Inflation, uncertainty, and monetary policy


Low inflation likely reflects factors whose influence should fade over time. But many uncertainties attend this assessment, and downward pressures on inflation could prove to be unexpectedly persistent. My colleagues and I may have misjudged the strength of the labor market, the degree to which longer-run inflation expectations are consistent with our inflation objective, or even the fundamental forces driving inflation. In interpreting incoming data, we will need to stay alert to these possibilities and, in light of incoming information, adjust our views about inflation, the overall economy, and the stance of monetary policy best suited to promoting maximum employment and price stability. How should policy be formulated in the face of such significant uncertainties? In my view, it strengthens the case for a gradual pace of adjustment. But we should also be wary of moving too gradually. It would be imprudent to keep monetary policy on hold until inflation is back to 2%.

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Fig. 1

Source: Bureau of Labor Statistics and Federal Reserve Summary of Economic Projections

Fig. 2

Source: Bureau of Labor Statistics and Federal Reserve Summary of Economic Projections

Fig. 3

Source: Federal Reserve Board using data from the BEA, BLS, CBO, and SPF. See the appendix for further details

Fig. 4

Source: Bureau of Labor Statistics and Federal Reserve Bank of Dallas

Fig. 5

Source: Bureau of Economic Analysis and Federal Reserve Summary of Economic Projections

Fig. 6

Source: Bureau of Labor Statistics

Fig. 7

Source: Bureau of Labor Statistics; Conference Boar; National Federation of Independent Business

Fig. 8

Source: Bureau of Labor Statistics; Federal Reserve Bank of Atlanta

Fig. 9

Source: For households, mean response from University of Michigan Surveys of Consumers. For professional forecasts, median response from Survey of Professional Forecasters, FRB Philadelphia. Inflation compensation computed by Federal Reserve Board staff using FRB New York financial market data


  1. 1.

    The Statement on Longer-Run Goals and Monetary Policy Strategy is available on the Board’s website at

  2. 2.

    The simple model links the current rate of inflation to several factors, including lagged inflation, long-run inflation expectations, labor utilization, and changes in the relative prices of food, energy, and imports (Yellen 2015). Additional details on the model can be found in the appendix.

  3. 3.

    In the decomposition procedure, movements in core inflation affect headline inflation one-for-one; as a result, the contributions of food and energy price inflation are defined as each component’s price change relative to the core, weighted by its share in total nominal consumer spending. The estimated contribution of movements in import prices is also computed relative to core inflation; thus, if import prices are rising at the same rate as core inflation, they have no estimated effect on the shortfall of overall inflation from 2%. In addition, the decomposition takes account of lags in the adjustment of core inflation to movements in resource utilization and other factors. More details on the decomposition procedure can be found in the appendix.

  4. 4.

    In the simple model, inflation depends in part on lagged inflation. As a result, an unexplained movement in inflation is predicted to influence inflation beyond the current quarter, but to a degree that fades over time. On average, the model predicts that roughly 85% of any unexplained movement will have disappeared after four quarters.

  5. 5.

    In general, price changes measured over a few months tend to be noisy, even when measured on a core or trimmed-mean basis. For this reason, the FOMC usually focuses on the growth rate of PCE prices over the previous 12 months, which smooths through the volatility in the monthly price data. This approach also sidesteps distortions in the monthly data associated with residual seasonality; these distortions are likely to hold down month-to-month changes in prices over the balance of the year (see Peneva 2014). That said, 12-month rates of inflation will continue to be held down through early 2018 by the unusually weak monthly readings on price changes recorded in early 2017.

  6. 6.

    See Reifschneider and Tulip (2017) for details on the calculation of these confidence intervals.

  7. 7.

    This statement abstracts from any persistent effects such disturbances might have on real activity, which could have implications for monetary policy.

  8. 8.

    For example, Aaronson and others (2015) estimate that increases in the average age and educational attainment of U.S. workers will reduce the sustainable rate of unemployment almost 1/2 percentage point between 2014 and 2020. Barnichon and Mesters (2017) also present evidence that demographic changes have somewhat reduced the structural unemployment rate in the United States in recent years. Relatedly, Yoon, Kim, and Lee (2014) and Juselius and Takats (2015) estimate that ongoing demographic transitions are having modest disinflationary effects in the United States and other developed economies.

  9. 9.

