Posts

The Slow Death of Neoliberalism: Part 3 The Phillips Curve and Critical Theory

/26 Comments/in , /by

Part 1.
Part 2.

I described attacks on the Phillips Curve in Part 2. This part discusses the history of the Phillips Curve in detail, and concludes with a discussion of the problems revealed by the failure. The Observations are the fun part if this is too long.

History of the Phillips Curve

This section is based on parts 1-3 of The History of the Phillips Curve: Consensus and Bifurcation by Robert Gordon, an economist at Northwestern, published in the 2008 in the journal Economica at p. 10 et seq. (behind paywall, but available online through your local library). In 1958, William Phillips published a paper which as Gordon puts it,

… replaced discontinuous and qualitative descriptions by a quantitative hypothesis based on an unusually long history of evidence. Since 1861 there had been a regular negative relationship in Britain between the unemployment rate and the growth rate of the nominal wage rate. P. 12.

Phillips fitted a curve to data from the period 1861-1913, and plotted data for the remaining periods, through 1957 against that curve to find disagreements. Phillips found that his curve was close across the entire time except for a couple of years that he explains away. Here’s the curve Phillips fitted to his data:

1) wt = -.90 + 9.64U-1.39

Gordon says “… the inflation rate would be expected to equal the growth rate of wages minus the long-term growth rate of productivity.” P. 12.

1a) p = w – k

For some reason p is inflation and k is productivity. Upper case letters are levels and lower case letters are rates of change. So equation 1 can be written

2) p = -.90 + 9.64U-1.39 – k.

Paul Samuelson and Robert Solow discussed the Phillips results in the US context in a 1960 article. They found no similar data for the US, but they did some estimates and suggested that the PC doesn’t fit their data for several periods, and that it can shift up and down. Phillips estimated that an unemployment rate of about 2.5% was consistent with zero-inflation, while Samuelson and Solow think it might have been 3% pre-World War II and was about 5-6% in the early 60s.

With this seal of approval, the idea was incorporated into econometric models in two equations. In one, the PC was embodied and other variables were added, including demand, unemployment, the rate of change of unemployment, taxes, expected inflation and others in different combinations. This result was fed into an equation that calculates inflation based on wage levels, price levels and trend productivity. Gordon explains that

The reduced form of this approach implied that the inflation rate depended on the level and rate of change of unemployment, perhaps other measures of demand, and lagged inflation.

This is followed by a long discussion of the views of the Chicago School, which Gordon dismisses as utter failures. Moving along to 1975, Gordon turns to efforts to modify the Phillips Curve by adding supply and demand shocks. The price of oil shot up in 1973 because of OPEC. The demand for oil doesn’t decrease quickly in the short run, so people spend more on oil and less on other things. The Phillips Curve didn’t predict the results. Gordon says

The required condition for continued full employment is the opening of a gap between the growth rate of nominal GDP and the growth rate of the nominal wage to make room for the increased nominal spending on oil. P. 21, cite omitted.

That means wages must fall, Gordon says, or we have to add money to the economy, but the latter would lead to inflation. What we actually did, he says, was wage rigidity, increased unemployment, and some nominal (meaning not adjusted for inflation) GDP growth. Gordon then developed and published this version of the Phillips Curve:

3. pt = Ept + b(Ut – UtN) + zt + et

The second U term is the “natural” rate of unemployment, which I’m not going to take up. The z term represents cost-push pressure from unions and supply monopolies. The e term is apparently a constant but it seems odd that it might vary over time. Gordon explains that this version incorporates inertia, the idea that if there’s inflation in one period, there will be inflation in the next. It also reflects supply and demand issues, like wage and price rigidity.

Gordon then mentions in passing that the wage equation (Equation 1a) is only valid if labor’s share of the GDP is fixed, but it isn’t. Here’s a chart from FRED

That problem, says Gordon, is “fruitfully ignored”. We don’t need to consider wages, we just look at prices. With these changes, we can understand the past by explaining away variations with negative or “beneficial supply shocks” and other variables. Gordon says that Equation 3 is foundation of the mainstream model. There is a related model, the New Keynesian Phillips Curve which is similar except that it incorporates future expectations of inflation, and makes no specific provision for supply and demand shocks. I assume these in some combination are the models used by the Fed, and heavily criticized as discussed in Part 2.

Observations

The concept is replaced by the formula, the cause by rules and
probability. Dialectic of Enlightenment, Horkheimer and Adorno,p. 3.

