Abstract
In this paper, we revisit the relationship between educational and income inequalities in a historical perspective, using a newly developed annual dataset of average years of education in Europe. Theoretically one would expect a reduction in educational inequality should, given the positive correlation between education level and income, initially increase and then, at a later stage, reduce income inequality. Testing for such a Kuznets-type relationship between educational and income inequalities yields an unexpected result: we find the expected inverse U-curve before the 1950s, but the relationship changes into a normal U-curve afterward. We explain this observation by a change in the trend of skill premium during the second half of the twentieth century due to an increased relative demand for skills, which contradicts the usual assumption of decreasing returns to education. Due to lack of appropriate wage data, we cannot directly capture this effect. Yet, once we use an instrumental variable estimation method to filter out the effect of the omitted skill premium, the expected inverse U-curve also appears for the latter decades of the twentieth century.
Similar content being viewed by others
Notes
While several theoretical models were developed (see Banerjee and Newman 1993; Perotti 1993; Galor and Tsiddon 1996) that produce the inverted U-curve, the empirical results are inconclusive. Bruno et al. (1996), Deininger and Squire (1998), Matyas et al. (1998) and Fields (2001) for example cannot find empirical support for it.
The enrollment data for the UK by Mitchell (2003), however, do not include enrollment to non-state inspected schools and can hence lead to and underestimate of educational attainment for the second half of the nineteenth century. For this reason, we rather used Lindert’s (2004) enrollment data, but also run all regressions excluding the UK. Since the difference was not significant, we do not report those results in the paper.
The most recent estimates by Barro and Lee (2010) employ additional statistical data to correct for the problem of the relationship between mortality and educational attainment. Such an approach would not be feasible on historical data; for this reason we believe that the method by Foldvari and van Leeuwen (2009) may be advantageous for historical research.
For clarity, let us take an example: if we know the average years of education from census data for the years 1960 and 1970, we can estimate the average years of education in 1965 as an average of the 1965 value estimated backward from 1970 and forward from 1960. Similarly, we can use this corrected 1965 estimate together with the census data from 1960 to estimate a corrected value for 1963 and so on for all unknown years. The main assumption is that the bias resulting from neglecting the interrelation between mortality and education depends on the distance from the point of departure, but not from the year. In this case the two biases should have equal magnitude and opposite sign and they should cancel out when taking an average.
An obvious advantage of annual data is that one can rely on time-series techniques (autoregressive models, especially VAR and VEC) that would not be applicable if only benchmarks were available.
The dataset by Morrisson and Murtin does not contain Eastern Europe (with the sole exception of Bulgaria and Hungary) and omits several of the, admittedly smaller, Western European countries as well. In addition, it reports the data by decade rather than annually. Methodologically, the dataset of Morrisson and Murtin is very similar to ours with the main distinction that their data are based on a strong assumption regarding enrollment numbers in the nineteenth century. They assume very low primary school enrollment rates for less developed countries for the start of the nineteenth century, and then they link these assumptions to the first available observation by assuming a constant growth rate. This basically means that the longer the missing period is, the larger the measurement error for a country becomes at the start of their series. Other assumptions used such as for drop-out rates and duration of schooling do not significantly bias the estimates in either series (Morrisson and Murtin 2009).
They use the following identity from Robinson (1976): \(\sigma^{2} = p_{s} \sigma_{s}^{2} + (1 - p_{s})\sigma_{u}^{2} + p_{s} (1 - p_{s})(\bar{y}_{s} - \bar{y}_{u})^{2}\), where σ, σ s , and σ u denote the total income inequality, the income inequality of schooled and unschooled worker respectively, ps is the share of schooled workers in total population, and finally \(\bar{y}_{s}, \bar{y}_{u}\) are the mean incomes of the two groups. When they difference this expression with respect to p s they assume that \(\frac{{\partial \bar{y}_{s}}}{{\partial p_{s}}} < 0,\frac{{\partial \bar{y}_{u}}}{{\partial p_{s}}} > 0\), that is they assume that the wage of educated individuals is monotonic function of their share in the population i.e. the expansion in education necessarily compresses wages.
