The Atlanta Fed's macroblog provides commentary on economic topics including monetary policy, macroeconomic developments, financial issues and Southeast regional trends.

Authors for macroblog are Dave Altig and other Atlanta Fed economists.

June 23, 2015

Approaching the Promised Land? Yes and No

Last Friday, we released our June installment of the Business Inflation Expectations (BIE) survey. Among the questions we put to our panel of businesses was a quarterly question on slack, asking firms to consider how their current sales levels compare to what they would consider normal.

The good news is, on average, the gap between firms' current unit sales levels and what they would consider normal sales levels continues to close (see the chart).


By our measure, firm sales, in the aggregate, are 1.9 percentage points below normal, a bit better than when we polled them in March (when they were 2.1 percent below normal) and much improved from this time last year (3.7 percent below normal). For comparison, the Congressional Budget Office's (CBO) estimate of slack on a real gross domestic product (GDP) basis was 2.6 percent in the first quarter (though this estimate will almost certainly be revised to something closer to 2.4 percent when the revised GDP estimates are reported later today). And if GDP growth this quarter comes in around 2.5 percent as economists generally expect, the CBO's GDP-based slack estimate will be 2.2 percent this quarter, just a shade larger than what our June survey data are saying.

Now, as we have emphasized frequently (for example, in macroblog posts in May 2015, February 2015, and June 2013), performance in the aggregate and performance within select firm groups can differ widely. For example, while small firms continue to have greater slack than larger firms, their pace of improvement has been much more rapid (see the table).


Likewise, some industries (such as transportation and finance) see current sales as better than normal. But others, like manufacturers, are currently reporting considerable slack—and findings from this group appear to show a marginal worsening in sales levels over the past 12 months.

Another item that caught our attention this month was the differing pace of narrowing in the sales gap among those firms with significant export exposure (greater than 20 percent of sales) relative to those with no direct export exposure. We connected these dots using responses to this month's special question, in which responding firms specified their share of customers by geographic area: local, regional (the Southeast, in our case), national, and international (see the table).


So things are still getting better for the economy overall, and the small firms in our panel have displayed particularly rapid improvement during the last year. But if you've got exposure to the "soft" export markets, as mentioned in the June 17 FOMC statement, you've likely experienced a slower pace of improvement.

Photo of Mike Bryan
By Mike Bryan, vice president and senior economist,
Photo of Brent Meyer
Brent Meyer, economist, and
Photo of Nicholas Parker
Nicholas Parker, economic policy specialist, all in the Atlanta Fed's research department

June 23, 2015 in Business Cycles, Business Inflation Expectations, Economic conditions | Permalink


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June 19, 2015

Will the Elevated Share of Part-Time Workers Last?

There seems to be mounting evidence that at least part of the elevated share of part-time employment in the economy is here to stay. We have some insights to offer based on a recent survey of our business contacts.

Why are we interested? A higher part-time share of employment isn't necessarily a bad thing, if people are doing so voluntarily. Unfortunately, the elevated share is concentrated among people who would prefer to be working full-time. Using the average rate of decline over the past five years, the part-time for economic reasons (PTER) share of employment is projected to reach its prerecession average in about 10 years.

This is significantly slower than the decline in the unemployment rate, whose trajectory suggests a much sooner arrival—in around a year. The deviation raises an important policy question for measuring the amount of slack there is beyond what the unemployment rate suggests, and ultimately the extent to which policy can effectively reduce it.

What are the drivers? Data versus anecdotes
Researchers (here, here, and here) have pointed to factors such as industry shifts in the economy, changing workforce demographics, rising health care costs, and the Affordable Care Act as potentially important drivers of this shift. But we can glean only so much information from data. When a gap develops, we generally turn to our business contacts who are participating members in our Regional Economic Information Network (REIN) to fill in the missing information.

According to our contacts, the relative cost of full-time employees remains the most important reason for having a higher share of part-time employees than before the recession, which is the same response we received in last summer's survey on the same topic. Lack of strong enough sales growth to justify conversion of part-time to full-time workers came in as a close second.

The importance rating for each of the factors was notably similar to last year's survey, with one exception. Technology was rated as somewhat important, reflecting an uptick from the average response we received last year. We've certainly heard anecdotally that scheduling software has enabled firms to better manage their part-time staff, and it seems that this factor has gained in importance over the past year.

The chart below summarizes the reasons our business contacts gave in the July 2014 and the May 2015 surveys. The question was asked only of those who currently have a higher share of part-time workers than they did before the recession. The chart shows the results for all respondents, whether they responded to one or both surveys. When we limited our analysis to only those who responded to both surveys, the results were the same.

Will the elevated share persist?
The results suggest that a return to prerecession levels is unlikely to occur in the near term.

The chart below shows employers' predictions for part-time employment at their firms, relative to before the recession. About 27 percent of respondents believe that in two years, their firms will be more reliant on part-time work compared to before the recession. About 7 percent do not currently have an elevated share of part-time employees but believe they will in two years. About two-thirds believe their share of part-time will be roughly the same as before, while only 8 percent believe they will have less reliance on part-time workers compared to before the recession.

The majority of our contacts believe their share of part-time employment will normalize over the next two years, but some believe it will stay elevated. Still, 2017 does not mean the shift will be permanent. In fact, firms cited a balance of cyclical and structural factors for the higher reliance on part-time. Low sales growth and an ample supply of workers willing to take part-time jobs could both be viewed as cyclical factors that will dissipate as the economy further improves.

Meanwhile, higher compensation costs of full-time relative to part-time employees and the role of technology that enables companies to more easily manage their workforce can be considered structural factors influencing the behavior of firms. Firms that currently have a higher share of part-time employees gave about equal weight to these forces, suggesting that, as other research has found, both cyclical and structural factors are important explanations for the slow decline in the part-time share of employment.

June 19, 2015 in Business Cycles, Employment, Labor Markets, Unemployment | Permalink


Current technologies are a great enabler, this may not have been the case in the past. But one of the reasons, which needs further study is the fall out of M&A and the impact on payrolls, which makes very little allowance for full-time additions thereafter. The full time additions have been more in the retail space or service area, followed by technology, while we have seen dwindling fortunes in the Oil & Natural Gas sector, the last one has seen a switch to part-time.

