Global Economic Watch


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  • Economic Letter: Weakness in Recovery of Housing Market

    The economy may not be recovering at enough of a pace to please everybody, but it has been steadily getting better in most areas. But over the last nine months or so, the housing market has been bucking the trend--in a bad way. We'll get updated existing home sales data tomorrow, and perhaps we'll see a turn. But that seems unlikely. In a new Economic Letter , San Francisco Fed senior economist John Krainer shares some key data about home sales, and observes that investors, "may be pulling back as house values have increased in comparison with rental prices." Many indicators of housing market activity stalled over the second half of 2013, but the weakness is most evident in existing home sales. Sales of existing single-family homes reached a recent peak of 4.75 million units in July 2013, compared with the year before and adjusted for seasonal trends. Sales have fallen ever since. Figure 1 shows that the pattern of declining home sales has been broadly similar across different regions of the country. Sales in these regions all reached their peaks in July 2013 and then fell about 10% through October; the figure shows the regions indexed to 100 in July for comparison. The fact that home sales in different parts of the country peaked and fell together suggests that some common underlying factors were at play. One such factor that could account for the decline in home sales is rising mortgage interest rates. Starting in May 2013, financial market participants became increasingly convinced that the Federal Reserve would soon taper its long-term asset purchases, and interest rates moved up. Mortgage rates in particular rose by nearly a full percentage point. Higher mortgage rates generally have a direct dampening effect on home sales, as buyers face constraints on the size of loans they can secure and on loan payments relative to their incomes. Since individual incomes likely did not rise over this short period, and house prices continued to grow in most regions, the rise in mortgage rates was expected to have an unambiguous negative impact on sales. To gauge the effects of higher mortgage rates on home sales over time, I use a simple statistical model that relates existing home sales to past sales, past mortgage rates, and house price appreciation. I include past values of single-family construction permits to control for conditions in the market for new homes—a substitute for existing homes. Figure 2 shows both actual data and dynamic simulations of existing home sales during the period of interest. The model simulations use seasonally adjusted monthly data through March 2013. Beyond that date, I use actual mortgage rates, house price appreciation, and building permits to predict sales of existing homes. This simulation is dynamic in the sense that the model predictions are based on past values of home sales, which themselves are predictions from early periods in the simulation. In the figure, the solid blue line shows the actual path of existing single-family home sales, and the dashed red line is the simulated path from the model. The dashed green line offers another simulation of what sales would have been if mortgage rates had remained at the low levels observed in April 2013. Read The Slowdown in Existing Home Sales here .
  • Economic Letter: 'College Degree Remains Worthwhile Investment'

    Mary C. Daly , senior vice president at the San Francisco Fed, and Leila Bengali , research associate, weigh in on the value of higher education in a new Economic Letter . And like others who take a research driven approach, as opposed to the anecdotal approach that some in the media seem to prefer, they find that there is still clear value in going to college. In fact, they say the value "remains high." A common way to track the value of going to college is to estimate a college earnings premium, which is the amount college graduates earn relative to high school graduates. We measure earnings for each year as the annual labor income for the prior year, adjusted for inflation using the consumer price index (CPI-U), reported in 2011 dollars. The earnings premium refers to the difference between average annual labor income for high school and college graduates. We use data on household heads and partners from the Panel Study of Income Dynamics (PSID). The PSID is a longitudinal study that follows individuals living in the United States over a long time span. The survey began in 1968 and now has more than 40 years of data including educational attainment and labor market income. To focus on the value of a college degree relative to less education, we exclude people with more than a four-year degree. Figure 1 shows the earnings premium relative to high school graduates for individuals with a four-year college degree and for those with some college but no four-year degree. The payoff from a degree is apparent. Although the premium has fluctuated over time, at its lowest in 1980 it was about $15,750, meaning that individuals with a four-year college degree earned about 43% more on average than those with only a high school degree. In 2011, the latest data available in our sample, college graduates earned on average about $20,050 (61%) more per year than high school graduates. Over the entire sample period the college earnings premium has averaged about $20,300 (57%) per year. The premium is much smaller, although not zero, for workers with some college but no four-year degree. A potential shortcoming of the results in Figure 1 is that they combine the earnings outcomes for all college graduates, regardless of when they earned a degree. This can be misleading if the value from a college education has varied across groups from different graduation decades, called “cohorts.” To examine whether the college earnings premium has changed from one generation to the next, we take advantage of the fact that the PSID follows people over a long period of time, which allows us to track college graduation dates and subsequent earnings. Using these data we compute the college earnings premium for three college graduate cohorts, namely those graduating in the 1950s–60s, the 1970s–80s, and the 1990s–2000s. The premium measures the difference between the average annual earnings of college graduates and high school graduates over their work lives. To account for the fact that high school graduates gain work experience during the four years they are not in college, we compare earnings of college graduates in each year since graduation to earnings of high school graduates in years since graduation plus four. We also adjust the estimates for any large annual fluctuations by using a three-year centered moving average, which plots a specific year as the average of earnings from that year, the year before, and the year after. Read Is It Still Worth Going to College? here .
  • SF Fed Economic Letter: 'Career Changes Decline During Recessions'