    The statistical evidence also suggests that the sustainable rate of unemployment could be higher. As illustrated by the results reported in Reifschneider et al. (2015) and Barnichon and Matthes (2017), standard errors for estimates of the sustainable rate of unemployment are typically at least 1/2 percentage point. Accordingly, if the sustainable rate is estimated to be about 4–1/2%, there is roughly a 15% probability that the actual value is less than 4%; symmetrically, there is a 15% probability that it is greater than 5%.

  10. 10.

    Several years ago, I discussed the interpretation of a wide range of labor market indicators at length (Yellen 2014).

  11. 11.

    The employment-to-population ratio for all persons aged 16 and over has recovered much less than the prime-age ratio since 2007, in large part reflecting the ongoing retirement of the baby boomers and a rise in school attendance rates for young adults aged 20–24 (Aaronson and others 2014). Schanzenbach and others (2017) estimate that the substantial overall employment-to-population gap that opened up in the wake of the financial crisis finally closed in July 2017.

  12. 12.

    The labor force participation rate for prime-age men has been declining for decades. Evidence suggests that a portion of the decline is attributable to a reduction in the demand for low-skilled workers resulting from advances in technology and globalization. For a general discussion of the decline in male labor force participation, see Aaronson and others (2014). For a discussion of the role played by technical factors in this decline, see Deming (forthcoming) and Acemoglu and Autor (2011); for a discussion of the role of globalization, see Autor et al. (2013) and Pierce and Schott (2016). In addition to these factors, Autor and Duggan (2003) and French and Song (2014) present evidence suggesting that increases in the number of people on disability rolls have also been important. Relatedly, an alarming deterioration in health outcomes among low-education workers, including a rise in deaths related to alcohol, drugs, and suicide, may be having an adverse effect on both male and female employment (Case and Deaton 2017).

  13. 13.

    For a discussion of how secular forces may be influencing the trend share of part-time employment, see Valletta and van der List (2015).

  14. 14.

    In contrast to the other wage and compensation measures, the Wage Growth Tracker only measures wage changes for individuals who had a job in both the current month and a year ago.

  15. 15.

    For example, predictions from a simple empirical model track recent movements in the employment cost index reasonably well, because the model estimates that the increasing upward pressure on compensation growth from rising labor utilization is being offset by a declining contribution from productivity growth. (See the appendix for further details.) Relatedly, research also suggests that cyclical changes in the composition of the workforce associated with the absorption of new workers with relatively low skills and experience may be currently restraining growth in both aggregate wages and productivity. See Daly and Hobijn (2017) and Daly et al. (2016), who also point to the retirement of baby boomers as a factor holding down wage growth.

  16. 16.

    See Morgan (2017) for more on this analysis.

  17. 17.

    As I discussed in a speech one year ago, I view expectations formation as one of the key areas requiring further research by economists (see Yellen 2016).

  18. 18.

    In the Survey of Primary Dealers conducted by the Federal Reserve Bank of New York, the median of respondents’ longer-term projections for PCE inflation have been essentially flat at 2% since the survey began in 2011. Similarly, in the Blue Chip Financial Indicators survey, which solicits the views of a large number of financial firms (as well as a few other institutions) about the extended outlook every June and December, the median of long-run expectations for GDP price inflation has stayed close to 2.1% over the past six years. Comparisons of results from these surveys to those reported in the Survey of Professional Forecasters (as well as surveys of households) are somewhat complicated by differences in the projection period used. For example, some surveys include the low rates of inflation expected over the next few years in the calculation of projected longer-run averages, while other surveys exclude them.

  19. 19.

    Expected inflation over the next 5–10 years as reported in the Michigan survey runs appreciably above PCE price inflation on average since the mid-1990s, perhaps because households are less informed about actual inflation developments than professional forecasters and financial firms. For this reason, it may be best to focus on changes over time in the Michigan measure, not on the level.

  20. 20.

    In addition to monitoring survey measures of expected inflation, Federal Reserve staff also use statistical techniques to try to directly estimate possible movements over time in the underlying long-run trend in inflation, using data for actual inflation and other series, including resource utilization. Many of these statistical estimates suggest that the underlying trend in PCE inflation is currently somewhat below 2%. Econometrically, however, it is extremely difficult if not impossible to disentangle estimates of the underlying trend in PCE inflation from estimates of the sustainable rate of unemployment. To be consistent with the data, the higher one’s estimate of trend inflation or expected long-run inflation, the lower must be one’s estimate of the sustainable unemployment rate, at least over the medium run.

  21. 21.