Posted by: Procyon Mukherjee | June 21, 2015 at 11:26 PM

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May 18, 2015

Sales Flexing Muscle at More Firms

The news in this month's Business Inflation Expectations (BIE) report is that, in the aggregate, firms' unit sales levels continue to strengthen: Specifically, the survey question measures firms' perceptions of current unit sales levels relative to "normal times."

This month, 70 percent of firms indicated their sales levels are at or above what they consider normal. Last November, that share was 61 percent, and one year ago, it was only 54 percent. We typically report the aggregate results in a diffusion index (see the chart), which also shows the overall progression toward "normal times" (a value of 0).

But, typical of aggregate statistics, these results obscure the diversity of experience among sectors. Digging deeper, we found that most (but not all) of the sectors represented in our panel have shown further improvement in their sales performance relative to last November (see the chart).

Retailers and those in the real estate and rental leasing/construction sectors reported the most significant improvement since November, with retailers approaching what they consider normal sales levels. This news is likely to be most welcome to Dennis Lockhart, our boss here in Atlanta, who has put the performance of the consumer on his "must watch" list. Two industries—finance and insurance, and transportation and warehousing—reported above-normal sales levels in our recent survey.

Only the manufacturers in our panel indicated that their sales performance has deteriorated since November, and they are now reporting sales well below normal. Of course, this news shouldn't be terribly surprising given the recent softness in the manufacturing indexes from both the Institute for Supply Management and industrial production data. This information was also on the boss's watch list, as he made clear in his speech:

The stronger dollar was likely reflected in a drag on net exports...[and] looking ahead, I expect net exports to be a modest drag on economic activity over much of the year.... It should be noted, however, that in recent weeks the dollar has stabilized and oil prices have begun to move up a little. These developments, if they stick, could dilute somewhat what would otherwise be drags on the economy in the near term. We shall see.

Well, judging from our May BIE report, manufacturers aren't seeing improvement quite yet.

Photo of Nicholas Parker
By Nicholas Parker, an economic policy analysis specialist in the research department of the Atlanta Fed

May 18, 2015 in Business Cycles, Business Inflation Expectations, Economic conditions | Permalink


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June 26, 2014

Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 3)

On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.

This is the last of three posts on that talk. The first post reviewed alternative inflation measures; the second looked at ways to work with the Consumer Price Index to get a clear view of inflation. The full text of the speech is available on the Atlanta Fed's events web page.

The challenge of communicating price stability

Let me close this blog series with a few observations on the criticism that measures of core inflation, and specifically the CPI excluding food and energy, disconnect the Federal Reserve from households and businesses "who know price changes when they see them." After all, don't the members of the Federal Open Market Committee (FOMC) eat food and use gas in their cars? Of course they do, and if it is the cost of living the central bank intends to control, the prices of these goods should necessarily be part of the conversation, notwithstanding their observed volatility.

In fact, in the popularly reported all-items CPI, the Bureau of Labor Statistics has already removed about 40 percent of the monthly volatility in the cost-of-living measure through its seasonal adjustment procedures. I think communicating in terms of a seasonally adjusted price index makes a lot of sense, even if nobody actually buys things at seasonally adjusted prices.

Referencing alternative measures of inflation presents some communications challenges for the central bank to be sure. It certainly would be easier if progress toward either of the Federal Reserve's mandates could be described in terms of a single, easily understood statistic. But I don't think this is feasible for price stability, or for full employment.

And with regard to our price stability mandate, I suspect the problem of public communication runs deeper than the particular statistics we cite. In 1996, Robert Shiller polled people—real people, not economists—about their perceptions of inflation. What he found was a stark difference between how economists think about the word "inflation" and how folks outside a relatively small band of academics and policymakers define inflation. Consider this question:


And here is how people responded:


Seventy-seven percent of the households in Shiller's poll picked number 2—"Inflation hurts my real buying power"—as their biggest gripe about inflation. This is a cost-of-living description. It isn't the same concept that most economists are thinking about when they consider inflation. Only 12 percent of the economists Shiller polled indicated that inflation hurt real buying power.

I wonder if, in the minds of most people, the Federal Reserve's price-stability mandate is heard as a promise to prevent things from becoming more expensive, and especially the staples of life like, well, food and gasoline. This is not what the central bank is promising to do.

What is the Federal Reserve promising to do? To the best of my knowledge, the first "workable" definition of price stability by the Federal Reserve was Paul Volcker's 1983 description that it was a condition where "decision-making should be able to proceed on the basis that 'real' and 'nominal' values are substantially the same over the planning horizon—and that planning horizons should be suitably long."

Thirty years later, the Fed gave price stability a more explicit definition when it laid down a numerical target. The FOMC describes that target thusly:

The inflation rate over the longer run is primarily determined by monetary policy, and hence the Committee has the ability to specify a longer-run goal for inflation. The Committee reaffirms its judgment that inflation at the rate of 2 percent, as measured by the annual change in the price index for personal consumption expenditures, is most consistent over the longer run with the Federal Reserve's statutory mandate.

Whether one goes back to the qualitative description of Volcker or the quantitative description in the FOMC's recent statement of principles, the thrust of the price-stability objective is broadly the same. The central bank is intent on managing the persistent, nominal trend in the price level that is determined by monetary policy. It is not intent on managing the short-run, real fluctuations that reflect changes in the cost of living.

Effectively achieving price stability in the sense of the FOMC's declaration requires that the central bank hears what it needs to from the public, and that the public in turn hears what they need to know from the central bank. And this isn't likely unless the central bank and the public engage in a dialog in a language that both can understand.

Prices are volatile, and the cost of living the public experiences ought to reflect that. But what the central bank can control over time—inflation—is obscured within these fluctuations. What my colleagues and I have attempted to do is to rearrange the price data at our disposal, and so reveal a richer perspective on the inflation experience.