    The great recession has spawned something of a jobless recovery--at least for the long term unemployed. As Carlos Carrillo-Tudela , Bart Hobijn , and Ludo Visschers note in a new Economic Letter for the San Francisco Fed , many of the jobs lost during the recession have gone away. So it would make sense if we saw a lot of people changing careers. But that isn't happening. Figure 1 shows the fraction of hires out of unemployment that change industries (panel A) and occupations, (panel B). The shaded areas depict recessions. Because industry and occupation definitions and classification systems have changed over time, data are not continuous for the period we study, as shown by the vertical dashed lines in 1983, 1992, and 2003. Two other dashed lines in 1985 and 1995 show periods when we cannot link CPS respondents across surveys. The more detailed our industry and occupation categories are, the more career changes we identify. This is why the line showing changes in industry and occupation groups at the major level lies below that showing the most detailed code level in both panels. Though the levels of industry and occupational mobility vary with the level of detail, the fluctuations in mobility over the business cycle are remarkably similar for both levels. These patterns for occupational switches also appear in data from the U.S. Census Bureau’s Survey of Income and Program Participation (see Carillo-Tudela and Visschers 2013). The common cyclical pattern between these series clearly shows that the fraction of unemployed people who change careers upon getting rehired declines during recessions. All the recessions in our sample follow this pattern, from those in the early 1980s to the Great Recession that started in 2007. Likewise, the figures show that career changes increase when the labor market is strong, as at the end of the 1980s and the 1990s. The fact that the rate of career change for unemployed workers declines during recessions seems counterintuitive, but there are several possible explanations for this phenomenon. These explanations can be divided into two broad categories. The first focuses on why those unemployed during recessions are less likely to pursue a change in career. For example, Carrillo-Tudela and Visschers (2013) consider aggregate unemployment fluctuations based on unemployed workers’ decisions to change occupations. They argue that in recessions, two factors reduce the incentives for unemployed people to change careers. One, though their job opportunities in their old careers might have dried up during the recession, it is also harder to find jobs in the alternate careers that they consider pursuing. And two, workers take into account that they may be less likely to start a particularly successful career path during a recession, which further reduces their incentives to change careers. Read the full letter here .
  • Economic Letter: 'Private Credit and Public Debt in Financial Crises'

    In a new San Francisco Fed Economic Letter , economists Òscar Jordà , Moritz Schularick , and Alan M. Taylor try to settle the debate over whether private credit or public debt was the bigger culprit in the global economic crisis. They award points to each. In short, their research seems to show that private credit booms put economies in difficult positions. And public debt makes it difficult for economies to recover. The narrative of the recent the global financial crisis in advanced economies falls into two camps. One camp emphasizes private-sector overconfidence, overleveraging, and overborrowing; the other highlights public-sector profligacy, especially with regard to countries in the periphery of the euro zone. One camp talks of rescue and reform of the financial sector. The other calls for government austerity, noting that public debt has reached levels last seen following the two world wars. Figure 1 Credit and debt since 1870: 17-country average Credit and debt since 1870: 17-country average Source: Jordà, Schularick, and Taylor (2013). Figure 1 displays the average ratio of bank lending and public debt to GDP for 17 industrialized economies (Australia, Belgium, Canada, Denmark, Finland, France, Germany, Italy, Japan, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United States). Although public debt ratios had grown from the 1970s to the mid-1990s, they had declined toward their peacetime average before the 2008 financial crisis. By contrast, private credit maintained a fairly stable relationship with GDP until the 1970s and then surged to unprecedented levels right up to the outbreak of the crisis. Spain provides an example of the woes in the euro zone periphery and the interplay of private credit and public debt. In 2007, Spain had a budget surplus of about 2% of GDP and government debt stood at 40% of GDP (OECD Country Statistical Profile). That was well below the level of debt in Germany, France, and the United States. But by 2012, Spain’s government debt had more than doubled, reaching nearly 90% of GDP, as the public sector assumed large losses from the banking sector and tax revenues collapsed. Thus, what began as a banking crisis driven by the collapse of a real estate bubble quickly turned into a sovereign debt crisis. In June 2012, Spanish 10-year bond rates reached 7% and, even at that rate, Spain had a hard time accessing bond markets. Once sovereign debt comes under attack in financial markets, banks themselves become vulnerable since many of them hold public debt as assets on their balance sheets. The new bout of weakness in the banking system feeds back again into the government’s future liabilities, setting in motion what some have called the “deadly embrace” or “doom loop.” The conundrum facing policymakers is this: Implement too much austerity and you risk choking off the nascent recovery, possibly delaying desired fiscal rebalancing. But, if austerity is delayed, bond markets may impose an even harsher correction by demanding higher interest rates on government debt. Matters are further complicated for countries in a monetary union, such as Spain. Such countries do not directly control monetary policy and therefore cannot offset fiscal policy adjustments through monetary stimulus by lowering domestic interest rates. In addition, central banks in these countries have limited capacity to stave off self-fulfilling panics since their lender-of-last-resort function evaporates. Fluctuations in fiscal balances over the business cycle are natural. As economic activity temporarily stalls, revenues decline and expenditures increase. With the recovery, fiscal balances typically improve. But the debate on what is a country’s appropriate level of public debt in the medium run continues to rage. It is unclear whether high debt is a cause or a consequence of low economic growth. That said, public debt is not a good predictor of financial crises. Read the full letter here .
  • Economic Letter: Mortgage Choices and Lower Rated Borrowers

