Flat Phills, all around [feedly]

Flat Phills, all around
http://jaredbernsteinblog.com/flat-phills-all-around/

I've got a piece in today's WaPo on the diminished correlation between the tightening labor market and wage and price growth. This is evidence of the well-known flattening of the "Phillips Curve," the statistical relationship between nominal wages, prices, and tightness in the job market.

The figure below shows annualized growth rates of a) core PCE inflation and b) nominal wages of blue-collar factory workers and non-managers in services over numerous periods of falling unemployment. Since the 1980s, those growth rates have been falling. In the current episode of falling unemployment, price growth has been particularly slow. Those familiar with this phenomenon will recognize this observation as the flipside of the question we were asking when unemployment was 10 percent: "why isn't the rate of inflation falling."

Source: BLS, BEA

My WaPo piece gets into the why's and why-this-matters. Here, I just wanted to post some complementary evidence.

A simple model does a decent job of predicting yearly changes in the ECI wage index. The model includes two lags of the dependent variable and a measure of full employment: u-u*, or unemployment minus the CBOs estimate of the full employment rate.

The figure shows that the model tracks wage growth through the tight-labor market of the 1990s, but over-predicts in the 2000s. Toward the end of the series, there's a hint that ECI wage growth may start to underperform the forecast.

The growth in the blue-collar, non-managerial hourly wage has also flattened in recent months, even as the job market has tightened further (the smooth line is a 6-mos moving average).

Finally, Kalman filtering is a useful statistical technique to test whether and how much an economic relationship–in this case, the correlation between ECI wage growth and u-u*, or labor market tightness–is changing over time. The last figure shows that in a model with yearly ECI changes as the dependent variable, the coefficient on u-u* has drifted up and is about zero now. Moreover, the upward drift accelerated a lot in the last few years.

I say what I think this means–and cite many explanations from others whom I bugged about it–in Monday's paper. But the facts of the case look pretty solid to me, at least for now.

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Chart of the Week: Conflict’s Legacy for Growth [feedly]

Chart of the Week: Conflict's Legacy for Growth
https://blogs.imf.org/2017/05/08/chart-of-the-week-conflicts-legacy-for-growth/

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A New Twist in the Link Between Inequality and Economic Development [feedly]

A New Twist in the Link Between Inequality and Economic Development
https://blogs.imf.org/2017/05/11/a-new-twist-in-the-link-between-inequality-and-economic-development/

By Francesco Grigoli

May 11, 2017

Version in Español (Spanish)

Much has been written about the relationship between inequality and economic development, but theory remains inconclusive. When income is more concentrated in the hands of a few individuals, this can lead to less demand by the general population and lower investment in education and health, impairing long-term growth. At the same time, a certain level of inequality endows the rich with the means to start businesses, and creates incentives to increase productivity and investment, promoting economic activity. But the initial inequality levels also matter to explain why an increase in inequality varies in its impact on economic development across countries.

Empirical research assumes that the relationship between inequality and economic development stays the same no matter where a country is on the inequality scale, as measured by the Gini coefficient (which ranges from zero, when everyone has the same income, to 100, when a single individual receives all the income).

In two recent papers—Inequality Overhang and Inequality and Growth: A Heterogeneous Approach—we dig deeper into the direction of this relationship, using a sample of 77 countries at different stages of development and representing all geographical regions, with at least 20 years of data, and employing techniques that address some shortcomings in the literature. Owing to data limitations, we focus on income inequality only and refrain from analyzing the equally relevant concept of wealth inequality.

What we find is that the effect of income inequality on economic growth can be either positive or negative, and that at a particular level of inequality—at a Gini of about 27 percent to be exact—the direction of the relationship changes—that is, where inequality begins to hurt economic development.

We also assess if some of the commonly proposed tools to combat the harmful effects of rising inequality—such as boosting financial inclusion and promoting female labor participation—effectively mitigate the impact on economic development.

Not all countries are alike

Our results show that a change in income inequality growth does not have the same effect across countries. While the median impact of inequality growth on per capita GDP growth is negative and significant, lasting about 2 years, this is not true for all countries. In Ecuador, Jordan, Nigeria, and Panama, for example, the effect is large and negative.

For other countries, like Finland, for instance, the impact is positive, as the results for the 25^th percentile show. This large dispersion highlights the limited relevance of the average effect typically estimated.