    For example, Andreasen and Christensen (2016) show that once TIPS liquidity premiums are taken into account, the model-implied one-year inflation expectation becomes more stable and shows a smaller decline since 2013. In addition, quotes on inflation derivatives suggest that most of the decline in inflation compensation over this period is associated with investor perceptions of reduced risks of above-target inflation outcomes rather than increased risks of below-target inflation outcomes.

  22. 22.

    Personal consumption expenditures include all medical services, including those paid by Medicare and Medicaid; prices for the latter may be viewed as “administered” because they are essentially set by the government. The formulas used to set Medicare prices were adjusted by the 2010 Affordable Care Act and additional legislation passed in 2015, resulting in smaller increases in prices for the same increase in costs than would have been the case in the prior decade. In addition, Medicaid prices have probably been restrained somewhat by budget pressures on state governments. Aside from these direct influences of government policy on healthcare prices, some research suggests that lower Medicare prices tend to lead to lower negotiated prices by private insurers as well (see Clemens et al. 2016).

  23. 23.

    In an early study, Borio and Filardo (2007) reported results suggesting that global economic slack adds considerable explanatory power to reduced-form inflation equations (such as the one discussed in the appendix), and that its role has been growing over time. However, Ihrig et al. (2010) subsequently argued that the estimated link was not robust to alternative measures of global resource utilization. Federal Reserve Board staff have updated this analysis using data through early 2017 and confirmed that global slack does not appear to exert an appreciable direct effect on domestic inflation in the United States and most other advanced economies.

  24. 24.

    Using sector-level data, Elsby et al. (2013) estimate the contributions of offshoring, the substitution of capital for low-skilled labor, and several other factors on the aggregate U.S. labor share of income, and find that only offshoring has been important. They also conclude that the decline in the labor share since the late 1980s has been overstated as a result of statistical measurement problems. In contrast to the influence of globalization on the U.S. labor share, Feenstra and Weinstein (2017) find that the influence of increased globalization on price markups in the United States has been modest.

  25. 25.

    For more on the inflation implications of innovation in the retail sector, see Curran and Jamrisko (2017) and Trainer (2016).

  26. 26.

    For a review of changes over time in the competitive structure of the overall economy, see Council of Economic Advisers (2016). For a discussion of the evidence for, and some of the implications of, changes in the dynamism of the economy, see Hathaway and Litan (2014) and Decker and others (2016).

  27. 27.

    The median of FOMC participants’ projections of the longer-run unemployment rate has declined almost a full percentage point over the past five years; the revision in the long-run consensus forecast reported in the Blue Chip Survey between October 2012 and March 2017 was slightly larger.

  28. 28.

    It might be thought that the FOMC could mitigate this problem by raising the federal funds rate higher than might otherwise be called for while the economy continues to expand in order to increase the extent to which interest rates could be cut later should a recession occur. But this strategy would be counterproductive, because it would only serve to weaken economic activity and push down inflation before the recession.

  29. 29.

    Although the data used in the decomposition analysis have been revised and extended, the specification of the model and the estimation period are the same as that discussed in a speech I gave two years ago (Yellen 2015). As a result, the estimated coefficients of the model are essentially unchanged. Extending the estimation period through 2017:Q2 has little effect on the estimated coefficients and the decomposition estimates.

  30. 30.

    This measure of core import prices is constructed by Board staff using published and unpublished data provided by the Bureau of Economic Analysis and the Bureau of Labor Statistics.

  31. 31.

    The information on participants’ forecasts provided at the September 20, 2017, press conference is available on the Board’s website at

  32. 32.

    The level of core import prices, expressed relative to core consumer prices, displayed a modest downward trend from 1990 through 2001 but since then has displayed little persistent trend, particularly if one controls for shifts related to recent changes in the real exchange rate. If the post-2001 pattern persists in coming years, then \( {\text{RPIM}}_{t} \) would be expected to converge to zero within a few quarters and core PCE inflation to converge to 2% within two or three years, assuming that the unemployment rate remains near 4–1/2% (the median of the longer-run projections provided by FOMC participants) and there are no further shocks to the exchange rate and other factors. If, however, core import prices were expected to resume trending down relative to consumer prices, then the model as specified would imply that the unemployment rate consistent with inflation stabilizing at 2% in the longer run would be somewhat lower than 4–1/2%.

  33. 33.

    The ECI series used here is obtained from a ratio splice of the SIC- and NAICS-based indexes; the SIC-based index is used before 2001 and the NAICS-based index used thereafter. (All data used in the model were current as of September 1, 2017).

  34. 34.