    One feature of the recession that received a lot of attention was the glut of foreclosures resulting from high-risk borrowers with adjustable rate mortgages. In a new Economic Letter, San Francisco Fed researchers Fred Furlong , David Lang , and Yelena Takhtamanova look at what drives borrowers to choose riskier loans. Turns out the popular narrative--that borrowers with less wealth lack "financial sophistication"--is not a satisfactory answer: Our model of mortgage choice allows us to examine how these factors affected the decisions of borrowers at different credit risk levels. We studied a sample of about 9 million first-lien U.S. home loans originated between January 1, 2000, and December 31, 2007. We allow for three mortgage choices: FRMs, basic ARMs, and option ARMs. Key model determinants are FRM and ARM margins, the 10-year Treasury term premium, expectations for short-term interest rates over time, and interest rate volatility. We include controls such as loan-to-value ratios, borrower credit risk, the two-year average change in house prices, and a measure of house price volatility. Finally, we define three credit risk groups according to borrower FICO credit rating scores: low of 660 or below, high of 760 or above, and medium of 661 to 759. A key model feature is that it allows the impact of interest-rate-related fundamentals to change as house prices rise. Our estimates show that rising house prices have a sizable influence on the effect these fundamentals have on mortgage choice. The size of this effect differs according to borrower credit ratings. Figure 1 shows the impact of ARM and FRM margins and the term premium on the probability that borrowers with low and high credit ratings will choose an ARM. The green bars show these factor’s marginal effects if house prices were not rising. A higher margin makes ARMs less attractive, so the marginal effects are negative. This effect is greater for the low FICO group, indicating that they tend to be more sensitive to ARM mortgage pricing than the higher FICO group. Specifically, if house prices were flat, a 0.8 percentage point increase in the ARM margin would reduce the probability of low FICO borrowers choosing an ARM 13 percentage points and high FICO borrowers 8 percentage points. It is useful to compare this with the ARM share of mortgage originations, shown in Figure 2, which peaked at 50%. The red bars show the offsetting effects of 16% house price appreciation, the two-year average in our sample. This reduces the ARM marginal effect by about one-third, making the overall effect 8 percentage points for low FICO borrowers and 5 percentage points for high FICO borrowers. Similarly, house price appreciation reduces the impact of increases in the FRM margin and term premium on mortgage choice. Thus, even accounting for the influence of house price gains, lower FICO borrowers generally were at least as sensitive, if not more sensitive, to fundamentals as high FICO borrowers. Read Drivers of Mortgage Choices by Risky Borrowers here .
  • SF Fed Economic Letter: 'Consumer Inflation Views in Three Countries'