Inequality overhang

Different effects across countries can be linked to different initial inequality levels. If income is not highly concentrated, an increase in inequality can provide incentives for countries to be more productive. If highly concentrated, that same increase can lead to rent-seeking behaviors—the top appropriating a larger and larger share of the nation's pie for themselves. Also, when inequality is low, it is unlikely that any increase would lead to social unrest; conversely, when inequality is already high, any further increase would likely reduce social consensus, and the ability to implement pro-growth reforms.

The chart below highlights the existence of a hump-shaped relationship between inequality and economic development, revealing the existence of what we call an "inequality overhang."

In other words, the impact of income inequality on economic development is positive for values of a net Gini below 27 percent (where net refers to its measurement after taxes and transfers), but the impact becomes negative for values above 27 percent. Also, as countries become more unequal, the negative impact on economic development becomes larger.

Trade-offs and win-win policies

Improving access of households and business to banking services, as well as promoting participation of women in the labor force can help combat the negative impact of increasing inequality on economic growth. However, they could also make things worse by over-leveraging poorer households or generating an oversupply of labor.

We find that, while financial access is generally desirable, it can lead to a greater negative impact of income inequality on economic development, as banks may curtail credit to customers at the lower end of the income distribution because of their inability to repay. To prevent this trade-off, mechanisms should be considered to ensure that those who lose access to credit when income becomes more concentrated can continue consuming even when their income falls. On the other hand, greater female labor participation is a win-win in that it enlarges the pool of talent that is available to work and reduces (or even reverse) the negative impact of inequality on growth. 

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SNAP Helps Low-Wage Workers [feedly]

SNAP Helps Low-Wage Workers
http://economistsview.typepad.com/economistsview/2017/05/snap-helps-low-wage-workers.html

Brynne Keith-Jennings at the CBPP:

SNAP Helps Low-Wage Workers: For millions of Americans, work doesn't provide enough income for them to feed their families. Our major new report explains that SNAP (formerly food stamps) provides workers with low pay and often fluctuating incomes with crucial additional monthly income to help put food on the table. It also helps workers get by while they're between jobs.

Up to 30 percent of Americans earn pay that would barely lift a family above the poverty line for full-time, year-round work. And, in many cases, workers who want a full-time job can only get part-time work or have irregular schedules that can change from week to week, with little advance notice or worker input.

Also, low-wage jobs tend to lack crucial supports such as paid sick leave, which can cost workers their jobs when they get sick or must care for an ill family member. In addition, low-wage workers are less likely than other workers to qualify for unemployment insurance.

SNAP benefits support work. The benefit formula phases out benefits slowly as earnings rise and includes a 20 percent deduction for earned income to reflect work-related expenses. As a result, SNAP benefits fall by only 24 to 36 cents for each additional $1 of earnings for most households. SNAP benefits can help smooth out volatile income and provide much-needed food assistance when workers' hours are cut or they lose their jobs.

SNAP participants work in a wide range of jobs but, compared to all workers, a greater share of them are in service occupations (see graph) and industries such as retail and hospitality — jobs likelier to have low wages and other disadvantages. In some occupations, such as dishwashers, food preparation workers, and nursing, psychiatric, and home health aides, at least one-quarter of workers participate in SNAP. For them and millions of others whose jobs don't provide enough or steady income to provide for their families, SNAP provides essential support.

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The Economics of Trust [feedly]

The Economics of Trust
http://economistsview.typepad.com/economistsview/2017/05/the-economics-of-trust.html

From the IMFBlog:

The Economics of Trust: Trust in other people – the glue that holds society together – is increasingly in short supply in the United States and Europe, and inequality may be the culprit.

In surveys over the past 40 years, the share of Americans who say that most people can be trusted has fallen to 33 percent from about 50 percent. The erosion of trust coincides with widening disparities in incomes.

But does inequality reduce trust? There is evidence that it does, according to researchby Eric D. Gould, a professor of economics at Hebrew University, and Alexander Hijzen, a senior economist at the Organisation for Economic Cooperation and Development. They analyzed data from the American National Election Survey from 1980 to 2010. The results show that wider income inequality explains 44 percent of the drop in trust. The authors, who reported their findings in an IMF working paper, found similar results in Europe...

