FACTOR COMPONENTS OF INEQUALITY. Cecilia García-Peñalosa and Elsa Orgiazzi GINI DISCUSSION PAPER 12 JULY 2011 GROWING INEQUALITIES IMPACTS

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1 FACTOR COMPONENTS OF INEQUALITY Cecilia García-Peñalosa and Elsa Orgiazzi GINI DISCUSSION PAPER 12 JULY 2011 GROWING INEQUALITIES IMPACTS

2 Acknowledgement This research was partly supported by the Institut d Economie Publique in Marseille (IDEP) and the Marie Curie Fellowship program at the Universidad Carlos III. We are greatly indebted to Richard Breen or the discussions that gave rise to this paper. The paper has beneited rom the comments at the Journées Louis-André Gérard- Varet 2008, as well as those by Tony Atkinson, Daniele Checchi and Marc Gurgand. July 2011 Cecilia García-Peñalosa and Elsa Orgiazzi, Amsterdam General contact: gini@uva.nl Correspondence to: Cecilia García-Peñalosa, GREQAM and CNRS. Centre de la Vieille Charité, 2 rue de la Charité, Marseille, France. cecilia.garcia-penalosa@univmed.r Bibliographic Inormation García-Peñalosa, C. and Orgiazzi, E. (2011). DFactor Components o Inequality: A Cross-Country Study. Amsterdam, AIAS, GINI Discussion Paper 12. Inormation may be quoted provided the source is stated accurately and clearly. Reproduction or own/internal use is permitted. This paper can be downloaded rom our website

3 Factor Components o Inequality A Cross-Country Study Cecilia García-Peñalosa GREQAM and CNRS Elsa Orgiazzi University o Rennes 21 July 2011 DP 12

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5 Factor Components o Inequality Table o contents 1. INTRODUCTION TRENDS IN INCOME INEQUALITY The data Inequality trends What may drive changes in inequality? INEQUALITY INDEX DECOMPOSITIONS DECOMPOSITION BY INCOME SOURCES Absolute actor contributions Relative actor contributions DECOMPOSITION BY AGE GROUP The Anglo-Saxon Economies The Continental Economies Within-group and Between-group Inequality CONCLUSIONS...31 APPENDIX I: DATA SOURCE AND DESCRIPTIVE STATISTICS...35 REFERENCES...37 APPENDIX - TABLES...41 GINI DISCUSSION PAPERS...57 INFORMATION ON THE GINI PROJECT...59 Page 5

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7 Factor Components o Inequality Abstract This paper uses data rom the Luxembourg Study to examine some o the orces that have driven changes in household income inequality over the last three decades o the 20th century. We decompose inequality or 6 countries (Canada, Germany, Norway, Sweden, the UK, and the US) into the three sources o market income: earnings, property income and income rom sel-employment. Our indings indicate that although changes in the distribution o earnings are an important aspect o recent increases in inequality, they are not the only one. In some countries the contribution o sel-employment income to inequality has been on the rise. In others, increases in inequality in capital income probably caused by tax changes- account or a substantial raction o the observed changes in the distribution o income. JEL classiication numbers: D31, D33 Key words: income inequality, actor decomposition, decomposition by population subgroups Page 7

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9 Factor Components o Inequality 1. Introduction The extent to which dierent sources o income inluence overall income inequality across households has interested economists or several decades. 1 One o the problems o this type o research is the act that because income concepts vary across national surveys, most existing studies deal with a single country. In this paper, we exploit the data collected by the Luxemburg Study in order to decompose income inequality into its actor components or six countries over a 30-year period. A number o industrial countries have experienced an increase in household income inequality in the last decades o the 20 th century. At the same time, they have also experienced an increase in earnings dispersion. 2 By decomposing inequality by actor sources we can assess whether increased earnings dispersion has been the only culprit or observed inequality trends, or whether other actors have also contributed to the changing distribution o income. Gottschalk and Smeeding (1997) ind that in a number o countries increased earnings dispersion was not accompanied by increased household income inequality, and there are indications in the literature that other actors have been important. Notably, Jenkins (1995) inds that both changes in the distribution o capital income and selemployment income contributed to the increase in income inequality in the UK in the irst hal o the 1980s. The availability o new data allows us to examine whether these trends have persisted or i they were only a temporary eature. Moreover, by comparing six economies we address the question o whether such pattern has been a more generalized phenomenon present also in other countries or simply restricted to the UK. The second aspect on which we ocus is the age composition o the population and the dierences in inequality across age groups. There are two main reasons why a decomposition by age can help us understand the orces that drive inequality changes. First, we want to understand the role o capital income inequality. High inequality in this actor can be due to two eects. One possibility is that it is the result o an unequal distribution o wealth or all age groups. Alternatively, it may be caused by lie-cycle savings, in which case the data should show that capital income inequality is mainly due to dierences across age groups and not within age groups. Moreover, i lie cycle considerations were the main cause o wealth inequality we should also observe important dierences across countries. In countries with generous public pension systems, old individuals would tend to live o state pensions rather than their own savings, and hence we would expect to observe less inequality in the distribution o capital incomes. Second, a number o papers examining the recent increase in earnings dispersion have shown that, at least in the US and the UK, greater wage dispersion has been partly the result o increased returns to expe- 1 See, amongst others, Fei et al. (1978), Fields (1979), Pyatt et al. (1980), Lerman and Yitzhaki (1985), Shorrocks (1983), Podder (1993), Jenkins (1995). 2 See Atkinson (1997), Gottschalk and Smeeding (1997), Acemoglu (2003), and Lemieux (2008). Page 9

