10 PART 1: RECENT ECONOMIC AND FINANCIAL DEVELOPMENTS Employment Disparities between Rural and Urban Areas The U.S. labor market has recovered substantially A. Employment-to-population ratios since 2010. For people in their prime working years (ages 25 to 54), the unemployment rate has move Monthly down steadily to levels below the previous business cycle peak in 2007, the labor force participation rate (LFPR)has retraced much of its decline and the share of the population who are employed-known as the mployment-to-population ratio, or EPOP ratio- has returned to about its level before the recession However, the labor market recovery has been uneven across the country, with"rural"(or nonmetro)areas howing markedly less improvement than cities and ndings(metro areas).' Non-MSA The extent of the initial decline and subsequent improvement in the EPOP ratio varied by metropolitan LLL⊥⊥⊥ LILL⊥⊥L status. The gap between the EPOP ratios in rural and 19982001200420072010201320162019 before the recession, and the cyclical recovery stane. as larger urban areas is now noticeably wider than it MSAs consist later in rural areas. Specifically, as shown in figure A 500,000 people. The shaded bars indicate periods of business efined by the National Bureau of Econc the prime-age EPOP is now slightly above its pre- eferences listed in box note 2 recession level in larger urban areas, whereas it is just below its pre-recession average in smaller urban areas and much below its pre-recession level in rural areas. B. Unemployment rates The EPOP ratio can usefully be viewed as summarizing both the LFPR--that is, the share of the population that either has a job or is activel king for work-and the unemployment rate, which measures the share of the labor force without a job and actively searching. The divergence in rural and urban EPOP ratios during the economic expansion almost entirely reflects divergences in LFPRs rather than in unemployment rates(figures B and C). In particular, the rural and urban unemployment rates have tracked each (continued) Non-M 1. For convenience, we refer to metropolitan counties with strong commuting ties to an urbanized center as"urban"and Larger MSAs nonmetropolitan counties that lack such ties as"rural. 2. For all figures in this discussion, the raw data are from the U.S. Census Bureau, Current Population Survey; note L⊥L⊥⊥⊥LL⊥L⊥1L⊥⊥LL⊥1L process for the Current Population Survey. Calculations o> hat the bureau of labor statistics is involved in the su 99820012004200720102015 he series shown are as described in Alison Weingarde (2017),"Labor Market Outcomes in Metropolitan and lon-metropolitan Areas: Signs of Growing Disparities, of100.000to500.000 he sh bars indicate periods of business FEDS Notes (Washington: board of Governors of the Federal recession as defined by SOURCE: References box note 2 ReserveSystemSeptember25),www.federalrese otes/labor-market. sparities-20170925. htm. The figures show 12-month moving es of the monthly time-series. 3. Specifically, the EPOP ratio equals(LFPR)x( bor force. "These numbers are multiplied by unemployment rate), where LFPR is defined as"labor force/ 100 for presentation purposes in the figures
10 PART 1: RECENT ECONOMIC AND FINANCIAL DEvELOPMENTS Employment Disparities between Rural and Urban Areas The U.S. labor market has recovered substantially since 2010. For people in their prime working years (ages 25 to 54), the unemployment rate has moved down steadily to levels below the previous business cycle peak in 2007, the labor force participation rate (LFPR) has retraced much of its decline, and the share of the population who are employed—known as the employment-to-population ratio, or EPOP ratio— has returned to about its level before the recession. However, the labor market recovery has been uneven across the country, with “rural” (or nonmetro) areas showing markedly less improvement than cities and their surroundings (metro areas).1 The extent of the initial decline and subsequent improvement in the EPOP ratio varied by metropolitan status. The gap between the EPOP ratios in rural and larger urban areas is now noticeably wider than it was before the recession, and the cyclical recovery started later in rural areas. Specifically, as shown in figure A, the prime-age EPOP is now slightly above its prerecession level in larger urban areas, whereas it is just below its pre-recession average in smaller urban areas and much below its pre-recession level in rural areas.2 The EPOP ratio can usefully be viewed as summarizing both the LFPR—that is, the share of the population that either has a job or is actively looking for work—and the unemployment rate, which measures the share of the labor force without a job and actively searching.3 The divergence in rural and urban EPOP ratios during the economic expansion almost entirely reflects divergences in LFPRs rather than in unemployment rates (figures B and C). In particular, the rural and urban unemployment rates have tracked each 1. For convenience, we refer to metropolitan counties with strong commuting ties to an urbanized center as “urban” and nonmetropolitan counties that lack such ties as “rural.” 