Category Archives: Economics

@BillMoyersHQ Preview: #TooBigtoFail and Getting Bigger

In Washington, DC a bi-partisan effort is underway to chip away at the 2010 Dodd-Frank financial reform law, which is supposed to prevent the type of economic meltdown that brought the world to the brink in 2008.

Wall Street banks are lobbying to de-fang sections of the law related to derivatives — the complex financial contracts at the core of the meltdown. One deregulation bill, the “London Whale Loophole Act,” would allow American banks to skip Dodd-Frank’s trading rules on derivatives if they are traded in countries that have similar regulatory structures. Continue reading @BillMoyersHQ Preview: #TooBigtoFail and Getting Bigger

Moisés Naím: The Problem With Piketty’s Inequality Formula – The Atlantic

Moises NaimWho is to blame for the dramatic rise in inequality in recent years? The bankers, many people say. According to this view, the financial sector is guilty of triggering the global economic crisis that began in 2008 and still affects millions of middle-class families in Europe and the United States, who’ve seen their purchasing power diminish and job prospects wither. The outrage is amplified by the fact that not only have the bankers and financial speculators escaped punishment for their blunders, but many are now even richer than they were before the crash. Others blame growing inequality on wages in countries like China and India, where low salaries depress incomes of workers in the rest of the world. Asia’s cheap labor compounds the problem because it creates unemployment in countries where companies close factories and “export” jobs to cheaper markets overseas. Still others see technology as the culprit. Robots, computers, the Internet, and greater use of machines in factories, they say, are replacing workers and thus boosting inequality.

The true explanation is a lot more complicated, says Thomas Piketty, the French economist whose influential Capital in the Twenty-First Century has turned into a global sensation. In many countries, Piketty argues, capital (which he equates with wealth in the form of real estate, financial assets, etc.) is growing at a faster rate than the economy. The income produced by capital tends to be concentrated in the hands of a small group of people, whereas income from labor is dispersed throughout the entire population. Therefore, when capital earnings increase faster than wages, inequality grows because those who own capital accumulate a higher proportion of income. And given that growth in wages is directly dependent on the growth of the economy as a whole, economic inequality is bound to get worse if the economy expands at a slower clip than capital earnings.

Piketty summarizes this complicated theory with the formula “r > g” where “r” is the rate of return on capital and “g” is the rate of growth in the economy. The future is dire, he concludes, because he expects the economies of the countries he surveyed to grow at a rate of 1 to 1.5 percent per year, while the average return on capital increases at a rate of 4 to 5 percent per year. Inequality, in other words, is bound to rise. To avoid this, Piketty calls for a progressive tax on wealth in large countries—an idea that even he concludes is utopian. He acknowledges the enormous political hurdles that his proposal would face and the huge practical difficulties that would accompany its implementation. Last week, the Financial Times claimed that it had found grave defects in Piketty’s work, provoking an ongoing debate about his analysis. Nonetheless, most impartial observers believe that the issues with Piketty’s data are not serious enough to completely discredit his overall conclusions.

[. . .]

In order for this discussion to be valuable, however, the problem requires a more complete diagnosis. It is not accurate to assert that in countries like Russia, Nigeria, Brazil, and China, the main driver of economic inequality is a rate of return on capital that is larger than the rate of economic growth. A more holistic explanation would need to include the massive fortunes regularly created by corruption and all kinds of illicit activities. In many countries, wealth grows more as a result of thievery and malfeasance than as a consequence of the returns on capital invested by elites (a factor that is surely at work too).

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@Wonkblog: What our reasons for moving say about the state of the economy

By Emily Badger

The decision to move is an intensely personal and revealing one. We move homes because we lost a job or found a new one, because a new child was born or an older one finally left for college. We move because we have to, following a foreclosure, or because we can afford to, in search of a nicer place.

So many of life’s milestones — good or bad, qualifying for a first mortgage, surviving a hurricane — are accompanied by a moving van. In the aggregate, this means that we can add up all of the reasons why Americans move in a given year and glean something about what’s going on in their lives, and even, by extension, the economy.

Take the the 35.9 million people who moved between 2012 and 2013, according to the Census Bureau — either just down the block, into a new county or much farther away. Data from the Annual Social and Economic Supplement of the Current Population Survey reveals that, among their householders, 8.4 percent moved last year in search of cheaper housing. According to the data, 1.8 percent moved because of a foreclosure or eviction. Asked to pick the one reason that most contributed to their decision to move, 1.6 percent said they moved to look for work or because they lost a job.

Continue reading @Wonkblog: What our reasons for moving say about the state of the economy

Where’s the Automation in the Productivity Accounts? | Jared Bernstein (@EconJared)|

Yesterday’s productivity report for 2014q1 was predictably negative—we already knew that real GDP fell in the quarter while employment grew apace—but I don’t read much into the noisy quarterly changes.

But then there’s this: year-over-year, productivity growth was up 1% last year and has averaged 0.8% since 2011. The figure below plots the yearly changes, which are themselves pretty noisy. What’s more instructive is the smooth trend through the numbers.

The trend suggests that the pace of productivity growth has decelerated since the first half of the 2000s and this begs an important question. There’s considerable speculation that the pace at which machines are displacing workers has accelerated. I keep hearing about “the end of work” based on the assumption that the pace of labor-saving technology—robots, AI—has accelerated.

Continue reading Where’s the Automation in the Productivity Accounts? | Jared Bernstein (@EconJared)|