macroblog

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The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.

Authors for macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.


June 22, 2016


Was May's Drop in Labor Force Participation All Bad News?

The unemployment rate declined 0.3 percentage points from April to May, and this was accompanied by a similar drop in the labor force participation rate. It is tempting to interpret this as a “bad” outcome reflecting a weakening labor market. In particular, discouraged about their job-finding prospects, more unemployed workers left the labor force. However, a closer look at the ins and outs of the labor force suggests a possibly less troubling interpretation of the outflow from unemployment.

To get a handle on what is going on, it is useful to look at the number of people that transition among employment, unemployment, and out of the labor force. It is not that unusual for an individual to search for a job in one month and then enroll in school or assume family responsibilities the next. In fact, each month millions of individuals go from searching for work to landing a job or leaving the labor force, and vice versa.

The U.S. Bureau of Labor Statistics (BLS) publishes estimates of these gross flows. Analyzing these data shows that there was indeed an unusually large number of unemployed persons leaving the labor force in May. Curiously, the outflow was concentrated among people who had only been unemployed only a few weeks. It wasn't among the long-term unemployed. Therefore, it seems unlikely that discouragement over job-finding prospects was the main factor. Although it is plausible that people who say they are now doing something else outside the labor market feel disheartened, the number of unemployed who said they gave up looking because they were discouraged was largely unchanged in May.

So why was there an increase in the number of short-term unemployed who left the labor force in May? One clue is provided by the fact that the short-term unemployed tend to be relatively younger than other unemployed. Moreover, the single most common reason that unemployed young people leave the labor force is to go to school. Hence, there is a very distinct seasonal pattern in the outflow. It tends to be relatively low around May when school is ending and high around August when school is starting. Seasonal adjustment techniques correct for these patterns by lowering the unadjusted data in the fall and raising it in late spring.

The following chart shows the seasonally adjusted and unadjusted flow from unemployment to departure from the labor force. Although the trend has been declining during the last few years, a relatively large increase in the seasonally adjusted outflow took place in May of this year.

Monthly Exit from Unemployment Leaving the Labor Force

When I looked at the unadjusted microdata from the Current Population Survey (CPS), I found that the number of people who were unemployed in April 2016 but in May said that they were not in the labor force because they were in school did not exhibit the usual large seasonal decline. Therefore, when the seasonal adjustment is applied, the result is an increase in the estimated flow from unemployment to out of the labor force.

Taking the seasonally adjusted data at face value, it's not obvious that this is bad news. We know that people who leave unemployment to undertake further education tend to rejoin the labor force later. Moreover, they tend to rejoin with better job-finding prospects than when they left. Alternatively, it could be just a statistical quirk of the May survey. After all, the CPS has a relatively small sample, so the estimated flows have a large amount of sampling error. Either way, I don't think it is wise to conclude that the decline in the labor force participation in May reflected a marked deterioration in job-finding prospects. In fact, the job-finding rate among unemployed workers improved in May from 22 to 24 percent, contributing to the decline in the unemployment rate.

June 22, 2016 in Employment, Labor Markets | Permalink | Comments (0)

June 21, 2016


Wage Growth for Job Stayers and Switchers Added to the Atlanta Fed's Wage Growth Tracker

The Atlanta Fed's Wage Growth Tracker (WGT) moved higher again in May—the third increase in a row and consistent with a labor market that is continuing to tighten. At 3.5 percent, the WGT is at a level last seen in early 2009.

As was noted in an early macroblog post, when the labor market is tightening, people changing jobs experience higher median wage growth than those who remain in the same job. Median wage growth for job switchers has significantly outpaced that of job stayers in recent months. For job stayers, the May WGT was 3.0 percent, the same as in April, whereas for people switching jobs the median WGT increased from 4.1 percent to 4.3 percent in May (the highest reading since December 2007; see the chart).

Wage Growth Tracker

Because these patterns over time can help shed light on the relative strength of the labor market, we have added downloadable job stayer and job switcher WGT series to the Atlanta Fed's Wage Growth Tracker web page.

I should note that it is not possible to completely identify people who are in the same job as a year ago according to data from the Current Population Survey. Instead, we define a "job stayer" as someone whom we observe in the same occupation and industry as a year earlier, and with the same employer in each of the last three months. A "job switcher" includes everyone else (a different occupation or industry or employer). We'll be monitoring these data in coming months to see if discernable trends begin to emerge, and we'll discuss any findings here.