2. For all figures in this discussion, the raw data are from the U.S. Census Bureau, Current Population Survey; note that the Bureau of Labor Statistics is involved in the survey process for the Current Population Survey. Calculations of the series shown are as described in Alison Weingarden (2017), “Labor Market Outcomes in Metropolitan and Non-metropolitan Areas: Signs of Growing Disparities,” FEDS Notes (Washington: Board of Governors of the Federal Reserve System, September 25), www.federalreserve. gov/econres/notes/feds-notes/labor-market-outcomes-inmetropolitan-and-non-metropolitan-areas-signs-of-growingdisparities-20170925.htm. The figures show 12-month moving averages of the monthly time-series. 3. Specifically, the EPOP ratio equals (LFPR) x (1 – unemployment rate), where LFPR is defined as “labor force/ population” and the unemployment rate is defined as “persons unemployed/labor force.” These numbers are multiplied by 100 for presentation purposes in the figures. (continued)
MONETARY POLICY REPORT: FEBRUARY 2019 11 other fairly closely in this expansion, though they have C. Labor force participation rates difference between rural and urban LFPRs has widened significantly over the past decade. On average, people in rural areas tend to have fewer years of schooling than people in urban areas and because the epop ratio tends to be lower for individuals with less education, this demographic difference has contributed to the persistent rural-urban Larger MSAs divide. However, these educational differences do not rural and urban EPOP ratios have widened. Figure D shows that, in recent years, rural and urban EPOP ratios diverged substantially even within educational Non-MSA categories, similar to the divergence in EPOPs more generally The left panel of figure D shows that the EPOP ratio of non-college-educated adults ages 25 to L⊥L 54 has been much lower in rural areas than in urban 19982001200420072010201320162019 ones beginning in 2012. The right panel of figureD No hows that the EPOP ratio of college-educated adults but that is no longer so. Thus, the recent widening of ouRce eferences lised an ox note 2. the rural-urban disparity in EPOP ratios has not been primarily driven by differences in years of education. Nevertheless, because the recovery in the EPOP ratio for non-college-educated adults in rural areas (continued on next page) D. Employment-to-population ratio Noncollege adults College adults MSAs LLLLL⊥LL⊥⊥LLLL⊥L⊥⊥⊥L」 LLLL⊥LL⊥⊥LL⊥L⊥LL⊥⊥L」 2001200420072010201320162019 998200120042007201020132016 NOTE: Data are for persons aged 25 to 54. MSA is metropolitan statistical area. The shaded bars indicate periods of business recession as defined by the SoURCE: References listed in box note 2
MONETARy POLICy REPORT: FEBRUARy 2019 11 other fairly closely in this expansion, though they have diverged a little in the past few years. In contrast, the difference between rural and urban LFPRs has widened significantly over the past decade. On average, people in rural areas tend to have fewer years of schooling than people in urban areas, and because the EPOP ratio tends to be lower for individuals with less education, this demographic difference has contributed to the persistent rural–urban divide. However, these educational differences do not appear responsible for the fact that the gap between rural and urban EPOP ratios have widened. Figure D shows that, in recent years, rural and urban EPOP ratios diverged substantially even within educational categories, similar to the divergence in EPOPs more generally. The left panel of figure D shows that the EPOP ratio of non-college-educated adults ages 25 to 54 has been much lower in rural areas than in urban ones beginning in 2012. The right panel of figure D shows that the EPOP ratio of college-educated adults used to be higher in rural areas than in urban ones, but that is no longer so. Thus, the recent widening of the rural–urban disparity in EPOP ratios has not been primarily driven by differences in years of education. Nevertheless, because the recovery in the EPOP ratio for non-college-educated adults in rural areas (continued on next page)
