The program needs tweaking, not overhaul. This isn’t news, but it bears reiterating. Here’s Dean Baker, Kevin Drum, Greg Anrig, and the Center on Budget and Policy Priorities.
Inequality and mobility at the top
March 8, 2011Income inequality in America has soared over the past generation. But some see little cause for concern. One reason is that our inequality statistics — Gini coefficient, share of income going to the top 1%, and so on — are calculated based on households’ income in a single year. This misses the fact that people move up and down over time. Our incomes in any given year may be more dispersed now than several decades ago, but if many of us are switching places from year to year, why the fuss?
Two claims need to be distinguished here. One says there’s enough movement up and down in the income distribution over time (in technical lingo, relative intragenerational income mobility) that we needn’t worry about single-year inequality at all. It doesn’t matter whether inequality is high or low; it doesn’t matter whether it’s rising or falling. Single-year income inequality is simply irrelevant, on this view, because there is a lot of mobility. Since “a lot” and “enough” are in the eye of the beholder, evidence can’t confirm or refute this claim.
A second claim says that the rise in income inequality has been offset by a rise in mobility. Here we can look to the data for a verdict. Has income mobility increased?
For the bulk of the population — everyone but the richest — we have multiple sources of mobility data. One is the Panel Study of Income Dynamics (PSID); another is earnings records from the Social Security Administration. Both indicate that there has been no increase in income mobility in recent decades (see also here).
What about at the top? A good bit of the past generation’s rise in inequality consists of growing separation between the rich, especially the top 1%, and the rest of America. But has this been accompanied by increased churn among those at the top? In 2007 the Treasury Department released a study based on analysis of tax records. It included data on movement out of the top 1% over two nine-year periods: 1987-1996 and 1996-2005.
Single-year income inequality rose sharply during these two periods. The share of income going to the top 1% of households jumped from 11% in 1987 to 14% in 1996 to 18% in 2005. The Treasury study found that mobility, by contrast, was essentially unchanged.
The large increase in income inequality has not been offset by a rise in mobility at the top.
Price index clarification
February 3, 2011Paul Krugman rightly notes a potential problem in comparing the post-1973 trend in GDP with the trend in median income: the price indexes used to adjust for inflation differ. But that’s not an issue in this “decoupling” chart. It uses the same price index for both.
The great decoupling
January 31, 2011Tyler Cowen’s e-book The Great Stagnation offers a novel explanation of the slowdown in U.S. median income growth since the 1970s. Here’s his causal model:
Innovation —> economic growth —> median income growth
In this model there are three potential sources of the reduction in median income growth:
1. Innovation has slowed.
2. The degree to which innovation boosts economic growth has declined.
3. The degree to which economic growth boosts median income growth has declined.
Cowen argues for hypothesis #1. He cites an estimate by Jonathan Huebner, a Pentagon physicist, that the rate of global innovation per capita peaked in the late 1800s, remained high to the mid-1950s, and then steadily declined. And he suggests that whereas “The period from 1880 to 1940 brought numerous major technological advances into our lives…. Today … apart from the seemingly magical internet, life in broad material terms isn’t so different from what it was in 1953.” The high rate of innovation through the mid-1950s enabled rapid economic growth for a few additional decades. But beginning in the 1970s economic growth slowed, and along with it median income growth.
The book is well worth reading. (At four dollars it’s also a good deal — less than a large latte, a Sunday New York Times, or a newsstand copy of The Atlantic.) But I’m skeptical on two counts.
First, I’m not convinced that innovation has in fact slowed significantly. Cowen discusses the internet but not computers more generally. Computers are the engine of the postindustrial economy; they are the modern counterpart to steel, railroads, and the assembly line. Advances in computer hardware and software, their widespread dissemination, and their application to myriad tasks — automation and coordination of supply chains in manufacturing, record keeping and scheduling in services, and much much more — surely represent a massive improvement.
