Handbook of Cliometrics pp Cite as. This article provides an overview of current knowledge about economic inequality, of both income and wealth, in the very long run of history focusing on Western Europe and North America.
While most of the data provided by recent research cover the period from the late Middle Ages until today, some insights are also possible into even earlier epochs.
Based on these recent findings, economic inequality seems to have been growing over centuries, with phases of clear and marked inequality reduction being relatively rare and usually associated with catastrophic events, such as the Black Death during the fifteenth century or the World Wars in the twentieth.
Traditional explanations of long-term inequality growth are found to be unsatisfying, and a range of other possible causal factors are explored demographic, social-economic, and institutional. Skip to main content.
Alfani G The rich in historical perspective. Evidence for preindustrial Europe ca. Cliometrica 11 3 — CrossRef Google Scholar. Inequality and the rise of the fiscal state in preindustrial Europe. Alfani G, Murphy T Plague and lethal epidemics in the pre-industrial world. A comparison of inequality trends in Italy and the Low Countries, — Atkinson AB Income tax and top incomes over the twentieth century.
Borgerhoff Mulder M, Bowles S, Hertz T et al Intergenerational wealth transmission and the dynamics of inequality in small-scale societies. Science — CrossRef Google Scholar. Canbakal J. Filling the gap: long run Canadian wealth inequality in international context.
Research report n. Deaton A The great escape: health, wealth and the origins of inequality. Diamond J Guns, germs, and steel: a short history of everybody for the last 13, years. Vintage, London Google Scholar. Kuznets S Economic growth and income inequality. Am Econ Rev 45 1 :1—28 Google Scholar. Lindert PH Unequal English wealth since Lindert PH Toward a comparative history of income and wealth inequality. Income distribution in historical perspective. Cambridge University Press, Cambridge, pp.
Lindert PH Making the most of capital in the 21st century. NBER working paper no.This entry presents the empirical evidence of how inequality between incomes has changed over time, and how the level of inequality varies between different countries. We also present some of the research on the factors driving the inequality of incomes. A related entry on Our World in Data presents the evidence on global economic inequality.
That entry looks at economic history and how global inequality has changed and is predicted to continue changing in the future. The following graph demonstrates the level of economic inequality in pre-industrial societies in relation to the levels of prosperity in those same societies. Inequality is measured with the Gini index explained below and prosperity is measured by the gross domestic income per capita, adjusted for price differences to make comparisons in a common currency possible.
The idea behind this curve is that in a very poor society inequality cannot be very high: Imagine if the average level of income were just the bare minimum to survive, in such an economy there could not possibly be any inequality as this would necessarily mean that some people have to be below the minimum income level on which they could survive.
When average income is a little higher it is possible to have some small level of inequality, and the IPF shows how the maximum possible inequality increases with higher average income.
The authors found that many pre-industrial societies are clustered along the IPF. This means that in these societies, inequality was as high as it possibly could have been. In the cases of Holland and England, we see that during their early development they moved away from the IPF and the level of inequality was no longer at the maximum.
The United Kingdom is the country for which we have the best information on the distribution of income over the very long run. This information is visualized in this chart. The early estimates are based on social tables, and as with most estimates from the more distant past, there is some concern about how accurate these estimates are. The estimates presented in this visualization suggest that inequality in the UK was very high in the past, and did not change much until the onset of industrialization.
Starting in the late 19th century, income inequality began to decrease dramatically and reached historical lows in the late s. However, during the s inequality increased substantially in the UK and both the Gini and the top income share increased sharply. From the early s onwards, we see that the UK experiences a divergence between what the Gini and the top income shares tell us about inequality.
The Gini remained flat over these two decades and, if anything, fell somewhat during this period. This tells us that inequality across the bulk of the distribution has not increased further in the UK.
At the very top, however, the evidence shows a different story. We observe that income growth at the very, very top of the income distribution has outstripped the strong growth of incomes across the rest of the distribution. Researchers have a much better understanding of the long run evolution of income inequality thanks to the recent wave of research on top income shares.
Top income inequality is measured as the share of total income that goes to the income earners at the very top of the distribution. Historical top income inequality estimates are reconstructed from income tax records, and for many countries these estimates give us insights into the evolution of inequality over more than years.
Inequality in the long run
This is much longer than other estimates of income inequality allow as is the case with estimates that rely on income survey data. The fact that income shares are measured through tax records implies that these estimates measure inequality before redistribution through taxes and transfers.
What we can learn from this long-term perspective is summarized in this visualization. Consider the case of the USA, in the left panel. After the s inequality in the USA started increasing, and eventually returned to the level of the pre-war period. We see that this U-shaped long-term trend of top income shares is not unique to the USA.
In fact the development in other English-speaking countries, also shown in the left panel, follows the same pattern.All material on this site has been provided by the respective publishers and authors.
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Please note that corrections may take a couple of weeks to filter through the various RePEc services. Economic literature: papersarticlessoftwarechaptersbooks. FRED data. My bibliography Save this paper. Registered: Thomas Piketty Emmanuel Saez. This Review presents basic facts regarding the long-run evolution of income and wealth inequality in Europe and the United States.