He shows that \(G \approx \frac{1}{\sqrt 3}\frac{\sigma}{{\bar{y}}}\rho (y,r_{y})\), where G denotes the Gini coefficient, and ρ(y, r y ) is the rank correlation coefficient between income and rank. The latter we can take as constant for a given population.
If we take the total derivative of the CV, with skilled wages and the share of skilled workers allowed to change, we obtain the following:
\(d{\text{CV}}(y) = \left[ {\frac{{p_{s} (1 - p_{s} )(\bar{y}_{s} - \bar{y}_{u} )}}{{\sigma \bar{y}}} - \frac{{p_{s} \sigma }}{{\bar{y}^{2} }}} \right]d\bar{y}_{s} + \left[ {\frac{{0.5\left( {\sigma_{s}^{2} - \sigma_{u}^{2} + (1 - 2p_{s} )(\bar{y}_{s} - \bar{y}_{u} )^{2} } \right)}}{{\sigma \bar{y}}} - \frac{{\sigma (\bar{y}_{s} - \bar{y}_{u} )}}{{\bar{y}^{2} }}} \right]dp_{s}\)
As long as only the share of schooled workers (p s ) is allowed to increase, the effect can be either negative or, if the first term in the respective bracket is high enough and p s < 0.5, then initially positive and at higher values of ps negative. This can give rise to an inverse U-curve. When there is a wage change as well, then the coefficient of \(d\bar{y}_{s}\)will affect the behavior of the CV, which can be both positive and negative, depending on the parameters and ps, resulting in an inverse or a normal U-curve.
In every recent article Morrisson and Murtin (2013) take increasing returns to education into account, but they still find an inversed U-curve in their global dataset, even though less pronounced. A possible explanation is that the increase the rate of returns was strong enough in Europe in the second half of the twentieth century to cause such a reversal of the relationship, while outside Europe and North-America this effect was simply not strong enough to dominate the composition effect.
The importance of the state is initiating mass education is well described in the literature (e.g., Ramirez and Ventresca 1992; Cummings 2003). In Europe, several countries saw earlier proclamations from King and Church to parents to educate their children. It has been argued that these played an important role in the spread of literacy in Europe (Graff 1987; Mitch 1992; Vincent 2000). This led gradually to the spread of compulsory education. Compulsory education laws were first enacted in Prussia (1763) and Denmark (1814), followed by several South European and Scandinavian countries (Soysal and Strange 1989, 278). In the second half of the nineteenth century compulsory education laws were made in several Northwest European countries, followed by Eastern Europe (Benavot and Resnik 2006, p. 11). Yet, in all cases, the State played an important role by enacting compulsory mass education be it either because “the establishment of compulsory education addressed narrowly defined educational problems; in others, it was employed as a strategy to “solve” or defer solving long-standing economic, cultural, or social problems” (Benavot and Resnik 2006, pp. 13–14). Indeed, in a quantitative analysis Soysal and Strange (1989, p. 285) find that only the effect of the state on the enactment of compulsory education and increasing enrollments seems to matter.