Second, the data point to hypothesis #3. A key difference between the WW2-1973 period and the decades since then is that median income growth has become decoupled from economic growth. (Mark Thoma makes this point too.) The rate of economic growth has been lower in the recent era, but it’s nevertheless been decent. Yet median income growth has been very slow. This contrasts sharply with the prior period.
Here’s one way to see this (others here):
Between 1947 and 1973, GDP per family increased at a rate of 2.6% per year and median family income grew at 2.7% per year. From 1973 to 2007, GDP per family increased at 1.7% per year, but median family income grew at just 0.7% per year.
And note the absolute numbers: GDP per family rose by $52,000 during 1947-73 and then by $82,000 during 1973-2007. Median family income increased by $26,000 during 1947-73 but then by just $13,000 in 1973-2007.
Median family income was $64,000 in 2007. Had it kept pace with GDP per family since the mid-1970s, it instead would have been around $90,000.
I’m all for helping to accelerate the rate of innovation. But the big change in recent decades lies in the degree to which economic growth lifts middle-class incomes. If we want to understand slow income growth, that should be our focus.
Can we get to below-4% unemployment? Do we need to?
January 26, 2011Robert Pollin has a piece in Boston Review arguing for a return to full employment in the United States. The following is my comment, cross-posted from the Boston Review forum.
I share Robert Pollin’s view that the U.S. should strive for full employment — by which I mean, following his lead, an unemployment rate below 4%.
Can we do it? Pollin points to two historical precedents as grounds for optimism. The first is Sweden from 1960 to 1989. Sweden succeeded in keeping unemployment below 4% throughout those three decades by coupling employment-oriented monetary and fiscal policy with wage restraint. But Sweden’s central bank at that time was subordinate to the government. Ours, the Federal Reserve, is independent. Since the late 1970s, independent central banks such as the Fed almost always have prioritized low inflation, rendering low unemployment difficult to achieve. If the Fed isn’t on board, even a workable plan for full employment supported by the American public and our elected officials probably won’t be enough.
What about Pollin’s second precedent, the United States in the late 1990s? During those years the Fed, under Alan Greenspan, did keep interest rates low enough for the unemployment rate to drop below 4%. But Greenspan held rates low despite opposition from other Fed board members, who were concerned about potential inflationary consequences — particularly given the internet-driven stock market bubble. Greenspan took this stance in part because his belief in the self-correcting nature of markets led him to worry less than others about the bubble. In light of the painful consequences of the 2000s real estate bubble, I doubt we’ll see the Fed take that approach again for some time.
Do we need below-4% unemployment? Here a cross-national perspective might shed some light. The following charts show indicators of Pollin’s desired outcomes — a healthy economy, decent pay, low poverty, good working conditions, absence of discrimination — in twenty rich democratic nations. Each outcome is plotted against the number of years from 1979 to 2007 in which each country had sub-4% unemployment.
These charts tell us that while full employment may contribute to good outcomes, it isn’t a necessary condition. In each case, some countries have done well despite seldom or never reaching sub–4% unemployment during the measurement period. In some instances this is a function of strong unions or “production regimes” (think German manufacturing) that are unlikely to be relevant in the American context. In others, though, successful outcomes have owed much to government action.
This is good news because Americans have more influence on the policy choices of the government than on those of the Fed. Whether or not we get back to full employment, we can reach important economic and social goals.
Yet I fear this conclusion is too optimistic. I’m confident that the United States could achieve satisfactory economic growth, a reasonably high employment rate, decent wages, poverty reduction, good working conditions, and less discrimination without full employment. I’m less certain that we can manage sustained wage growth for those in the bottom half of the distribution.
The post–World War II experiences of the rich democracies suggest three routes to rising working- and middle-class wages. One is an environment in which firms face only moderate competition in product markets and limited pressure from shareholders, allowing them to pass on a significant share of growth to their employees. This characterized the period from the late 1940s through the mid 1970s, but it’s now long gone. The second is strong unions. I see little hope of that in America’s future. The third is full employment.