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Dan Little (Understanding Society): Gererativism

Generativism 

Dan Little

http://understandingsociety.blogspot.com/2017/05/generativism.html

There is a seductive appeal to the idea of a "generative social science". Joshua Epstein is one of the main proponents of the idea, most especially in his book, Generative Social Science: Studies in Agent-Based Computational Modeling. The central tool of generative social science is the construction of an agent-based model (link). The ABM is said to demonstrate the way in which an observable social outcome of pattern is generated by the properties and activities of the component parts that make it up -- the actors. The appeal comes from the notion that it is possible to show how complicated or complex outcomes are generated by the properties of the components that make them up. Fix the properties of the components, and you can derive the properties of the composites. Here is Epstein's capsule summary of the approach:

The agent-based computational model -- or artificial society -- is a new scientific instrument. It can powerfully advance a distinctive approach to social science, one for which the term "generative" seems appropriate. I will discuss this term more fully below, but in a strong form, the central idea is this: To the generativist, explaining the emergence of macroscopic societal regularities, such as norms or price equilibria, requires that one answer the following question: 

The Generativist's Question 

*How could the decentralized local interactions of heterogeneous autonomous agents generate the given regularity?  

The agent-based computational model is well-suited to the study of this question, since the following features are characteristic: [heterogeneity, autonomy, explicit space, local interactions, bounded rationality] (5-6)

And a few pages later:

Agent-based models provide computational demonstrations that a given microspecification is in fact sufficient to generate a macrostructure of interest. . . . To the generativist -- concerned with formation dynamics -- it does not suffice to establish that, if deposited in some macroconfiguration, the system will stay there. Rather, the generativist wants an account of the configuration's attainment by a decentralized system of heterogeneous autonomous agents. Thus, the motto of generative social science, if you will, is: If you didn't grow it, you didn't explain its emergence. (8)

Here is how Epstein describes the logic of one of the most extensive examples of generative social science, the attempt to understand the disappearance of Anasazi population in the American Southwest nearly 800 years ago.

The logic of the exercise has been, first, to digitize the true history -- we can now watch it unfold on a digitized map of Longhouse Valley. This data set (what really happened) is the target -- the explanandum. The aim is to develop, in collaboration with anthropologists, microspecifications -- ethnographically plausible rules of agent behavior -- that will generate the true history. The computational challenge, in other words, is to place artificial Anasazi where the true ones were in 80-0 AD and see if -- under the postulated rules -- the simulated evolution matches the true one. Is the microspecification empirically adequate, to use van Fraassen's phrase? (13)

Here is a short video summarizing the ABM developed under these assumptions:

The artificial Anasazi experiment is an interesting one, and one to which the constraints of an agent-based model are particularly well suited. The model follows residence location decision-making based on ground-map environmental information.

But this does not imply that the generativist interpretation is equally applicable as a general approach to explaining important social phenomena.

Note first how restrictive the assumption is of "decentralized local interactions" as a foundation to the model. A large proportion of social activity is neither decentralized nor purely local: the search for muons in an accelerator lab, the advance of an armored division into contested territory, the audit of a large corporation, preparations for a strike by the UAW, the coordination of voices in a large choir, and so on, indefinitely. In all these examples and many more, a crucial part of the collective behavior of the actors is the coordination that occurs through some centralized process -- a command structure, a division of labor, a supervisory system. And by its design, ABMs appear to be incapable of representing these kinds of non-local coordination.

Second, all these simulation models proceed from highly stylized and abstract modeling assumptions. And the outcomes they describe capture at best some suggestive patterns that might be said to be partially descriptive of the outcomes we are interested in. Abstraction is inevitable in any scientific work, of course; but once recognizing that fact, we must abandon the idea that the model demonstrates the "generation" of the empirical phenomenon. Neither premises nor conclusions are fully descriptive of concrete reality; both are approximations and abstractions. And it would be fundamentally implausible to maintain that the modeling assumptions capture all the factors that are causally relevant to the situation. Instead, they represent a particular stylized hypothesis about a few of the causes of the situation in question.  Further, we have good reason to believe that introducing more details at the ground level will sometimes lead to significant alteration of the system-level properties that are generated.

So the idea that an agent-based model of civil unrest could demonstrate that (or how) civil unrest is generated by the states of discontent and fear experienced by various actors is fundamentally ill-conceived. If the unrest is generated by anything, it is generated by the full set of causal and dynamic properties of the set of actors -- not the abstract stylized list of properties. And other posts have made the point that civil unrest or rebellion is rarely purely local in its origin; rather, there are important coordinating non-local structures (organizations) that influence mobilization and spread of rebellious collective action. Further, the fact that the ABM "generates" some macro characteristics that may seem empirically similar to the observed phenomenon is suggestive, but far from a demonstration that the model characteristics suffice to determine some aspect of the macro phenomenon. Finally, the assumption of decentralized and local decision-making is unfounded for civil unrest, given the important role that collective actors and organizations play in the success or failure of social mobilizations around grievances (link).