References
Abramovitz M (1986) Catching up, forging ahead, and falling behind. J Econ Hist 46:385–406
Acemoglu D (2002) Directed technological change. Rev Econ Stud 69:781–809
Alesina A, Perotti R (1996) Income distribution, political instability, and investment. Euro Econ Rev 40:1203–1228
Atkinson AB (2007) The long run earnings distribution in five countries: remarkable stability, U, V or W? Rev Income Wealth 53:1–24
Autor D, Katz L, Krueger A (1998) Computing inequality: have computers changed the labor market? Q J Econ 113:1169–1213
Banerjee A, Newman A (1993) Occupational choice and the process of development. J Polit Econ 101:274–298
Barro R (1991) Economic growth in a cross section of countries. Q J Econ 106:407–443
Barro R, Lee J-W (1993) International comparisons of educational attainment. J Monet Econ 32:363–394
Barro R, Lee J.-W (1996) International measures of schooling years and schooling quality. Am Econ Rev 86(2):218–223
Barro R, Lee J-W (2001) International data on educational attainment updates and implications. Oxf Econ Papers 53:541–563
Barro R, Lee J-W (2010) A new data set of educational attainment in the world, 1950–2010. NBER working paper no. 15902
Becker GS (1975) Human capital: a theoretical and empirical analysis, with special reference to education, 2nd edn. NBER, Cambridge
Becker GS, Chiswick BR (1966) Education and the distribution of earnings. Am Econ Rev 56:358–369
Benavot A, Resnik J (2006) Lessons from the past: a comparative socio-historical analysis of primary and secondary education. In: Benavot A, Resnik J, Corrales J (eds) Global educational expansion: historical legacies and political obstacles. American Academy of Arts and Sciences, Cambridge
Benhabib J, Spiegel M (1994) The role of human capital in economic development evidence from aggregate cross-country data. J Monet Econ 34:143–173
Bhalla S (2002) Imagine there is no country: poverty, inequality and growth in the era of globalization. Institute for International Economics, Washington
Bourguignon F (2009) A turning point in global inequality… and beyond. In: Krull W (ed) Research and responsibility. Reflections on our common future. CEP Europäisch Verlagsanstalt, Leipzig
Bruno M, Ravallion M, Squire L (1996) Equity and growth in developing countries: old and new perspectives on the policy issues. World bank policy research working paper series no. 1563
Card D (1999) The causal effect of education on earnings. In: Ashenfelter O, Card D (eds) Handbook of labour economics, vol 3B. Elsevier, Amsterdam
Card D (2001) Estimating the returns to schooling: progress on some persistent econometric problems. Econometrica 69:1127–1160
Card D, DiNardo J (2002) Skill-biased technological change and rising wage inequality: some problems and puzzles. J Labor Econ 20:733–783
Castello A, Doménech R (2002) Human capital inequality and economic growth: some new evidence. Econ J 112:187–200
Checchi D (2001) Education inequality and income inequality. STICERD distributional analysis research programme discussion paper no. 52
Chisick H (1981) The limits of reform in the enlightenment: attitudes towards the education of the lower classes in the eighteenth century. Princeton University Press, Princeton
Cohen D, Soto M (2007) Growth and human capital: good data, good results. J Econ Growth 12(1):51–76
Cummings W (2003) The institutions of education: a comparative study of educational development in six core nations. Symposium Books, Oxford
De Gregorio J, Lee J-W (2002) Education and income distribution: new evidence from cross-country data. Rev Income Wealth 48:395–416
De la Fuente A, Doménech R (2000) Human capital in growth regressions: how much difference does data quality make? OECD economics department working papers no. 262
Deininger K, Squire L (1998) New ways of looking at old issues: inequality and growth. J Dev Econ 57:259–287
Duncan O (1961) A socioeconomic index for all occupations. In: Reiss A (ed) Occupations and social status. Free Press, Glencoe
Fields G (2001) Distribution and development, a new look at the developing world. Russel Sage Foundation, New York and MIT Press, Cambridge