Is there any alternative? One possibility might be to use the Earned Income Tax Credit to subsidize wages. We could extend it higher in the income distribution (currently it phases out at about $45,000), reduce its connection to children (currently it’s minuscule for households with no kids), and index it to average wages (it’s now indexed to inflation). I would prefer the full employment path that Pollin envisions, in which wage growth comes from firms rather than taxpayers. But we ought to have a backup plan.
Is winner-take-all bad or good for the middle class? Evidence from baseball
January 11, 2011A “winner-take-all” market is one in which the top stars get paid much more than anyone else. It’s an apt description of the American economy in recent decades. Top financiers, CEOs, entertainers, and athletes now routinely earn more than ten million dollars a year, and the share of all income (after taxes) going to the top 1% of households jumped from 8% in 1979 to 17% in 2007.
What impact does the rise in the share taken by those at the top have on the incomes of those in the middle? On one view it’s bad: if the additional millions going to the “winners” had instead been spread among those in the middle, the latter would have been better off. Others suggest the impact is good: winner-take-all markets help make the pie bigger than it otherwise would have been, and a larger pie means a larger slice for the middle class in absolute terms, even if that slice has shrunk relative to the slice of those at the top.*
Pay in major league baseball is a good test case. Since the 1970s professional baseball has had the two defining characteristics of a winner-take-all market: owners’ and/or consumers’ judgment that top stars are much more valuable than the next best, and stars’ ability to exit if offered better pay elsewhere. Salaries for baseball’s top players have skyrocketed. Also helpful: unlike in pro football and basketball, baseball teams’ total pay is not limited by a salary cap.
Here are the two contending hypotheses:
1. Winner-take-all is bad for middle-pay players. Stars’ big paychecks come largely at the expense of their teams’ mid-level players.
2. Winner-take-all is good for middle-pay players. Teams that pay big money for top stars enjoy greater revenue growth via higher game attendance, richer TV deals, better jersey and hat sales, and so on. The stars collect a growing share of these teams’ total payroll, but this is more than offset by the degree to which they help boost the payroll. As a result, salaries for the middle players on these teams increase more than on other teams.
Baseball-almanac.com has data on the salaries of all major league players since the mid-1980s. I’ll examine change from 1989 to 2007, as both are business-cycle-peak years. (I exclude the four teams created after 1989. The Cincinnati Reds also are left out, due to missing 1989 salary data.)
Does paying big money for top stars enlarge the pie? On the horizontal axis of the following chart is change in the share of each team’s total pay that goes to its top three players. Consistent with what we would expect in a winner-take-all market, for most teams that share rose. For example, in 1989 the best-paid trio of players on the San Francisco Giants got 22% of the team’s total pay. In 2007 the Giants’ top three got 40% of the total pay, an increase of 18 percentage points. On the chart’s vertical axis is 1989-to-2007 change in each team’s total pay, in millions of inflation-adjusted dollars. The hypothesized positive association isn’t there. Teams that increased the portion of their pie going to their top three players haven’t gotten a faster-growing pie in return.
That points us toward hypothesis 1, which says a rising share of a team’s pay going to its top stars is bad for those in the middle. As the next chart shows, that’s indeed how things have played out. The chart plots the change in pay for each team’s middle five players from 1989 to 2007 by the change in the top three players’ share of the team’s total pay. Middle-player salaries have tended to grow less rapidly on teams in which the top three’s share has risen more.
The following set of charts elaborates a bit. It shows changes in top players’ pay and changes in middle players’ pay for four teams. The first two teams, the San Francisco Giants and Toronto Blue Jays, are on the right side of the second chart above. Pay for their top three players exploded. It rose for their middle players too, but much more modestly. The next two teams, the Baltimore Orioles and Milwaukee Brewers, are on the left side of the second chart above. Pay for their top three players rose sharply, but less than for their counterparts on the Giants and Blue Jays. Their middle players, by contrast, did better.