We are trying to take the torture out of the inflation discussion by accurately measuring the things that the Fed needs to worry about and by seeking greater clarity in our communications about what those things mean and where we are headed. Hard conversations indeed, but necessary ones.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department


June 26, 2014 in Business Cycles, Data Releases, Inflation | Permalink


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It would seem the non-economists may also be saying that the economists low inflation is their own stagnant wage.

Sure, they may see prices rising, but they stated what they suffer is the reduction of purchasing power.

Perhaps they would be happy to see prices rising rapidly as long as their own wages outpace.

The 70s may not have been so bad for them.

Posted by: cfaman | June 27, 2014 at 10:01 AM

In addition to the issues discussed in the article, Fed policy makers typically ignore one-time prices changes, particularly those originating on the supply side of the economy -- e.g., those caused by bad weather or a foreign conflict. 

The public can't ignore those price changes, which comprise their daily reality.

Posted by: Thomas Wyrick | July 06, 2014 at 05:57 PM

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June 24, 2014

Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 2)

On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.

This is the second of three posts based on that talk. Yesterday's post considered the median CPI and other trimmed-mean measures.

Is it more expensive, or does it just cost more money? Inflation versus the cost of living

Let me make two claims that I believe are, separately, uncontroversial among economists. Jointly, however, I think they create an incongruity for how we think about and measure inflation.

The first claim is that over time, inflation is a monetary phenomenon. It is caused by too much money chasing a limited number of things to buy with that money. As such, the control of inflation is rightfully the responsibility of the institution that has monopoly control over the supply of money—the central bank.

My second claim is that the cost of living is a real concept, and changes in the cost of living will occur even in a world without money. It is a description of how difficult it is to buy a particular level of well-being. Indeed, to a first approximation, changes in the cost of living are beyond the ability of a central bank to control.

For this reason, I think it is entirely appropriate to think about whether the cost of living in New York City is rising faster or slower than in Cleveland, just as it is appropriate to ask whether the cost of living of retirees is rising faster or slower than it is for working-aged people. The folks at the Bureau of Labor Statistics produce statistics that can help us answer these and many other questions related to how expensive it is to buy the happiness embodied in any particular bundle of goods.

But I think it is inappropriate for us to think about inflation, the object of central bank control, as being different in New York than it is in Cleveland, or to think that inflation is somehow different for older citizens than it is for younger citizens. Inflation is common to all things valued by money. Yet changes in the cost of living and inflation are commonly talked about as if they are the same thing. And this creates both a communication and a measurement problem for the Federal Reserve and other central banks around the world.

Here is the essence of the problem as I see it: money is not only our medium of exchange but also our numeraire—our yardstick for measuring value. Embedded in every price change, then, are two forces. The first is real in the sense that the good is changing its price in relation to all the other prices in the market basket. It is the cost adjustment that motivates you to buy more or less of that good. The second force is purely nominal. It is a change in the numeraire caused by an imbalance in the supply and demand of the money being provided by the central bank. I think the concept of "core inflation" is all about trying to measure changes in this numeraire. But to get there, we need to first let go of any "real" notion of our price statistics. Let me explain.

As a cost-of-living approximation, the weights the Bureau of Labor Statistics (BLS) uses to construct the Consumer Price Index (CPI) are based on some broadly representative consumer expenditures. It is easy to understand that since medical care costs are more important to the typical household budget than, say, haircuts, these costs should get a greater weight in the computation of an individual's cost of living. But does inflation somehow affect medical care prices differently than haircuts? I'm open to the possibility that the answer to this question is yes. It seems to me that if monetary policy has predictable, real effects on the economy, then there will be a policy-induced disturbance in relative prices that temporarily alters the cost of living in some way.

But if inflation is a nominal experience that is independent of the cost of living, then the inflation component of medical care is the same as that in haircuts. No good or service, geographic region, or individual experiences inflation any differently than any other. Inflation is a common signal that ultimately runs through all wages and prices.

And when we open up to the idea that inflation is a nominal, not-real concept, we begin to think about the BLS's market basket in a fundamentally different way than what the BLS intends to measure.

This, I think, is the common theme that runs through all measures of "core" inflation. Can the prices the BLS collects be reorganized or reweighted in a way that makes the aggregate price statistic more informative about the inflation that the central bank hopes to control? I think the answer is yes. The CPI excluding food and energy is one very crude way. Food and energy prices are extremely volatile and certainly point to nonmonetary forces as their primary drivers.

In the early 1980s, Otto Eckstein defined core inflation as the trend growth rate of the cost of the factors of production—the cost of capital and wages. I would compare Eckstein's measure to the "inflation expectations" component that most economists (and presumably the FOMC) think "anchor" the inflation trend.

The sticky-price CPI

Brent Meyer and I have taken this idea to the CPI data. One way that prices appear to be different is in their observed "stickiness." That is, some prices tend to change frequently, while others do not. Prices that change only infrequently are likely to be more forward-looking than are those that change all the time. So we can take the CPI market basket and separate it into two groups of prices—prices that tend to be flexible and those that are "sticky" (a separation made possible by the work of Mark Bils and Peter J. Klenow).

Indeed, we find that the items in the CPI market basket that change prices frequently (about 30 percent of the CPI) are very responsive to changes in economic conditions, but do not seem to have a very forward-looking character. But the 70 percent of the market basket items that do not change prices very often—these are accounted for in the sticky-price CPI—appear to be largely immune to fluctuations in the business conditions and are better predictors of future price behavior. In other words, we think that some "inflation-expectation" component exists to varying degrees within each price. By reweighting the CPI market basket in a way that amplifies the behavior of the most forward-looking prices, the sticky-price CPI gives policymakers a perspective on the inflation experience that the headline CPI can't.

Here is what monthly changes in the sticky-price CPI look like compared to the all-items CPI and the traditional "core" CPI.

Let me describe another, more radical example of how we might think about reweighting the CPI market basket to measure inflation—a way of thinking that is very different from the expenditure-basket approach the BLS uses to measure the cost of living.

If we assume that inflation is ultimately a monetary event and, moreover, that the signal of this monetary inflation can be found in all prices, then we might use statistical techniques to help us identify that signal from a large number of price data. The famous early-20th-century economist Irving Fisher described the problem as trying to track a swarm of bees by abstracting from the individual, seemingly chaotic behavior of any particular bee.