1. Phillips was working off empirical data when he fitted his curve, data about inflation and the rate of growth of wages. There are some theoretical issues in the preparation of that data. But the only abstract theory he adds to his data is Equation 1a, which Gordon says has a solid base in intuition. At the time he was writing, Phillips would only have seen data supporting that theory. We have new information:

As it happens, and perhaps not surprisingly, Phillips’ Equation 1 doesn’t work on US data. Gordon himself and others start adding things to make the Philips Curve work. They are convinced that there is a link between unemployment and inflation, and that they just need to add the relevant variables from their theoretical arsenal to get it to come out. Some focus on expectations, others on supply and demand shocks, and others add taxes or something else. Once they get those pesky variables set up, it’s just a matter of solving for constants. The point is to fit a curve to the actual data, not to use the actual data to see what’s happening. The concept connected to the real world is gone, replaced by the formula. The cause is replaced by the rules of economics.

2. If we set inflation at 0 in Equation 1a, the rate of wage growth is equal to the rate of productivity growth. As the above chart shows, this relationship broke about 50 years ago. If all the gains from productivity are not going to labor, they are going to capital. Of course, capital takes several forms, for example, housing, agricultural land and other domestic capital. See, Piketty, Capital in the Twenty-First Century, Figure 4.6. When you think about it, it seems almost impossible that some of the gains from productivity weren’t going to capital all along. But in the current economy, it’s obvious that companies like Facebook can provide vastly more services with disproportionally fewer additional employees, few of whom are well paid, so that most of the gains from increased sales go to capital. Or, suppose that manufacturing is outsourced, reducing labor costs. Some of the gains might go to cutting prices but surely some go to capital. Let’s rewrite Equation 1a to reflect this, using γ for the growth rate capital.

1b) p = w + γ – k.

Using Equation 1b instead of 1a, we would have this instead of Equation 2:

4) p = -.90 + 9.64U-1.39 + γ – k.

This equation focuses attention on the changes in the return to capital. That issue never seems to trouble most economists, but the rate of return to capital is the central focus of Piketty’s Capital In The Twenty-First Century. This chart from the Center on Budget and Political Priorities shows that top wealth started on its climb at the same time wages diverged from productivity, which supports the idea that gains from productivity are going to capital:

It also calls attention to the fact that nowhere in Gordon’s paper is there a mention of power, market power, political power, or social power, all of which Piketty talks about. Actually, hidden away in Gordon’s article is a backhanded reference to power. Equation 3 (Equation 7 in Gordon’s paper) includes a term “…zt to represent ‘cost-push pressure by unions, oil sheiks, or bauxite barons’”. P. 22. Obviously Gordon understands that the power to control the price of goods and services could create a negative supply shock, and the loss of control could produce a beneficial supply shock. P. 25. However, this is not explicit, and it certainly doesn’t deal with our current economy, in which almost all goods and services are dominated by a small number of gigantic companies exercising a significant degree of price control.

The tweaking Gordon describes might work for a while, but as the degree of price control through monopoly and oligopoly power increases, and γ becomes a bigger factor, the tweaks quit working.

3. Let’s put this in a larger context. For many economists, the Phillips Curve is structural. But why would you think so? It seems more likely that the relationship holds in a certain set of social conditions, including legislation and regulation, power conditions, and people’s attitudes. A logical use of the data is to work out the conditions that must exist to make it so. That’s how Piketty approaches his inequality data.

It’s a mistake to use a coincidence to predict the future. It seems to be a particular problem in economics. Even people who seem to know better continue to believe in the Phillips Curve. Here’s the President of the Boston Fed, Eric Rosengren:

A number of papers at the conference highlighted that some of the economic relationships that are frequently assumed to be stable over time have proven to be not so stable as we have come out of the financial crisis. These structural changes mean that if you tried to have a model that was fairly invariant to these changes, or a process that was invariant to these changes, there would start being big misses in monetary policy.

He goes on to explain that we have to raise interest rates because maybe not the Phillips Curve, but when employment goes up, inflation goes up. Rosengren knows there’s a problem, but he doesn’t have any idea of how to cope, so he keeps doing what he thinks he knows is right. It’s another example of Horkheimer and Adorno’s statement in action.

Updated to define γ more exactly.

Stagnant Wages And Slow Productivity Growth

/14 Comments/in , /by

This article on productivity at Forum Economics says that there has been a global slowdown in productivity growth, and discusses some common explanations. As I pointed out, there is every reason to think that the actual slowdown in productivity growth is greater than the numbers suggest. That’s because productivity grows when output increases while hours worked remains the same or declines, as happens when firms exercise market power to increase prices without changed costs. Forum Economics argues that if productivity growth slows down, workers will not be able to improve their standards of living, explaining:

Household income is dependent on wages, which are consequently dependent on a firm’s ability to grow through greater productivity. The widening gap in productivity would account for the widening gap in household income and consequently, social equality.

