Understanding material deprivation: A comparative European analysis

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Abstract

In this paper, taking advantage of the inclusion of a special module on material deprivation in EU-SILC 2009, we provide a comparative analysis of patterns of deprivation. Our analysis identifies six relatively distinct dimensions of deprivation with generally satisfactory overall levels of reliability and mean levels of reliability across countries. Multi-level analysis based on 28 European countries reveals systematic variation in the importance of within and between country variation for a range of deprivation dimensions. The basic deprivation dimension is the sole dimension to display a graduated pattern of variation across countries. It also reveals the highest correlations with national and household income, the remaining deprivation dimensions and economic stress. It comes closest to capturing an underlying dimension of generalized deprivation that can provide the basis for a comparative European analysis of exclusion from customary standards of living. A multilevel analysis revealed that a range of household characteristics and household reference person socio-economic factors were related to basic deprivation and controlling for contextual differences in such factors allowed us to account for substantial proportions of both within and between country variance. The addition of macro-economic factors relating to average levels of disposable income and income inequality contributed relatively little further in the way of explanatory power. Further analysis revealed the existence of a set of significant interactions between micro socio-economic attributes and country level gross national disposable income per capita. The impact of socio-economic differentiation was significantly greater where average income levels were lower. Or, in other words, the impact of the latter was greater for more disadvantaged socio-economic groups. Our analysis supports the suggestion that an emphasis on the primary role of income inequality to the neglect of differences in absolute levels of income may be misleading in important respects.

Introduction

Research on poverty in rich countries relies primarily on household income to capture living standards and distinguish those in poverty, and this is also true of official poverty measurement. However, awareness has been increasing of the limitations of income and increased attention has been focused on the role which non-monetary measures of deprivation can play in improving our measurement and understanding of poverty.1 This is true when one focuses on an individual country, but even more so when the perspective is comparative (Guio, 2009, Nolan and Whelan, 2011). Widely used income poverty thresholds in the more affluent member states are higher than the average income in the poorest member states, and those below them have higher standards of living than the well-off in the poorest countries. The strikingly different picture produced by these ‘at risk of poverty’ (ARP) indicators compared with average GDP per head and comparable measures, and unease with the current EU practice of keeping entirely distinct concerns about inequality of living standards across versus within countries, helps to motivate interest in moving beyond relying entirely on relative income (Brandolini, 2007, Fahey, 2007).

The limitations of the ARP approach have resulted in the development of the EU 2020 Poverty Target which combines information on income poverty, a material deprivation index and a measure of work intensity (EC, 2011). However, as Nolan and Whelan (2007) stress, the superiority of any particular multidimensional measurement approach cannot be read of the multidimensional nature of the concepts. Instead it is necessary to demonstrate empirically the added value of dimensions other than income in relation to both the underlying theoretical constructs which are the focus of our attention and the particular substantive issues that are addressed.

Analysis of the factors contributing to within and between country differences in the EU has been greatly handicapped by the limited quality of the available data. The annual round of the European Union Survey of Income and Living Conditions (EU-SILC), which has been the main data source since 2004, is distinctly inferior in relation to the quality of deprivation data available in its predecessor the European Community Household Panel (ECHP). In this paper we will seek to show that the absence of high quality data has limited earlier efforts to understand cross-national variation in material deprivation.

Kenworthy, Epstein, and Duerr (2011, pp. 32–33), having noted the burgeoning interest in material deprivation, observe that most existing research has been aimed at gauging the extent of deprivation and the degree to which it correlates with income and that explanatory level analysis has mainly sought to understand why certain households are materially deprived. They proceed to pose the question of the extent to which economic growth and generosity of social policy and their implications for income levels and income inequality can account for cross-national variation in material deprivation. Having, established that in most countries economic growth has led to rising incomes for low end households, they consider the question of whether growth has been similarly helpful in reducing material deprivation. Employing a 7-item material deprivation index developed by Boarini and Mira d’Ercole (2006) they examine the relationship between material deprivation and GDP per capita and social policy generosity for fifteen countries comprising a number of the more affluent European countries together with Australia and the US.2 They found no association to speak of between per capita GDP and material deprivation. However, they observed a significant relationship between social policy generosity, as captured by government social expenditure as a percentage of GDP (GSP) and material deprivation.

Given the counterintuitive nature of the relationship between GDP and material deprivation observed by Kenworthy et al. (2011), we consider it is well worthwhile exploring whether this relationship is robust to changes in the specification of the material deprivation variable and consideration of a wider range of European countries. This is particularly true because of concerns we have regarding the 7-item measure of Boarini and Mira d’Ercole (2006). Two of the seven items relate to overcrowding and poor environmental conditions. Such items have been found to correlate fairly modestly with items capturing deprivation relating to food, clothing and ability to participate in social life (Fusco, Guio, & Marlier, 2010). Furthermore, they are weakly associated with income and other measures of command over economic resources and tend to be significantly influenced by factors such as urban-rural location (Whelan et al., 2001, Whelan and Maître, 2007). In addition, a further three items relate to arrears in payment of bills and in mortgage and difficulty in making ends meet. While the limited number of deprivation items available in EU-SILC has led researchers to include such items in indices of material deprivation, they seem more usefully thought of as measures of subjective economic stress. They seem more fruitfully thought of as consequences of material deprivation rather than as indicators of deprivation as such. The argument for making this distinction is reinforced by the evidence that the relationship between such stress and material deprivation varies systematically across country with the magnitude of the association being stronger in more affluent countries. As a consequence of such variation, the inclusion of items relating to economic stress will attenuate any underlying relationship between measures such as GDP and household deprivation (Whelan and Maître, 2009, Whelan and Maître, 2012).