But that’s not the full story. To the two hypotheses listed above we should add a third:
3. Winner-take-all is bad for middle-pay players, but its harm is outweighed by other developments.
The “other” development that has mattered most is the growth in team payrolls. Total pay for the median team soared from $23 million in 1989 to $89 million in 2007. This has been the key determinant of salary growth for middle-pay major league players. On average, the pay of the middle five players rose by $300,000 less on a team with a ten-percentage-point increase in the top three players’ pay share than on a comparable team with no change in the top three’s share.** But salaries for the middle five players nevertheless increased on almost all teams, in many instances handsomely so. Across all teams, the average increase for the middle five between 1989 and 2007 was $1 million, nearly a 200% rise. Even among the six teams on which the top three players’ share of pay rose the most — those to the right in the second chart: Houston, Pittsburgh, San Francisco, Toronto, Oakland, and the L.A. Angels — the average increase for the middle five players was $540,000.
What accounts for the sharp jump in team payrolls? One element is enhanced revenues due to expanded demand for tickets, TV rights, and team paraphernalia. Another is a shift in the balance of power away from owners in favor of players. These developments have enabled some teams — the New York Yankees are the paramount example, as you can see in the second chart above — to concentrate a growing share of pay on their top three ballplayers and simultaneously provide a large rise in pay for their “middle-class” players.
Implications for the broader economy probably are limited. One, though, is that even if winner-take-all hurts middle-class incomes, if we had very rapid economic growth it might not matter much. Alas, figuring out how to get that isn’t so easy. A good substitute might be moderately strong growth coupled with strong unions (as in the 1950s and 1960s) or low unemployment (as in the late 1990s). But I’m not too optimistic about that either.
__________
* Some recent analysis and commentary: Andrews-Jencks-Leigh, Cowen, Drum, Kenworthy, Klein, Thoma, Yglesias.
** This is based on a regression of change in middle-five players’ pay on change in top-three players’ share of team pay, change in total team pay, and 1989 level of middle-five players’ pay.
The science of basketball
January 6, 2011Bill Simmons’ The Book of Basketball is part extended sports column, part scholarly tome. The mixture works well. Simmons has taken advantage of the massive increase in available historical information on professional sports to produce a book that is insightful, colorfully written, and steeped in data.
The Book of Basketball offers thoughtful and informed answers to a number of interesting questions: Who was a better player: Bill Russell or Wilt Chamberlain? Who were the top 96 players, in order, in NBA history? Which were the best teams in NBA history? Which twelve players would form the best basketball team? The most interesting chapter of all, in my view, is one titled “How the Hell Did We Get Here?” — a fascinating year-by-year discussion of developments in the league, the players, the styles, and how they were influenced by trends in American society.
The data come from the usual statistics on scoring, rebounding, assists, turnovers, shot blocks, and other quantifiable aspects of basketball. They also come from journalist reports, from basketball books, from Simmons’ interviews and discussions with (current and former) players, coaches, and basketball executives, and from thousands of games and game segments that are now viewable on the internet and on channels like ESPN Classic.
Simmons has a deep passion for his topic, stemming partly from his having attended hundreds of Boston Celtics home games as a kid in the 1970s and 1980s. That passion is key to the book. It helps not because it leads him to openly reveal his love for the Celtics or his lack of love for Wilt Chamberlain, Kareem Abdul-Jabbar, and Kobe Bryant. Simmons’ frankness, coupled with his enthusiasm and flowing prose, no doubt help make this book a hit with many basketball fans. For me, Simmons’ passion matters because it’s surely what led him to spend so much time examining individual and team statistics, reading about and digesting reports and books on earlier eras, watching countless hours of game footage, and talking and debating with other experts and analysts. It’s Simmons’ knowledge about his subject — his reliance on evidence, in various forms and from an array of sources — that makes this a terrific book.