At one level, this is just a version of the economic maxim that markets pay people what they are worth. In this case, the argument is that the productive people get the increased rewards. In the case of exercise of market power, this means that some people benefit from exercise of market power, and we know it isn’t the producers of the goods and services; it’s the people at the top, holders of debt and equity, and financiers.

At another level, it says that companies can’t pay higher wages unless workers increase their productivity. And certainly not at the expense of returns to capital.

Economists used to think there was some magic connection between productivity and wages. That was generally true for some time. But, as this This chart shows the relationship between wages and productivity split beginning around 1980, while productivity was growing rapidly.

That’s just after Paul Volker, then Fed Chair, raised interest rates to ludicrous levels. At the same time, economists were preaching that the problem facing the economy was inadequate levels of capital. So Reagan and the Republicans, along with plenty of complicit Democrats, slashed taxes on the rich, reduced regulations, deregulated industries, and clobbered unions. At the same time, they increased taxes on the working people of the country by increasing FICA taxes.

That worked. According to this 2012 report from Bain & Co.:

By 2010, global capital had swollen to some $600 trillion, tripling over the past two decades. Today, total financial assets are nearly 10 times the value of the global output of all goods and services. …

Our analysis leads us to conclude that for the balance of the decade, markets will generally continue to grapple with an environment of capital superabundance.

This article estimates total financial assets at about $294 Trillion in 2014. And, of course, banks have an almost unlimited capacity to lend for any useful purpose. There is certainly no shortage of capital today.

Once capital achieves a new baseline of return, it doesn’t drop back without a bitter fight, sometimes just political, but always with the threat or reality of physical violence. That’s how labor got its share in the first place, a fact no one wants to talk about. When was the last time you heard an economist discuss the violence in the coal fields, the violence that won miners safer working conditions and better wages. Once labor loses its power, workers can’t defend themselves, and can’t force the rich to share the benefits that flow from any level of productivity, whether or not that level is increasing. And indeed, the rich are now taking all the gains from productivity and more, the labor participation rate is at pre-1980 levels, and wages have been stagnant for decades. Even so, all discussion about wages is centered around increasing productivity, as if it mattered to workers when all the benefits flow to the richest among us.

One school of thought blames workers, saying they have to increase their training and preparation for the work force. A kinder version blames hysterisis effects, the idea that when workers are unemployed for extended periods, they lose their skills. The Republican answer is invest in yourself, borrow money, and get that training. Of course, you take all the risks, for example, whether you can master the schooling, or figure out what training might get you a job, or find a school that will actually train you, and by the way, if you fail, you still have to pay until you die. The Democratic version is jobs training, but that’s only sporadically available, and it’s always underfunded and rarely useful, thanks to the neoliberals in both parties. As to the older people in the workforce who can’t retrain, and can’t move to where there are jobs, both parties do nothing. We don’t just blame the victims, we ignore them, and treat them as losers who deserve nothing.

Many of the 23 economic writers cited in the Focus Economics article, and the other experts it discusses, say the problem is inadequate business investment. So the solutions offered are centered around stimulating demand and cutting taxes and regulations. No one explains how this solves the problem of the rich taking all the gains.

There are few outside the box observations. A couple of the writers think maybe the problem is that there are too many low-productivity jobs available, and too few high-productivity jobs. People see the available jobs as dead-end, and their treatment as demeaning, and they don’t do more than the absolute minimum necessary to get that minuscule paycheck. Another writer points out that the next wave of capital investment is not going to make people more productive, it’s going to replace them. I assume he means industrial robots, for the short term at least.

Another suggests that we are already very efficient at a lot of things, and in those areas, improvements in productivity won’t make much difference. In areas we aren’t very efficient at, it’s going to require something enormous to make a difference, or we would already done it. John Quiggan says that the financial sector has separated itself from the productive sector, which seems true. You can almost hear the words “Vampire Squid”. All these are intractable problems.

But I think the problem is different. The economic orthodoxy is that capital is always efficient, while labor is always bloated, lazy, indifferent, greedy, demanding, corrupt and insufferable. That was and is the rallying cry of the union-busters, and you can hear it today. That is a perfect description of the capitalists of today. They don’t want to take risks. They want protected markets, special tax treatment, immunity from criminal prosecution and civil suits, and they have the money to pay off politicians to get that and more. They want all the money. They don’t want to pay their share. They want the right to wreck the economy with impunity. They want the right to screw consumers into the ground. They want the right to destroy the environment. And they want to make all the decisions about the future.

We have the power to solve that problem if we have the will.

Update: after I posted, I ran across this astonishing article by Michael Hiltzik at the Los Angeles Times, discussing the reaction of Wall Street analysts to American Airlines decision to increase pay to its pilots and flight attendants. Do read it.