    Inflation expectations among consumers are a bit off of actual inflation trends, not just in the U.S. but also in other top economies. That can make the life of central bankers a little more tricky. In an Economic Letter for the San Francisco Fed , Bharat Trehan and Maura Lynch dig into the inflation expectations in Britain, Japan, and the U.S., and the gap between expectations and "relatively long-lasting shifts in the inflation rate." ...Above-target consumer expectations are ironic since the Fed and the Bank of Japan have been worrying, to different degrees, about deflation. The data also show that consumer inflation expectations are extremely sensitive to oil prices. Somewhat alarmingly, those expectations seem to be related to the level of oil prices, not the rate of change as economic theory would suggest. These two characteristics of consumer inflation expectations may be related and could arise from the way consumers form expectations. Rational inattention theory, which emphasizes the costs of processing information, suggests that households may not spend a lot of time and effort rethinking their estimate of the prevailing inflation rate (see Sims 2010). These information processing costs tend to make consumers update their inflation expectations infrequently, especially during periods when inflation is relatively stable. Moreover, instead of using sophisticated models to predict inflation, consumers are more likely to rely on a few simple rules of thumb. Because oil prices are highly volatile, one such rule of thumb could be linked to the price of oil. The apparent importance of the level of oil prices may be related to this casual way of forming expectations. Consumers may well have been feeling the pinch of rising oil prices over the past few years. In an era of stagnant incomes, they could be equating high oil prices with high inflation, an association that presumably will weaken over time. By contrast, the evidence indicates that consumers have not reacted much to central bank inflation target announcements in recent years. This insensitivity is at least partly the result of the prevailing low and stable inflation rates and could go away if the behavior of inflation changed significantly. And even if it were long-lived, the insensitivity of consumer inflation expectations to inflation targets or other central bank announcements does not mean that monetary policy cannot influence consumer behavior. There is no doubt that financial market participants react to monetary policy announcements, and those reactions often have important economic effects. As financial markets respond, the resulting changes in asset prices affect consumer behavior. For instance, if a central bank announces that it expects to ease monetary policy in the future, the currency exchange rate would probably drop. That in turn would tend to lead to higher inflation over time, which would affect consumer behavior. Read the full post here .
  • SF Fed President on the Challenge of Rebalancing Economies in China and US

    Speaking to community leaders in Los Angeles, San Francisco Fed President John C. Williams compared the challenges for U.S. policymakers to those of their counterparts in China. While the details in each economy are rather different, the overall challenges are similar. Both countries need to rebalance their economies for future growth. But that is no small undertaking, and it is made more difficult by short-term challenges. From the speech: Unsurprisingly, economists can’t agree about the primary reason China’s domestic consumption is so low and what should be done about it. One possibility is the population’s focus on saving—in large part to cover the cost of health care, education, and preparation for old age. This is exacerbated by China’s massive and rapid urbanization; as it currently stands, most social services, such as education and health care, are administered in one’s home city. This means that much of the migrant workforce can’t access these services in their new cities, and is forced to save to cover those expenses. While local authorities may balk at paying more for social services, there is a trade-off: addressing such structural barriers would free up workers’ income that could be spent locally, stimulating host cities’ economies. Another issue is increasing income inequality—something we in the United States can relate to. What money is flowing to households is concentrated largely in the expanding class of wealthy citizens, rather than in rural and middle-class families. The final and perhaps most important factor is that, while corporate profits have risen, a comparable rise in individual income has not followed. Again, something that has happened in the United States as well. Low borrowing costs for state-supported firms, combined with low wages for many workers, have helped business profits at the expense of households. If China is to rebalance the economy away from exports and towards domestic consumption, there must be an increase in household incomes. That means higher wages and dividend payments from firms. Further liberalization of the financial system will also help, as higher deposit rates and more investment options would boost spending power. Furthermore, China’s citizens must feel a sense of stability and certainty regarding their future. When we’re worried about the future, the natural response is to want to save more. So, even if these steps were to be taken, the question remains whether China’s middle- and rural-class citizens are willing to become bigger spenders anytime soon. Turning to the United States, over the longer run we need to increase investment in education, physical capital, technology, and infrastructure. We will also need to put federal fiscal policy on a sustainable path, which involves making some tough decisions about taxes and spending. Importantly, spending less on current consumption will free up resources for investment areas that foster greater production and will increase the size of the economy over the long term. However, to succeed at these longer-run goals, we first need to get our economy working at its full potential. That’s where the Federal Reserve and monetary policy come in. Since the early days of the crisis and recession, the Federal Reserve’s monetary policy body, the Federal Open Market Committee (FOMC), has been taking strong actions to foster economic recovery and get people back to work. We lowered short-term interest rates to near zero almost five years ago. The goal was simple: With very low interest rates, households and businesses are more willing to spend. This increase in demand for goods and services leads businesses to hire more workers. Read Rebalancing the Economy: A Tale of Two Countries here .
  • Economic Letter: 'Why Are Housing Inventories Low?'