The point here is not that the generativist approach is invalid as a way of exploring one particular set of social dynamics (the logic of decentralized local decision-makers with assigned behavioral rules). On the contrary, this approach does indeed provide valuable insights into some social processes. The error is one of over-generalization -- imagining that this approach will suffice to serve as a basis for analysis of all social phenomena. In a way the critique here is exactly parallel to that which I posed to analytical sociology in an earlier post. In both cases the problem is one of asserting priority for one specific approach to social explanation over a number of other equally important but non-equivalent approaches.

Patrick Grim et al provide an interesting approach to the epistemics of models and simulations in "How simulations fail" (link). Grim and his colleagues emphasize the heuristic and exploratory role that simulations generally play in probing the dynamics of various kinds of social phenomena.

--

John Case
Harpers Ferry, WV

The Winners and Losers Radio Show

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Simon Wren-Lewis (Mainly Macro): Why are the UK and US more vulnerable to right wing populism?

Why are the UK and US more vulnerable to right wing populism?

https://mainlymacro.blogspot.com/2017/05/why-are-uk-and-us-more-vulnerable-to_9.html

Cartoon by @ThomasHTaylor

A week or so ago, anticipating Macron's victory and following defeats of the far right in Holland and Austria, I asked on twitter why the US and UK seem to be more susceptible to right wing populism than elsewhere. It is a question that requires much more than a post to answer, but I thought the replies to my question were interesting.

Quite rightly, a large number of people questioned the premise. We have populist far right leaders in parts of Eastern Europe, for example. Maybe timing is also important, with the US and UK acting as warnings to other countries.

Nor should differences be exaggerated. Macron is quite unique in his achievements, and a runoff between Le Pen and the conventional right or left might have been closer. Trump lost the popular vote, and the Brexit vote was very close. What exactly is populism anyway: as someone said to me recently, elites use the label populist much as populists use the label elites.

On the other hand, one of the features of the Macron campaign is that he championed all the things that Brexit and Trump led us to believe were now politically unpopular and therefore to some extent compromised, especially globalisation and the EU. A number of people suggested specific features of European economies that might have cushioned the impact of globalisation more effectively: a stronger welfare state, for example, or stronger union power. One way of describing this is to say that neoliberalism has been less successful in Western Europe. Real wage growth has been poor in the UK and US, which may have a wider impact in electoral terms than higher unemployment in Europe.

Another set of suggested explanations focused on the rise of the very rich in the US and UK. Those who had recently achieved much higher incomes and wealth would be naturally keen to keep it, and would therefore do what they could to ensure democracy allowed them to keep (or increase) it. The obvious way to do this is through the media, although recent attempts at voter persuasion discovered by Carole Cadwalladr suggest it is not the only way. The UK press is perceived to be the most biased to the right among this sample of European countries apart from Finland. The US has talk radio and Fox news. These may persuade the non-partisan media to give undue coverage to far right individuals, which then increases their support. To the extent that the very rich are able to influence elections, we get what could be described as a managed democracy.

That in turn may be related to a remark by Matthew Yglesias: "You see in Trump vs Le Pen once again that authoritarian nationalist movements only win with the support of the establishment right." (The centre-right candidate in the French elections, Fillon, recommended his supporters vote for Macron.) Brexit was enabled by a Conservative leader offering a referendum, and more importantly Brexit was encouraged by his party attempting to shift the blame for austerity on to immigrants. Trump has been embraced by the Republican party. This narrative fits with this past post of mine.

It seems to me that these various explanations are quite compatible with each other. Where what we might call neoliberal policies had been strong - weak unions, declining welfare state, stagnant wages - these policies created a very large group in society that were looking for someone to blame. In a managed economy that allowed the parties of the right either to use nationalism and anti-immigration rhetoric to deflect blame from themselves, or for the far right to capture those parties. As that rhetoric also hit out at globalisation it potentially was a direct threat to global business interests, but those interests could either do nothing about this or felt they could manage that threat.

One final set of answers to my original question focused on history. Europe still has enough memory of living under authoritarian nationalist governments to want to avoid going down that route again. (Macron's vote was highest amongst the 70+ age group.) The UK and US do not have that experience, and perhaps nostalgia for empire (or WWII) in the case of the UK or watching an empire decline in the case of the US created unique tensions.

While these are dark times to be living through (and I suspect many others besides myself certainly think they are), for anyone interested in political economy they are also fascinating times.   

--

John Case
Harpers Ferry, WV

The Winners and Losers Radio Show

7-9 AM Weekdays, The EPIC Radio Player Stream, 

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