Presentation on theme: "JAMES K. GALBRAITH THE UNIVERSITY OF TEXAS AT AUSTIN & LEVY ECONOMICS INSTITUTE FOR THE INSTITUTE FOR NEW ECONOMIC THINKING INAUGURAL CONFERENCE APRIL."— Presentation transcript:
JAMES K. GALBRAITH THE UNIVERSITY OF TEXAS AT AUSTIN & LEVY ECONOMICS INSTITUTE FOR THE INSTITUTE FOR NEW ECONOMIC THINKING INAUGURAL CONFERENCE APRIL 10, 2010 Inequality in the World Economy
A few words from the Master “For my own part, I believe that there is social and psychological justification for significant inequalities of incomes and wealth, but not for such large disparities as exist today. Moreover, dangerous human proclivities can be canalised into comparatively harmless channels by the existence of opportunities for money-making…. It is better that a man should tyrannize over his bank balance than over his fellow- citizens…. But it is not necessary… that the game should be played for such high stakes as at present. (1936, 374)
Inequality as Global Macroeconomics At the national level, inequality is a curvilinear function of income level – a matter of macroeconomics, not microeconomics. Changes in inequality are driven in part by changing inter-sectoral terms of trade. The dominant movements in global pay inequality reflect changing financial regimes Global factors dominate the picture. In the US, the stock market has driven income inequality.
A Stylized “Augmented Kuznets Curve”
Brazil on the Kuznets Curve Rate of Economic Growth`
Sources of Global Data Rich geographic and sectoral data sources in the US, including Local Area Personal Income, SIC, NAICS Goskomstat, China State Statistical Yearbook, and other national data sources Eurostat for regional data in Europe UNIDO Industrial Statistics (source of maps following) and other global data sources: ~3200 country-year observations Common method: Between-groups component of Theil’s T Statistic
Global Movement of Inequality Brown: Very large decreases in inequality; more than 8 percent per year. Red Moderate decreases in inequality. Pink: Slight Decreases. Light Blue: No Change or Slight increases Medium Blue: Large Increases -- Greater than 3 percent per year. Dark Blue: Very Large Increases -- Greater than 20 percent per year.
1963 to 1969
1970 to 1976 The oil boom: inequality declines in the producing states, but rises in the industrial oil-consuming countries, led by the United States.
1977 to 1983
1981 to 1987 … the Age of Debt Note the exceptions to rising inequality are mainly India and China, neither affected by the debt crisis… Start of the “Super-Bubble ”
1984 to 1990
1988 to 1994 The age of globalization… Now the largest increases in inequality in are the post-communist states; an exception is in booming Southeast Asia, before 1997…
Debt Crisis End of Bretton Woods 9/11 “Concept 4” Inequality: The Common Movement of Inequality Measured within Countries, Across Time Note: The vertical axis represents the time element in a two-way fixed effects panel regression, across the panel of country-year observations. Vertical scale is log(T) units. Source: Kum Milanovic Concept 1 Profit Share in OECD The Super Bubble
Note: Bands indicate two standard deviations of country observations within each year shown. OECD and non-OECD countries shown separately. Vertical scale is log(T) units. Source: Galbraith and Kum, What would have happened without the Global Element?
Did Loose Monetary Policy Cause the Super- Bubble? “… even if we were to suppose that contemporary booms are apt to be associated with a momentary condition of full investment or over-investment in the strict sense, it would still be absurd to regard a higher rate of interest as the appropriate remedy. For in this event the case of those who attribute the disease to under-consumption would be wholly established. The remedy would lie in various measures designed to increase the propensity to consume by the redistribution of incomes or otherwise…” (1936, 324)
China: Contributions to inequality by Province Beijing Contributions to a Theil T-Statistic, measured across provinces
The US: Inequality in Pay and Unemployment, Inequality measured on earnings across industries in manufacturing, monthly data; recessions entered in gray.
The US: Income Inequality and the NASDAQ, Income inequality measured between counties, from tax data Tax Reform Act Internet Bubble Inequality Log of NASDAQ
This broad picture of the world economy from the standpoint of inequality measure suggests that the “super-bubble” was also, for most of the world’s population, a “super-crisis.” The super-bubble came to a peak in The period since then was marked in the United States by efforts to keep the bubble going, in part through aggressive efforts to relax standards, which may be described as the growth of a “predator state.” This led to the corruption of the financial markets whose collapse produced the great crisis.
A final word from the Master “In so far as millionaires find their satisfaction in building mighty mansions to contain their bodies when alive and pyramids to shelter them after death, or, repenting of their sins, erect cathedrals and endow monasteries or foreign missions, the day when the abundance of capital will interfere with abundance of output may be postponed… It is not reasonable, however, that a sensible community should be content to remain dependent on such fortuitous and often wasteful mitigations when once we understand the influences upon which effective demand depends.” (1936, 220)
Type “Inequality” into Google; you’ll get ~17,900,000 hits: we’re #11 as of last week in the US; ahead of Harvard, Stanford and Cornell. New peer review for new thinking…