10 Cecilia García-Peñalosa and Elsa Orgiazzi rience. 3 Our analysis can then help us understand to what extent the increase in overall earnings inequality across households is due to the act that older individuals now receive higher wages. Existing work -such as Cowell and Jenkins (1995), Jenkins (1995), and Jäntti (1997)- has ound that inequality across age groups has little explanatory power, but this could be due to the short time periods considered. Here we examine whether this result still holds over the substantially longer period that we analyse. The paper closest to our analysis is Jäntti (1997), to our knowledge the only cross-country study o actor decompositions o inequality. He uses data rom the Luxembourg Study or ive countries -Canada, the Netherlands, Sweden, United Kingdom and United States- and has two observations, one or the early and one or the late 1980s. He concludes that the increase in household income inequality that took place in Sweden, the UK and the US during the period was mainly due to an increase in labour earnings inequality. We extend the work o Jäntti in two dimensions. First, we increase the number o countries and consider a longer time period. The increase in available data is signiicant: our sample includes 6 countries, and we have at best nine observations per country, going rom 1969/1970 to This implies an substantially longer period o study, and allows us to assess to what extent the increases in inequality observed in the 1980s have continued or been reversed. Second, although Jäntti perorms decompositions both by actors and by household characteristics such as age, these decompositions are perormed separately. In contrast, we nest the decompositions by actors and by age. This allows us to examine not only whether the incomes o the young are more or less unequal than those o the old, but also which are the actors that have generated the dierences across age groups. Methodologically, we ollow a large literature that has preormed decompositions o an inequality index into a within-group and between-group component; see, or instance, Mookherjee and Shorrocks (1982), Karoly (1992), Parker (1999), Brandolini and D Alessio (2001). However, there are only a ew studies that perorm both decompositions across groups and actors. As well as Jenkins (1995) and Jäntti (1997) discussed above, this approach has been taken by Fluckiger and Silber (1995), Achdut (1996) and Drescher (1999), who ocus, respectively, on Switzerland, Israel and Denmark, all countries that are not included in our sample. However, all these papers consider either the actor decomposition or the decomposition by age (or other characteristics). In contrast, we decompose inequality using a nested approach that allows us to dierentiate the contribution o various actors to inequality within each age group. 4 Some recent work, such as Jenkins and van Kerm (2005), proposes as an alternative density unction decompositions that allow a richer analysis o distributional changes at all points o the distribution. This method has the advantage o being independent o the choice o inequality index, but does not provide sum- 3 See, or example, Gottschalk and Smeeding (1997), Machin (1996), and Machin and Van Reenen (1998). 4 See Mussard (2004) and Giammatteo (2007) or analyses o nested decompositions. Page 10

11 Factor Components o Inequality mary measures o the decomposition. Given that we ocus on several countries and years, standard decompositions o an inequality index are more suitable. Our results indicate that the stability o the share o earnings in household income in the US is remarkable when compared to the experience o other countries. The share o earnings ell sharply in the other Anglo-Saxon economies, dropping by 11 percentage points in the UK and by 12 in Canada (over the periods and , respectively). As a result, although all countries in our sample experienced an increase in earnings inequality, the contribution o this source o income to overall inequality oten remained unchanged due to a reduction in the earnings share. The share o dierent actors also luctuates over time. Consider, or example, the UK over the period : the share o earnings ell steadily, that o sel-employment income grew rom 7% to over 15%, while that o capital income irst increased and then decreased. The contribution o dierent actors to overall inequality varies sharply across countries. That o earnings accounted, in 2004, or as much as 86% in the US and as little as 70% in Norway, where both capital and selemployment income make large contributions. In the UK and Canada the contribution o sel-employment income to overall inequality has been on the rise, while greater inequality in income rom property is crucial in explaining the experience o the Scandinavian economies. These results indicate the diiculty in generalizing the causes o distributional changes even within a relatively homogeneous group o countries. The paper is organized as ollows. Section 2 presents an overview o the data and discusses some o the explanations or observed changes in inequality. We then present the decomposition rule o our inequality measure, the hal the squared coeicient o variation, into actor components and population groups. Sections 4 and 5 present the results o the decomposition o the inequality index, examining irst decompositions by actor and subsequently the nested decompositions by age-groups and actor. Lastly, section 6 concludes. Page 11