    Have you received a cold-call from a realtor asking whether you or any of your neighbors are thinking of selling a house? This is a sure sign of low inventory in your area. Sales have been sluggish of late, despite the economic recovery, and a primary factor is the lack of homes on the market. William Hedberg and John Krainer of the San Francisco Fed 's Economic Research Department have been looking at potential causes for the low inventory. As they write in a new Economic Letter , lower home prices post-recession may be key: Falling prices may hold down home sales for several reasons. If house prices fall far enough to push a homeowner underwater so that the market value of the home is less than the value of the mortgage, then the owner may be unwilling or unable to realize this loss and choose to delay a sale. In this case, the homeowner may be locked into the house because a sale wouldn’t provide enough cash to make the down payment on a new home. Figure 3 plots the correlation between the share of mortgages underwater in a county at a given point in time and the share of total units for sale averaged over a quarter in that same county. Homes for sale are scaled by total units to facilitate cross-county comparisons. Since early 2008, homes for sale and mortgages underwater have been negatively correlated. Counties with higher shares of mortgages underwater tended to have lower inventories. Though this relationship is significant, its strength diminished as the recession ended and the recovery got under way. Underwater borrowers may have been locked into their houses in a way that impaired the normal functioning of the housing market. But that effect seems to be waning. Another possible explanation for the breakdown in the normal relationship between prices and inventories of homes for sale is that homeowners may be taking a longer-term view of the housing market. It is well documented that house price changes are persistent, meaning that price rises are likely to be followed by more rises, and price drops by more drops. Homeowners with flexibility on the timing of their home sales can potentially take advantage of this persistence. If they observe prices going up, they may want to wait and gamble that the increases will continue, allowing them to sell later at a higher price. The data are consistent with this explanation. Figure 4 confirms on a county level the negative relationship between prices and inventories shown at the aggregate level in Figure 1. On balance, counties that experienced relatively large increases in house prices over the past year also experienced relatively large declines in inventories available for sale. It turns out that variables such as recent house price appreciation and changes in employment are the most robust predictors of recent changes in housing inventory. In other words, once we account for changes in house prices and employment in a county, other variables, such as changes in the for-rent inventory, the underwater share, or local price-rent ratios, do little to explain the inventory of houses for sale. Thus, current homeowners may be making a rational choice to postpone selling in the hope that prices will rise further. However, this behavior tends to be short run. In the longer run, the link between the level of house prices and for-sale inventories is strong. If prices continue to rise, inventories for sale should eventually rise too. Read the full Economic Letter here .
  • SF Fed Economic Letter: 'Gaug[ing] the Current Momentum of the Labor Market Recovery'

    You'll no doubt recall that the Federal Reserve Board of Governors have tied changes in monetary policy to "substantial improvement in the labor market." In an Economic Letter for the San Francisco Fed , Mary C. Daly , Bart Hobijn , and Benjamin Bradshaw examine whether there are any signs of improvement. We begin by considering a wide array of data on labor market conditions in the United States. This includes information on employment, unemployment, the rate at which people quit existing jobs, the number of people who get hired, employers’ perceptions of the ease of filling their job vacancies, and workers’ sentiment about the state of the overall labor market. Because each of these series comes from a different source, comparing them requires putting them on equal footing in terms of how they’re measured. We do this by normalizing each indicator, as well as its 6-month change, to reflect how much it deviates from its own historical average at any point in time. In particular, we perform a statistical test by measuring how many standard deviations an indicator is from its historical average. The normalized six-month change in an indicator gives us a sense of whether it has a persistently strong correlation with the unemployment rate. We call this persistence number “momentum.” Finally, to make these data easier to compare, we transform them so they all move in the same direction over the business cycle. For example, the unemployment rate tends to decline when payroll job growth increases. To make job growth move in the same direction as the unemployment rate, we change its sign. We focus on the period from January 1978 to mid-2013. Our main interest is identifying those indicators whose movements over the past six months are most highly correlated with changes in the unemployment rate in the next six months. Because we are interested in the signals these data send about improvement in the outlook for the labor market, we calculate correlations over labor market expansions only, and do not include recessions. This is important because indicators that lead the labor market during downturns are not necessarily as informative during expansions. A prime example is the number of layoffs, which helps assess the depth of a downturn but is of little use in gauging the strength of a recovery. This is because the strength of recoveries is based on the rate at which people find jobs, which can remain low for some time after layoffs have subsided (Elsby, Hobijn, and Şahin, 2013). Among the 30 indicators we analyze, six stand out as excellent predictors of future improvements in the unemployment rate. Indeed, these six predict future changes in the unemployment rate better than lagged improvements in the unemployment rate itself. These indicators are the insured unemployment rate, initial claims for unemployment insurance, capacity utilization, the jobs gap, the Institute for Supply Management (ISM) manufacturing index, and private payroll employment growth. Among these common indicators, the jobs gap is the least familiar. Taken from the Conference Board’s Consumer Confidence Survey, it measures the difference between the percentage of households that considers jobs hard to get and the percentage that considers jobs plentiful. The six indicators are listed in Table 1 in order of their predictive power for future changes in the unemployment rate, as captured by the correlation between the indicators’ momentum, and changes in the unemployment rate during the subsequent six months. These correlations are printed in boldface in the second column of the table. The unemployment rate is listed in the first row for comparison. Comparing the first row with the other rows shows that the momentum of these indicators are all more closely correlated with the future change in the unemployment rate than the momentum of the unemployment rate itself. That is, when considering the speed at which the unemployment rate will come down, changes in our six indicators are better predictors than changes in the unemployment rate. This is precisely the value of these six momentum indicators. Read Gauging the Momentum of the Labor Recovery here .
  • The Stickiness of Wages