Income and wealth inequality was very high a century ago, particularly in Europe, but dropped dramatically in the first half of the 20th century. Income inequality has surged back in the United States since the s so that the United States is much more unequal than Europe today.
We discuss possible interpretations and lessons for the future. Download full text from publisher To our knowledge, this item is not available for download. To find whether it is available, there are three options: 1.
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Zero Growth and Long-Run Inequality
Corrections All material on this site has been provided by the respective publishers and authors. Louis Fed. Help us Corrections Found an error or omission?We estimate the long-run cointegrating relationship between schooling and income inequality using annual data from 48 contiguous U. Our study contributes to the literature in several ways in terms of data and empirical methodology.
First, we take into account integration and cointegration properties of the data and estimate the cointegrating relationship between schooling and income inequality using Fully Modified OLS FMOLS following Pedroni Second we investigate the direction of the causality.
Using several different measures of income inequality, we find that an increase in the average level of schooling decreases income inequality in the long-run and Granger causality runs from schooling to income inequality, not the other way around.
This is a preview of subscription content, access via your institution. Rent this article via DeepDyve. For a meta analysis of schooling and income inequality see Abdullah et al. See Sylwester b for a theoretical model of public spending on education and income inequality.
Atkinson Turner et al. Unfortunately, we are unable to control for several independent variables used in studies investigating income inequality such as share of population living in urban areas and share of female headed families in population because of data unavailability.
Data used in income inequality studies are mostly from the Current Population Survey CPS of the Census Bureau and state level data are available only after A meta-regression analysis. J Econ Surv 29 2 — Article Google Scholar. Amos O Unbalanced regional growth and regional income inequality in the latter stages of development.
Reg Sci Urban Econ 18 4 — Arellano M, Bond S Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev Econ Stud 58 2 — Atkinson A On the measurement of inequality.Bill Gates: How to Narrow the Gap of Inequality
J Econ Theory 2 3 — Econ Inq 44 1 — J Monet Econ 32 3 — Bergh A, Fink G Higher education policy, enrollment, and income inequality. Soc Sci Q 89 1 —New research shows that before the industrial revolution many more houses in south-east England had more fireplaces than houses in the Midlands and northern England. When Mrs Gaskell wrote North and Southshe reflected on a theme which was nearly two centuries old and which continues to divide England.
Since the s, historians have wanted to use the Restoration hearth tax to provide a national survey of distributions of population and wealth. But, for technical reasons until now, it has not been possible to move beyond city and county boundaries to make comparisons. This digital resource provides free access to the tax returns, with full transcription of the records and links to archival shelf marks and location by county and parish.
In the s and s, after London, the West Riding of Yorkshire and Norfolk stand out as densely populated regions. The early stages of industrialization meant that Leeds, Sheffield, Doncaster and Halifax were overtaking the former leading towns of Hull, Malton and Beverley.
But the empty landscapes of north and east Norfolk, enjoyed by holiday makers today, were also densely populated then. The hearth tax, as a nation-wide levy on domestic fireplaces, was charged against every hearth in each property, and the tax was collected twice a year at Lady Day March and Michaelmas September. In after 27 years it was abolished in perpetuity in England and Wales, but it continued to be levied in Ireland until the early nineteenth century and it was levied as a one- off tax in Scotland in Any property with three hearths and over was liable to pay the tax, and many properties with one or two hearths, such as those occupied by the ordinary poor, were exempt from the tax.
The destitute and those in receipt of poor relief were not included in the tax registers.
Wealth and Income Inequality in the Long Run of History
A family living in a home with one hearth had to use it for all their cooking, heating and leisure purposes, but properties with more than three hearths had at least one hearth in the kitchen, one in the parlour and one in an upstairs chamber.
In a substantial majority of parishes in northern England County Durham, Westmorland, the East and North Ridings of Yorkshire less than 20 per cent of households had three hearths and over, and only in the West Riding was there a significant number of parishes where 30 percent and more of households had three hearths and over. But, in southern England, across Middlesex, Surrey, southern Essex, western Kent and a patchwork of parishes across Norfolk, it was common for at least a third of the properties to have three hearths and over.
There are many local contrasts to explore further. South-east Norfolk and north-east Essex were notably more prosperous than north-west Essex, independent of the influence of London, and the patchwork pattern of wealth distribution in Norfolk around its market towns and prosperous villages is repeated in the Midlands. Nonetheless, the general pattern is clear enough: the distribution of population in the late seventeenth century was quite different from patterns found today, but Samuel Pepys and Daniel Defoe would have recognized a world in which south-east England abounded with the signs of prosperity and comfort in contrast to the north.
You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account. You are commenting using your Facebook account. Notify me of new comments via email. Notify me of new posts via email. Maps of England circaDarbie 10 of Eric R. Young's research interests are the macroeconomics of inequality, consumer finance, and computational economics.