Foldvari P, Van Leeuwen B (2009) Average years of education in Hungary: annual estimates 1920–2006. Eastern Euro Econ 47:5–20
Freeman RB, Katz LF (1995) Differences and changes in wage structures: introduction and summary. In: Freeman RB, Katz LF (eds) Differences and changes in wage structures. NBER comparative labour markets series. University of Chicago Press, Chicago, London
Galor O (2005) From stagnation to growth: unified growth theory. In: Aghion Ph, Durlauf S (eds) Handbook of economic growth. Amsterdam, North-Holland, pp 172–293
Galor O (2011) Unified growth theory. Princeton University Press, Princeton
Galor O, Tsiddon D (1996) Income distribution and growth: the Kuznets hypothesis revisited. Economica 63:S103–S117
Goldin C, Katz L (2009) The race between education and technology. Harvard University Press, Cambridge
Graff HJ (1987) The legacies of literacy: continuities and contradictions in western culture and society. Indiana University Press, Bloomington
Hall R, Jones Ch (1999) Why do some countries produce so much more output per worker than others? Q J Econ 114:83–116
Jonsson G, Magnusson M (eds) (1997) Sogulegar hagtolur um Island (Iceleandic Historical Statistics). Reykjavik, Hagstofa Islands
Katz L, Murphy K (1992) Changes in relative wages, 1963–1987: supply and demand factors. Q J Econ 107:35–78
Knight J, Sabot R (1983) Educational expansion and the Kuznets effect. Am Econ Rev 73:1132–1136
Krueger A, Lindahl M (2001) Education for growth: why and for whom? J Econ Lit 39:1101–1136
Kuznets S (1955) Economic growth and income inequality. Am Econ Rev 45:1–28
Kyriacou G (1991) Level and growth effects of human capital: a cross-country study of the convergence hypothesis. Economic research reports 19–26, C.V. Starr Center for Applied Economics, New York University
Lains P (2003) Catching up to the European core: Portuguese economic growth, 1910–1990. Explor Econ Hist 40:369–386
Leamer EE (1988) Measures of openness. In: Baldwin RE (ed) Trade policy issues and empirical analysis. University of Chicago Press, Chicago
Lindert PH (2004) Growing public: social spending and economic growth since the eighteenth century, vol 2. Cambridge University Press, Cambridge
Ljungberg J, Nilsson A (2009) Human capital and economic growth: Sweden 1870–2000. Cliometrica 3:71–95
Machin S, Van Reenen J (1998) Technology and changes in skill structure: evidence from seven OECD countries. Q J Econ 113:1215–1244
Maddison A (2007) The world economy: a millennial perspective/ historical statistics. OECD, Development Centre Studies, Paris
Matyas L, Konya L, MaCquarie L (1998) The Kuznets U-curve hypothesis: some panel data evidence. Appl Econ Lett 5:693–697
Milanovic B (1997) A simple way to calculate the Gini coefficient, and some implications. Econ Lett 56(1):45–49
Mincer J (1974) Education, experience, and earnings. Columbia University Press, New York
Mitch D (1992) The rise of popular vernacular literacy in victorian England. University of Pennsylvania Press, Philadelphia
Mitchell B (2003) International historical statistics: Europe, 1750–1993. M. Stockton Press, New York
Mitchell M (2005) Specialization and the skill premium in the 20th century. Int Econ Rev 46:935–955
Morrisson C, Murtin F (2007) Education inequalities and the Kuznets curves: a global perspective since 1870. Paris school of economics, working paper no. 2007–12
Morrisson C, Murtin F (2009) The century of education. J Hum Cap 3:1–42
Morrisson C, Murtin F (2010) The Kuznets curve of education: a global perspective on education inequalities. Centre for the economics of education discussion paper 116
Morrisson C, Murtin F (2013) The Kuznets curve of human capital inequality: 1870–2010. J Econ Inequal 11(3):283–301
Núñez C (2005) Educación. In: Carreras A, Tafunell X (eds) Estadísticas Históricas de España, siglos XIX y XX. Fundación BBBV, Bilbao, pp 155–244
Perotti R (1993) Political equilibrium, income distribution and growth: theory and evidence. Rev Econ Stud 60:755–766
Perotti R (1996) Growth, income distribution, and democracy: what the data say. J Econ Growth 1:149–187
Pina A, St. Aubyn M (2002) Public capital, human capital and economic growth: Portugal 1977–2001. Departamento de Prospectiva e Planeamento, Ministério das Finanças