    In a new Economic Letter , San Francisco Fed economists Mary Daly , Bart Hobjin , and Timothy Ni take a look at wage rigidity. In what may seem counter-intuitive, wage growth did not slow much during the Great Recession, even as unemployment climbed rapidly. And now wages are not rising much during the economic recovery and dropping unemployment. Apparently, this has happened in other recent recessions, though the extent to which wages have been slow to respond to overall economic change seems greater. Figure 1 clearly shows downward nominal wage rigidity in the distribution of wage changes among U.S. workers in 2006 and 2011. The data cover all workers and measure how their wages compared with their previous year’s wages, if they were employed. We use 2006 as an example of a typical wage change distribution and compare those numbers with the post-recession wage changes for 2011. The distribution of wage changes in 2006 and 2011 both spike at zero, suggesting that the wages of many workers did not change from year to year. In both years, the distribution is larger to the right of zero, that is, for wage increases, than to the left of zero, for wage cuts. Consistent with downward nominal rigidity, this suggests that a large fraction of wage cuts employers wanted to carry out were not actually made. Instead, those workers were swept into the zero-change group. What is more interesting in this figure is how 2006 and 2011 data differ. First, the fraction of workers whose wages were frozen jumped from 12% of the workforce in 2006 to 16% in 2011. Second, despite the severity of the Great Recession, very few workers experienced wage cuts. These numbers edged up only slightly from 2006 to 2011. Finally, and perhaps most interestingly, the percentage of workers who received wage increases dropped notably in 2011 compared with 2006. This compression of wage increases resulted in a larger spike at zero. Read The Path of Wage Growth and Unemployment here .
  • San Francisco Fed President on Fed Policy and the Past, Present, and Future of the Economic Recovery

    San Francisco Fed President John C. Williams has no qualms about the quality of the Federal Reserve System's work over the past several years. Speaking to the Sonoma County Economic Development Board last week, Williams gave a clear, concise roundup of the economic recovery so far, and offered up some prognostication of where things are headed. Williams made the point that the recovery has exceeded expectations. And Fed response, Williams argues, was key to that success: During the recession and early in the recovery, the federal government threw a critical lifeline to the economy. Congress and the White House boosted spending substantially and cut taxes for households and businesses, which partly offset the collapse of the private economy. The $800 billion stimulus package passed in 2009 was a huge help.6 But this has turned on its head. That stimulus has wound down. And, at the beginning of 2013, tax rates rose for upper-income households and the Social Security payroll tax cut ended. More recently, the sequestration process has forced major cuts in federal spending. By contrast, fiscal policy at the state and local government level has been a drag on the economy since the beginning of the recession. Unlike Uncle Sam, state and local governments typically must balance their budgets each year. As revenues plunged, they cut spending and employment deeply and, in some cases, raised taxes. Thankfully, that painful process may be drawing to a close. Recent data show state and local government revenue is climbing again, something we’re certainly happy to see in California. Still, expenditures and employment remain well below pre-recession levels. Here is a way to appreciate how big the swing in the role of government has been: In the two years beginning in the fourth quarter of 2007, spending at all levels of government, adjusted for inflation, increased more than 6½ percent, while private-sector spending fell nearly 6 percent. But, since the end of 2009, government spending has fallen nearly 7½ percent and private spending has risen more than 10½ percent. Employment data paint a similar picture. Since the end of 2009, governments have shed more than 600,000 jobs. At the same time, private employers outside the farm sector have added 6.9 million jobs. Clearly, government austerity is one factor holding back economic growth. In the job market, private-sector hiring has actually picked up. Over the past six months, nonfarm private payrolls have grown by just under 200,000 jobs per month compared with an average of about 160,000 in the previous six months. The unemployment rate has fallen six-tenths of a percentage point over the past 12 months. What about the future? San Francisco Fed researchers have identified indicators that provide information about how the labor market is likely to fare over the next six months. These include data you may be familiar with, such as initial unemployment claims, and less well-known data, such as the percentage of people who say in surveys that it’s hard to find a job. These indicators suggest that the labor market will continue to strengthen. Here then is my forecast. I expect the unemployment rate to fall to roughly 7¼ percent at the end of this year and drop to about 6¾ percent by the end of 2014. Economic growth is likely to be sluggish in the current and next quarter, reflecting federal spending and employment cuts related to sequestration. It should pick up later in the year. For 2013 as a whole, I see inflation-adjusted GDP growing about 2¼ percent and picking up to around 3¼ percent in 2014. Read the full speech here .
  • SF Fed Economic Letter: 'Crises Before and After the Creation of the Fed'