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13 Factor Components o Inequality 2. Trends in income inequality 2.1. The data The source o our data is the Luxembourg Study (LIS). The Luxembourg Study is a project started in 1983 by researchers in several European and American countries in order to collect income, demographic, labour market and expenditure inormation at the micro-economic level in a way that is consistent across countries. Surveys are conducted every ew years, and the number o member countries has expanded over time, with the project now covering 32 countries. As is well known, the data on income inequality are problematic and international comparisons diicult (see Atkinson and Brandolini, 2001). Although some cross-country dierences in methodology remain, LIS provides the best existing data on inequality in terms o cross-country consistency. In this paper we have chosen to ocus on only 6 countries. There are two reasons or this. First, we wanted countries or which we have data going back to the 1980s. Second, we required having comparable measures. This ruled out including France and Italy, since they have inormation on net rather than gross wages. 5 Details on the data are provided in the Appendix. The number o observations varies across countries, depending on the number and requency o surveys, with countries having between 5 and 9 observations spread over the period. Our sample includes three Anglo-Saxon countries (US, UK, and Canada), one o the large continental European economies (Germany), and two Scandinavian countries (Sweden and Norway), and the data range between 1969 and Because our ocus is on actor share, we use gross income measures. 6 Our deinition o gross income consists in the sum o earnings, capital income, sel-employment income, and a residual category termed other. This last category includes transers rom various sources, and comprises pensions, state transers such as unemployment beneit or child beneit, and private transers such as alimony payments. We would have liked to separate pensions rom the remaining sources o income, but or many countries they are not reported separately. Hence, in order to make our results comparable across countries, we grouped pensions with other income even when the inormation was available. 5 We have, nevertheless, perormed the decompositions or France and Italy, and the data are available rom the authors on request. 6 The alternative would have been to consider disposable income, which, arguably, is a better measure o welare. The reason or not doing so is that when using measures o disposable income the direct impact o tax changes can result in rapid and large changes in inequality (see, or example, Jäntti, 1997). Understanding these changes would have required us to discuss changes in taxation and progressivity in the 8 countries under consideration, a task beyond the scope o this paper. Note, nevertheless, that tax changes will also have direct eects on actor prices and shares and thus on inequality, and these are o course captured by our income concept. Page 13

14 Cecilia García-Peñalosa and Elsa Orgiazzi 2.2. Inequality trends Figure 1 presents the evolution o inequality, measured by the squared coeicient o variation, in the 6 countries we consider. The data show the well-documented pattern that inequality is highest in the Anglo-Saxon economies, lowest in Scandinavian countries, with the large European economies being somewhere in between. Note, nevertheless that there have been large luctuations. In the 1970s the SCV in the UK (and also the Gini coeicient; see igure 2) was roughly similar to those observed in the Scandinavian economies. The dierences we obtained across groups o countries are smaller than those commonly reported or disposable income. This is not surprising given that we measuring gross income inequality, rather than inequality in disposable income. Moreover, as Brandolini and Smeeding (2008) show, some European countries, notably Germany and Sweden, have levels o market income inequality comparable to that in the US, and it is dierences in the tax-transer system that create the gap in disposable income inequality. We observe the trends that have been widely discussed by the literature, such as the increase in household income inequality in the US and the UK rom the early 1980s onwards. The increase in income inequality is also apparent or Canada and, starting in the mid-1980s, or the Scandinavian countries. The German data indicate rather lat time trend. Since the most cross-country comparisons o inequality uses the Gini coeicient, igure 2 reports the Gini coeicients we obtained rom the LIS data. Our deinition o income is, as beore, gross household income. The ranking o countries in terms o the Gini coeicient and observed time trends reproduce those obtained with the SCV. The two measures indicate, nevertheless, dierences in the timing, notably or the US where the Gini coeicient peaked in the mid-1990s while the SCV kept increasing till Because the Gini coeicient places less weight at the extremes o the distribution, this dierence is probably due to an increase at the top or bottom o the distribution What may drive changes in inequality? There are three basic reasons why the distribution o household income may change: changes in market incomes, such as earnings or income rom property; a dierent demographic structure; and changes in tax and transer policies. In what ollows, we have chosen to concentrate on the irst two. This is not because we believe tax and transer changes to be unimportant, but simply because discussing them would require detailed understanding o the tax-transer systems in each o the six countries examined here, a task beyond the scope o this paper. 7 In 7 A number o single-country studies have examined the role o the tax-transer system. See, or example, Jenkins (1995) or the UK, Fjærli and Aaberge (2000) or Norway, and Björklund and Palme (1997) or Sweden. Page 14