Cecchetti and I experimented along these lines to measure a common signal running through the CPI data. The basic idea of our approach was to take the component data that the BLS supplied, make a few simple identifying assumptions, and let the data itself determine the appropriate weighting structure of the inflation estimate. The signal-extraction method we chose was a dynamic-factor index approach, and while we didn't pursue that work much further, others did, using more sophisticated and less restrictive signal-extraction methods. Perhaps most notable is the work of Ricardo Reis and Mark Watson.

To give you a flavor of the approach, consider the "first principal component" of the CPI price-change data. The first principal component of a data series is a statistical combination of the data that accounts for the largest share of their joint movement (or variance). It's a simple, statistically shared component that runs through all the price data.

This next chart shows the first principal component of the CPI price data, in relation to the headline CPI and the core CPI.

Again, this is a very different animal than what the folks at the BLS are trying to measure. In fact, the weights used to produce this particular common signal in the price data bear little similarity to the expenditure weights that make up the market baskets that most people buy. And why should they? The idea here doesn't depend on how important something is to the well-being of any individual, but rather on whether the movement in its price seems to be similar or dissimilar to the movements of all the other prices.

In the table below, I report the weights (or relative importance) of a select group of CPI components and the weights they would get on the basis of their contribution to the first principal component.


While some criticize the CPI because it over weights housing from a cost-of-living perspective, it may be these housing components that ought to be given the greatest consideration when we think about the inflation that the central bank controls. Likewise, according to this approach, restaurant costs, motor vehicle repairs, and even a few food components should be taken pretty seriously in the measurement of a common inflation signal running through the price data.

And what price movements does this approach say we ought to ignore? Well, gasoline prices for one. But movements in the prices of medical care commodities, communications equipment, and tobacco products also appear to move in ways that are largely disconnected from the common thread in prices that runs through the CPI market basket.

But this and other measures of "core" inflation are very much removed from the cost changes that people experience on a monthly basis. Does that cause a communications problem for the Federal Reserve? This will be the subject of my final post.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department


June 24, 2014 in Business Cycles, Data Releases, Inflation | Permalink


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Great thoughts, thanks for sharing. taking the the idea of core inflation as the movements in prices that contain information about future inflation, have you ever thought about applying partial least squares (PLS) rather than PCA for dimension reduction, and making a future value of headline inflation the Y variable in the PLS decomposition of the Y'X? then you would get weightings that reflected the information content of each price series x on future Y, rather than PCA which simply decomposes the variance within X'X

Posted by: Michael Hugman | June 25, 2014 at 11:10 AM

This is very interesting. But I wonder, is it really possible to distinguish monetary inflation from cost-of-living inflation? As you say, monetary inflation reflects an imbalance between the supply and demand for money. Where does the demand for money come from? Presumably from the level of real activity. And how do we measure real activity independent of money, if not as a level of well-being?

In fact, the measurement of quantity in terms of well-being is the explicit basis of the hedonic price adjustments that go into a significant fraction of the CPI. So at the least, if you want a pure monetary measure of inflation, shouldn't you strip those adjustments back out?

Along the same lines, you say the inflation controlled by the central should be identical in New York and Cleveland. But what if monetary policy produces identical rates of money supply growth in both cities, while different real growth rates mean that money demand is rowing faster in one place than the other?

Posted by: JW Mason | June 27, 2014 at 09:42 AM

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April 10, 2014

Reasons for the Decline in Prime-Age Labor Force Participation

Editor's note: Since this post was written, we have developed new tools for examining labor market trends. For a more detailed examination of factors affecting labor force participation rates, please visit our Labor Force Participation Dynamics web page, where you can create your own charts and download data.

As a follow up to this post on recent trends in labor force participation, we look specifically at the prime-age group of 25- to 54-year-olds. The participation decisions of this age cohort are less affected by the aging population and the longer-term trend toward lower participation of youths because of rising school enrollment rates. In that sense, they give us a cleaner window on responses of participation to changing business cycle conditions.

The labor force participation rate of the prime-age group fell from 83 percent just before the Great Recession to 81 percent in 2013. The participation rate of prime-age males has been trending down since the 1960s. The participation rate of women, which had been rising for most of the post-World War II period, appears to have plateaued in the 1990s and has more recently shared the declining pattern of participation for prime-age men. But the decline in participation for both groups appears to have accelerated between 2007 and 2013 (see chart 1).


We look at the various reasons people cite for not participating in the labor force from the monthly Current Population Survey. These reasons give us some insight into the impact of changes in employment conditions since 2007 on labor force participation. The data on those not in the official labor force can be broken into two broad categories: those who say they don't currently want a job and those who say they do want a job but don't satisfy the active search criteria for being in the official labor force. Of the prime-age population not in the labor force, most say they don't currently want a job. At the end of 2007, about 15 percent of 25- to 54-year-olds said they didn't want a job, and slightly fewer than 2 percent said they did want a job. By the end of 2013, the don't-want-a-job share had reached nearly 17 percent, and the want-a-job share had risen to slightly above 2 percent (see chart 2).


Prime-Age Nonparticipation: Currently Want a Job
Most of the rise in the share of the prime-age population in the want-a-job category is due to so-called marginally attached individuals—they are available and want a job, have looked for a job in the past year, but haven't looked in the past four weeks—especially those who say they are not currently looking because they have become discouraged about job-finding prospects (see the blue and orange lines of chart 3). In 2013, there were about 1.1 million prime-age marginally attached individuals compared to 0.7 million in 2007, and the prime-age marginally attached accounted for about half of all marginally attached in the population.


The marginally attached are aptly named in the sense that they have a reasonably high propensity to reenter the labor force—more than 40 percent are in the labor force in the next month and more than 50 percent are in the labor force 12 months later (see chart 4). This macroblog post discusses what the relative stability in the flow rate from marginally attached to the labor force means for thinking about the amount of slack labor resources in the economy.


Prime-Age Nonparticipation: Currently Don't Want a Job
As chart 2 makes evident, the vast majority of the rise in prime-age nonparticipation since 2009 is due to the increase in those saying they do not currently want a job. The largest contributors to the increase are individuals who say they are too ill or disabled to work or who are in school or training (see the orange and blues lines in chart 5).


