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2 edition of Estimating population and income of small areas found in the catalog.

Estimating population and income of small areas

National Research Council (U.S.) Panel on Small-Area Estimates of Population and Income

Estimating population and income of small areas

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  • 10 Currently reading

Published by National Academy Press, 1980. in Washington, D.C .
Written in English

    Subjects:
  • Population forecasting -- ,
  • Income forecasting --

  • Edition Notes

    Includes bibliographies.

    Other titlesSmall areas
    StatementPanel on Small-Area Estimates of Population and Income, Committee on National Statistics, Assembly of Behavioral and Social Sciences, National Research Council.. --
    The Physical Object
    Paginationxiii, 247 p. ;
    Number of Pages247
    ID Numbers
    Open LibraryOL21365811M

    Geospatial Data Methods for Estimating Population Health Outcomes \爀屲Usually we treat geographic areas lower than the original geographic lev\൥ls by survey design as small areas.\爀屲For example, county is a small area for most national, even state health surveys. \爀屲The對 main purose of small area estimation is to generate File Size: 1MB.


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Estimating population and income of small areas by National Research Council (U.S.) Panel on Small-Area Estimates of Population and Income Download PDF EPUB FB2

Suggested Citation:"SUMMARY REPORT."National Research Council. Estimating Population and Income of Small gton, DC: The National Academies Press. doi. Suggested Citation:"Front Matter."National Research Council. Estimating Population and Income of Small gton, DC: The National Academies Press.

doi. Download a PDF of "Estimating Population and Income of Small Areas" by the National Research Council for free. Download a PDF of "Estimating Population and Income of Small Areas" by the National Research Council for free. Copy the HTML code below to embed this book in your own blog, website, or application.

Panel on Small-Area Estimates of population and income. Estimating population and income of small areas. Washington, D.C.: National Academy Press, (OCoLC) Document Type: Book: All Authors / Contributors: Assembly of Behavioral and Social Sciences (U.S.).

Panel on Small-Area Estimates of Population and Income. ISBN: X. Demographic Techniques: Small-area Estimates and Projections Population estimates and projections play a critical role in market analysis, facility planning, environmental planning, and the allocation of public and private funds.

Estimates and projections for small areas, in particular, are used extensively in the public and private sectors,File Size: KB. Estimation of Income Quantiles at the Small Area Level in Tuscany and the third quartiles of the household equivalised income in the small areas.

A simple method for estimating population. Small area estimation is important in light of a continual demand by data users for finer geographic detail of published statistics and for various subpopulations.

Traditional demographic sample surveys designed for national estimates do not provide large enough samples to produce reliable direct estimates for small areas such as counties and. Even so, comparing model-based with directly calculated survey-based estimates of the target population in the large area (i.e., the aggregate of local areas) can provide some indication of the performance of a model.

For example, our method estimated that % of California women aged 40 years or older were service-eligible, whereas the Author: Kirsten Knutson, Weihong Zhang, Farzaneh Tabnak.

Download Small Area Income and Poverty Estimates: [PDF - MB] This document presents summary statistics of the data released by the Small Area Income and Poverty Estimates (SAIPE) program of the U.S. Census Bureau in November This paper describes the results of applying a spatial microsimulation approach to the estimation of small area (LSOA) income deprivation for Wales for using the Census and the FRS Five innovative methods of establishing the population characteristics of small areas are introduced and evaluated in this book.

Changes in communities can be slow, but recent history has seen huge growth in some areas and depopulation of others. As a result, population estimating has grown up under pressure from legislators and administrators who place a high premium on validity.

Estimating income, expenditure and time-use within small areas. Paper presented at the ESRC Microsimulation Seminar Series Workshop III ‘Moving beyond tax-benefit and demographic modelling’, University of Leeds, Leeds, UK.

Google ScholarCited by: Download Small Domain Methodology for Estimating Income and Poverty Characteristics for States in [PDF - income year of income and poverty by state produced as part of the Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) project.

the distribution of earned income conditioned on education and gender. An Application of the Inequality Process to the Estimation of Earned Income for Small Areas In areas with fewer residents than the minimum offor a PUMA but with at le residents, the following three types of summary statistics based on ACS.

Estimating income for small areas may be done in several ways. The "long methods" aggregate each component so far as data will per­ mit and allocate the remaining income on the basis of relationships observed for large areas, usually states.

A description of detailed methods and procedures is summarized by Lewis C. Copeland   15 Small Area Estimation for Lognormal Data Emily Berg, Hukum Chandra and Ray Chambers.

Introduction Literature on Small Area Estimation for Skewed Data Small Area Predictors for a Unit-Level Lognormal Model The Linear Unit-Level Mixed Model A Synthetic Estimator A Model-Based Author: Monica Pratesi.

Estimating distributions of household income for middle layer super output areas in using small area estimation methods A method developed in academia in is used which combines parameter estimates from a multilevel model fitted to the Family Resources Survey (FRS) with household-level Census data.

Assessment of the Feasibility of Calculating Small Area Median Family Income Estimates. To assess the feasibility of calculating area median family income estimates at smaller levels of geography than those currently used, HUD must review both the statutes governing the MFI estimates as well as the data available for making these estimates.

from small numbers of counts and deaths often results in highly erratic schedules that are very difficult to interpret. In this paper we give an in-depth overview of the method adopted by Statistics Portugal for estimating life expectancy in small population (sub-national) areas (NUTS II and NUTS III).

This chapter discusses a newly proposed method by the author for estimating small area demographics, and explains how to apply this method to long-term small area population projection.

Since small area demographics are generally very unstable, various methods of estimating the true values of such data have been developed or considered, chiefly Author: Takashi Inoue.

