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Europe's growth will have to be golden in yet another sense. Economic prosperity has brought to Europeans the gift of longer lives, and the continent's population has aged a lot over the last five decades. Over the next five, it will age even more by 2060; almost a third of Europeans will be older than 65 years. Europe will have to rebuild its structures to make fuller use of the energies and experience of its more mature population's people in their golden years. These desires and developments already make the European growth model distinct. Keeping to the discipline of the golden rule would make it distinguished. This report shows how Europeans have organized the six principal economic activities trade, finance, enterprise, innovation, labor, and government in unique ways. But policies in parts of Europe do not recognize the imperatives of demographic maturity and clash with growth's golden rule. Conforming growth across the continent to Europe's ideals and the iron laws of economics will require difficult decisions. This report was written to inform them. Its findings the changes needed to make trade and finance will not be as hard as those to improve enterprise and innovation; these in turn are not as arduous and urgent as the changes needed to restructure labor and government. Its message the remedies are not out of reach for a part of the world that has proven itself both intrepid and inclusive.

In July 1986, Warren C. Baum was interviewed on behalf of the World Bank Group Archives oral history program by Robert W. Oliver. Mr. Baum earned a PhD in economics from Harvard University, and he joined the World Bank after working on the Marshall Plan with the US Government, During his tenure at the Bank from 1959 to 1986, Mr. Baum worked in the following areas: in the Europe, Africa and Australasia department as an economist/loan officer (1959-1962); in the department of operations, Europe, as a loan officer (1962-1964); in the projects department, transportation, as an assistant director (1964-1968) and associate director (1968-1972); as vice president of projects staff (1972-1974); as chairman of the consultative group on international agricultural research (1974-1984); and in operations policy as a vice president (1982-1986). His transcript concerns his time working on projects for France, Algeria, Spain, and Portugal, as well as becoming a liaison between the projects department and the transportation division. His appreciation of the unique experience inspired him to write two books on the work of the World Bank, Investing in Development: Lessons of World Bank Experience and Partners Against Hunger.

Income modeling is crucial in determining workers’ earnings and is an important research topic in labor economics. Traditional regressions based on normal distributions are statistical models widely applied. However, income data have an asymmetric behavior and are best modeled by non-normal distributions. The objective of this work is to propose parametric quantile regressions based on two asymmetric income distributions: Dagum and Singh–Maddala. The proposed quantile regression models are based on reparameterizations of the original distributions by inserting a quantile parameter. We present the reparameterizations, properties of the distributions, and the quantile regression models with their inferential aspects. We proceed with Monte Carlo simulation studies, considering the performance evaluation of the maximum likelihood estimation and an analysis of the empirical distribution of two types of residuals. The Monte Carlo results show that both models meet the expected outcomes. We apply the proposed quantile regression models to a household income data set provided by the National Institute of Statistics of Chile. We show that both proposed models have good performance in model fitting. Thus, we conclude that the obtained results favor the Singh–Maddala and Dagum quantile regression models for positive asymmetrically distributed data related to incomes. The economic implications of our investigation are discussed in the final section. Hence, our proposal can be a valuable addition to the tool-kit of applied statisticians and econometricians.

This paper provides an evaluation of the main income distribution databases in Latin America: the CEPALSTAT and the SEDLAC databases. Alhough they rely on the same household surveys conducted by national statistical offices in the region, the indicators reported in the two databases differ substantially in a number of cases. Those differences come from distinct adjustments made to the original data, in particular an adjustment to National Accounts aggregate income data in the CEPALSTAT database. Based on this comparison, the paper then provides a general discussion of the adjustment of household survey data to National Accounts as well as other issues which may be responsible for biases in the way inequality is estimated and reported.

The paper provides estimates of global relative poverty trends from 1970 onwards. Relative poverty is shown to have decreased significantly, but at the same time there has been a worsening poverty outcome among up to one billion of the world's poorest citizens. The paper also proposes a straightforward method for dividing an income distribution into classes of poor, rich, and middle-class.

This chapter contains sections titled: Introduction Consumer Demand Systems Miscellaneous Applications Compositional Time Series New Directions Conclusion References

This paper presents new findings on global inequality dynamics from the World Wealth and Income Database (WID.world), with particular emphasis on the contrast between the trends observed in the United States, China, France, and the United Kingdom. We observe rising top income and wealth shares in nearly all countries in recent decades. But the magnitude of the increase varies substantially, thereby suggesting that different country-specific policies and institutions matter considerably. Long-run wealth inequality dynamics appear to be highly unstable. We stress the need for more democratic transparency on income and wealth dynamics and better access to administrative and financial data.

This article combines tax, survey, and national accounts data to estimate the distribution of national income in the United States since 1913. Our distributional national accounts capture 100% of national income, allowing us to compute growth rates for each quantile of the income distribution consistent with macroeconomic growth. We estimate the distribution of both pretax and posttax income, making it possible to provide a comprehensive view of how government redistribution affects inequality. Average pretax real national income per adult has increased 60% from 1980 to 2014, but we find that it has stagnated for the bottom 50% of the distribution at about $16,000 a year. The pretax income of the middle class—adults between the median and the 90th percentile—has grown 40% since 1980, faster than what tax and survey data suggest, due in particular to the rise of tax-exempt fringe benefits. Income has boomed at the top. The upsurge of top incomes was first a labor income phenomenon but has mostly been a capital income phenomenon since 2000. The government has offset only a small fraction of the increase in inequality. The reduction of the gender gap in earnings has mitigated the increase in inequality among adults, but the share of women falls steeply as one moves up the labor income distribution, and is only 11% in the top 0.1% in 2014.

Objective. Since 2008, the Standardized World Income Inequality Database (SWIID) has provided income inequality data that seek to maximize comparability while providing the broadest possible coverage of countries and years. This article describes the current SWIID’s construction, highlighting differences from its original version, and reevaluates the SWIID’s utility to cross-national income inequality research in light of recently available alternatives. Methods. Coverage of inequality data sets is assessed across country-years; comparability is evaluated in terms of success in predicting the Luxembourg Income Study (LIS), recognized in the field as the gold standard in comparability, before those data are released. Results. The SWIID offers coverage double that of the next largest income inequality data set, and its record of comparability is three to eight times better than those of alternate data sets. Conclusions. As its coverage and comparability far exceed those of the alternatives, the SWIID remains better suited for broadly cross-national research on income inequality than other available sources.

Using unique linked data, we examine income inequality and mobility across racial and ethnic groups in the United States. Our data encompass the universe of income tax filers in the United States for the period 2000-2014, matched with individual-level race and ethnicity information from multiple censuses and American Community Survey data. We document both income inequality and mobility trends over the period. We find significant stratification in terms of average incomes by racial/ethnic group and distinct differences in within-group income inequality. The groups with the highest incomes—whites and Asians—also have the highest levels of within-group inequality and the lowest levels of within-group mobility. The reverse is true for the lowest-income groups: blacks, American Indians, and Hispanics have lower within-group inequality and immobility. On the other hand, low-income groups are also highly immobile in terms of overall, rather than within-group, mobility. These same groups also have a higher probability of experiencing downward mobility compared with whites and Asians. We also find that within-group income inequality increased for all groups between 2000 and 2014, and the increase was especially large for whites. The picture that emerges from our analysis is of a rigid income structure, with mainly whites and Asians positioned at the top and blacks, American Indians, and Hispanics confined to the bottom.