Those who say they don't want a job because they are disabled have a relatively low propensity to subsequently (re)enter the labor force. So if the trend of rising disability persists, it will put further downward pressure on prime-age participation. Those who say they don't currently want a job because they are in school or training have a much greater likelihood of (re)entering the labor force, although this tendency has declined slightly since 2007 (see chart 6).


Note that the number of people in the Current Population Survey citing disability as the reason for not currently wanting a job is not the same as either the number of people applying for or receiving social security disability insurance. However, a similar trend has been evident in overall disability insurance applications and enrollments (see here).

Some of the rise in the share of prime-age individuals who say they don't want a job could be linked to erosion of skills resulting from prolonged unemployment or permanent changes in the composition of demand (a different mix of skills and job descriptions). It is likely that the rise in share of prime-age individuals not currently wanting a job because they are in school or in training is partly a response to the perception of inadequate skills. The increase in recent years is evident across all ages until about age 50 but is especially strong among the youngest prime-age individuals (see chart 7).


But lack of required skills is not the only plausible explanation for the rise in the share of prime-age individuals who say they don't currently want a job. For instance, the increased incidence of disability is partly due to changes in the age distribution within the prime-age category. The share of the prime-age population between 50 and 54 years old—the tail of the baby boomer cohort—has increased significantly (see chart 8).


This increase is important because the incidence of reported disability within the prime-age population increases with age and has become more common in recent years, especially for those older than 45 (see chart 9).


The health of the labor market clearly affects the decision of prime-age individuals to enroll in school or training, apply for disability insurance, or stay home and take care of family. Discouragement over job prospects rose during the Great Recession, causing many unemployed people to drop out of the labor force. The rise in the number of prime-age marginally attached workers reflects this trend and can account for some of the decline in participation between 2007 and 2009.

But most of the postrecession rise in prime-age nonparticipation is from the people who say they don't currently want a job. How much does that increase reflect trends established well before the recession, and how much can be attributed to the recession and slow recovery? It's hard to say with much certainty. For example, participation by prime-age men has been on a secular decline for decades, but the pace accelerated after 2007—see here for more discussion.

Undoubtedly, some people will reenter the labor market as it strengthens further, especially those who left to undertake additional training. But for others, the prospect of not finding a satisfactory job will cause them to continue to stay out of the labor market. The increased incidence of disability reported among prime-age individuals suggests permanent detachment from the labor market and will put continued downward pressure on participation if the trend continues. The Bureau of Labor Statistics projects that the prime-age participation rate will stabilize around its 2013 level. Given all the contradictory factors in play, we think this projection should have a pretty wide confidence interval around it.

Note: All data shown are 12-month moving averages to emphasize persistent shifts in trends.

Melinda PittsBy Melinda Pitts, director, Center for Human Capital Studies,

John RobertsonJohn Robertson, a vice president and senior economist in the Atlanta Fed's research department, and

Ellyn TerryEllyn Terry, a senior economic analyst in the Atlanta Fed's research department

April 10, 2014 in Business Cycles, Employment, Labor Markets | Permalink


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have you considered that a number of people will say they dont want a job because they have experienced repeated frustration in finding one? it's better for one's psyche to lie to yourself and to others about such than to accept the fact that one has repeatedly been rejected...

Posted by: rjs | April 10, 2014 at 04:39 PM

Astonishing decline in male labor force participation since 1970s.

I would be interested to see more detailed age bracket than category of the 25 - 54 age brackets.

This is so we can see if the decline over time is consistent for all ages or the particular works from certain age that flows through remainder of their working life.


Posted by: Jason | April 12, 2014 at 10:21 PM

Clearly there is nobody who is unemployed who does not want a job. This article is simply a deceptive representation of the facts. The problem is largely that employers will not hire qualified people unless they have done the exact same job before. They will not for example hire an Architect to work as a project manager at a company that manufactures windows, because the HR people use IT to scan the resumes in place of interviews and will only choose from the set of people who have been employed by manufacturers of windows in the past.

Do the survey and the research over again and ask the right questions. The problem more than likely is that the most qualified people are being overlooked, are frustrated because they can,t crossover to a different industry or are victims of age discrimination. You can be certain that most people want to have a job. Sop, dig deeper.

Posted by: Terry L. Walker, ARCHITECT | April 14, 2014 at 11:01 AM

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April 08, 2014

A Closer Look at Post-2007 Labor Force Participation Trends

Editor's note: Since this post was written, we have developed new tools for examining labor market trends. For a more detailed examination of factors affecting labor force participation rates, please visit our Labor Force Participation Dynamics web page, where you can create your own charts and download data.

The rate of labor force participation (the share of the civilian noninstitutionalized population aged 16 and older in the labor force) has declined significantly since 2007. To what extent were the Great Recession and tepid recovery responsible?

In this post and one that will follow, we offer a series of charts using data from the Current Population Survey to explore some of the possible reasons behind the 2007–13 drop in participation. This first post describes the impact of the changing-age composition of the population and changes in labor force participation within specific age cohorts—see Calculated Risk posts here and here for a related treatment, and also this recent BLS study. The next post will look at the issue of potential cyclical impacts on participation by examining the behavior of the prime-age population.

Putting the decline in context
After rising from the mid-1960s through 1990, the overall labor force participation rate was relatively stable between 1990 and 2007. But participation has declined sharply since 2007. By 2013, participation was at the lowest level since 1978 (see chart 1).


For men, the longer-term declining trend of participation accelerated after 2007. For women, after having been relatively stable since the late 1990s, participation began to decline after 2009. The decline for both males and females since 2009 was similar (see chart 2).


The impact of retirement
One of the most important features of labor force participation is that it varies considerably over the life cycle: the rate of participation is low among young individuals, peaks during the prime-age years of 25 to 54, and then declines (see chart 3). So a change in the age distribution of the population can result in a significant change in overall labor force participation.


The age distribution of the population has been shifting outward for some time. This is a result of the so-called baby boomer generation—that is, people born between 1946 and 1964 (see chart 4). The oldest baby boomers turned 62 in 2008 and became eligible for Social Security retirement benefits.