15 Factor Components o Inequality order to abstract rom tax changes, we have chosen as our income concept gross household income. Transer policies will, nevertheless, aect household income since government transers are part o our ourth category, other income. An alternative would have been to ocus only on the distribution o market incomes. We chose not to do so or comparability with existing work. The irst question we want to address is to what extent dierent sources o market income have driven inequality changes. Market income may come rom three sources: earnings, selemployment income, and capital income. The increase in earnings inequality has been well documented, 8 although there has been little work examining to what extent changes in the distribution o individual earnings drive changes in the distribution o household income. A notable exception is Gottschalk and Danziger (2005), who examine the evolution o hourly wage rates and household income inequality in the US. 9 One o our objectives is to quantiy the extent to which earnings inequality has been the culprit or the observed increase in household income inequality. Although earnings are the largest source o household income, changes in income rom selemployment and property can also play a major role. Jenkins (1995) identiied a substantial contribution o sel-employment income to the increase in inequality in the UK in the irst hal o the 1980s. Since we can use data or a longer period, we will be able to assess whether the increased contribution o sel-employment has continued, and whether this phenomenon also took place in other countries. The early 1980s also witnessed a sharp rise in the contribution o property income to overall inequality. There are three elements that may have contributed to this: changes in the labour and capital shares in aggregate value added, changes in the rate o return, and changes in taxation that may have avoured property income. One possibility is that the changes in property income inequality in the 1980s were the result o the high interest rates that prevailed at the time, rather than o an increase in the concentration o wealth. I this were the case, we would expect that the subsequent reduction in interest rates caused a reduction both in the share o property income in total household income and in its dispersion. Moreover, i it were high interest rates that drove the increase in capital income inequality in the UK, we should observe a similar increase in the other countries in our sample. The second aspect on which we ocus is the age composition o the population and the dierences in inequality across age groups. There are two main reasons why a decomposition by age can help us understand the orces that drive inequality changes. First, we want to understand the role o capital income inequality. High inequality in this actor can be due to two reasons. It may be the result o an unequal distribution o wealth or any age group. Alternatively, it may be caused by lie-cycle savings, in which case the data should show that capital income inequality is mainly due to dierences across age groups and not within age groups. Moreover, i lie cycle considerations 8 See Gottschalk and Smeeding (1997) and Atkinson (2007a,b). 9 See also Gottschalk (1997) and Checchi and García-Peñalosa (2008, 2010) on the relationship between wage inequality and household income inequality. Page 15

16 Cecilia García-Peñalosa and Elsa Orgiazzi were the main cause o wealth inequality we should also observe important dierences across countries. In countries with generous public pension systems, old individuals would tend to live o state pensions rather than their own savings, and hence we should observe less inequality in the distribution o capital incomes across age groups. Second, the literature on the increase in earnings dispersion has shown that, at least in the US and the UK, greater wage dispersion has been, partly the result o increased returns to experience. This would imply that we should observe an increase in earnings inequality across age groups. A urther question concerns sel-employment. There is evidence that sel-employment is more requent amongst mature workers, 10 and this too should be relected in a greater contribution o sel-employment income to inequality or those age groups. Both Jenkins (1995) and Jäntti (1997) ind little role or demographic changes in their inequality decompositions. However, their data spans a substantially shorter period o time, with the ormer having data or a 15-year period and the latter or just under a decade. In our case the data cover a longer period, particularly or the UK and the US, were we have inormation rom 1969 to We would hence expect that changes in the demographic composition are more pronounced and play a greater role in explaining inequality. 10 See, or example, Evans and Leighton (1989). Page 16

17 Factor Components o Inequality 3. Inequality index decompositions A large theoretical literature has examined possible ways o decomposing inequality indices by actor components, and illustrated the methodologies proposed with some empirical evidence. As is well known, dierent inequality indices have dierent merits and drawbacks. 11 We have chosen to employ as our measure o inequality the squared coeicient o variation, denoted SCV, as is common in the empirical literature on inequality decompositions. The SCV has two key eatures, as compared to other inequality indices. The irst one is that decompositions can be nested, allowing us to examine the changes in actor contributions by population subgroups. The second is that it is more sensitive to extreme values than the Gini coeicient. Although this is an argument that is oten used to preer the use o the latter index, it is useul when we perorm decompositions by actor incomes. In those decompositions we ind that there are many observations with zero values, notably in the case o selemployment and property income, and we want to use an index that is sensitive to such extreme values. The hal squared coeicient o variation is deined as y I i 1, (1) 2 2n i 2 where the population consists o n individuals indexed by i, with mean income and variance 2 The income o individual i, is denoted by y i,, and incomes are received rom various sources or actors, denoted by, so that y i y i. The population can be partitioned in J mutually exclusive age groups, index by j=1, J. We can then deine the inequality index or a particular actor and a particular group as I 2, (2) 2 2 I j 2 j. (3) 2 2 j A number o deinitions will be useul or the subsequent decompositions / actor s share correlation between actor and total income p n n population share o group j j j / j j / group j s mean income relative to population mean / groups j s mean actor- income relative to population mean j j j 11 See or example Fei et al. (1978), Bourguignon (1979), Pyatt et al. (1980), Shorrocks (1982), Lerman and Yitzhaki (1985), and Fournier(2001). Page 17