June 21, 2016 in Employment, Labor Markets, Wage Growth | Permalink | Comments (0)

June 16, 2016


Experts Debate Policy Options for China's Transition

After nearly three decades of rapid economic growth, China today faces the challenge of economic rebalancing against the backdrop of slow and uncertain global growth. Although investment and exports have been a motor for growth, China is increasingly experiencing structural issues: widening inequality, overcapacity as a consequence of policy distortions, unsustainable environmental costs, volatile financial markets, and rising systemic risk.

On April 28–29, I attended the First Research Workshop on China's Economy, organized jointly by the International Monetary Fund (IMF) and the Atlanta Fed. The workshop, held at the IMF's headquarters in Washington DC, explored a series of questions that have emerged as China shifts toward a new growth model. Is this the end of the growth miracle? Will the Chinese renminbi one day be as important as the U.S. dollar? Should the rapidly increasing shadow banking activity in China be a source of concern? How worrisome is the rapid rise in China's housing prices?

Panelists shared their views on these and other issues facing the world's second-largest economy (or largest, if measured on a purchasing-power-parity basis). Plans are under way for a second workshop to be held in 2017.

The following is a nice summary of the research discussed at the workshop. It was originally published in the IMF Survey Magazine, and was written by Hui He, IMF Institute for Capacity Development, and Nan Li, IMF Research Department. Thanks to the IMF for allowing me to repost it here.

Is China's economic growth sustainable?
Understanding the source of China's tremendous growth was a recurring theme at the workshop. "China's economy combines enormous dynamism with huge distortions," observed Loren Brandt (University of Toronto). Brandt described his research based on China's firm-level data and emphasized that firm dynamics (entry and exit), especially firm entry, have been the main source of the productivity growth in the manufacturing sector.

Echoing Brandt's message, Kjetil Storesletten (University of Oslo) discussed regional growth disparities and showed that barriers preventing firms from entering an industry account for most of the disparities. Such barriers are more severe for privately owned firms in regions in which state-owned enterprises (SOE) dominate, he said.

In his keynote speech, Nicholas Lardy (Peterson Institute for International Economics) offered an upbeat view on China's transition to a new growth model, one in which the service sector plays a larger role than manufacturing. The bright side of the service sector, he noted, is its continued strong productivity growth. The development of financial deepening and the stronger social safety net are contributing to increased consumption, which helps to rebalance the economy.

However, he emphasized, SOE reforms remain critical as the service sector cannot provide a silver bullet for a successful transition.

Central bank's policy decisions
Several participants tried to discern how the People's Bank of China (PBC) conducts monetary policy. Tao Zha (of the Atlanta Fed's Center for Quantitative Economic Research and Emory University) found that the PBC reacts sharply when the gross domestic product's growth rate falls below its target, increasing the money supply by 11.5 percentage points for every 1 percentage point shortfall.

Mark Spiegel (Center for Pacific Basin Studies) discussed the trade-offs involved in Chinese monetary policy—for example, controlling the exchange rate versus maintaining inflation stability. He also argued that the heavy use of reserve requirements on banks as a monetary policy tool might have an unintentional consequence to reallocate capital from SOEs to more efficient privately owned firms and could therefore offset the resource misallocation caused by the easy credit to SOEs that banks granted in the high growth years.

Renminbi versus the dollar
Eswar Prasad (Cornell University and Brookings Institution) argued that China's capital account will become more open and the renminbi will be used more widely to denominate and settle cross-border transactions. But he also noted that legal and institutional constraints in China were likely to prevent the renminbi from serving as a safe-haven currency as the U.S. dollar does today.

Moreover, he said, the current sequencing of liberalization initiatives—that is, removal of capital account restrictions before appropriate financial market supervision and regulation and exchange rate reform—poses financial stability risks.

Shadow banking and the housing market
Recently, volatile Chinese financial markets and continued housing price appreciation have raised serious financial stability concerns.

Michael Song (Chinese University of Hong Kong) argued that rapidly rising shadow banking activity is an unintended consequence of financial regulation. Restrictions on deposit rates and loan-to-deposit ratios have led to the issuance by banks of "wealth management products" to attract savers with higher returns. Because these restrictions had a greater impact on small banks, the big state banks had more room to undercut the smaller banks by offering wealth management products with higher returns and then restricting liquidity to them in interbank markets, ultimately making the banking system more prone to liquidity distress and runs.

