000 | 04643nam a22005895i 4500 | ||
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001 | 978-981-19-3639-5 | ||
003 | DE-He213 | ||
005 | 20240508090327.0 | ||
007 | cr nn 008mamaa | ||
008 | 220702s2022 si | s |||| 0|eng d | ||
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_a9789811936395 _9978-981-19-3639-5 |
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024 | 7 |
_a10.1007/978-981-19-3639-5 _2doi |
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050 | 4 | _aQA276-280 | |
072 | 7 |
_aPBT _2bicssc |
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_aMAT029000 _2bisacsh |
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082 | 0 | 4 |
_a519.5 _223 |
100 | 1 |
_aDaniels, Reza Che. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aHow Data Quality Affects our Understanding of the Earnings Distribution _h[electronic resource] / _cby Reza Che Daniels. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2022. |
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300 |
_aXX, 114 p. 11 illus., 5 illus. in color. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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505 | 0 | _aIntroduction -- A Framework for Investigating Micro Data Quality, with Application to South African Labour Market Household Surveys -- Questionnaire Design and Response Propensities for Labour Income Micro Data -- Univariate Multiple Imputation for Coarse Employee Income Data -- Conclusion: How Data Quality Affects our Understanding of the Earnings Distribution. | |
506 | 0 | _aOpen Access | |
520 | _aThis open access book demonstrates how data quality issues affect all surveys and proposes methods that can be utilised to deal with the observable components of survey error in a statistically sound manner. This book begins by profiling the post-Apartheid period in South Africa's history when the sampling frame and survey methodology for household surveys was undergoing periodic changes due to the changing geopolitical landscape in the country. This book profiles how different components of error had disproportionate magnitudes in different survey years, including coverage error, sampling error, nonresponse error, measurement error, processing error and adjustment error. The parameters of interest concern the earnings distribution, but despite this outcome of interest, the discussion is generalizable to any question in a random sample survey of households or firms. This book then investigates questionnaire design and item nonresponse by building a response propensity modelfor the employee income question in two South African labour market surveys: the October Household Survey (OHS, 1997-1999) and the Labour Force Survey (LFS, 2000-2003). This time period isolates a period of changing questionnaire design for the income question. Finally, this book is concerned with how to employee income data with a mixture of continuous data, bounded response data and nonresponse. A variable with this mixture of data types is called coarse data. Because the income question consists of two parts -- an initial, exact income question and a bounded income follow-up question -- the resulting statistical distribution of employee income is both continuous and discrete. The book shows researchers how to appropriately deal with coarse income data using multiple imputation. The take-home message from this book is that researchers have a responsibility to treat data quality concerns in a statistically sound manner, rather than making adjustments to public-use data in arbitrary ways, often underpinned by undefensible assumptions about an implicit unobservable loss function in the data. The demonstration of how this can be done provides a replicable concept map with applicable methods that can be utilised in any sample survey. . | ||
650 | 0 | _aStatistics . | |
650 | 0 | _aSampling (Statistics). | |
650 | 0 | _aQuantitative research. | |
650 | 0 |
_aAfrica _xEconomic conditions. |
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650 | 0 |
_aAfrica _xHistory. |
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650 | 1 | 4 | _aStatistical Theory and Methods. |
650 | 2 | 4 | _aSurvey Methodology. |
650 | 2 | 4 | _aData Analysis and Big Data. |
650 | 2 | 4 | _aMethodology of Data Collection and Processing. |
650 | 2 | 4 | _aAfrican Economics. |
650 | 2 | 4 | _aAfrican History. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811936388 |
776 | 0 | 8 |
_iPrinted edition: _z9789811936401 |
776 | 0 | 8 |
_iPrinted edition: _z9789811936418 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-19-3639-5 |
912 | _aZDB-2-SMA | ||
912 | _aZDB-2-SXMS | ||
912 | _aZDB-2-SOB | ||
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_c37759 _d37759 |