It’s therefore particularly surprising and disappointing that the book’s key chapter is missing. In chapter 1, before he gets to history’s best players and teams, Simmons heads straight to basketball’s most important question: What explains which teams win championships? He gives us a sensible though debatable hypothesis (pp. 46-48 in the 2010 paperback edition). But then he moves on, offering only some scattered analysis.
Simmons’ hypothesis: “teamwork over talent.”
A little elaboration: “Teams that play together, kill themselves defensively, sacrifice personal success and ignore statistics invariably win the title.”
More elaboration:
Here’s what we know for sure:
1. You build potential champions around one great player. He doesn’t have to be a super-duper star or someone who can score at will, just someone who leads by example, kills himself on a daily basis, raises the competitive nature of his teammates, and lifts them to a better place.
2. You surround that superstar with one or two elite sidekicks who understand their place in the team’s hierarchy, don’t obsess over stats, and fill in every blank they can.
3. From that framework, you complete your nucleus with top-notch role players and/or character guys who know their place, don’t make mistakes, and won’t threaten that unselfish culture, as well as a coaching staff dedicated to keeping those team-ahead-of-individual values in place.
4. You need to stay healthy in the playoffs and maybe catch one or two breaks.
That’s how you win an NBA championship.
This seems plausible, even compelling. Then again, it sounds like a to-the-tee description of the Utah Jazz from 1988 to 2003. The number of NBA titles the Jazz won during that span: zero.
We need evidence and analysis. Here’s what Simmons offers (pp. 47-48):
1. The list of Best Players on an NBA Champ Since Bird and Magic Joined the League looks like this: Kareem (younger version), Bird, Moses, Magic, Isiah, Jordan, Hakeem, Duncan, Shaq (younger version), Billups, Wade, Garnett, Kobe. It’s a list that looks exactly how you’d think it should look with the exception of Billups.
2. The list of Best Championship Sidekicks Since 1980: Magic, Parish/McHale, Kareem (older version), Worthy, Doc/Toney, DJ, Dumars, Pippen/Grant, Drexler, Pippen/Rodman, Robinson, Kobe (younger version), Parker/Ginobili, Shaq (older version), Pierce/Allen, Gasol. You would have wanted to play with everyone on that list … even younger Kobe.
3. Too many to count, but think Robert Horry/Derek Fisher types.
4.
Sprinkled throughout the book are additional bits and pieces of evidence that bear on the “teamwork over talent” hypothesis. But the only systematic analysis is in the chapter I mentioned earlier in which Simmons goes through the 1960s Russell-Chamberlain years comparing their teams and outcomes. It’s a very good chapter. The key conclusion is that contrary to conventional belief, Russell’s supporting cast wasn’t consistently better talent-wise than Chamberlain’s. And there’s loads to indicate that Russell prioritized and fostered a team-first approach whereas Wilt did not. Russell’s teams won eleven NBA titles; Chamberlain’s won two. Hypothesis confirmed.
But only through the early 1970s. The Russell-Chamberlain chapter ends on page 83, and I spent the rest of the 734-page book waiting, largely in vain as it turned out, for examples of post-Chamberlain teams that had sufficient talent to win an NBA title but didn’t because they lacked the teamwork element. Surely the 2004 Lakers. Possibly the post-1986 Houston Rockets, though Simmons says they also were hindered by Ralph Sampson’s bad luck and by cocaine. Others?
So here’s what I’m hoping for in the second edition: the missing chapter(s) in which Simmons walks us through each of the past forty years with an assessment of the talent and teamwork of the top four or five or eight teams. Why add more to a book that’s already very long? Because we need that analysis, and Simmons is the person to do it. It would ensure that The Book of Basketball, already splendid in many respects, remains the book of basketball for many years to come.
Why do some rich economies grow faster than others?
