Smeeding et al (1985b:54) note that the proportionate reduction in the head-count is 'an important dimension of inter-country comparisons of poverty.'

measures of poverty reduction using head-counts with the measures using poverty gaps. Do the two measures rank countries in the same order? Are they equally robust to the choice of poverty line (and also to the choice of equivalence scale)? If both questions are answered in the affirmative, we may conclude that although the poverty gap approach is superior in principle, little information is lost for practical purposes of inter-country comparison by using the simpler head-count approach. If, however, the answers are negative we may conclude that the extra information contained in the poverty gap measures is of operational significance.

The relevance of poverty reduction as an indicator of the effectiveness of a transfer system depends on an implicit assumption that pre-transfer incomes are independent of transfers. In discussing this assumption, O'Higgins et al (1985:6) argue:

Plainly, this is not the case, particularly when some of the government programs (eg: pensions) have existed for so long that individuals have taken them into account when planning and anticipating their future income needs.

This point can be illustrated in a hypothetical example of countries A and B which start off with identical transfer systems and identical pre- and post­ transfer poverty rates of 20% and 10%. Suppose country B expands its state welfare payments to a hitherto neglected group, the aged. Suppose furthermore, that people nearing retirement respond to this policy change by abandoning their private pension and investment plans so that when they reach retirement their market income is lower by the exact amount of the new transfers which they receive from the state. We will then observe that the pre-transfer poverty rate in country B is now, say, 25% whilst the post-transfer poverty rate is still 10%. Measured poverty reduction in country A is still 50% (ie 100% x 10/20), but in country B it has risen to 60%

(ie 100% x 15/25), although post-transfer incomes are still identical.

In this hypothetical example substitution between market and state provision makes the poverty reduction measure misleading. How important is this in practice? One way of attempting to answer this question is to compare poverty reduction measures with both pre-transfer and post­ transfer poverty rates. If countries with high poverty reduction also have high pre-transfer poverty, there is some evidence that substitution does occur between market and state provision. If the countries with the highest poverty reduction do not have the lowest post-transfer poverty rates, we

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may conclude that poverty reduction measures are not a good indicator of the overall effectiveness of a transfer system in eliminating poverty. In other words, the post-transfer poverty rate is an alternative indicator of effectiveness which needs to be compared with the poverty reduction measure before we can claim that one country is unambiguously more effective than another in reducing poverty.

There are two further questions concerning the effectiveness of poverty reduction which are addressed in this chapter. First, how is poverty reduction distributed by demographic status? While the aggregate poverty rate and poverty gap measures give an overview of the effectiveness of these systems, they do not tell us whether the outcomes are uniformly spread across the population, or concentrated in a few areas. A recent OECD (1988:6) survey of social security programs noted that poverty amongst the aged has declined dramatically in the OECD countries in the period since 1945:

The available evidence indicates that the relative income position of the elderly has improved significantly in most countries; in some countries their average level of economic welfare equals or even slightly exceeds that of the non-elderly population.

The survey goes on to point out that among the OECD countries a number of new groups requiring income Support have emerged over the past decade (ieg: sole parents, the young and long-term unemployed). Unlike the aged, these groups do not attract the same level of popular support and have increasingly come to dominate the poor population (OECD,1988:6):

In those OECD countries which have measures of poverty or low income, the general trend in recent years has been of a static or declining number of elderly poor, with the non-elderly increasingly to be found in the lower parts of the income distribution.

In looking at the disaggregated measures, the study considers the effectiveness of these transfer systems in alleviating poverty across a range of groups. Poverty rates are reported for family types as a proportion of each family type and as a proportion of the poor population. Poverty gaps are reported as a proportion of the poverty line for each family type. The section also compares the resources devoted to each group with their pre-transfer poverty rates and gaps.