    With the Federal Reserve turning 100, San Francisco Fed economists Early Elias and Òscar Jordà take a moment to look at the impact of their parent institution on crisis mitigation. They point to fewer crises over the last 100 years than in the previous century, and the less severe results of the Great Recession compared to the Panic of 1907 as evidence of the Fed's relative success. Here is an excerpt from their Economic Letter: Recessions originating from a financial event were common in the late 19th and early 20th centuries. Many stemmed from banking panics. Figure 1 provides a global historical perspective. We calculate by decade the number of countries that experienced financial crises among a sample of 17 industrialized economies representing more than half of global GDP during the past 140 years (for details, see Jordà, Schularick, and Taylor 2012). Figure 1 shows a notable downward global trend in the incidence of these highly disruptive events, with the conspicuous exceptions of the Great Depression and the Great Recession of 2007–09. In the United States, the rate of banking crises declined markedly after the 1913 creation of the Federal Reserve System. Other than the Great Depression and Great Recession, the only significant banking crisis of the past century was the savings and loan crisis. By contrast, ten significant banking crises occurred in the 19th century. The panic of 1907 and the resulting recession are generally credited with providing the catalyst for the creation of the Federal Reserve System. When the Federal Reserve was chartered, the United States had been without a central bank for about 70 years. Congress chartered The First Bank of the United States in 1791 during the Washington presidency, under the guiding hand of Secretary of Treasury Alexander Hamilton. However, its 20-year charter was allowed to expire in 1811. Then, under President Madison, the Second Bank of the United States was created in 1817 for another 20-year period. Once again, the charter was allowed to expire amid President Jackson’s strong opposition to the central bank. Read the full letter here .
  • San Francisco Fed: 'Will the Unemployment Rate Stall in 2013?'

    Watching the ups and downs of unemployment statistics in the monthly jobs report can become too much like following a sporting event. Thinking of it as a score can hide some key variables. That said, it has been promising to see the unemployment rate drop so significantly over the last year. Even though it is not as strong an indicator--by itself--as the media coverage may make it seem, it is better to see it drop at that fast rate than not. Can it continue to drop? Well, that depends greatly on what happens with discouraged workers. If the labor market continues to improve at a fast enough rate that discouraged workers get less discouraged and return to the labor force, we could see a stalling in the unemployment rate even as the overall jobs picture improves. Òscar Jorda of the San Francisco Fed explains all of this in a helpful Economics in Person video: Watch live streaming video from frbsf at
  • SF Fed President: "An aggregate demand shortfall is exactly the kind of problem monetary policy can address"