18 Cecilia García-Peñalosa and Elsa Orgiazzi In order to analyse the impact o various income sources we ollow Shorrocks (1982) and Jenkins (1995). A decomposable inequality index can be expressed as I S (4) where S is the absolute contribution o actor to overall inequality. Let s S I be the relative actor / contribution, such that s 1. Shorrocks makes the case or using a decomposition based on the point estimate o a regression o income o source on total income, that is 2 s Cov( yi, yi ) /. (5) It is then possible to express the absolute contributions in terms o the squared coeicient o variation or aggregate and actor incomes, S s I I I. (6) There are two ways in which we can assess how the contribution o dierent sources o income varies across groups. First, we can simply compute inequality indices by age-groups and obtain the contribution o dierent sources or each group. We can perorm the actor decomposition described above or each age group, with the actor shares being deined by S j I I (7) j j j j and I j S j. The term S j then tells us how much o the overall inequality within-group j is due to inequality in incomes rom actor. Alternatively we can use a group decomposition o the inequality index. It is possible to express our inequality index I as 2 j I j p j j wg bg I p j 1 (8) 2 j 1 2 j Page 18 where the irst term captures inequality within age groups, wg, and the second term represents inequality between-groups, bg. For actor we can express the inequality index as I 2 j I j p j j p 1 2 j 1 j 2 j and using this expression we can write overall inequality as I wg bg, (9) S wg bg, (10) with S / I. The term wg represents within-group inequality in actor, while wg captures the contribution o within-group inequality in actor to overall inequality. Similarly bg represents between-group inequality in actor, and bg is the contribution o between-group inequality in actor to overall inequality. This decomposition allows us to irst determine the contribution o inequality in actor to overall inequality, and then assess how much o it is due to within- and how much to between-group inequality.

19 Factor Components o Inequality 4. Decomposition by income sources 4.1. Absolute actor contributions Tables 1, 2 and 3 report the actor decomposition or the six countries in our sample, or selected years. 12 The inequality index, the SCV, is calculated both or total gross income (irst column) and or its our components: earnings, sel-employment income, capital income and other. We then calculate the absolute contribution o each o these actors to overall inequality, that is, S as given by equation (6), so that the horizontal sum o actor contributions sums up to overall income inequality or each year. The third panel reports the share o actor in total household income,, which as we ill see played an important role in observed inequality changes. The observations or the UK and the US are reported or ive dates, 1969, 1979, 1991, 1999/2000 and This allows us to asses the sources o changes in inequality in the 1970s, 1980s, and 1990s. The US experienced a reduction in inequality in the irst decade and an increase in latter ones, while the SCV dropped again at the end o the period (rom to between 2000 and 2004). The UK had an initially lower degree o inequality than the US which increased through to 2000, and exhibited little change between 2000 and The patterns or the two countries are similar in many aspects. During the 1970s a decline in the contribution o selemployment and capital income inequality implied a reduction in inequality in the US and a moderate increase in the UK, despite the act that earnings inequality had already started to increase. In the US, the increase in the SCV o earnings between 1969 and 1979 was moderate (rom to 0.466) but in the UK it rose by 30 percent (rom to 0.488). Over the next 25 years, inequality increased by 0.12 points in both the US and the UK. That is, it increased by 40 percent in the US and by 50 percent in the UK. As has been well documented, both countries witnessed a large increase in wage inequality over this period. We ind that earnings inequality started rising in the 1970s, i.e. beore the increase in wage inequality documented in the data). Between 1969 and 2004, the SCV o earnings more than doubled in the UK and increased by 68% in the US, and this change was clearly the main orce driving the increase in income inequality. There are three notable dierences between these economies. The irst concerns the timing: in the US, the largest increase in inequality took place in the 1990s, while in the UK it occurred during the 1980s. Second, selemployment income plays a much more important role in the UK. The contribution o sel-employment to the increase in inequality between 1979 and 2004 was o 0.038, a third o the total in crease, while more dispersed 12 We have chosen not to report the decomposition or all available years or all countries and give results (roughly) or each decade. Other country-year decompositions are available upon request. Page 19

20 Cecilia García-Peñalosa and Elsa Orgiazzi earnings account or two thirds o the increase. The large contribution o sel-employment to rising inequality is due to the sharp rise o the share o sel-employment in total household income. During this period, the share o earnings ell rom 73 to 66 per cent while that o sel-employment income rose rom 5 to 8 per cent. In contrast, in the US, the earnings share was stable while that or sel-employment income ell by two points, implying that it tended to reduce inequality. In act, increased earnings inequality accounts or the entire change in the scv o income, with a small positive contribution o capital income being oset by a small negative contribution o selemployment inequality. Two remarks are in order concerning capital income. In both countries the capital share is well below those oten obtained rom national accounts, which attribute about percent o national income and the rest to labour. There are several reasons or this discrepancy. First, standard estimates rom national accounts deine the labour share as the ratio o payments to employees to output and attribute the remainder to capital. This method o accounting ignores sel-employment income, thus overstating the share o capital. When sel-employment income is accounted or properly, the capital share alls substantially: rom 40 to 23 percent in the US and rom 43 to 19 percent in the UK. 13 This adjustment still leaves a substantial discrepancy between our capital shares and those obtained rom aggregate data. There are various likely causes. A substantial raction o the capital income generated by a irm is retained in order to inance uture investments and hence not distributed as interest and dividends to households. Capital gains are not included in the LIS deinition o capital income and hence not accounted or. Lastly, some under reporting is likely given that capital incomes tend not to be paid in the same regular basis as wages and salaries. These last two actors imply that our measures probably understate capital incomes. The second comment concerns the returns to capital. As argued by van den Noord and Heady (2001) capital income is deined as the nominal return on capital rather than the real one, which should be adjusted or inlation. As a result periods o high inlation that are accompanied by high nominal interest rates would yield large shares o capital income even i the real incomes generated by those assets were no dierent rom those obtained in periods o low inlation and nominal interest rates. 13 See Gollin (2002, table 2); the igures reer to the 1990s. Similar changes are reported or Norway and Sweden, the data or Canada and Germany not being available. Gollin also discusses the act that sel-employment income is composed o both labour and capital income and proposes a number o alternative adjustments to compute actor shares that capture this act. Page 20