At the same time the age distribution of the population has shifted out, the rate of retirement of older Americans has been declining. Retirement rates have generally been drifting down since the early 2000s (see chart 5). The decline in age-specific retirement rates has resulted in rising age-specific labor force participation rates. For example, from 1999 to 2013, the share of 62-year-old retirees declined from 38 percent to 28 percent. The BLS projects that this trend will continue at a similar pace in coming years (see table 3 of the BLS report).


Although the decline in the propensity to retire has put some upward pressure on overall labor force participation, that effect is dominated by the sheer increase in the number of people reaching retirement age. The net result has been a steep rise in the share of the population saying they are not in the labor force because they are retired (see chart 6).


Participation by age group
Individuals aged 16–24
The labor force participation rate for young individuals (between 16 and 24 years old) has been generally declining since the late 1990s. After slowing in the mid-2000s, the decline accelerated again during the Great Recession. However, participation has been relatively stable since 2009 (see chart 7). Nonetheless, the BLS projects that the participation rate for 16- to 24-year-olds will decline further, albeit at a slower pace than it declined between 2000 and 2009, and will fall a little below 50 percent by 2022.


The change in participation among young people can be attributed almost entirely to enrollment rates in education programs (see here) and lower labor force participation among enrollees (see chart 8). The change in the share of 16- to 24-year-olds who say they don't currently want a job because they are in school closely matches the change in labor force participation for the entire cohort.


Individuals aged 25–54 (prime age)
Generally, people aged 25 to 54 are the group most likely to be participating in the labor market (see chart 3). These so-called prime-age individuals are less likely to be making retirement decisions than older individuals, and less likely to be enrolled in schooling or training than younger individuals.

However, the prime-age labor force participation rate declined considerably between 2007 and 2013, and at a much faster pace than had been seen in the years prior to the recession (see chart 9). Reflective of the overall gender-specific participation differences seen in chart 2, the decline in prime-age female participation did not take hold until after 2009, and since 2009 the decline in both prime-age male and female participation has been quite similar. Nevertheless, the BLS projects that prime-age participation will stabilize in coming years and prime-age participation in 2022 will be close to its 2013 level.


The BLS projects that participation by age group will look like this in 2022 relative to 2013 (see chart 10).


Participation by youths is projected to continue to fall. The participation of older workers is projected to increase, but it will remain significantly lower than that of the prime-age group. Combined with an age distribution that has also continued to shift outward (see chart 11), the overall participation rate is expected to decline over the next several years from its 2013 level of around 63.3 percent. From the BLS study:

A combination of demographic, structural, and cyclical factors has affected the overall labor force participation rate, as well as the participation rates of specific groups, in the past. BLS projects that, as has been the case for the last 10 years or so, these factors will exert downward pressure on the overall labor force participation rate over the 2012–2022 period and the rate will gradually decline further, to 61.6 percent in 2022.


However, an important assumption in the BLS projection is that the post-2007 decline in prime-age participation will not persist. Indeed, the data for the first quarter of 2014 does suggest that some stabilization has occurred.

But separating what is trend from what is cyclical is challenging. The rapid pace of the decline in participation among the prime-age population between 2007 and 2013 is somewhat puzzling. Could this decline reflect a temporary cyclical effect or something more permanent? A follow-up blog will explore this question in more detail using the micro data from the Current Population Survey.

Note: All data shown are 12-month moving averages to emphasize persistent shifts in trends.

Update: The authors acknowledge a debt to Tomaz Cajner and Bruce Fallick for their influence on some of this material. We regret inadvertently omitting this acknowledgement in the original post.

Melinda PittsBy Melinda Pitts, director, Center for Human Capital Studies,

John RobertsonJohn Robertson, a vice president and senior economist in the Atlanta Fed's research department, and

Ellyn TerryEllyn Terry, a senior economic analyst in the Atlanta Fed's research department

April 8, 2014 in Business Cycles, Employment, Unemployment | Permalink


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I am having difficulty reconciling Charts 1 and 2 as chart 2 seems to suggest much lower total participation rates than are suggested in Chart 1. Any help much appreciated.

Posted by: James Thomas | May 28, 2014 at 01:30 PM

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September 26, 2013

The New Normal? Slower R&D Spending

In case you need more to worry about, try this: the pace of research and development (R&D) spending has slowed. The National Science Foundation defines R&D as “creative work undertaken on a systematic basis in order to increase the stock of knowledge” and application of this knowledge toward new applications. (The Bureau of Economic Analysis (BEA) used to treat R&D as an intermediate input in current production. But the latest benchmark revision of the national accounts recorded R&D spending as business investment expenditure. See here for an interesting implication of this change.)

The following chart shows the BEA data on total real private R&D investment spending (purchased or performed on own-account) over the last 50 years, on a year-over-year percent change basis. (For a snapshot of R&D spending across states in 2007, see here.)

Real Spending on Research and Development

Notice the unusually slow pace of R&D spending in recent years. The 50-year average is 4.6 percent. The average over the last 5 years is 1.1 percent. This slower pace of spending has potentially important implications for overall productivity growth, which has also been below historic norms in recent years.

R&D spending is often cited as an important source of productivity growth within a firm, especially in terms of product innovation. But R&D is also an inherently risky endeavor, since the outcome is quite uncertain. So to the extent that economic and policy uncertainty has helped make businesses more cautious in recent years, a slow pace of R&D spending is not surprising. On top of that, the federal funding of R&D activity remains under significant budget pressure. See, for example, here.

So you can add R&D spending to the list of things that seem to be moving more slowly than normal. Or should we think of it as normal?

Photo of John RobertsonBy John Robertson, vice president and senior economist in the Atlanta Fed’s research department

September 26, 2013 in Business Cycles, Capital and Investment, Productivity | Permalink


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As someone who has spent many years in corporate R&D, I think I would advise some caution in interpreting these numbers. My experience is that an enormous amount of corporate R&D spending is simply wasted, essentially through poor management (alternatively just the fact that managing R&D from ideation through to product creation and monetization is really a very difficult task).