12 PART 1: RECENT ECONOMIC AND FINANCIAL DEVELOPMENTS Employment Disparities(continued) has been particularly weak, it is likely that broader Insurance(SSDI)benefits, and, in fact, take-up macroeconomic trends--including the ongoing shift in increased a little more in rural areas than it did in urban bor demand that has favored individuals with more ones over the past decade education--have had more adverse consequences When regions are faced with adverse changes for the populations in rural areas than in urban areas. in labor demand, some residents may respond by For example, manufacturing, where employment has migrating to more prosperous areas. The more out gnated, accounts for a larger share of employment ation that occurs from areas with relatively fewer in rural areas than in urban areas, while fast-growing labor market opportunities, the smaller should be the ervices industries, such as health-care and professional observed decline in local-area EPOPs. 5 However, some services that tend to employ workers with more research suggests that the average migration response education are more concentrated in urban areas. to adverse demand shocks has decreased in recent Indeed, employment in manufacturing has not yet decades, which could amplify the labor market effects fully recovered from the recession. And, despite of local s cks and lead to persistent disparities in the strength in the past two years, the share of total EPOP ratios across areas. 6 manufacturing has remained near its post-recession low 4. This increase could reflect growing public health The fact that most of the epop divergence is seen in labor force participation rather than unemployme for SSDI) and sluggish labor demand in rural areas(which fy rates suggests that many rural workers who experienced benefits d increases the propensity of individuals to apply for SSDI o permanent job loss, perhaps due to a factory closing, 5. Although a higher rate of rural out-migration would hel decided to eventually exit the labor force rather than close the EPOP gap, depopulation might exacerbate economic continue their job search. Some individuals who had emain in rural areas een working, despite ongoing health problems, may ample, Mai Dao, Davide Furceri, and Prakash have responded to job loss and poor reemployment oungani(2017), "Regional Labor Market Adjustment in the opportunities by applying for Social Security Disability Statistics, vol 99(May), pp 243-5 ew of Economics and United States: Trend and Cycle, "Re
12 PART 1: RECENT ECONOMIC AND FINANCIAL DEvELOPMENTS Insurance (SSDI) benefits, and, in fact, take-up increased a little more in rural areas than it did in urban ones over the past decade.4 When regions are faced with adverse changes in labor demand, some residents may respond by migrating to more prosperous areas. The more outmigration that occurs from areas with relatively fewer labor market opportunities, the smaller should be the observed decline in local-area EPOPs.5 However, some research suggests that the average migration response to adverse demand shocks has decreased in recent decades, which could amplify the labor market effects of local shocks and lead to persistent disparities in EPOP ratios across areas.6 has been particularly weak, it is likely that broader macroeconomic trends—including the ongoing shift in labor demand that has favored individuals with more education—have had more adverse consequences for the populations in rural areas than in urban areas. For example, manufacturing, where employment has stagnated, accounts for a larger share of employment in rural areas than in urban areas, while fast-growing services industries, such as health-care and professional services that tend to employ workers with more education, are more concentrated in urban areas. Indeed, employment in manufacturing has not yet fully recovered from the recession. And, despite the strength in the past two years, the share of total employment in manufacturing has remained near its post-recession low. The fact that most of the EPOP divergence is seen in labor force participation rather than unemployment rates suggests that many rural workers who experienced a permanent job loss, perhaps due to a factory closing, decided to eventually exit the labor force rather than continue their job search. Some individuals who had been working, despite ongoing health problems, may have responded to job loss and poor reemployment opportunities by applying for Social Security Disability Employment Disparities (continued) 4. This increase could reflect growing public health problems (which expands the pool of individuals who qualify for SSDI) and sluggish labor demand in rural areas (which increases the propensity of individuals to apply for SSDI benefits). 5. Although a higher rate of rural out-migration would help close the EPOP gap, depopulation might exacerbate economic difficulties for those who remain in rural areas. 6. See, for example, Mai Dao, Davide Furceri, and Prakash Loungani (2017), “Regional Labor Market Adjustment in the United States: Trend and Cycle,” Review of Economics and Statistics, vol. 99 (May), pp. 243–57