21 Factor Components o Inequality The irst panel o table 2 perorms the same decomposition or Canada. As we saw earlier, ater a decline during the 1970s, starting in 1981 inequality rose, although by less than in the US and the UK (0.09 points). All actors except or capital income contributed to this increase. Although the increase in earnings dispersion was the largest actor (contributing 72 percent o the increase), inequality in sel-employment income accounted or 23 per cent o the overall increase. As in the UK, there was little change in the SCV o sel-employment income but it share rose over the period while that o earnings ell by 10 percentage points. Other incomes played an important role, since they tended to reduce inequality at the start o the period but to increase it at the end. This could relect either changes in the extent o redistribution, or an increase in the share o pensions in household income associated with an aging population. Their share in household income also rose substantially (rom 11 to 21 per cent o household income). The results or Germany, reported in the second panel o table 2, are unortunately or a shorter period due to data availability, 1984 to The SCV o gross income declined slightly in the irst decade and increased during the second one, remaining in 2004 slightly lower than it was in This stability hides substantial changes in actor income inequality. Earnings dispersion increased by more than in the US: in Germany the SCV o earnings went rom in 1984 to in 2004, while in the US it increased rom to over the period However, the share o earnings in household income is lower in Germany than in the US and it declined by 7 percentage points over the period, leaving their contribution to overall inequality unchanged. The contribution o both sel-employment and capital incomes declined as the dispersion o both sources o income ell, tending to reduce inequality. However, the contribution o other incomes increased, which oset the previous eect. Decompositions or Norway and Sweden are reported in table 3. As discussed above, these two economies experienced increases in gross income inequality although o smaller magnitude than those observed in the UK and the US, with the SCV increasing by points in Norway and by in Sweden between the 1979/81 and 2004/5. These changes were mainly the result o a more dispersed distribution o earnings. Starting in 1979/81, the SCV o earnings rose by 18 and 19 percent in Norway and Sweden respectively. Although this was a smaller increase than that experienced by the US and the UK, earnings inequality was, by the end o the period similar to that observed in the Anglo-Saxon economies. For example, in 2004 the SCV o earnings was in the US and Page 21

22 Cecilia García-Peñalosa and Elsa Orgiazzi in Sweden. Its contribution to overall inequality is, however, much small in the Scandinavian economies because the share o earnings is about 10 percentage points lower than in the Anglo-Saxon ones. 14 There are two important dierences between the two Scandinavian economies we consider. In Sweden, the increase in overall inequality that started in 1981 was exclusively due to greater earnings dispersion, and the impact on overall inequality o this increased dispersion was partly oset by a reduction in the contribution o capital income. The Swedish data illustrate the importance o actor shares. Recall that the contribution o actor depends both on the SCV o that actor and on the share o the actor in total household income (see equation (6)). We can see rom table 3 that the contribution o earnings was the same in 1975 as in 2004, However, in 1975 this was the result o a moderate degree o inequality (0.508) and a high earnings share (0.710) while in 2004 the same contribution was due to substantially higher inequality (0.660) but a lower earnings share (0.632). In Norway three actors played a role in the increased in inequality observed between 1979 and 2004: a more dispersed distribution o earnings, a greater contribution o capital income inequality and a reduction in the redistributive role o other incomes (their contribution ell rom to ). The increase in the contribution o capital income was particularly large: it rose by points while the SCV o overall income increased by 0.038, and it was the results o both a more dispersed distribution o capital income (the SCV o capital income rose rom 5 to almost 17) and a greater share o this actor in household incomes (under 3% in 1979 and almost 5% by 2004). As it has been documented, 15 the increase in the contribution o capital income inequality was largely due to iscal reorms that took place in the early 1990s. These reorms increased, on the part o households, the incentives to realize capital gains on inancial assets and, on the part o irms, the incentives to pay dividends. Note, however, that the LIS data does not include capital gains; hence our measure o inequality captures only the impact o the tax reorms through increased dividend payments. I we compare these two economies with the US and the UK we see that, by the end o the period, earnings inequality was o similar magnitude (the SCV o earnings is almost identical in the US and Sweden), while the two Scandinavian countries exhibit a greater dispersion o capital incomes and, in the case o Sweden, much more dispersed sel-employment incomes. The major dierence is that the share o earnings in household income is much lower and the share o other incomes much higher in the Scandinavian than in the Anglo-Saxon economies. Since a major component o other incomes are welare transers, this is capturing the role o redistribution. 14 See Gustavsson (2008) on the evolution o the distribution o earnings in Sweden, and Aaberge and Atkinson (2010) and Roine and Waldenström (2010) on the evolution o top incomes in the two Scandinavian economies. 15 See Aaberge et al. (2000) and Fjærli and Aaberge (2000). Page 22