Fortunately the inclusion of a special module on material deprivation in the 2009 wave EU-SILC provides us with a substantially improved date base with which to explore such issues. Our purpose in this paper is not to provide a comprehensive analysis of multidimensional material deprivation in the EU but to use the 2009 special module data to construct an index appropriate to exploring the sources of within and between country deprivation. The criteria we apply in developing such an index are as follows.

  • In seeking to overcome the limitations of measures based solely on relative income, we wish to construct a deprivation measure that is consistent with an understanding of poverty as involving households’ inability to participate in a minimally acceptable way of life owing to lack of resources (Citro and Michael, 1995, Townsend, 1979). Our focus will be on enforced and generalized deprivation, rather than on deprivation that is attributable to factors other than lack of resources, or deprivation that is enforced but only for specific areas of life. This conception suggests that the former should be more closely associated with current income and indeed other variables capturing command over resources than the latter. It should also be positively associated with other dimensions of deprivation. In addition we anticipate that such measures should display stronger levels of association with factors such as economic stress than more specific forms of deprivation (Nolan & Whelan, 1996, p. 223).

  • The index should display a high level of overall reliability and relative uniformity in such reliability across country.

  • It should also display significant variation across countries that is, in principle, explicable in terms of corresponding variation in household and macro-economic conditions.

In what follows we shall seek to demonstrate that the deprivation items in the EU-SILC 2009 special module provide the basis for constructing such a measure.

As Kenworthy et al. (2011) observe, previous work has focused predominantly on the impact of household conditions and needs to be supplemented by consideration of the role of macro-economic conditions. The 2009 EU-SILC data set has the advantage that it allows us to undertake a formal multilevel analysis of the contributions of macro and micro factors and the manner in which they interact. Problems relating to multicollinearity ensure that it is not possible for a cross-sectional analysis with only 28 macro units to provide the basic for a causal analysis of a set of highly correlated macro variables. In the analysis that follows we focus on gross income per capita (GNDH) and GINI.3 GNDH is our preferred measure of absolute living standards but, as our analysis will reveal, given that it is almost perfectly correlated with the GDP measure substituting the latter would have little effect on our conclusions. Similarly, further analysis also revealed that adding measures such as government social expenditure as a percentage of GDP (GSP) to GINI provided little in the way of additional explanatory power. Focusing on GNDH and GINI has the advantage of allowing us to connect to a wider sociological literature relating to the impact of absolute income differences and income inequality (Wagstaff and Doorslaer, 2000, Wilkinson and Pickett, 2009a, Wilkinson and Pickett, 2009b).

Our analysis will proceed as follows:

  • Drawing on a relevant set of items relating to enforced deprivation, we identify a set of deprivation dimensions.

  • We then proceed to assess the reliability of these dimensions and the extent of variation in such reliability across countries.

  • We then consider the pattern of interrelations between the deprivation dimensions.

  • We go on to consider the relationship between each of the dimensions of deprivation and household income and economic stress.

  • We proceed to break down levels of deprivation by country and establish the partitioning of variance within and between countries for each dimension.

  • Taking into account the findings from the foregoing analysis, we opt for a measure of material deprivation that fulfils the conditions set out earlier for a dependent variable appropriate for utilisation in a multilevel analysis of the role of micro and macro factors.

  • Finally employing multilevel models we analyse the relationship between our preferred measure of material deprivation and a range of household characteristics and macro-economic variables and the manner in which micro and macro-economic variables interact.

Section snippets

Data

In this paper we make use of the 2009 wave of EU-SILC which includes a special module on material deprivation. The availability of this module allows us to explore the dimensionality of deprivation. Portugal has been excluded from our analysis because of missing values on key variables. Our analysis therefore covers 28 countries comprising 26 European Member States together with Norway and Iceland. The total number of households in our analysis is 205,226.

Our analysis of the EU-SILC data is

Dimensions of deprivation

The purpose of the analysis that follows is not to provide a comprehensive analysis of multidimensional deprivation in the EU but rather to identify an index of deprivation that fulfils the requirements for a dependent variable appropriate for use in a cross-national analysis of material deprivation that seeks to overcome some of the limitations of a sole reliance on income. In Table 1 we set out the results of an exploratory factory analysis. Our analysis was influenced by earlier studies of

Deprivation, household income and economic stress

At this point we consider the relation between the dimensions of deprivation and both household income and economic stress. If our interest is in capturing exclusion from customary pattern of living due to lack of resources, what we require is a measure of deprivation that is significantly related to but by no means identical to income. In column two of Table 4 we show the correlation between the log of household equivalized income and each of the deprivation dimensions.11

Deprivation levels by country

In Table 5 for each deprivation dimension we show the intra-class correlation coefficients (ICC) for clustering by countries. The ICC captures the between cluster variance as a proportion of the total variance. It can also be interpreted as the expected correlation between two randomly drawn units from the same cluster (Snijders & Bosker, 1999).

Focusing first on the findings relating to between countries differences, we find that between clusters variation is extremely modest for neighbourhood

Cross-national variation in basic deprivation

Before proceeding to multivariate analysis of the micro and macro factors associated with basic deprivation we provided a description of variation across countries for this measure and extend our analysis to take into account to the degree of association between such deprivation and a range of macro-economic factors. In Table 6 we break down basic deprivation levels by country, and scores are ordered by GNDH. The scores are generally in line with GNDH levels but with a tendency for Scandinavian

Conclusions

In this paper we have sought to take advantage of the special module on material deprivation in EU-SILC 2009 in order to enhance our understanding of the role of micro and macro factors in accounting for variation in material deprivation within and between European countries. Our analysis allowed us to identify a basic deprivation dimension that fulfils a range of conditions required for a dependent variable appropriate for inclusion in such a comparative analysis. These included a satisfactory

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