The Unassuming Economist

Chris Wellisz profiles Branko Milanovic, a leading scholar of inequality for the March 2019 issue of Finance & Development:

“As a child growing up in Communist Yugoslavia, Branko Milanovic witnessed the protests of 1968, when students occupied the campus of the University of Belgrade and hoisted banners reading “Down with the Red bourgeoisie!”

Milanovic, who now teaches economics at the City University of New York, recalls wondering whether his own family belonged to that maligned group. His father was a government official, and unlike many Yugoslav kids at the time, Milanovic had his very own bedroom—a sign of privilege in a nominally classless society. Mostly he remembers a sense of excitement as he and his friends loitered around the edge of the campus that summer, watching the students sporting red Karl Marx badges.

“I think that the social and political aspects of the protests became clearer to me later,” Milanovic says in an interview. Even so, “1968 was, in many ways, a watershed year” in an intellectual journey that has seen him emerge as a leading scholar of inequality. Decades before it became a fashion in economics, inequality would be the subject of his doctoral dissertation at the University of Belgrade.

Today, Milanovic is best known for a breakthrough study of global income inequality from 1988 to 2008, roughly spanning the period from the fall of the Berlin Wall—which spelled the beginning of the end of Communism in Europe—to the global financial crisis.

The 2013 article, cowritten with Christoph Lakner, delineated what became known as the “elephant curve” because of its shape (see chart). It shows that over the 20 years that Milanovic calls the period of “high globalization,” huge increases in wealth were unevenly distributed across the world. The middle classes in developing economies—mainly in Asia—enjoyed a dramatic increase in incomes. So did the top 1 percent of earners worldwide, or the “global plutocrats.” Meanwhile, the lower middle classes in advanced economies saw their earnings stagnate.

The elephant curve’s power lies in its simplicity. It elegantly summarizes the source of so much middle class discontent in advanced economies, discontent that has turbocharged the careers of populists from both extremes of the political spectrum and spurred calls for trade barriers and limits on immigration.”

Continue reading here.

A new IMF working paper revisits ” the issue of classification errors in the U.S. Current Population Survey. While the results still support the previous literature’s conclusion that the job finding probability plays a more important role in explaining unemployment fluctuations (“outs of unemployment”) than the job separation probability does (“ins to unemployment”), they moderate the conclusion that “Out Wins”. Moreover, once the proposed adjustment is applied, the importance of the participation margin in explaining unemployment fluctuations becomes smaller than previously argued—around 10 percent in this paper vs previous estimates of 20 to 30 percent (Elsby, Hobijn and Sahin, 2015). Therefore, the misclassification correction procedures in the labor force survey continue to be an important issue in understanding labor market dynamics. The results of this paper suggest that policymakers should pay closer attention to the job separation margin than previously thought and less on the participation margin.”

From a new post by Timothy Taylor:

“A lot of people have heard, one way or another, that the country of Bhutan decided back in the early 1970s to pursue Gross National Happiness. The King at that time is supposed to have said:  “Gross National Happiness is more important than Gross Domestic Product.” But in practical terms, what does that actually mean?”

[…]

“1) It is bog standard economics that GDP was never intended to measure happiness, nor to measure broader social welfare. Any intro econ textbook makes the point.  A well-known comment from “Robert Kennedy on Shortcomings of GDP in 1968” (January 30, 2012) make the point more poetically. But for those who need a reminder that social welfare is based on a wide variety of outcomes, not just GDP, I suppose a reminder about Gross National Happiness might be useful.

2) Bhutan’s measurement of 124 weighted indicator variables, and their distribution through the population,  is probably about as good a way of measuring Gross National Happiness as any other, and better than some. But it’s also pretty arbitrary in its own way.

3) The interesting question about GDP and social welfare isn’t whether they are identical, but whether they tend to rise together in a broad sense. For example, countries with higher per capita income also tend to have more education and health care, better housing and nutrition, more participatory governance, and a variety of other good things. .A few years ago I wrote about “GDP and Social Welfare in the Long Run” (April 6, 2015), or see “Why GDP Growth is Good” (October 11, 2012).

4) “Happiness” is of course a tricky subject, which is why it’s the stuff of literature and love.  After a lot of consideration, Daniel Kahneman has argued that “people don’t want to be happy.”  Instead, they want to have a satisfactory narrative that they can tell themselves about how their life is unfolding. If incomes, education, and life expectancy rise over, say, 40-50 years but on a scale of 1-10 people don’t express greater “happiness” with their live, does that really mean they would be equally happy with lower incomes, education and life expectancy–especially if other countries in the world were continuing to make gains on these dimensions? There is an ongoing argument over whether those who have higher income express more happiness because they get to consume more, or because they feel good about comparing themselves who are worse off. It’s easy to say that “money doesn’t bring happiness,” and there’s some truth in the claim. But for most of us, if we lived in a country with lower income levels and could watch the rest of the world through the internet and television, it would bug us at least a little, now and then.