MONETARY POLICY REPORT: FEBRUARY 2019 13 Price inflation is close to 2 percent Consumer price inflation has fluctuated around the FOMC's objective of 2 percent, largely reflecting movements in energy prices As measured by the 12-month change in 8. Change in the price index for personal consumption the price index for personal consumption expenditures(PCe), inflation is estimated 12-month percent change to have been 1.7 percent in December after being above 2 percent for much of 2018 (figure 8). Core PCE inflation-that is Total Trimmed mean Excluding food 2.5 inflation excluding consumer food and energy and energy prices-is estimated to have been 1.9 percent n December. Because food and energy prices are often quite volatile, core inflation typically provides a better indication than the total measure of where overall inflation will be in the future. Total inflation was below core inflation for the year as a whole not only 2012201320142015201620172018 because of softness in energy prices, but also toTE: The data for total and excluding food and because food price inflation has remained December 2018 final values are staff estimates. The trimmed data extend relatively low. ederal Reserve Bank of Dallas: for all else Bureau of Economic Analysis; all via Haver Analytics. Core inflation has moved 017. when inflation was held down by some unusually rge price decline categories of spending, such as mobile phone services. The trimmed mean PCe price index produced by the Federal Reserve Bank of inflation of transitory influences, and it may be less sensitive than the core index to idiosyncratic price movements such as those noted earlier. The 12-month change in this measure did not decline as much as core PCe inflation in 2017. and it was 2.0 percent in November. Inflation likely has been increasingly supported by the strong labor market in an environment of stable inflation expectations: infation last year was 6. The partial government shutdown has delayed publication of the Bureau of Economic Analysis's estimate for PCE price inflation in December, and the numbers reported here are estimates based on the December consumer and producer price indexes. 7. The trimmed mean index excludes whichever prices showed the largest increas decreases in a given month. Note that over the past 20 years, changes in the trimmed mean index have averaged about 74 percentage point above core PCE inflation and 0. I percentage point above total pce inflation
MONETARy POLICy REPORT: FEBRUARy 2019 13 Price inflation is close to 2 percent Consumer price inflation has fluctuated around the FOMC’s objective of 2 percent, largely reflecting movements in energy prices. As measured by the 12-month change in the price index for personal consumption expenditures (PCE), inflation is estimated to have been 1.7 percent in December after being above 2 percent for much of 2018 (figure 8).6 Core PCE inflation—that is, inflation excluding consumer food and energy prices—is estimated to have been 1.9 percent in December. Because food and energy prices are often quite volatile, core inflation typically provides a better indication than the total measure of where overall inflation will be in the future. Total inflation was below core inflation for the year as a whole not only because of softness in energy prices, but also because food price inflation has remained relatively low. Core inflation has moved up since 2017, when inflation was held down by some unusually large price declines in a few relatively small categories of spending, such as mobile phone services. The trimmed mean PCE price index, produced by the Federal Reserve Bank of Dallas, provides an alternative way to purge inflation of transitory influences, and it may be less sensitive than the core index to idiosyncratic price movements such as those noted earlier. The 12-month change in this measure did not decline as much as core PCE inflation in 2017, and it was 2.0 percent in November.7 Inflation likely has been increasingly supported by the strong labor market in an environment of stable inflation expectations; inflation last year was 6. The partial government shutdown has delayed publication of the Bureau of Economic Analysis’s estimate for PCE price inflation in December, and the numbers reported here are estimates based on the December consumer and producer price indexes. 7. The trimmed mean index excludes whichever prices showed the largest increases or decreases in a given month. Note that over the past 20 years, changes in the trimmed mean index have averaged about ¼ percentage point above core PCE inflation and 0.1 percentage point above total PCE inflation