Portela M, Alessie R, Teulings C (2004) Measurement error in education and growth regressions. Tinbergen Institute discussion paper, TI 2004-040/3
Prados de la Escosura L, Rosés J (2010) Human capital and economic growth in Spain, 1850–2000. Explor Econ Hist 47:520–532
Pritchett L (2001) Where has all the education gone? World Bank Econ Rev 15:367–391
Psacharopoulos G (1994) Returns to investment in education: a global update. World Dev 22:1325–1343
Psacharopoulos G, Patrinos H (2004) Returns to investment in education: a further update. Educ Econ 12:111–134
Ram R (1984) Population increase, economic growth, educational inequality, and income distribution: some recent evidence. J Dev Econ 14:419–428
Ram R (1989) Can educational expansion reduce income inequality in less-developed countries? Econ Educ Rev 8:185–189
Ramirez F, Ventresca M (1992) Building the institution of mass schooling: isomorphism in the modern world. In: Fuller B, Rubinson R (eds) The political construction of education. Praeger, New York, pp 47–60
Ritzmann-Blickenstorfer H (ed) (1996) Historische Statistik der Schweiz = : Statistique historique de la Suisse = Historical statistics of Switzerland. Chronos Verlag, Zurich
Robinson S (1976) A note on the U hypothesis relating income inequality and economic development. Am Econ Rev 66:437–440
Sachs JD, Shatz HJ (1994) Trade and jobs in U.S. manufacturing. Brookings Papers Econ Act 1:1–84
Schulze M-S, Fernandes FT (2009) Human capital formation in Austria-Hungary and Germany: time series estimates of educational attainment, 1860–1910. In: Halmos K, Klement J, Pogány Á, Tomka B (eds) A felhalmozás míve. Történeti tanulmányok Kövér György tiszteletére. Századvég Kiadó, Budapest, pp 275–290
Soysal Y, Strange D (1989) Construction of the first mass education systems in 19th century Europe. Sociol Educ 62:277–288
Teixeira A (2004) Measuring aggregate human capital in Portugal. An update up to 2001. FEP working paper 152, Faculdade de Economia da Universidade do Porto
Thomas K (1987) Numeracy in early modern England: the Prothero lecture. Trans R Hist Soc 37:103–132
Thomas V, Wang Y, Fan X (2000) Measuring education inequality: Gini coefficients of education. The World Bank, Mimeo. http://econ.worldbank.org/files/1341_wps2525.pdf
UNESCO (1953) Progress of literacy in various countries. A preliminary statistical study of available census data since 1900. United National Editorial, Scientific and Cultural Organisation, Paris
UNESCO (1964–99) Statistical yearbook 1963–1999. UNESCO, Paris
Van Leeuwen M (2000) Logic of charity: a simple model applied to Amsterdam 1800–1850. Palgrave MacMillan, London
Van Leeuwen B, Foldvari P (2013) Capital accumulation and growth in central Europe, 1920–2006. Eastern Euro Econ
Van Leeuwen B, van Leeuwen-Li J, Foldvari P (2012) Education as a driver of income inequality in twentieth-century Africa, MPRA Paper No. 43574
Van Zanden JL, Baten J, Foldvari P, Van Leeuwen B (2011) World Income Inequality 1820–2000. CGEH working paper no. 1
Van Zanden JL, Baten J, Foldvari P, Van Leeuwen B (2013) The changing shape of global inequality 1820–2000. Rev Income Wealth. doi:10.1111/roiw.12014
Vincent D (2000) The rise of literacy: reading and writing in modern Europe. Polity Press, Cambridge
Wood A (1994) North-south trade, employment and inequality: changing fortunes in a skill-driven world. Clarendon Press, Oxford
Wood A (1995) How trade hurt unskilled workers. J Econ Perspect 9:57–80
Wood A (1997) Openness and wage inequality in developing countries: the Latin American challenge to East Asian conventional wisdom. World Bank Econ Rev 11:33–57
Zeira J (2009) Why and how education affects economic growth. Rev Int Econ 17(3):602–614
Acknowledgments
The authors wish to express their gratitude to the two anonymous referees for their valuable and constructive comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Földvári, P., van Leeuwen, B. Educational and income inequality in Europe, ca. 1870–2000. Cliometrica 8, 271–300 (2014). https://doi.org/10.1007/s11698-013-0105-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11698-013-0105-3