It seems to me easy enough to make the case that looking at Gross National Happiness as is better than an exclusive focus on doing nothing but boosting short-term GDP. But outside the fictional mustachio-twirling econo-villains of anti-capitalist comic books, no one actually believes in an exclusive focus on GDP. For me as an outsider, it’s hard to see how Gross National Happiness has made Bhutan’s development strategy different. After all, lots of countries at all income levels emphasize lots of goals other than short-term GDP. And the government of Bhutan pays considerable attention to GDP, as the authors note, “While there is importance given to GNH in Bhutan, governmental organizations (especially commerce related ones) focus keen attention on GDP and how it measures trade, commerce and the economic prosperity of the country. In addition, the IMF has provided a great deal of technical assistance to Bhutan to help improve its national accounts …”

My own favorite comment on the connection from GDP to social welfare is from a 1986 essay by Robert Solow (“James Meade at Eighty,” Economic Journal, December 1986, pp. 986-988), where he wrote: “If you have to be obsessed by something, maximizing real National Income is not a bad choice.” At least to me, the clear implication is that it’s perhaps better not to be obsessed by one number, and instead to cultivate a broader and multidimensional perspective. If you want to refer to that mix of statistics as Gross National Happiness, no harm is done. But yes, if you need to pick one number out of all the rest (and again, you don’t!), real per capita GDP isn’t a bad choice. To put it another way, a high or rising GDP certainly doesn’t assure a high level of social welfare, but it makes it easier to accomplish those goals than a low and falling GDP.”

From a new VOX post:

“The role of exchange rate policies in economic development is still largely debated. This column argues that there are theoretical foundations for policies that guarantee competitive and stable real exchange rates. When there are constraints on the available set of policy instruments, the complementary use of competitive exchange rates with export taxes for traditional export sectors would result in effectively multiple real exchange rates. The empirical evidence suggests that both foreign exchange interventions and capital account regulations can be effectively used for maintaining competitive exchange rates and for dampening the effects of boom-bust cycles in external financing and the terms of trade on the exchange rate, thereby promoting growth and stability.”

“A variety of historical experiences support the claim that stable and competitive real exchange rate (SCRER) policies are good for economic development (Rodrik 2008, Razmi et al. 2012). We have argued that there are theoretical foundations for such an approach as an optimal policy strategy in the presence of certain constraints on the available set of policy instruments. The main argument against such interventions – that they represent interference in the free functioning of markets, which, in the absence of such intervention would ensure efficiency – misses two fundamental points:

1. every central bank intervention, including the setting of interest rates, affects the value of the exchange rate; this means, in fact, that there is no such thing as a ‘pure’ market exchange rate; and
2. all economies, and especially developing and emerging markets, are rife with market imperfections, including learning and macroeconomic externalities.

Our analysis of the empirical evidence on the effectiveness of different policy instruments suggests that both foreign exchange interventions and capital account regulations can be effectively used for maintaining competitive exchange rates and for dampening the effects of boom-bust cycles in external financing and the terms of trade on the exchange rate, thereby promoting growth and stability.”

From a new VOX post:

“Short-time work schemes are a fiscal stabiliser in Europe. Between 2010 and 2013, they were used by 7% of firms, employing 9% of workers in the region. This column uses ECB data to show that firms use the schemes to offset negative shocks and retain high-productivity workers. High firing costs and wage rigidity increase the use of short-time work, which in turn reduces the fall in employment brought on by a recession.”

“STW clearly shelters individual workers or firms from the worst effects of recessions. The question of whether it has a significant aggregate impact is the focus of several country-specific papers (Balleer et al. 2016, for Germany, is one example).

To answer this question using the WDN3 data, we divide countries and sectors into those with high levels of STW take-up (in which more than 10% of firms use STW in the country-sector) and those with low levels (in which fewer than 1% of firms use STW). Using Eurostat data on employment and output per sector from 2008-13, we then estimate the response of employment to falls in output for high- and low-STW sectors.

Figure 5 shows the results in the form of the responses of employment to a 1% fall in output. The fall in employment is considerably lower for high-STW sectors, where it peaks at 0.12% after three to four quarters. In low-STW sectors, by contrast, the employment fall peaks at the much higher level of almost 0.40%,after just two quarters. This suggests that STW can have significant aggregate effects, smoothing changes in overall employment through the cycle.”