Small area estimation for the tobaccouse supplement to the current population survey. Topics in small area estimation with applications to the. The sample size in the domain of interest is too small to use a standard estimator. Small area estimation techniques combine multiple data sources to capitalize on each data sources strengths. Pdf small area estimation of income using spatiotemporal. Popular techniques for small area estimation use implicit or explicit statistical models to indirectly estimate the small area parameters of interest.
Small area estimation eprints soton university of southampton. Small area estimation sae is an area of active growth and research in survey statistics that emerged since the 1990s. The key to small area estimation is shrinkage of direct estimates to ward some regression estimates. Methods for indirect small area estimation parameters of interest. The idea is to relate similar small areas via supplementary data e.
Indirect est area level model unitlevel model eb method binary data small area estimation isabel molina and j. It is always possible to modify the survey sample size allocation so as to. The research field is called small area estimation sae. Small area demography refers to demographic applications and analyses executed at local and regional scales smith and morrison, 2005. Some of the small area methodology research involves nding more accurate methods for incorporating the sample design into modelling. A comparison of smallarea estimation techniques to. Sae addresses the problem of obtaining reasonable estimates for domains where small sample sizes do. Small area estimation is of particular interest for the economics in transition in central and eastern european countries and the former soviet union countries. A commonly acceptable description of synthetic estimator due to gonzalez 1973 is as follows. Small area estimation of school district child population and. Methodology for the modelbased small area estimates of. On small area estimation a dissertation submitted to the faculty of the graduate school of the university of minnesota by abhishek nandy in partial fulfillment of the requirements for the degree of doctor of philosophy snigdhansu chatterjee, adviser october 2016. The programme for the international assessment of adult competencies piaac sample is. We focus here on poverty estimates of schoolaged 517 children for.
Selected sae methods were compared for estimating a variety of forest attributes for small areas using ground data and light detection and ranging. Uses a basic area level linear model to illustrate the methods. Small area estimation sae is a topic of great importance due to the growing. Buy this book isbn 9781846281952 digitally watermarked, drmfree included format. If a survey has been carried out for the population as a whole for example, a. Small area estimation is becoming important in survey sam. Small area estimation of poverty under structural change. Small area estimation sae has become a dynamic field of research over the last. A typical income consumption or living standards survey collects detailed information that can be used for estimation of our statistic of interest.
A methodological approach to small area estimation for the. Different direct small area estimation techniques are described in section 4. Small area estimation sae of survey data down to small area level has become an increasingly widespread activity as scholars and policymakers have sought to gain ever more detailed spatial information to better target interventions or resources and to evaluate local policy impacts. Small area estimation is important in survey analysis when domain subpopulation sample sizes are too small to provide adequate precision for direct domain estimators. This paper presents a new method which allows for the estimation of uptodate small area poverty maps when only a. They are typically estimated based on a consumption survey reporting on pov erty and a census providing the spatial disaggregation. Small area poverty maps allow for the design of policies based on spatial differences in welfare. Mixed models with unit level auxiliary data have been used for small area estimation by a good number of authors.
Written by two experts in the field, small area estimation, second edition provides a comprehensive and uptodate account of the methods and theory of small area estimation sae, particularly indirect estimation based on explicit small area linking models. On small area estimation a dissertation submitted to the faculty of the graduate school of the university of minnesota by abhishek nandy in partial fulfillment of the. Small area estimation sae is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and auxiliary information is available. For surveys of governments, small area refers to their state by function or itemcode. Pushpal k mukhopadhyay and allen mcdowell, sas institute inc. This followed greater demands for detailed estimates from data users accompanied with greater availability of computing power. Download applying bivariate binomiallogit normal models to small area estimation pdf small area income and poverty estimates program estimates poverty for various age groups for states, counties, and school districts of the u. Small area estimation, part 1 jerzy wieczorek small area estimation research group, csrm 11720 outline basic approach for continuous area level data the estimates we need and how to get them sas example by hand with proc regand datasteps sas example automated with proc mixed further resources plan for. Missing data and smallarea estimation modern analytical. An overview aapor 2014 25 28 referencesii datta, g. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation. Matching data from the 2011 health survey for england and the 2011 census in england and wales, we proposed a new global optimisation go survey calibration. Small area estimation of nonmonetary poverty with geospatial data.
Many of the techniques used in small area estimation combine data from multiple sources. Estimates for small areas are referred to as small area statistics. Small area estimation methods, applications and practical. Coats building, tunneys pasture, ottawa, ontario, k1a 0t6, canada abstract small area estimation sae was first studied at statistics canada in the seventies. But small area estimation is one area where these groups of statistician have a consensus on the need for modeldependent estimation. Spatial disaggregation and smallarea estimation methods. Computer applications for small area estimation, part 1. Using small area estimation techniques, we developed a populationwide dataset of comorbidity of cardiovascular disease, diabetes, and obesity for england at the small area level. In jsm proceedings, survey research methods section. Jan 09, 2003 an accessible introduction to indirect estimation methods, both traditional and modelbased.
