Item response theory and the measurement of deprivation: evidence from Luxembourg data

Szeles, Monica Răileanu; Fusco, Alessio

doi:10.1007/s11135-011-9607-x

Cited by 35 publications

(25 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…> 0.4 ) used by (Guio et al 2016(Guio et al , 2012Nandy and Pomati 2015). The emerging practice of analysing reliability in poverty research certainly should continue and be encouraged in poverty research (Saunders and Naidoo 2009;Fusco and Dickens 2008;Nolan and Whelan 2010;Szeles and Fusco 2013). However, it is important to stress that although reliability increases the likelihood of correct classification, there might be other reasons for using weights, such as placing emphasis on the most extreme forms of poverty and making comparisons across years.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study

Nájera

2018

Soc Indic Res

120

View full text Add to dashboard Cite

In poverty measurement, differential weighting aims to take into account the unequal importance of the diverse dimensions and aspects of poverty and to add valuable information that improves the classification of the poor and the not-poor. This practice, however, is in contention with both classical test theory and modern measurement theories, which state that high reliability is a necessary condition for consistent population classification, while differential weighting is not so. The literature needs a clear numerical illustration of the relationship between high/low reliability and good/poor population classification to dissolve this tension and assist applied researchers in the assessment of multidimensional poverty indexes, using different reliability statistics. This paper uses a Monte Carlo study based on factor mixture models to draw up a series of uni-and multidimensional poverty measures with different reliabilities and predefined groups. The article shows that low reliability results in a high proportion of the poor group erroneously classified as part of the not poor group. Therefore, reliability inspections should be a systematic practice in poverty measurement. The article provides guidelines for interpreting the effects of unreliability upon adequate population classification and suggest that the classification error of current unreliable multidimensional indexes is above 10%.

show abstract

Section: Conclusion and Discussionmentioning

confidence: 99%

Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study

Nájera

2018

Soc Indic Res

120

View full text Add to dashboard Cite

show abstract

“…IRT is often used for the selection of questions in educational assessment and for psychological testing. It has also been used for developing measures of poverty (e.g., Cappellari and Jenkins, 2007;Fusco and Dickes, 2008;Martini and Vanin, 2010;Raileanu Szeles and Fusco, 2013). …”

Section: Reliabilitymentioning

confidence: 99%

Improving the measurement of material deprivation at the European Union level

Guio

Marlier

Gordon

et al. 2016

Journal of European Social Policy

103

115

View full text Add to dashboard Cite

In June 2010, European Union (EU) Heads of State and Government adopted a social inclusion target as part of the new ‘Europe 2020 Strategy’: to lift at least 20 million people in the EU from the risk of poverty and exclusion by 2020. One of the three indicators used to monitor progress towards this target is the EU indicator of severe material deprivation (MD). A main limitation of this indicator is the weak reliability of some of the items it is based on. For this reason, a thematic module on MD was included in the 2009 wave of the EU Statistics on Income and Living Conditions (EU-SILC) survey. This article assesses the 2009 EU-SILC MD data and proposes an analytical framework for developing robust EU MD indicators. It carries out a systematic item by item analysis at both EU and country levels to identify the MD items which satisfactorily meet suitability, validity, reliability and additivity criteria across the EU. This approach has resulted in a proposed 13-item MD indicator covering some key aspects of living conditions which are customary across the whole EU covering a broad range of basic (food, clothes, shoes, etc.) as well as social (Internet, regular leisure activities, etc.) necessities.

show abstract

“…Gailly and Hausman (1984) or Dickes et al (1984)) contemporaneously to the oft-cited work of Townsend (1979). Recently, Fusco and Dickes (2008) and Raileanu Szeles and Fusco (2013) explored the use of the Item Response Theory framework in the measurement of deprivation and Hildebrand et al (forthcoming) focused on the measurement and explanation of deprivation differentials between Portuguese immigrants and natives. Elements of the impact of income on various deprivation measures can be found in these papers.…”

Section: Income and Housing Deprivationmentioning

confidence: 99%

“…average income across years for each observation) in the pooled OLS regression. 4 For example, Raileanu Szeles and Fusco (2013) analysed the determinants of a 'global'…”

Section: Income and Housing Deprivationmentioning

confidence: 99%

Item response theory and the measurement of deprivation: evidence from Luxembourg data

Cited by 35 publications

References 24 publications

Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study

Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study

Improving the measurement of material deprivation at the European Union level

The relationship between income and housing deprivation: A longitudinal analysis

Contact Info

Product

Resources

About