14 PART 1: RECENT ECONOMIC AND FINANCIAL DEVELOPMENTS also boosted slightly by the tariffs that were imposed throughout 2018 Oil prices have dropped markedly in recent months As noted, the slower pace of total inflation 9. Spot and futures prices for crude oil in late 2018 relative to core inflation largely reflected softening in consumer energy price Dollars per bam toward the end of the year After peaking Brent spot price 130 at about $86 per barrel in early October, the p and has averaged around S60 per barrel this 24-month-ahead year(figure 9). The recent decline in oil prices has led to moderate reductions in the cost of gasoline and heating oil. Supply factors, including surging oil production in Saudi Arabia, Russia, and the United States, appear to be most responsible for the recent price declines, but concerns about weaker global growth likely also played a role NoTE The data are weekly averages of daily data and extend through SouRcE: ICE Brent Futures via Bloomberg while prices of imports other than energy have also declined After climbing steadily since their early 2016 lows, nonfuel import prices peaked 10. Nonfuel import prices and industrial metals indexes May 2018 and declined for much of the rest of 2018 in response to dollar appreciatio January 2014=100 January 2014=100 lower foreign inflation and declines in 120一 commodity prices. In particular, metal prices fell markedly in the second half of 2018, partly reflecting concerns about prospects for the global economy(figure 10). Nonfuel import prices, before accounting for the effects of tariffs on the price of imported goods, had nfuel import prices roughly a neutral influence on U.S. price inflation in 2018 Survey-based measures of inflation 2018 expectations have been stable for nonfuel import prices hly. The data for are a monthly average of daily data and extend through Expectations of inflation likely influence February onfuel import prices, Bureau of Labor Statistics: for actual infation by affectin and industrial setting decisions. Survey-based measures of inflation expectations at medium -and longer term horizons have remained generally stable over the second half of 2018. In the Survey of Professional Forecasters, conducted by the Federal Reserve Bank of Philadelphia the median ex for the annual rate of increase in the PCe price index over the
14 PART 1: RECENT ECONOMIC AND FINANCIAL DEvELOPMENTS also boosted slightly by the tariffs that were imposed throughout 2018. Oil prices have dropped markedly in recent months . . . As noted, the slower pace of total inflation in late 2018 relative to core inflation largely reflected softening in consumer energy prices toward the end of the year. After peaking at about $86 per barrel in early October, the price of crude oil subsequently fell sharply and has averaged around $60 per barrel this year (figure 9). The recent decline in oil prices has led to moderate reductions in the cost of gasoline and heating oil. Supply factors, including surging oil production in Saudi Arabia, Russia, and the United States, appear to be most responsible for the recent price declines, but concerns about weaker global growth likely also played a role. . . . while prices of imports other than energy have also declined After climbing steadily since their early 2016 lows, nonfuel import prices peaked in May 2018 and declined for much of the rest of 2018 in response to dollar appreciation, lower foreign inflation, and declines in commodity prices. In particular, metal prices fell markedly in the second half of 2018, partly reflecting concerns about prospects for the global economy (figure 10). Nonfuel import prices, before accounting for the effects of tariffs on the price of imported goods, had roughly a neutral influence on U.S. price inflation in 2018. Survey-based measures of inflation expectations have been stable . . . Expectations of inflation likely influence actual inflation by affecting wage- and pricesetting decisions. Survey-based measures of inflation expectations at medium- and longerterm horizons have remained generally stable over the second half of 2018. In the Survey of Professional Forecasters, conducted by the Federal Reserve Bank of Philadelphia, the median expectation for the annual rate of increase in the PCE price index over the