Small area estimation is witnessing phenomenal growth in recent years. Traditionally, small area is a small geographic area within a larger geographic area or a small demographic group within a larger demographic group. Evaluations and improvements in small area estimation. Small area estimation sae is concerned with the development of statistical procedures for producing efficient precise estimates. On small area estimation under informative sampling. Small area estimation curve carleton university research.
Theory and practice michael hidiroglou statistical innovation and research division, statistics canada, 16 th floor section d, r. This method can be used to estimate parameters of sub. Small area estimation sae methods were developed to address the need for estimates of characteristics for geographic areas or other domains population subgroups, for example that cannot be obtained directly from survey or administrative data. Introduction small area estimation sae is an important concept in survey sampling especially for indirect parameter estimation of relatively small samples. The r package sae is mainly designed for modelbased small area estimation. Read download small area estimation pdf pdf download. Rao school of mathematics and statistics, carleton university. The r package sae implements small area estimation methods under the following arealevel models. Small area estimates have been produced using administrative. The package also includes small area estimation methods based on the basic unit level model called. Then a summary sketch of overall methodologies is provided in section 3. Have options of using available small area estimates as an additional component to.
Pdf small area estimation under spatial sar model jan. Small area estimation sae is a statistical technique to. Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. Introduction to small area estimation small area estimation in r application to mexican income data conclusion r packages for sae other packages i bayessae for area level models in bayesian context i saerobust for robust area level models i saery and sae2 for area level models with time e ects i sae for a wide variety of sae methods including area level and unitlevel models for the mean as. Small area estimation from multiple overimputation james honaker y eric plutzer z april 1, 2016 abstract researchers of state and local politics often want to uncover relationships between locallevel attitudes, and local policy implementation. Classical small area estimation techniques assume either that all the areas are represented in the sample or that the selection of the areas to the sample is noninformative. Small area estimation of nonmonetary poverty with geospatial. On small area estimation under informative sampling danny pfeffermann1 and michael sverchkov2 1hebrew university and university of southampton, 2b u r ea of l b s ti s c nd u t h l gy associates, inc.
A comparison of smallarea estimation techniques to estimate. In particular, the mixed model involving random area speci c e ects that account for between area variation. Pdf small area estimation sae was first studied at statistics canada in the seventies. The small area estimation sae methods included in the r package sae have applications in many different. We can then consider and contrast solutions from that literature, particularly the widely used statistical literature of multiple imputation. An application of jamesstein procedure to census data. Section 2 highlights why small area estimation techniques are necessary in the current world and what are the problems in small area estimation. Studying use of irs income tax data pdf small area income and poverty estimates saipe program provides estimates for selected income and poverty statistics for states, counties, and school districts. Smallarea estimation of poverty and malnutrition in cambodia.
The vastness of the area makes it near impossible to cover each and every emerging topic. It assumes, that the area parameter for domain d at current time t is estimated borrowing strength from the t time instants and from the d domains. The local level is the geographical level at which data are requested with a view to planning subregional policies or evaluating the results of policy. Spatial disaggregation and smallarea estimation methods for. Introduction to small area estimation techniques asian. Small area estimates, themselves, will provide more disclosure avoidance than the original estimates. It can also be used to denote a small demographic group, such as a small group with certain social economic status or a sexraceethnicity group.
Pdf ebooks can be used on all reading devices immediate ebook. When the areas are sampled with unequal selection probabilities that are related to the values of the response variable, the classical. Small area estimation is any of several statistical techniques involving estimation of parameters in small subpopulations of interest included in a larger survey. An unbiased estimate is obtained from a sample survey for a larger area. In the 1990s these countries have moved away from centralized decision making. For a comprehensive account of sae techniques, seerao2003. Small area estimation of school district child population. One way to analyze this information is by utilizing small area analysis. It is also referred to as small area estimation or small domain analysis. Producing estimates for small areas with an adequate level of precision often requires indirect estimators that use auxiliary data or values of the variable of interest.
Download small area estimation of school district child population and poverty. Small area estimation in r with application to mexican. The modelbased approach to small area estimation offers several advantages including. This report presents methods for estimating agricultural and rural statistics at the local level small area estimation sae. The client will always require more than is specified at the design stage fuller 1999. Applying binomialnormal models to small area estimation. This paper is a product of the poverty and equity global practice and a background report for the 2021. Pushpal k mukhopadhyay and allen mcdowell, sas institute. Small area estimation is a mathematical and statistical method that models data collected from one or more data sources, to produce estimates, for example of poverty, that are more accurate at small area level than using only data collected from each small area. Small area estimation using esds government surveys.
Small area estimation a perspective and some applications. Small area estimation under spatial sar model econstor. In estimating means, totals, and other parameters for small areas of a. While no universally accepted definition exists for what constitutes a small area for population estimation and projection purposes, it commonly involves administrative units below the national and state level. For this purpose a region can be split into subsets or domains.
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