Growth prospects, the natural interest rate, and monetary policy

Fiedler, Salomon; Gern, Klaus-Jürgen; Jannsen, Nils; Wolters, Maik H. Working Paper Growth prospects, the natural interest rate, and monetary policy Economics Discussion Papers, No. 2019-17 Provided in Cooperation with: Kiel Institute for the World Economy – Leibniz Center for Research on Global Economic Challenges Suggested Citation: Fiedler, Salomon; Gern, Klaus-Jürgen; Jannsen, Nils; Wolters, Maik H. (2019) : Growth prospects, the natural interest rate, and monetary policy, Economics Discussion Papers, No. 2019-17, Kiel Institute for the World Economy (IfW), Kiel This Version is available at: https://hdl.handle.net/10419/193180 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Discussion Paper No. 2019-17 | February 18, 2019 | http://www.economics-ejournal.org/economics/discussionpapers/2019-17 Growth prospects, the natural interest rate, and monetary policy Salomon Fiedler, Klaus-Jürgen Gern, Nils Jannsen, and Maik Wolters Abstract The recovery from the Global Financial Crisis was characterized by sluggish output growth and by inflation remaining persistently below the inflation targets of central banks in many advanced economies despite an unprecedented monetary expansion. Ten years after the Global Financial Crisis, GDP remains below its pre-crisis trend in many economies and interest rates continue to be very low. This raises the question of whether low GDP growth and low interest rates are a temporary phenomenon or are due to a decline in long-run growth prospects (potential output growth) and equilibrium real interest rates (natural interest rate). Addressing this question is important for central banks for conducting monetary policy and adjusting their strategy. In this paper, the authors address this question based on a review of the literature and an evaluation of the most recent data and discuss implications for monetary policy. (Submitted as Policy Paper) JEL E31 E32 E43 E52 E58 Keywords Natural interest rate; potential output; output gap; monetary policy Authors Salomon Fiedler, Kiel Institute for the World Economy, Germany Klaus-Jürgen Gern, Kiel Institute for the World Economy, Germany Nils Jannsen, Kiel Institute for the World Economy, Germany, [email protected] Maik Wolters, Friedrich Schiller University Jena, Germany This Paper is based on a Briefing Paper that was prepared for the Committee on Economic and Monetary Affairs of the European Parliament (ECON) as an input for the Monetary Dialogue of November 2018 (Fiedler et al. 2018a).The authors thank Stefan Kooths and Mewael F. Tesfaselassie for very useful comments and suggestions. Citation Salomon Fiedler, Klaus-Jürgen Gern, Nils Jannsen, and Maik Wolters (2019). Growth prospects, the natural interest rate, and monetary policy. Economics Discussion Papers, No 2019-17, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2019-17 Received February 7, 2019 Accepted as Economics Discussion Paper February 14, 2019 Published February 18, 2019 © Author(s) 2019. Licensed under the Creative Commons License - Attribution 4.0 International (CC BY 4.0) 1 1 INTRODUCTION The recovery from the Global Financial Crisis was characterized by sluggish output growth and inflation remaining persistently below the inflation targets of central banks in many advanced economies despite extraordinary monetary policy stimulus. Ten years after the Global Financial Crisis, GDP remains below its pre-crisis trend in many economies and interest rates continue to be very low. This raises the question of whether low GDP growth and low interest rates are a temporary phenomenon or due to a secular decline in long-run growth prospects (potential output growth) and equilibrium real interest rates (natural interest rate). This question is very important for central banks. For example, if sluggish output growth was mainly due to temporary factors and GDP still far below potential output, central banks should strive for an even more expansionary monetary policy to close this gap, which in turn would lead to higher inflation rates. Moreover, if the natural interest rate had fallen to levels close to currently observed interest rates, then the current stance of monetary policy (measured via the distance between current rates and the natural rate) might be less expansionary than intended and one reason behind sluggish output growth and low inflation. Addressing this question is crucial for central banks in assessing whether they can soon reverse interest rates and go back to standard monetary policy tools or whether keeping interest rates low and using unconventional measures will be the new normal for monetary policy. However, potential output and the natural interest rate are not observable and estimates are subject to large uncertainty. From a theoretical perspective, there could be several factors behind fluctuations in potential output or the natural interest rate. Moreover, there could be interdependencies between both variables. For example, fluctuations in potential output growth are typically seen as one potential factor behind fluctuations in the natural interest rate. There are also underlying factors that may affect potential output and the natural interest rate jointly, such as demographic change or productivity growth. In this regard, it has been argued that the world economy may have drifted into a ‘secular stagnation’ characterized by low natural interest rates reflecting a high propensity to save and low potential growth (Summers 2014). In this paper, we analyse recent developments in potential growth and the natural real interest rate and discuss the most important factors behind based on the recent literature and discuss implications for monetary policy. We start by analysing whether sluggish GDP growth is mainly due to temporary factors or due to lower potential growth (Section 2). In doing so, we first discuss the impact of the Global Financial Crisis on GDP and potential output (2.1). Second, we focus on long-run trends in potential output and productivity growth (Section 2.2). We proceed by analysing long-run developments in the natural interest rate (Section 3). We start by describing the results of the recent empirical literature on natural interest rates and discuss problems and uncertainties with regard to estimation methods (Section 3.1). We then discuss potential drivers of the natural interest rate (Section 3.2). Section 4 summarizes our results and discusses implications for monetary policy, Section 5 concludes. 