23 Factor Components o Inequality 4.2. Relative actor contributions A convenient way o examining the sources o changes in inequality is to consider the evolution o relative actor contributions. These are captured by the term S, as given by equation (5), which measures the share o inequality that is due to inequality in actor. Figure 3 depicts he relative actor contributions or the US, Canada and the UK, respectively. We can see that in the US earnings are by ar the most important source o inequality, and that their relative contribution has increased over time, while that o other actors has diminished. Canada presents a similar pattern to that observed in the US: a high relative contribution o earnings and moderate contributions o capital and sel-employment incomes. In the UK, there is greater variability in actor contributions over time. The contribution o earnings increased over the irst decade, ell in the 1980s and increased again in the 1990s. The role o capital income also exhibits luctuations over the period. We can observe the increase in its contribution to overall inequality between 1979 and 1991, consistent with the result obtained by Jenkins (1995) o a rising contribution o investment income over the period , but its relative contribution ell subsequently. The contribution o sel-employment also presents substantial variation over the sample period, and has been particularly high since Jenkins (1995) argues that the increasing incidence o sel-employment in the 1980s may also have led to a greater accumulation o assets and hence investment income. Although the data or 1979, 1986 and 1991 seem to support this hypothesis, it is not consistent with those or latter years. The data or 1994, 1999, and 2004 exhibit an even higher relative contribution o sel-employment inequality, accompanied by a reduction in the contribution o capital income inequality. An alternative explanation, which would also be consistent with the movements o the capital share reported in table 1, is that the pattern in capital income is due to the high interest rates o the 1980s and early 1990s. Indeed, between 1979 and 1992 the interest rate on 3-month Treasury bills was between 9 and 15 per cent, and declined aterwards, lying between 3.5 and 6.8 percent in the period Figure 4 present the actor decomposition or the three continental European countries, Germany, Norway and Sweden. All three igures illustrate the smaller contribution that earnings inequality has compared to the Anglo-Saxon economies. For example, in Norway both in 1979 and in 2004, earnings accounted or only around 70 per cent o overall inequality. Both Norway and Sweden experienced a reduction in the contribution o selemployment income, but dier in that the ormer experience a large increase in the contribution o capital income inequality that we do not observe in Sweden. Page 23

24 Cecilia García-Peñalosa and Elsa Orgiazzi Figure 5 depicts the relative actor contributions or all countries, and illustrates the dierences across them. The upper panel is or the mid-1980s (the earliest period or which we have data or all countries), while the bottom panel reports relative actor contributions in the most recent year available, 2004/05. In the top panel, we observe large dierences across countries. Earnings inequality is most important in the UK and Sweden (86% in both countries) and lowest in Germany and Norway (72 and 73%, respectively). The contribution o sel-employment income ranges rom 5% to 22% (Sweden and Germany, respectively) and that o capital income rom 4% to 12% (Sweden and Germany, respectively). A striking eature o the data is that there do not seem to be patterns common to the countries within each o the two groups Anglo-Saxon, versus European. The contribution o earnings is high in the Anglo-Saxon economies, but also in Sweden. The two Scandinavian countries exhibit very dierent decompositions, with capital and sel-employment income playing a much more important role in Norway than in Sweden. When we do the decomposition or 2004/05 (lower panel o igure 5) we observe the same eatures just described, with the US, Sweden and the UK having the largest earnings contribution, and Norway the lowest. The irst two countries also exhibit a particularly low contribution o selemployment income (3 and 7%), while or the other countries it ranges between 13 and 19%. The most noticeable change is the large increase in the contribution o capital income in the two Scandinavian countries, but particularly in Norway. Page 24

25 Factor Components o Inequality 5. Decomposition by age group 5.1. The Anglo-Saxon Economies Trends in inequality by age As we have argued, there are two main reasons why a decomposition by age can help us understand the orces that drive inequality changes. First, we have seen that capital income inequality has played an important role, and in some cases, such as or Norway, a crucial one in changes in inequality. I dierences in wealth and hence in capital income- are mainly due to lie-cycle considerations, then the data should show that capital income inequality is largely due to dierences across age groups and not within age groups. Second, the increase in earnings dispersion has also played a central role in inequality changes. A number o authors have shown that, at least in the US and the UK, greater wage dispersion has been, partly the result o increased returns to experience. This would imply that we should observe an increase in earnings inequality across age groups. A urther question concerns sel-employment. There is evidence that sel-employment is more requent amongst mature workers, and this too should be relected in pattern across age groups. 16 In order to examine these questions, we decompose the population in each country year in subgroups by age o the household head. We consider 7 subgroups: <25, 25-34, 35-44, 45-54, 55-64, 65-74, >74. Figures 6 and 7 depict the evolution o total gross income inequality, measured by the SCV, or each age subgroup in each o the six countries (to make the igures easier to read, we do not depict the two end groups, <25 and >74). In general, although not always, inequality is lower or young (25-34) and prime-age households (35-54) and higher or older households (55-74). This pattern is clearly present or the US and Canada, as can be seen in igure 6. In both countries, the decline in inequality in the 1970s was largely driven by lower inequality or older households, while all age groups experienced an increase in inequality in the last two decades o the century. 17 As a result, dierences in withingroup inequality were smaller in 2000 than at the start o our sample period. For example, in the US in 1969 inequality in the group was 4.3 times than in the group, while this ratio had allen to 1.4 by 2000 (see table 4). Note also that in Canada inequality ell substantially or older households (those between 65 and 74 years) in the late 1990s, so that all groups except the old, had roughly the same degree o inequality by the end o the period. Our last observation, that or 2004, indicates a reduction in overall inequality in the US (see table 1). We can see that all groups except or the oldest cohorts experienced such a reduction, and it 16 See, or example, Evans and Leighton (1989). 17 See Cowell and Jenkins (1995) or decompositions by race and age in the US. Page 25