So it's possible that a gradual fall in overall R&D expenditure, especially relative to its natural variability, could actually reflect a healthy re-balancing of corporate spending, either through improved research productivity or through a shift towards more product-oriented expenditures. Without a lot more analysis it's difficult to really assess what's going on here.

Posted by: Mark Thomson (@markmthomson) | September 26, 2013 at 05:43 PM

Do these data include expenditures at universities? Maybe it's a low share. But as a public good every state has an incentive to let someone else provide elite higher education (as they're the most mobile geographically) and R&D.

Posted by: mike smitka | October 03, 2013 at 02:03 PM

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December 16, 2011

Maybe this time was at least a little different?

Earlier this week, Derek Thomson, a senior editor at The Atlantic, began his article "The Graph That Proves Economic Forecasters Are Almost Always Wrong" with some observations that don't really require a graph:

"As the saying goes: 'It's hard to make predictions. Especially about the future.' Thirty years ago, it was obvious to everybody that oil prices would keep going up forever. Twenty years ago, it was obvious that Japan would own the 21st century. Ten years ago, it was obvious that our economic stewards had mastered a kind of thermostatic control over business cycles to prevent great recessions. We were wrong, wrong, and wrong."

In a recent speech, Dennis Lockhart—whom most of you recognize as president here at the Atlanta Fed—offered his own thoughts on why forecasts can go so wrong:

"… you may wonder why forecasters, the Fed included, don't do a better job. To answer this question, let me suggest three reasons why forecasts may be off.

"While it's relatively trivial in my view, the first reason involves missing the timing of economic activity. An example of that was mentioned earlier when I explained that GDP for the third quarter had been revised down while the fourth quarter is expected to compensate.

"A second reason that forecasts miss the mark is, in everyday language, stuff happens.

"To be a little more precise, unforeseen developments are a fact of life. In my view, the energy and commodity shocks early in the year had a significant impact on growth in the first half of 2011. The tsunami-related supply disruptions, though temporary, were an exacerbating factor. In fact, a lot of shocks or disruptions are quite temporary and don't cause one to rethink the narrative about where the economy is likely going.

"Which brings me to the third reason why economic prognostications go off track: we, as forecasters, simply get the bigger story wrong.

"What I mean by getting the bigger story wrong is failing to understand the fundamentals at work in the economy."

"Getting the bigger story wrong" is Simon Potter's theme in the New York Fed's Liberty Street Economics blog post, "The Failure to Forecast the Great Recession":

"Looking through our briefing materials and other sources such as New York Fed staff reports reveals that the Bank's economic research staff, like most other economists, were behind the curve as the financial crisis developed, even though many of our economists made important contributions to the understanding of the crisis. Three main failures in our real-time forecasting stand out:

1.  Misunderstanding of the housing boom …

2. A lack of analysis of the rapid growth of new forms of mortgage finance …

3. Insufficient weight given to the powerful adverse feedback loops between the financial system and the real economy …

"However, the biggest failure was the complacency resulting from the apparent ease of maintaining financial and economic stability during the Great Moderation."

Potter does not implicate any of his Federal Reserve brethren, but you can add me to the roll call of those having made each of the mistakes on the list.

Should we have known? A powerful narrative that we should have has taken hold. The boom-bust cycle associated with large bouts of asset appreciation and debt accumulation has a long history in economics, and the theme has been pressed home in its most recent incarnation by the work of Carmen Reinhart and coauthors, including the highly influential book written with Kenneth Rogoff, This Time is Different: Eight Centuries of Financial Folly.

Unfortunately, even seemingly compelling historical evidence is not always so clear cut. An illustration of this, relevant to the failure to forecast the Great Recession, was provided in a paper by Enrique Mendoza and Marco Terrones (from the University of Maryland and the International Monetary Fund, respectively), presented last month at a Central Bank of Chile conference, "Capital Mobility and Monetary Policy." What the paper puts forward is described by Mendoza and Terrones as follows:

"… in Mendoza and Terrones (2008) we proposed a new methodology for measuring and identifying credit booms and showed that it was successful in identifying credit boom events with a clear cyclical pattern in both macro and micro data.

"The method we proposed is a 'thresholds method.' This method works by first splitting real credit per capita in each country into its cyclical and trend components, and then identifying a credit boom as an episode in which credit exceeds its long-run trend by more than a given 'boom' threshold, defined in terms of a tail probability event… The key defining feature of this method is that the thresholds are proportional to each country's standard deviation of credit over the business cycle. Hence, credit booms reflect 'unusually large' cyclical credit expansions."

And here is what they find:

"In this paper, we apply this method to data for 61 countries (21 industrialized countries, ICs, and 40 emerging market economies, EMs), over the 1960-2010 period. We found a total of 70 credit booms, 35 in ICs and 35 in EMs, including 16 credit booms that peaked in the critical period surrounding the recent financial crisis between 2007 and 2010 (again with about half of these recent booms in ICs and EMs each)…

"The results show that credit booms are associated with periods of economic expansion, rising equity and housing prices, real appreciation and widening external deficits in the upswing of the booms, followed by the opposite dynamics in the downswing."

That certainly sounds familiar, and supports the "we should have known" meme. But the full facts are a little trickier. Mendoza and Terrones continue:

"A major deviation in the evidence reported here relative to our previous findings in Mendoza and Terrones (2008) is that adding the data from the recent credit booms and crisis we find that in fact credit booms in ICs and EMs are more similar than different. In contrast, in our earlier work we found differences in the magnitudes of credit booms, the size of the macroeconomic fluctuations associated with credit booms, and the likelihood that they are followed by banking or currency crises.

"… while not all credit booms end in crisis, the peaks of credit booms are often followed by banking crises, currency crises of Sudden Stops, and the frequency with which this happens is about the same for EMs and ICs (20 to 25 percent for banking and currency for banking crisis, 14 percent for Sudden Stops)."

Their notion still supports the case of the "we should have known" camp, but here's the rub (emphasis mine):

"This is a critical change from our previous findings, because lacking substantial evidence from all the recent booms and crises, we had found only 9 percent frequency of banking crises after credit booms for EMs and zero for ICs, and 14 percent frequency of currency crises after credit booms for EMs v. 31 percent for ICs."