Hanming Fang (University of Pennsylvania) found that, except in big cities such as Beijing and Shanghai, housing prices in China's urban areas between 2003 and 2013 more or less tracked rising household incomes. In his view, the Chinese housing boom is thus unlikely to trigger an imminent financial crisis. He warned, however, that housing prices may fall rapidly if economic growth slows dramatically, and that such a development could, in turn, amplify the economic downturn.

Rising wage inequality
China's rapid growth over the past two decades has been accompanied by rising wage inequality, an issue highlighted by two conference participants. Dennis Yang (University of Virginia) explored the distributional effects of trade openness in China and found a significant impact on wage inequality of China's accession to the World Trade Organization in 2001.

Chong-En Bai (Tsinghua University) argued that the decline after 2008 of the skill premium—that is, the ratio of the skilled labor wage to the unskilled labor wage—can be explained by the Chinese government's targeted credit extension to unskilled labor-intensive infrastructure sector (as part of the fiscal stimulus following the global financial crisis). Such distortionary policies might have short-run growth benefits but could lead to long-run welfare losses, he said, especially when rural-to-urban migration has run its course.

June 16, 2016 in Asia, Economic Growth and Development, Labor Markets, Monetary Policy, Real Estate | Permalink | Comments (0)

June 09, 2016


It’s Not Just Millennials Who Aren't Buying Homes

In recent years, much attention has been focused on the growing tendency of millennials to rent. Theories for the decrease in homeownership among young adults abound. They include rising student debt levels that crowd out additional borrowing, a tendency to live in more urban areas where the cost to buy is relatively high, a generally tougher credit environment, and even shifts in the perception of homeownership in the wake of the housing bust. The ideas have been widely debated, and yet no single factor seems to neatly explain the declining share of the millennial population opting to buy a house. (See this webcast by the Atlanta Fed's Center for Real Estate Analytics for a discussion of these issues.)

To the extent that these factors are true, they may be affecting the decisions of other generations as well. Chart 1 below shows the overall average homeownership rate and homeownership rates by age group from 1982 to 2015. It's clear that homeownership rates have declined for everyone during the past 10 years, not just for millennials.

In fact, homeownership among young Generation Xers has fallen by a bit more than the millennial generation since the housing peak—declining 11 percentage points since 2005 compared with a decline of 9 percentage points for those under 35 years old.

Another interesting point of comparison is the mid-1980s to mid-1990s, a period in which the United States had a relatively stable share of owner-occupied housing of around 64.0 percent. During the subsequent housing boom, the homeownership rate climbed to a peak of 69 percent in 2004, only to fall back down to 63.7 percent in 2015, a level similar to that prevailing before 1995. However, each age group under age 65 has a somewhat lower homeownership rate than their same-aged peers had during the 1986–94 period.

Chart 1: Homeownership Rates by Age

The fact that the average U.S. homeownership rate is close to rates seen in the mid-1980s and mid-1990s while homeownership rates within age groups (under 65) are currently lower than their respective averages in the mid-1980s to mid-1990s suggests that factors other than age may be affecting the average person's decision to buy or rent.

To investigate what else may be going on, charts 2 and 3 show homeownership rates by family type and race. Between 2005 and 2015, the trend mirrors what's happening by age group. The tendency to own a home has been falling for all family types and races over the past decade. In general, economic incentives (or cultural attitudes) appear to have shifted the population toward renting and away from buying.

However, the picture is quite different when you compare homeownership rates by family type and race to the pre-1995 period. While homeownership rates within age groups are generally lower today, married couples, one-person households, and nonmarried, multiperson households were all more likely to own their home in 2015. Homeownership rates across race (except for blacks) were also higher in 2015 than in 1994.

Chart 2: Homeownership Rates by Type of Family

Chart 3: Homeownership Rates by Race or Ethnicity

So how do we interpret the fact that the overall homeownership rate is close to its average in the 1986 to 1994 period? Are millennials to blame? Yes. But so is everyone else under the age of 65. The data suggest that whatever is affecting millennials' homeownership decisions is applicable to older individuals as well. Further, it seems there are other, possibly larger, factors affecting homeownership, such as the changing face of America. Although homeownership rates by family types and racial groups are a bit above the level seen in 1994, the average person in 2015 was about as likely to live in a home that is owned or being bought. Thus, the shift in the distribution of the population toward racial groups and family types (and likely other factors) that tend to have lower homeownership rates is likely exerting an important influence on the overall homeownership rate.

June 9, 2016 in Housing, Real Estate | Permalink | Comments (2)

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