2 2 LONG-RUN TRENDS IN POTENTIAL OUTPUT We start with discussing how the Global Financial Crisis affected GDP and potential output (2.1) and then analyzing longer-run trends in potential output and productivity growth (2.2). 2.1 Growth prospects after the Global Financial Crisis The Global Financial Crisis was associated with deep recessions and sluggish recoveries in many advanced economies, raising the question of whether GDP was dampened temporarily or whether the crisis has led to a permanent decline in the level of potential output or even to a decline in potential growth. Financial crises can have permanent effects on potential output, e.g. if they are associated with financial constraints that hinder firms from making productive investments or with hysteresis effects due to long-lasting unemployment. However, financial crises do not hit countries arbitrarily, but are usually linked to unsustainable pre-crisis developments. For example, build-ups of imbalances in credit or housing markets can be driving factors behind financial crises and are in fact reliable predictors, in particular for banking crises (Borio and Drehmann 2009; Jorda et al. 2015; Schularick and Taylor 2012). To the extent that the build-up of these imbalances is associated with higher GDP growth, a permanent decline in GDP following a financial crisis need not be a direct consequence of the crisis but is rather a consequence of unsustainable pre-crisis developments. Figure 1: GDP following normal recessions and banking crises Source: OECD Main Economic Indicators; Laeven and Valencia (2013); own calculations. The effects of financial crises on GDP and potential output have been analysed in several studies. These studies usually find that financial crises lead to a permanent decline in the level of GDP in advanced economies (Cerra and Saxena 2008; Jorda et al. 2013; Reinhart and Rogoff 2009). -12 -10 -8 -6 -4 -2 0 1234567 normal recession banking crisis Annual data. Year 1: First year of a recession identified as decline in GDP. Level of GDP following normal recessions (recessions not associated with banking crises) and banking crises. Estimation via local projections method as in Jorda et al. (2013) for a sample of 18 adavanced economies from 1970 to 2016. Dotted lines indicate 90 percent confidence bands. percent year 3 One reason for the permanent decline in GDP is that recoveries following financial crises are much weaker than those following normal recessions (Boysen-Hogrefe et al. 2016). Figure 1 summarizes the general pattern of the results of these studies based on a sample of 18 advanced economies from 1970 to 2016 using the local projections method following Jorda et al. (2013).1 After a financial crisis, GDP remains permanently below the path of GDP that would have been reached without a financial crisis (indicated by the zero line), while after a normal recession GDP is recovering to levels close to its former path. In line with these results, studies that analyse the development of potential output find that the level of potential output is permanently lower following financial crises (Furceri and Mouroungane 2012; Ollivaud and Turner 2014). While financial crises lead to a permanent decrease in the level of GDP and potential output, most studies find that negative effects on output growth are temporary and potential output growth remains largely unaffected by crises. For example, the results in Figure 1 shows that after about five years the level of GDP does not decline further compared to a scenario in which a country was not hit by a financial crisis, indicating that GDP growth is not permanently reduced. Studies focusing on potential output, find the same pattern for potential GDP growth (Furceri and Mouroungane 2012; IMF 2009; Ollivaud and Turner 2014).2 Moreover, pre-crisis developments are systematically related to the magnitude of the decline during a crisis. For example, stronger credit growth (Jorda et al. 2013; Ollivaud and Turner 2014), a housing boom (Boysen-Hogrefe et al. 2016; Jorda et al. 2015), or a high investment share (IMF 2009) before a crisis are associated with a stronger decline in GDP and potential output. To the extent that these pre-crisis developments have contributed to stronger GDP growth and higher potential output estimates before a crisis, post-crisis weaknesses in GDP and potential output are normalizations rather than direct consequences of the crisis itself. Against this backdrop, the sluggish recovery after the Global Financial Crisis was not unprecedented but in line with historical experience based on earlier crises. However, potential output cannot be directly observed and therefore has to be estimated. International organizations, such as the European Commission, the International Monetary Fund, or the OECD, use a production function approach to estimate potential output. This approach relies on filtering methods using past as well as future