    The estimation procedure imposes the joint restriction that the sum of the coefficients on \( \pi_{t - 1}^{e} \) and the lagged ECI growth terms are equal to 1, and that the coefficients on \( \pi_{t - 1}^{e} \) and \( {\text{MA}}\_{\text{PROD}}_{t} \) are equal. This joint restriction receives a p value of 0.57.

  35. 35.

    The low-pass component is obtained from a band-pass filter. The filter width and cutoffs are set equal to the values used in Douglas Staiger, James Stock, and Mark Watson (2001), “Prices, Wages, and the U.S. NAIRU in the 1990s,” in Alan Krueger and Robert Solow, eds., The Roaring Nineties: Can Full Employment Be Sustained? (New York: Russell Sage Foundation and Century Foundation Press), pp. 3–60. Before the series’ starting point in 1947:Q2, actual productivity growth is padded with an ARIMA(4,1,0) model; after its 2017:Q2 endpoint, the series is padded with the CBO’s January 2017 forecast of average nonfarm business trend productivity growth from 2017 to 2027 (which is 1.67% in log differences) and with the 2027 value of the CBO forecast (1.77%) thereafter.


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Correspondence to Janet L. Yellen.

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This text is reproduced from the original speech given at NABE’s Annual Meeting on September 26, 2017. Available at


Appendix: PCE inflation model, inflation decomposition procedure, and the ECI growth equation

PCE inflation model

The inflation model used in the decomposition procedure includes two equations: an identity for the change in the price index for total personal consumption expenditures (PCE) and a simple reduced-form forecasting equation for core PCE price inflation. The identity is

$$ \pi_{t} = \pi_{t}^{c} + \omega_{t}^{e} {\text{RPIE}}_{t} + \omega_{t}^{f} {\text{RPIF}}_{t} , $$

where \( \pi_{t} \) and π c t denote growth rates (expressed as annualized log differences) of total and core PCE prices, respectively. RPIE t and \( {\text{RPIF}}_{t} \) are annualized growth rates for prices of consumer energy goods and services and prices of food and beverages, both expressed relative to core PCE prices, and \( \omega_{t}^{e} \) and ω f t are the weights of energy and food in total consumption. The core inflation forecasting equation is

$$ \pi_{t}^{c} = .41\pi_{t}^{e} + .36\pi_{t - 1}^{c} + .23\pi_{t - 2}^{c} - .08{\text{SLACK}}_{t} + .56{\text{RPIM}}_{t} + \in_{t} , $$

where π e t is expected long-run inflation; \( {\text{SLACK}}_{t} \) denotes the level of resource utilization, \( {\text{RPIM}}_{t} \) controls for the effect of changes in the relative price of core imported goods, \( \in_{t} \) is a white-noise error term, and the coefficients are ordinary least squares estimates obtained using data from 1990:Q1 to 2014:Q4.Footnote 29

For estimation purposes, \( {\text{SLACK}}_{t} \) is approximated using the unemployment rate less the Congressional Budget Office’s (CBO) historical series for the long-run natural rate. From 2007 to the present, π e t is approximated using the median forecasts of long-run PCE price inflation reported in the Survey of Professional Forecasters; from 1991:Q4 to 2006:Q4, the series is based on the median long-run forecasts of inflation as measured by the consumer price index (CPI), less a constant adjustment of 40 basis points to put the CPI forecasts on a PCE basis; before 1991:Q4, π e t is approximated by the long-run inflation expectations reported in the Hoey survey. The relative import price term, RPIM t , is defined as the annualized growth rate of the price index for core imported goods (defined to exclude petroleum, natural gas, computers, and semiconductors) less the lagged four-quarter change in core PCE inflation, all multiplied by the share of nominal core imported goods in nominal GDP.Footnote 30