The Productivity Problem

/15 Comments/in , /by

Productivity growth is apparently trending downward around the globe. The problem is addressed in Focus Economics, Why is Productivity Growth So Low: 23 Economic Experts Weigh In. The author, whose name I can’t find, begins by explaining the problem as economists see it.

Productivity is considered by some to be the most important area of economics and yet one of the least understood. Its simplest definition is output per hour worked, however, productivity in the real world is not that simple. Productivity is a major factor in an economy’s ability to grow and therefore is the greatest determinant of the standard of living for a given person or group of people. It is the reason why a worker today makes much more than a century ago, because each hour of work produces more output of goods and services.

It’s certainly true that the concept is important. The simple definition gives us the rough idea but the details are very difficult indeed. The text gives us the example of productivity at a branch bank.

Bill Conerly put it well in an article for Forbes: “Take banking, for example. Your checking account is clear as mud. The bank provides to you the service of processing checks, for which you don’t pay (aside from exorbitant fees for bounced checks and stop-payments). However, the bank does not pay you a market rate of interest on the money you keep in your checking account. It’s a trade: free services in exchange for free account balances. Government statisticians estimate the dollar value of the trade, so that the productivity of bankers can be assessed, but the figures are not very precise.

At least in that example, we can see how productivity improvement at a bank might improve your standard of living, perhaps indirectly by enabling the bank to pay a bit more interest on your checking account. Here are three different kinds of examples, in which we can see how improvements in reported productivity result in worse outcomes for us.

Productivity is defined as the ratio of output to hours worked. Output is measured by receipts to the producer. Hours worked are collected by the Census Bureau.

1. A pharmaceutical company raises the price of its generic drugs with no change in its costs. Its receipts go up while hours worked remain the same. Under the definition, productivity goes up.

2. A high frequency trading company inserts itself into an increasing number of purchases of securities on stock exchanges. The purchaser pays a higher price. The HFT company has higher revenue but hours worked remain the same. Again, by this definition, productivity goes up.

3. Two dominant corporations in the same industry merge. The new company fires a lot of people. Hours worked go down. Prices remain the same in the short run, and rise as the new entity exercises oligopoly power. With hours down and receipts up, productivity rises by definition.

Are these examples realistic? In the medicine example, this article lays out the issues. For those interested, this chart shows the value of pharmaceuticals and medicines shipped by manufacturers beginning in 2000. It shows that there was a steady rise, with a sudden jump in 2013. This chart shows that per capita expenditure on pharmaceuticals and other medical products has nearly doubled since 2000.

It’s likely that there are several causes for this, not least the startling prices sought for new drugs. Government productivity figures do not take into account any improvement in the results that new drugs bring, although quality adjustments are made in calculating inflation figures. Given the increased pressure from insurers and doctors to switch to generics, and increased focus on drug prices as a problem, it’s reasonable to see this data and various reports as support for my drugs example. But it’s hard to put a dollar value on it.

On the second example, here’s an article from CFA Magazine written in 2011, detailing the costs of high frequency trading. More recent reports say that the problems are going away, and who knows because it’s hidden behind a wall of words mostly from the people who run the systems and their friends at the exchanges, and the captured SEC. Here’s a review of the literature (behind a paywall), which concludes with this: “This suggests that the identified economic benefits of HFTs (market making, venue competition, more trading opportunities) outweigh their economic costs (large-order predation and run games).” For my purposes, it’s clear that the older article tells us that initially, at least, HFT operated as my example suggests, raising productivity without doing anything useful.

As to the third example, the impact of private equity on employment is everywhere, and the concentration of economic power in oligopoly control of most industries is obvious. Dave Dayen has been writing about it for some time; here’s a recent example. Oligopolistic control also reduces paychecks for the remaining workers.

In these examples, and I could produce many more, productivity as defined by economists goes up but individual consumers are worse off. That is maddening. Once upon a time, we might have thought we could just ignore this kind of thing as an insignificant part of GNP, but that’s not true today, either in the US or globally. The economy, measured by output, is growing, but it is the opposite of the notion of productivity as good for society: it makes people’s lives worse. Except, of course, for a few rich people.

My three examples are exercises of market power. Here’s a long but worthwhile discussion of the harm it does and its increasing presence in the economy. Market power is not the same as rent-seeking, which is usually defined as an effort to get the government to give special treatment to one of a number of competitors. Both are damaging and both inflate productivity figures.

My examples show that reported productivity growth is most likely higher than the kind of productivity growth that the author discusses, the kind that increases the amount of goods and services available in the economy. It’s not unusual for an economics writer to assume only good people operate in the capitalist economy, and ignore the crooks and the cheats. Suppose the author is right that rising productivity that makes for a better life. If real productivity growth is even lower than the low reported productivity growth, his logic explains why life is getting worse for most of us.