January 4, 2011Between 1973 and 2007 the twenty rich nations in the following chart averaged a 2% per year growth rate of per capita GDP. But some of them grew faster than others.
Why?
One reason is “catch-up”: partly because they could borrow technology from the leaders, countries that began with a lower per capita GDP tended to grow more rapidly. The growth rates shown here adjust for this.
What else matters? The list of hypothesized causes is lengthy. It includes investment, consumption, education, natural resources, macroeconomic policy, levels of taxation, welfare state size and structure, industrial policy, government regulations, the distribution of income, interest group organization, corporatist concertation, the partisan complexion of government, interest group-government coherence, cooperation-promoting institutions, and institutional coherence, among others.
In a chapter in the Oxford Handbook of Comparative Institutional Analysis, I take a stab at assessing the merits of some of these hypotheses. Many turn out to be of little use in understanding the cross-country variation in catchup-adjusted growth. Two that do seem to help are business and labor participation in policy making (“corporatism”) and limited product and labor market regulations, yet these go only a small part of the way toward accounting for the country differences.
An interesting element of the story is the tendency of countries that do well for a while to then lapse. During the course of these four decades an array of national models have gone in and out of fashion, first performing effectively and then falling on hard times: Germany (“modell Deutschland”) and Japan (“Japan Inc.”) in the 1970s and 1980s; the United States in the 1980s and 1990s; the Netherlands (“Dutch miracle”) in the 1990s; Denmark (“flexicurity”) and Ireland (“Celtic tiger”) in the 1990s and 2000s. Some later rebound, such as Sweden in the 2000s.
My conclusion: we know far less than we’d like to about this very important issue.
Has rising inequality been bad for the poor?
December 14, 2010Income inequality has risen sharply in the United States and some other affluent countries since late 1970s, with much of the increase consisting of growing separation between the top 1% and the rest of the population.
Has this been bad for the incomes of the poor?
In a relative sense, the answer is yes, at least in the United States. According to the best available U.S. data, from the Congressional Budget Office, the share of income going to households at the bottom has decreased.
What about in an absolute sense? Would the incomes of low-end households have grown more rapidly in the absence of the top-heavy rise in inequality? If we look across the rich nations, it turns out that there is no relationship between changes in income inequality and changes in the absolute incomes of low-end households. The reason is that income growth for poor households has come almost entirely via increases in net government transfers, and the degree to which governments have increased transfers seems to have been unaffected by changes in income inequality. (For more detail, see my piece in the November-December issue of Challenge.)
In some countries with little or no rise in income inequality, such as Sweden, government transfers increased and so did the incomes of poor households. In others, such as Germany, transfers and the incomes of low-end households did not increase.
Among nations with sharp increases in top-heavy inequality, we observe a similar disjunction. Here the U.S. and the U.K. offer an especially revealing contrast. The top 1%’s income share soared in both countries, and through the mid-1990s poor households made little progress, as the following chart shows. But over the next decade low-end American households advanced only slightly, whereas their British counterparts experienced sizable gains. The New Labour governments under Tony Blair and Gordon Brown increased benefits and/or reduced taxes for low earners, single parents, and pensioners. As Jane Waldfogel documents in her book Britain’s War on Poverty, these were big policy shifts, even if not always high-profile ones. They produced a significant rise in the real disposable incomes of poor households.
Rising income inequality has a number of potential consequences — some of them, perhaps many, undesirable. Its apparent lack of impact on the absolute incomes of the poor over the past generation ought not lead us to overlook this. Still, it is noteworthy that some affluent countries have managed to engineer income growth for low-end households despite a significant top-heavy rise in inequality. For American policy makers, that might serve as welcome inspiration.
SASE 2011 conference in Madrid
December 13, 2010For those interested, the 2011 conference of the Society for the Advancement of Socio-Economics (SASE) is June 23-25 in Madrid. Details are here.