Inflation decomposition procedure

To decompose recent movements in inflation into its various components, the series used in the inflation model—for which complete quarterly data are available only through 2017:Q2 in most cases—are first extended through the end of 2017. In the case of inflation, the extensions are consistent with the medians of Federal Open Market Committee (FOMC) participants’ projections for total and core PCE inflation in 2017 that were reported at the press conference following the September 2017 FOMC meeting.Footnote 31 Similarly, SLACK t over the second half of 2017 is defined to be consistent with the median of FOMC projections for the 2017:Q4 unemployment rate less the CBO’s estimates of the historical path of the long-run natural rate. The CBO’s 2017 estimate is slightly higher than the median of FOMC participants’ most recent projections of the normal longer-run level of the unemployment rate. For changes in the price of core imports, the 2017:H2 extrapolations are based on a regression of this series on current and lagged changes in exchange rates. This approach predicts that core import prices should rise about 4–1/2% at an annual rate in the second half of this year.Footnote 32 Energy and food prices over the second half of 2017 are assumed to rise at annual rates of 10 and 1.6%, respectively; these assumptions (which take into account published monthly PCE data through July and published CPI data through August, as well as recent movements in gasoline prices in the wake of Hurricanes Harvey and Irma) ensure that the combined contribution of food and energy prices to inflation in 2017 is consistent with the median difference between FOMC participants’ projections for total and core inflation. Finally, nominal spending shares for food, energy, and core imports are assumed to remain unchanged at their 2017:Q2 levels, and long-run inflation expectations are assumed to remain constant at 2%.

After computing historical \( \in_{t} \) tracking errors for the two equations of the model, the final step in the decomposition procedure is to run a sequence of counterfactual simulations of the model from 1990:Q1 through 2017:Q4. One by one, each explanatory variable of the model is set to zero, and the model is simulated; the resulting difference between actual inflation and its simulated value equals the historical contribution of that particular factor. Importantly, the simulations are all dynamic in that the lagged inflation term in the core inflation equation is set equal to its simulated value in the preceding period rather than its actual value. As a result, the decompositions incorporate the effects of changes in lagged inflation that are attributable to previous movements in the explanatory variables.

ECI growth equation

The estimated equation for the employment cost index (ECI) is

$$ \pi_{t}^{w}\,=\,- 0.72 + .58\pi_{t - 1}^{e} + .10\pi_{t - 1}^{w} + .12\pi_{t - 2}^{w} + .10\pi_{t - 3}^{w} + .11\pi_{t - 4}^{w} - .19{\text{SLACK}}_{t} - .57\Delta {\text{SLACK}}_{t} + .58{\text{MA}}\_{\text{PROD}}_{t} + \varepsilon_{t} , $$

where π w t is the annualized log difference of the ECI for hourly compensation of private industry workers; π e t and \( {\text{SLACK}}_{t} \) have the same definition as the corresponding variables from the PCE price inflation model; \( \Delta {\text{SLACK}}_{t} \) denotes the first difference of SLACK t ; \( {\text{MA}}\_{\text{PROD}}_{t} \) is a moving average of an estimate of trend productivity growth for the business sector; and ɛ t is an error term.Footnote 33 The coefficients are obtained from a restricted least squares regression using quarterly data from 1988:Q1 to 2017:Q2.Footnote 34 Trend productivity growth is estimated as the low-frequency component of the annualized log difference of business-sector output per hour from the Bureau of Labor Statistics Productivity and Costs report.Footnote 35 The moving average of trend productivity growth (which is used in the estimation) is computed as a geometrically declining weighted average,

$$ {\text{MA}}\_{\text{PROD}}_{t} = 0.95{\text{MA}}\_{\text{PROD}}_{t - 1} + 0.05{\text{PROD}}_{t} , $$

where \( {\text{PROD}}_{t} \) denotes trend productivity growth and where the moving average is initialized in 1955:Q1 with that quarter’s estimate of the trend growth rate.

The model is used to compute a decomposition of ECI growth following a procedure similar to that used to construct the decomposition for core PCE price inflation. The table summarizes the results of this decomposition over various periods; note that the column labeled “Slack” combines the effects of \( \Delta {\text{SLACK}}_{t} \) and SLACK t , the effect of the model’s constant term is included in the column labeled “Trend productivity,” and the column labeled “Other” gives the contributions of the model’s tracking errors.

Model-based decomposition of ECI hourly compensation growth

  ECI growth Contributions of
Expected inflation Trend productivity Slack Other
2002–2007 3.28 2.09 1.44 − 0.08 − 0.17
2008–2009 1.80 2.16 1.18 − 0.97 − 0.56
2010–2011 2.08 2.14 0.82 − 1.09 0.22
2012–2013 1.92 2.12 0.44 − 0.67 0.02
2014–2015 2.05 2.01 0.15 − 0.20 0.09
2016–2017:Q2 2.31 1.99 0.01 0.03 0.28
  1. ECI growth is reported as average percent changes at an annual rate for the periods shown; contributions are expressed in percentage points. The contribution of the model’s constant term is included in the contribution for trend productivity. Contributions may not sum to total growth because of rounding

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Yellen, J.L. Inflation, uncertainty, and monetary policy. Bus Econ 52, 194–207 (2017).

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