Colombia. Additionally, the estimated coefficients of variation are lower than 20% for municipalities for both frequentist and Bayesian approaches and large demographically-relevant capital cities and therefore estimates may be considered to be reliable. Finally, we illustrate how the proposed alternative leads to important reductions of the estimated coefficients of variations for the areas with very small sample sizes.

Schlüsselwörter

  • Small area estimation
  • international migration
  • Fay-Herriot model
  • coefficient of variation
  • direct estimator
  • model-based estimator
  • hierarchical Bayes prediction

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