In other words, based on this particular evidence, we should have been looking for a run on the dollar, not a banking crisis. What we got, of course, was pretty much the opposite.

No excuses here. Speaking only for myself, I had the story wrong. But the conclusion to that story is a lot clearer now than it was in the middle of the tale.

David AltigBy Dave Altig, senior vice president and research director at the Atlanta Fed


December 16, 2011 in Business Cycles, Financial System, Forecasts | Permalink


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When your currency is the global reserve currency, there is nothing
available in sufficient size to run TO. Therefore, a run ON the dollar
was an impossibility. The ONLY other possibility was the only one remaining, a run on the Banking System.

Posted by: Robert K | December 18, 2011 at 01:13 PM

Indeed, you can't predict economic events. No kidding.

However, that fact means you must also give up attempts to control the economy.

If you cannot predict any future, how do you navigate to one particular desired future?

There is no actual evidence over 50-year periods that any country has successfully done so. Economists have destroyed a lot of countries in their attempts, however.

Abolish the Fed.

Posted by: Lew Glendenning | December 18, 2011 at 08:51 PM

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August 26, 2011

Lots of ground to cover: An update

If you have to discuss a difficult circumstance, I guess Jackson Hole, Wyo., is as nice as place as any to do so. This morning, as most folks know by now, Federal Reserve Chairman Bernanke reiterated the reason that most Federal Open Market Committee (FOMC) members support the expectation that policy rates will remain low for the next couple of years:

"In light of its current outlook, the Committee recently decided to provide more specific forward guidance about its expectations for the future path of the federal funds rate. In particular, in the statement following our meeting earlier this month, we indicated that economic conditions—including low rates of resource utilization and a subdued outlook for inflation over the medium run—are likely to warrant exceptionally low levels for the federal funds rate at least through mid-2013. That is, in what the Committee judges to be the most likely scenarios for resource utilization and inflation in the medium term, the target for the federal funds rate would be held at its current low levels for at least two more years."

There are two pieces of information that emphasize the economy's recent weakness and potential slow growth going forward. The first is this week's revised forecasts and potential for gross domestic product (GDP) from the Congressional Budget Office (CBO), and the second is today's revision of second quarter GDP from the U.S. Bureau of Economic Analysis (BEA). Though estimates of potential GDP have not greatly changed, the CBO's downgrade in forecasts and BEA's report of much lower than potential growth in the second quarter have the current and prospective rates of resource utilization lower than when macroblog covered the issue just about a month ago.

Key to the CBO's estimates is a reasonably good outlook for GDP growth after we get past 2012:

"For the 2013–2016 period, CBO projects that real GDP will grow by an average of 3.6 percent a year, considerably faster than potential output. That growth will bring the economy to a high rate of resource use (that is, completely close the gap between the economy's actual and potential output) by 2017."

The margin for slippage, though, is not great. Assuming that GDP ends 2011 having grown by about 2.3 percent—as projected by the CBO—here's a look at gaps between actual and potential GDP for different, seemingly plausible growth rates:

Attaining 3.5 percent growth by next year moves the CBO's date for closing the output gap up by about a year. On the other hand, a fall in output growth to an average of 3 percent per year moves the date for eliminating resource slack back to 2020. If growth remains below that—well, let's hope it doesn't.

David Altig By Dave Altig, senior vice president and research director at the Atlanta Fed


August 26, 2011 in Business Cycles, Economic Growth and Development, Employment, Forecasts, Saving, Capital, and Investment | Permalink


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«economic conditions—including low rates of resource utilization and a subdued outlook for inflation over the medium run—are likely to warrant exceptionally low levels for the federal funds rate at least through mid-2013.»

The exceptionally low funding rates to financial intermediaries are not resulting in equally low rates for customers of those intermediaries, because the Fed has repeatedly hinted that they want to rebuild the balance sheet of the finance sector boosting their profits by granting them a huge spread (and hoping that at least half of those profits go into capital instead of bonuses).

Bernanke's statement then may be interpreted as saying that the Fed does expects the financial sector to need another several years of extra profits resulting from the Fed "subsidy" because the finance sector seem unlikely to be able to make any profit if market conditions prevailed, and indeed it seems that the capital position of many finance sector "national champions" is still weak considering the cosmetically hidden capital losses they have.

As to inflation, wage inflation is indeed well contained (wages are declining in real terms) even if cost of living inflation seems pretty rampant; in a similar country like the UK where indices are less "massaged" the RPI has been running at over 5% and on an increasing trend:

Posted by: Blissex | August 26, 2011 at 05:28 PM

Why can't the Federal Reserve tell the public the obvious: Growth will only come about by hiring people with livable wages.

If we don't raise incomes nationally we will be forced to liquidate on a massive scale. It doesn't matter who does the hiring, just that it is done.

It isn't the deficit. It isn't the debt. It's the incomes, stupid.

Posted by: beezer | August 27, 2011 at 06:10 AM

Ken Rogoff says 3-5 years of 1-2% GDP and Carmen Reinhart thinks 5-6 years of 2%. =(

Posted by: DarkLayers | August 27, 2011 at 11:19 PM

In terms of econometrics, annual increment of real GDP per capita is constant over time . Therefore, the rate of real GDP per capita growth has to decay as a reciprocal function of the attained level of GDP per capita. The exponential component in the overall GDP is fully related to population growth which has been around 1% per year in the U.S. Currently, the rate of population growth falls and the trajectory of the overall GDP lags behind the projection which includes 1% population growth. If to look at the per head estimates, there is no gap between "potential" and observed levels.
In no case should an economist mix the growth in population and real economic growth.

Posted by: kio | August 28, 2011 at 04:03 AM

It's going to be a long time. Do you know how hard it will be for a person to live in the same town for 30 years?

Our money game will need new rules because 30 years at the same job/house/town is over.

But once that issue is fixed, watch out. Technologically America is so far ahead that earning a 100k(todays $$) salary can be done in 6 months.

To keep the NYC banks from leeching on it will be a task.

Posted by: FormerSSResident | August 31, 2011 at 07:00 PM

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