    San Francisco Fed President John C. Williams visited the Forecasters Club in New York last Thursday and gave his assessment of the economy. He named four key factors behind the slow, or "tepid" recovery: 1) the effects of the housing bubble and crash; 2) austerity measures reducing aggregate demand; 3) eroding demand for exports with a weakened global economy; and 4) unusually high levels of uncertainty. He then addressed the question of whether these factors affect supply and demand: So, is the problem today inadequate supply, or demand, or both? A useful way to think about this question is to compare the unemployment rate with the natural rate of unemployment. By the natural rate, I mean the unemployment rate that minimizes labor market imbalances and pressures—either upward or downward—on inflation. The unemployment gap—the difference between the unemployment rate and its natural rate—measures the degree to which labor demand is unequal to supply. Movements in the natural rate itself reflect changes in supply. Of course, we can’t directly measure the natural rate of unemployment. Rather, we must estimate it. This topic has appropriately garnered a great deal of attention among economists at the Federal Reserve and elsewhere in recent years. Extensive analysis of the labor market comes to a clear conclusion: Supply-side considerations explain only some of the rise in unemployment. Most of that rise is explained by a lack of labor demand. Let’s look at this more closely. Prior to the recession, a typical estimate of the natural rate of unemployment was between 4¾ and 5% (see Williams 2013). The empirical evidence suggests that the recession and policy responses to it, such as extended unemployment insurance benefits, contributed to dislocations in the labor market. These have pushed the natural rate above its pre-recession level by about 1 percentage point (see Congressional Budget Office 2013 and Daly et al. 2012b). Consistent with these findings, my estimate of the current natural rate of unemployment is about 6%, roughly 2 percentage points below the current unemployment rate. This 6% figure is consistent with many other estimates, including the most recent median estimate of the Survey of Professional Forecasters (Federal Reserve Bank of Philadelphia 2012). Fortunately, many of the influences that have elevated the natural rate of unemployment since the crisis and recession should fade over time. In fact, this process is already under way. The extended unemployment insurance programs have been scaled back and are affecting fewer and fewer people. Eventually these programs will be phased out. In addition, measures of mismatch between workers and available jobs are receding (Lazear and Spletzer 2012 and Șahin et al. 2012). And, at least so far, we are not seeing permanent scarring effects of long-term unemployment (Valletta 2013). I expect that, in coming years, the natural rate will return to a more historically typical level of about 5½%. I should note that the fact that economists are busily studying, debating, and revising their assessments of the supply side of the economy is encouraging. It makes a repetition of the mistakes of the late 1960s and 1970s much less likely. In our research, Orphanides and I found that, if economists and policymakers had similarly reevaluated their views back in the 1960s and 1970s, the stagflation of that period could have been avoided (Orphanides and Williams 2013). The conclusion that the economy is suffering primarily from weak demand rather than a shortage of supply receives additional support when the factors weighing on recovery are analyzed. The finding of the research that I mentioned on the economic effects of uncertainty—that heightened uncertainty raises unemployment and depresses inflation—is evidence that uncertainty primarily acts as a barrier to demand, not supply. Other research supports that view. In recent work published by the San Francisco Fed, Mian and Sufi (2013) compare state-level employment performance during the recession and recovery with state-level survey data from the National Federation of Independent Business. The NFIB survey asks small business owners to identify the single most important problem they face. Answers include taxes, poor sales, labor costs, government regulation, insurance costs, et cetera. Mian and Sufi find that declines in state employment were highly correlated with the percentage of respondents in each state citing lack of demand as their most important business problem. Read the full speech here .
  • SF Fed: Impact of Discouraged Workers Rejoining Labor Force on Unemployment Rate

    Take a look at the trend line for the percentage of Americans who are not currently looking for work but who want jobs, from a new Economic Letter by San Francisco Fed researchers Mary Daly , Early Elias , Bart Hobijn , and Òscar Jorda : There is a clear growth of what the Bureau of Labor Statistics terms "discouraged workers" since the recession. These workers do not count against the unemployment rate. So as we get set to begin another year of watching monthly job reports closely, we need to be aware of how a positive trend of these Americans returning to the workforce will affect the unemployment rate. Nearly 6.9 million people report being out of the labor force but wanting a job. As economic conditions improve, it is reasonable to expect that some of these workers will move back into the labor force or join for the first time. Based on historical averages, about 2.1 million of them could enter the job market. These potential entrants will either take jobs directly or join the labor force as unemployed workers actively searching for jobs. The near-term path of unemployment will reflect both how quickly potential workers enter the labor force and the rate at which jobs are created. Assume that the average pace of job creation over the past two years continues. We can then project the path of the unemployment rate over the next year according to the rate at which the 2.1 million potential workers enter the labor force. If these workers take a year and a half to join the labor force, which would be about a year faster than the entry rate from 1994 to 1999, the recent decline in the unemployment rate would stall at more than 8% by the end of next year. Suppose though that the number of workers who want a job but are not actively looking falls at a more moderate pace and it takes three-and-a-half years for this group to join the labor force. In that case, the unemployment rate would stay at 7.7% through the end of next year. For comparison, if none of the 2.1 million potential workers were to enter the labor market, the unemployment rate would fall to 7.4% by the end of 2013. Of course, the rate at which these workers join the labor force may reflect the labor market’s overall strength. A faster rate of job creation may offset a faster rate of labor force entry, allowing the unemployment rate to fall. Read Will the Jobless Rate Drop Take a Break? here .