26 Cecilia García-Peñalosa and Elsa Orgiazzi was particularly sharp or those in the group. The reason or this seems to be a large reduction in inequality in selemployment income, which in the 1990s was over and in 2004 dropped to 0.026, a change that could well be related to the burst o the dot-com bubble. In Canada, the overall inequality did not change much in the irst years o the century, but dierent groups had dierent experiences, with inequality alling or the young and the old and increasing or prime age workers (35-54). The UK also exhibits higher inequality or older households. With the exception o the oldest cohort, all age groups experience an increase in inequality rom 1979 onwards. Inequality or the oldest age-group luctuates substantially, and the data indicates large changes in the role played by the various actors. For example, the contribution o capital income inequality doubled between 1979 and 1991 and ell again to its initial value by 2004 (not reported), consistent with the hypothesis that interest rates aect the income o this group substantially Factor contributions We urther decompose inequality or each age group by income source. Tables 4 and 5 report the absolute contributions o the our actors examined in section 4 or the US and the UK in the years 1979 and Looking at the irst column, we observe the increase in income inequality or all age groups (except the under 25) reported in igure 6, with inequality increasing by between 8% (or the over 75) and 61% (or those 25 to 34). The same pattern is observed or almost all age groups: the increase in overall inequality was the result o a large increase in earnings inequality and a moderate increases in inequality in capital income. For both the youngest and oldest cohort there was a signiicant increase in the contribution o other incomes, probably due to a less progressive welare system. In the UK there is much greater variation across age groups. Inequality was between 1.6 times and almost 2.2 times higher in 2004 than in 1979 or households that were less than 64, and ell or those above 65. The contribution o earnings inequality rose or all groups except those above 65. Both the contributions o capital income and sel-employment inequality increased or all groups (with the exception or capital income or the cohort). The increase in the contribution o sel-employment is particularly large, and is important or all age groups. For example, or the age group, the relative contribution o this source o income rose rom 11% in 1979 to 16% in 2004, or the rom 6% to 20% and or the rom 3% to 18%. A possible explanation is that the development o IT technologies increased entrepreneurship in the UK. Table 6 reports absolute actor contributions by age groups or Canada in 1981 and The increase in inequality or those between 25 and 64 reported in igure 6 is driven by an increase in earnings and, to a lesser extent, by an increase in sel-employment income inequality. Meanwhile, the reduction in inequality or older households Page 26

27 Factor Components o Inequality (over 65 years) was driven by reductions in inequality in all three markets incomes, with the contribution o capital income being particularly important The Continental Economies Trends in inequality by age The evolution o inequality in the continental economies is depicted in igure 7. A common pattern or all three countries is that dierences across age groups are smaller than in the Anglo-Saxon economies, especially in the Scandinavian economies. Germany exhibits an age-group pattern with some luctuations but no clear trends. In both Norway and Sweden, dierences across age groups have been alling over time. For example, by the end o the period the SCV by age group in Sweden ranged between and 0.231, much smaller than the gap observed in the US (in 2004, the dierence between the SVC o the least and the most unequal age-groups was 0.207). In Norway, inequality increased or all groups except those over 65, or whom it irst ell and then stabilized. In Sweden we observe a small increase in inequality or all groups starting in the mid-1980s Factor contributions Factor decomposition across age groups does not allow us to discern a particular trend o inequality in Germany (table 7). Some groups (those in the and over 74 categories) experienced a reduction in inequality and others an increase. The contribution o earnings inequality increased or all groups except the two oldest ones, but those o the other actors change without any clear pattern. When we decompose inequality by actor in each group (tables 8 and 9) both Sweden and Norway exhibit the same main eature: the increase in inequality observed or all groups was due to a higher contribution o earnings inequality or all groups except the oldest (those over 65 in Norway, those over 75 in Sweden). With some exceptions, the contribution o sel-employment income ell and that o capital income rose in both countries, though more sharply in Norway than in Sweden. As we saw earlier, the increase in the contribution o capital income inequality was large in Norway, and our decomposition by groups indicates that this occurred or all age groups, including the young. The contribution o capital income increased sevenold or those between 35 and 64 and between three and ourold or other households. The increase in the contribution o capital income or young and prime-age households, or whom this source o income was a minor contribution in 1979, can be due to either an increased ability o younger households to accumulate assets or to transers across generations that result in a perpetuation o wealth inequality. For older households the increase in the importance o this source o income is Page 27