S.L. Lohr, in International Encyclopedia of the Social & Behavioral Sciences, 3 Models for Small Area Estimation. In small area estimation, a model is used to estimate the response in subpopulations with few or no sample an example, the US Current Population Survey (CPS) provides accurate statistics about income and poverty for the nation as a whole.

Appendix C Domain Estimates, Reliability, and Small-Area Estimation. The Small Area Income and Poverty Estimates Estimation of the proportion of overweight individuals in small areas—a robust extension of the fay-herriot model.

Statistics in Medicine 26(13)– Ministry for Welfare and Population Development. White Paper on Population Policy. 7 September Pretoria: Government Gazette. National Research Council.

Estimating Population and Income of Small Areas. Panel on Small-Area Estimates of Population and Income, Committee on National Statistics. Washington DC: The National Academies.

6 Science Report Methods of Estimating Population and Household Projections Contents Executive Summary 4 Contents 6 1. Background 8 Introduction 8 Structure of this report 8 2 Why are (small area) population and household estimates needed. 10 Introduction 10 Needs within the water industry 10 What levels of geographic scale File Size: KB.

Small Area Income and Poverty Estimates Data Description Citation This dataset was obtained from the US Census Bureau’s Small Area Income and Poverty Estimates Program available on the Internet at estimates for counties and other areas with a population of 65, or more are Size: KB.

Introduction. The small area model-based income estimates are the official estimates of weekly household income at the middle layer super output area (MSOA) level in England and Wales for / They are calculated using a model-based method to produce the following 4 estimates of income using a combination of survey data from the Family Resources Survey and previously.

The Changing Face of Rural &Small Town America • Changing demographics –growing Hispanic population –aging population –outflow of young adults--inflow of older adults, birth rates declining • Health issues –Obesity above national rates for all age groups –rural kids less likely to walk to school –Populace is very auto-reliantFile Size: 1MB.

According to recent reports, more than a quarter of the population living in rural areas of India is below the poverty line. Out of the total population living in the rural parts of India, % is living below the poverty line whereas in the urban areas, the situation is a bit better with % of the population living below the poverty line.

Poverty Estimation. Net annual income (csv, KB) Net annual income (equivalised) before housing costs (csv, KB) Net annual income (equivalised) after housing costs (csv, KB) Financial year ending Download Small area income estimates for middle layer super output areas, England and Wales: Financial year ending in xls format xls ( MB).

Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data ROBERT E. FAY III and ROGER A. HERRIOT* An adaptation of the James-Stein estimator is applied to sample estimates of income for small places (i.e., population less than 1,) from the Census of Population and Housing.

The adaptation. Estimation for small domains, often de ned by geographic and demographic characteristics, is known as small area estimation.

A common approach to small area estimation is to derive predictors under a speci ed mixed model for the direct estimators. A procedure of this type is developed for small areas de ned by the cells of a two-way table.

Estimation of Poverty Measures in Small Areas Author: Isabel Molina Departamento de Estadística, Universidad Carlos III de Madrid J.N.K. Rao School of Mathematics and Statistics, Carleton University Created Date: 2/11/ PM. The Small Area Income and Poverty Estimates (SAIPE) program produces single-year estimates of median household income and poverty for all counties and states and poverty and population for all Title I-eligible school by: 2.

Estimating Population Size. Background. Population genetics is the study of the genetic structure of populations, the frequencies of alleles and genotypes.

A population is a local group of organisms of the same species that normally interbreed. In this procedure, the organisms in a few small areas are counted and projected to the entire. individual and household (micro) survey data and population (macro) census data with the objective of estimating welfare indicators for speci c geographic area as small as village or hamlet.

Examples I Estimate income distribution at domain level I Estimate poverty and inequality indicators 2/ Population density varies depending upon the size of families, the nature of dwellings, the amount of non-residential area within settlements, and cultural differences.

Anthropologists and archaeologists have made an important effort to produce reliable methods for estimating population sizes from residential areas (Brown ).

the sampled data. Unfortunately, sampling from all areas can be expensive in resources and time. A more practical approach is to select a subset of areas where the survey is conducted; estimates for all areas are then produced using the sample and some additional auxiliary information which must be available for all small areas (S arndal et al.

If a nation's GNI is small, but a small percentage of its population receives a large percentage of that income A. it may be a good market for high-priced industrial products.

it may be a good market for high-volume, high-priced consumer products. This approach is then applied to the estimation of small area HBAI rates at the small area level in Wales in The paper discusses the results of this approach, contrasts them with contemporary ‘official’ income deprivation measures for the same areas and describes a range of ways to assess the robustness of the results.

Small Area Estimation: An Appraisal M. Ghosh and J. Rao Abstract. Small area estimation is becoming important in survey sam-pling due to a growing demand for reliable small area statistics from both public and private sectors.

It is now widely recognized that direct survey estimates for small areas are likely to yield unacceptably large. Middle income residents typically occupy to sq. ft. homes with moderate sized lawns.

Higher income residents occupy homes larger than sq. ft. with usually larger lots. With respect to water use, the greatest impact of income level is probably the extent and nature of, and investment in, the landscaping of the lot.A technique called sampling is sometimes used to estimate population size.

In this procedure, the organisms in a few small areas are counted and projected to the entire area. For instance, if a biologist counts 10 squirrels living in a square foot area, she could predict that there are squirrels living in a square foot area. 2.Using SOI’s national sample, let s denote the sample of tax returns drawn from the population of tax returns, s d ⊂ s the part of the sample in domain d, and w k the sampling weight for the k-th sampled tax return, k ∈ sampling weight w k is the inverse of the inclusion probability, adjusted for achieved population and sample sizes.

As described in Section 1, all formulas concern.