How is inequality measured, who produces key databases, and what does the data tell us?
Economic Inequality
How is inequality measured, who produces key databases, and what does the data tell us?
Global Inequality — Harvard University Press
Winner of the Bruno Kreisky Prize, Karl Renner InstitutA Financial Times Best Economics Book of the Year An Economist Best Book of the Year A Livemint Best Book of the YearOne of the world’s leading economists of inequality, Branko Milanovic presents a bold new account of the dynamics that drive inequality on a global scale. Drawing on vast data sets and cutting-edge research, he explains the benign and malign forces that make inequality rise and fall within and among nations. He also reveals who has been helped the most by globalization, who has been held back, and what policies might tilt the balance toward economic justice.“The data [Milanovic] provides offer a clearer picture of great economic puzzles, and his bold theorizing chips away at tired economic orthodoxies.”—The Economist“Milanovic has written an outstanding book…Informative, wide-ranging, scholarly, imaginative and commendably brief. As you would expect from one of the world’s leading experts on this topic, Milanovic has added significantly to important recent works by Thomas Piketty, Anthony Atkinson and François Bourguignon…Ever-rising inequality looks a highly unlikely combination with any genuine democracy. It is to the credit of Milanovic’s book that it brings out these dangers so clearly, along with the important global successes of the past few decades.—Martin Wolf, Financial Times
Is Inequality Inevitable?
Wealth naturally trickles up in free-market economies, model suggests
AI Adoption and Inequality
There are competing narratives about artificial intelligence’s impact on inequality. Some argue AI will exacerbate economic disparities, while others suggest it could reduce inequality by primarily disrupting high-income jobs. Using household microdata and a calibrated task-based model, we show these narratives reflect different channels through which AI affects the economy. Unlike previous waves of automation that increased both wage and wealth inequality, AI could reduce wage inequality through the displacement of high-income workers. However, two factors may counter this effect: these workers’ tasks appear highly complementary with AI, potentially increasing their productivity, and they are better positioned to benefit from higher capital returns. When firms can choose how much AI to adopt, the wealth inequality effect is particularly pronounced, as the potential cost savings from automating high-wage tasks drive significantly higher adoption rates. Models that ignore this adoption decision risk understating the trade-off policymakers face between inequality and efficiency.
The Divide — Jason Hickel
The Divide: A Brief Guide to Global Inequality and its Solutions Penguin Random House UK, 2017
The Origin and Future of Economic Inequality
Programmed Inequality
In 1944, Britain led the world in electronic computing. By 1974, the British computer industry was all but extinct. What happened in the intervening thirty y...
Wage Compression Drives Nordic Income Equality
Income inequality in the Nordic countries — Denmark, Finland, Norway, and Sweden — is substantially lower than in the United States or the United Kingdom despite similar levels of per capita income. The Gini coefficient for disposable income in Nordic countries averages 0.27, compared to 0.39 in the US and 0.36 in the UK. In Income Equality in the Nordic Countries: Myths, Facts, and Lessons (NBER Working Paper 33444), Magne Mogstad, Kjell G. Salvanes, and Gaute Torsvik analyze the underlying source of these disparities. They employ detailed microeconomic data and statistical decomposition techniques and consider distributional statistics on income, wages, working hours, education, and skills across these countries.
Thomas Piketty Knew This Was Coming
The scholar of inequality warned us that our economic systems couldn’t withstand a global catastrophe.
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
Many powerful computing technologies rely on implicit and explicit data contributions from the public. In this paper, we synthesize emerging research that seeks to better understand and help people action this data leverage. Drawing on prior work in areas including machine learning, human-computer interaction, and fairness and accountability in computing, we present a framework for understanding data leverage that highlights new opportunities to change technology company behavior related to privacy, economic inequality, content moderation and other areas of societal concern.
Power Laws, Weblogs, and Inequality - Clay Shirky
Diversity plus freedom of choice creates inequality.
Keys to Economic Systems - GDKeys
Currencies, sources, sinks, inflation, economic tools, currency protections, economic pillars... In this extensive "Keys to" article we tackle everything you need to know to create your very own, efficient, and self-sustaining economic systems!
Extreme Inequality Presages The Revolt Against It
Even the Davos elites are reading the tea leaves.
New Capitalism II: Compositional vs income inequality
Are all class-based societies unequal?
Are new technologies fuelling wage inequality? Evidence from Spain
New research shows the net effect of technological change (incl. artificial intelligence) on wages in Spain has been to fuel rising wage inequalities