To receive email when a new Economic Commentary is posted, subscribe. Using a basic model to study both wealth and income inequality and their relations to long-run economic growth may lead to questionable conclusions. We consider a more complex model that includes realistic variation in the levels of income and wealth across households in addition to a new ingredient, luck in each household's labor productivity. Using this model, we determine that existing estimates of the elasticity of substitution between capital and labor are generally far away from the region where inequality would explode if long-run growth were zero.
Inequality in wealth and income has become an issue of frequent debate, for not only policymakers but also the general public. Research by Thomas Piketty and co-authors has answered the question above in the affirmative; however, their work relies on strong assumptions about how the wealth distribution evolves and how the economy produces output. In a recent Federal Reserve Bank of Cleveland working paperwe explore the same question using modern macroeconomic models of income and wealth inequality, and we find that inequality is only weakly related to long-run economic growth.
What relationship is there tends to be negative rather than positive: income and wealth inequality tend to be lower when the long-run growth rate is zero i.
The direction of this relationship depends critically upon the degree to which capital and labor are interchangeable in production. When they are strong substitutes for each other, inequality can become very extreme, exactly as Piketty describes. On the other hand, when capital and labor are less interchangeable or when they work together, as the empirical literature strongly suggests, long-run inequality is lower under zero growth. As a result, while concerns about income and wealth inequality are understandable and warrant discussion, extreme inequality is not the likely outcome of low economic growth because capital and labor are not strong substitutes.
In our analysis, we draw on modern macroeconomic models of inequality that include a sophisticated treatment of the distribution of income and wealth. In particular, our models naturally give rise to distributions of income and wealth that respond to economic forces and do not require restrictive assumptions about a particular distribution. In a simplified version of the model, we find that a near-zero rate of long-run growth causes extreme income inequality only in calibrations of the model that are inconsistent with empirical evidence.
When we extend the model to include a more sophisticated treatment of income and wealth distributions, such as those found in real-world contexts, we find that zero growth has little effect on income and wealth inequality.
In fact, to the extent that different rates of trend growth are associated with changes in wealth inequality, lower growth tends to yield less inequality rather than more. It is helpful to introduce some fundamental concepts from the economic model.
The elasticity of substitution in production governs the ways in which capital and labor can be combined to produce the same level of output.Most of our information on wealth distribution and top incomes is derived from data on wealth left at death, recorded in probates and estate duty statistics.
Data for living millionaires are particularly valuable, given that even in the s millionaires often had considerable longevity, and data on wealth at death typically reflected fortunes made, or inherited, several decades previously.
The tax year to is a very useful bench-mark for assessing the impact of the First World War and its aftermath on the composition of the super-rich. Prior to the 20 th century, the highest echelons of wealth were dominated by the great landowners; reflecting a concentration of land-ownership unparalleled in Europe.
William Rubinstein found that the wealth of the greatest landowners exceeded that of the richest businessmen untilif not later. However, war-time inflation, higher taxes, and the post-war agricultural depression negatively impacted their fortunes. Meanwhile some industrialists benefitted enormously from the War. By business fortunes had pushed even the wealthiest aristocrats, the Dukes of Bedford and Westminster, into seventh and eighth place on the list of top incomes.
Moreover, the vast majority — These eight sectors collectively comprised Meanwhile important sectors such as chemicals, cotton and woollen textiles, construction, and, particularly, distribution, are substantially under-represented.
These included patents rayon ; control of distribution brewing and tobacco ; strong brands whiskey; branded packaged foods ; reputational assets merchant banking ; or membership of international cartels that granted territorial monopolies shipping; rayon. Instead, amalgamation or cartelisation were typically followed by rising real prices. Erecting or defending barriers to competition through cartels, mergers, and strategic assets may increase the number of very wealthy people, but unlikely to have generated a positive influence on national economic growth and living standards — unless accompanied by rationalisation to substantially lower costs.
In this respect typical inter-war business millionaires had strong commonalities with earlier, landed, British elites, in that they sustained their wealth through creating, and then perpetuating, scarcity in the markets for the goods and services they controlled.
Available here. Recent influential studies on the historical evolution of inequality and its causes Milanovic ; Piketty have attracted new interest in the topic. Yet, we do not know how differently this deceleration evolved across countries. Turbulent episodes during the first half of the twentieth century—including two World Wars, the Great Depression and the upsurge of radical parties—suggest that, at least in the short run, inequality may have followed very different patterns across European nations.
However, we have little empirical evidence, due to the lack of data on income distribution beforeespecially for the interwar years. In a forthcoming article we provide new annual data on income inequality for two leading European countries, Germany and Britain, for the first half of the twentieth century.
Using dynamic social tables, we obtain comparable annual estimates measured as Gini coefficients covering the full range of income distribution. Evidence from Germany and Britain Figure 1 yields two main results. First, the drop in inequality was neither steady nor similar across these countries, supporting the notion of inequality cycles Milanovic ; Prados de la Escosura Second, inequality trends in Germany and Britain tended to follow opposite patterns.
Figure 1. Inequality trends in Britain and Germany.