A new dataset for charting the development of global inequality between 1820 and 2000 is presented, based on a large variety of sources and methods for estimating (gross household) income inequality. On this basis we estimate the evolution of global income inequality over the past two centuries. Two sets of benchmarks about between‐country inequality (the Maddison 1990 benchmark and the recent 2005 ICP round) are taken into account. We find that between 1820 and 1950, increasing per capita income is combined with increasing global inequality. After 1950, global inequality as measured by the Gini coefficient or the Theil index remains more or less constant. It also appears that the global income distribution was uni‐modal in the nineteenth century, became increasingly bi‐modal between 1910 and 1970 with two world wars, a depression and de‐globalization, and was suddenly transformed back into a uni‐modal distribution between 1980 and 2000.
To date, the rise and fall of the (former) USSR has triggered a lot of research much of which has focussed on the accumulation of physical capital, growth, and consumption. Recently, also the accumulation of human capital has increasingly been incorporated in this picture. However, few datasets exist that cover this crucial variable for this vast area. Therefore, our main objective is to make available a new dataset that contains human capital related time-series for the USSR (and the Newly Independent States (NIS) after its dissolution), constructed mostly on an annual basis. These data are drawn together from various primary sources, available datasets and secondary literature where our focus was on constructing a dataset as consistent as possible. It is our hope that, by supplying these data in electronic format, it will significantly advance quantitative economic history research on Russia and all over the former Soviet Union area (FSU) and will inspire further research in various new fields relating to intellectual production. The data presented in this paper follow after the discussion of the information value of the primary sources utilised, and the various problems that arose when linking and splicing the data from various sources. After constructing series of human capital indicators we perform a time-series and spatial analysis in order to identify the long-term trends of education penetration and of the human capital development in the FSU area with a strong emphasis on inequality issues between the NIS. Applying these results in a simple growth accounting framework provides us with some preliminary insights on the role of human capital in economic development in the FSU area.
Personal security reflects a crucial component of well-being. This chapter relies on homicide rates (the number of intentional deaths per 100 000 inhabitants) to trace changes of violence in time and space. It finds that Western Europe was already quite peaceful from the 19th century onwards, but homicide rates in the United States have been high by comparison. Large parts of Latin America and Africa are also violent crime "hotspots", and so is the former Soviet Union (especially since the fall of communism), while large parts of Asia show low homicide rates. Homicide rates are in general negatively correlated with GDP per capita-the richer a country, the lower the level, but there are important exceptions. In addition, the chapter describes changes in the probability that a random individual lives in a country experiencing an armed internal or external conflict.
We estimate inequality in Indonesia between 1932 and 2008. Inequality increased at the start of this period but declined sharply from the 1960s onwards. The increase was due to a shift from domestic to export agriculture over the period up to the Great Depression. During the 1930s, as the price of export crops declined, the income of rich farmers suffered a blow. Yet this was counterbalanced by an increasing gap between expenditures in the urban and rural sectors, causing an overall rise in inequality. As for the second half of the century, we find that the employment shift towards manufacturing and services-combined with an increase in labour productivity in agriculture-accounts for inequality's decline, which was halted in the 1990s. These inequality trends affected poverty as well, but prior to the 1940s the negative impact of the rise in inequality was offset by an increase in per capita GDP.Between 1950 and 1980 a decline in inequality, combined with increased per capita GDP, rapidly raised a large portion of the population above the poverty line.
There is a general consensus that human capital is a major factor behind long‐run economic growth. Yet, on a macro level, the empirical results do not always seem to concur with this view. To explain this gap between theory and empirics, more focus has been laid on measurement error and data quality. Using an alternative estimate of the stock of human capital, based on Judson (2002), we find evidence that the two major views on the role of human capital in economic development by Lucas (1988) and Romer (1990) coexist and are by no means mutually exclusive. Using a Johansen cointegration test, we find that in India and Indonesia the level of human capital is cointegrated with the level of aggregate income during the whole 20th century, which confirms the theory of Lucas (1988). In Japan, however, the Lucasian approach can be verified only for the first half of the century, while after 1950 there is cointegration between the growth rate of aggregate income and the level of human capital, which is in line with Romer's view.
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