Second, to what extent is the poverty reduction of social security transfers offset by taxation? This question has been largely ignored in previous studies which present post-tax (ie disposable income) head-counts or gaps without indicating the extent to which the taxation system may reverse the gains made by the social security system.

report poverty rates and poverty gaps for: the range of poverty lines (Z*), both equivalence scales, seven family types and for the three stages of the income formation process. The complete set of results are available in Appendix B. Only the key results pertinent to the arguments in the chapter are reported here. Appendix G discusses the statistical significance of the empirical results reported in this study.

Where possible, the results obtained by other researchers using the LIS data will be noted and compared with the results in this study. A large part of the LIS research currently exists in the form of working papers. Appendix F reproduces the findings relevant to this study which have been draw n from the LIS Working Paper series and other published work. It is important to note however, that much of the analysis presented in this study (particularly in the ensuing chapters) covers new ground using the LIS data and comparable findings do not exist. Moreover, the results here have been obtained from the most recent version of the data (September,1989) which has removed certain anomalies (eg: coding errors) from the data. Some of these errors, especially those which affected the income observations, are reflected in existing publications and will contribute to some of the differences between this and other research.

4.2. Aggregate poverty measures: head-counts.

Following the methodology set out in Section 3.3, estimates of pre- and post­ transfer poverty rates have been made by observing the number of families whose pre- and post- transfer incomes are below their respective poverty lines. The post-transfer head-count measure is the most frequently cited statistic in the poverty literature. Despite its well docum ented flaws (Sen,1979; Foster,1984; Atkinson,1989b), this measure remains a vital statistic for politicians, policy analysts and social welfare lobbies seeking to convey a readily understood 'picture' of the level of poverty in the community.

In the context of com parative research the head-count holds similar attractions, even though LIS researchers have shown that poverty estimates and rankings are extremely sensitive to small variations in the poverty line and equivalence scales (Buhmann et al,1988).

Despite the problems w ith the head-count measure, these estimates have been made for the LIS data for two main reasons. First, following the Hill and Bramley model, post-transfer head-counts do represent an immediate

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outcome of the transfer process. If we concede that poverty alleviation is an aim common to the income transfer systems of the LIS countries then an estimate of the number of families or individuals who remain in poverty post-transfer is an inescapable requirement of the study, irrespective of the methodological flaws associated with head-counts.

Second, these estimates can be used as a standpoint to compare other measures used in this study in order to draw conclusions about the most appropriate methods for cross-national comparisons of poverty.

In this section I present post-transfer head-count estimates using the Fuchs' median income approach, but do so with a strong reminder that apart from extreme cases - eg: "there is less poverty in Sweden than in the US" - these head-count rankings need to be backed up by evidence from other measures such as the poverty gap, before any definite conclusions can be drawn about the comparative success of the income transfer systems of the LIS countries in reducing poverty.

Tables 4.1 to 4.3 show the estimates of pre- and post- transfer poverty rates for families in the LIS countries, using both the OECD and Whiteford equivalence scales. The tables also show the proportionate reduction in poverty rates pre- and post- transfer. These findings, in terms of rank orders, are very close to those of Buhmann et al (1988) and Smeeding et al (1989); and generally, are within two percentage points of the head-count estimates in both these studies for similar equivalence scales.25

4.2.1. Comparing post-transfer poverty rates: sensitivity to the choice of equivalence scale and poverty line.

The post-transfer rankings of countries by poverty rates are derived from Tables 4.1-4.3. These rankings are identical for the 40% poverty interval whether we use the OECD or the Whiteford equivalence scales. Identical rankings are indicated by a rank correlation coefficient (r) of 1, see Table 4.4. At the 50% poverty interval the rankings are almost identical (r=0.96) except that Norway and Sweden swap places. At the 60% poverty interval, however, there are significant differences between the rankings depending on which equivalence scale we use (r=0.88). Norway's ranking is particularly

25 Cf. Appendix Tables F.l and F.3. The equivalence scale closest to those used here, is the PROG scale