information to estimate potential output in a given year. Even though usually additional information, such as survey-based capacity utilization of firms, GDP growth forecasts, or inflation, are taken into account to improve the estimates, using filtering approaches implies that real-time estimates of potential output and, in turn, of the output gap are subject to high uncertainty and large revisions. Given that forecasts typically exhibit large and systematic errors in recessions (Dovern and Jannsen 2017), this uncertainty may amplify during recessions and financial crises. For example, Dovern and Zuber (2017) show for a sample of advanced economies that OECD estimates of potential output for the fifth year after the beginning of a recession are revised downwards by about 5 percent on average compared to estimates that were made before the beginning of a recession. Following financial 1 The sample includes Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Italy, Japan, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United States. Recessions are identified as years with negative GDP growth rate. Banking crises are identified according to Laeven and Valencia (2013). Estimation based on local projections method according to Jorda et al. (2013). 2 Furceri and Mouroungane (2012) find that potential growth is on average somewhat lower following financial crises, however, this decline is not statistically different from zero. 4 crises, potential GDP is revised downwards by up to 10 percent. Moreover, the downward revisions take place gradually and can differ substantially across recessions, indicating how problematic it is for central banks to rely on potential output and output gap estimates in times of recessions and financial crises. 2.2 Long-run trends in potential growth and productivity Potential output growth has been on a declining trend in advanced economies for many years, although with some fluctuations and significant differences across countries (Figure 2). In the US, potential growth was relatively stable at 3–3 ½ percent in the second half of the 1980s and the 1990s according to OECD estimates, but started declining around the turn of the century towards a level of below 2 percent in recent years. The growth rate of the Japanese potential output experienced a steep decline from around 4 percent at the beginning of the 1990s to close to zero around 2010, but has recovered somewhat since then to approximately 1 percent recently. Potential growth in the major European economies has been trending downwards since the mideighties until around 2010 (from around 2 ½ percent to close to 1 percent in the UK and Germany, slightly more in France, and even zero percent growth in Italy). In recent years, potential output growth has stabilized or partially recovered (especially in the UK and Germany), according to the estimates of the OECD. Figure 2: Potential output growth in advanced economies Source: OECD Economic Outlook. 0 1 2 3 4 5 1986 1990 1994 1998 2002 2006 2010 2014 United Kingdom Japan United States Annual growth rates. percent -1 0 1 2 3 4 1986 1990 1994 1998 2002 2006 2010 2014 Germany France Italy Annual growth rates. percent 6 Drivers of potential output growth The growth rate of potential output is affected by growth in labour input, capital input, and the efficiency with which the factors of production are combined – Total Factor Productivity, which is generally associated with technological progress (but also includes all other miscellaneous factors such as institutions, culture, etc.). In the advanced economies, demographics and their impact on labour force growth are partly responsible for the decline of potential growth. Especially in the US, slower labour force growth dampened the growth rate of potential output. Therefore, the slowdown in economic growth is much less pronounced with respect to GDP per labour force participant (Martin 2017). While a slowdown in trend growth is still apparent in recent years by this yardstick, too, the level of growth is not exceptionally low (Figure 3). In Japan, the working age population has already been in decline for quite some time, and the labour force started to shrink in the late 1990s. In recent years, however, the negative impact of population aging on labour force growth has been offset by an increase in the participation rate, particularly of women and the elderly. In Europe, labour force growth has shown no clear trend since the 1970s. Figure 3: US trend GDP growth 1965–2017 Source: Bureau of Economic Analysis, Bureau of Labor Statistics. Declining levels of capital formation are another part of the explanation of declining trend growth in advanced economies, although to a differing degree across countries. While the share of investment in GDP has been falling significantly over the past 35 years in a number of countries, including Japan, Germany, and the UK, the investment ratio has remained almost constant in other countries, such as the US and France (Figure 4). The third driver of potential output growth is productivity. Productivity developments differed across the advanced economies in the 1990s and early 2000s, with a steady decline in trend productivity growth (measured as output per hour worked) in Germany, Italy, and Japan, relatively stable productivity growth in France and the UK, and even accelerating productivity 0 1 2 3 4 5 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 real GDP real GDP per capita real GDP per labor force participant Annual growth rates, 10-year moving average. percent 7 growth in the US. More recently, productivity developments have become more uniform, with growth slowing down to exceptionally low levels almost across the board (Figure 5).3 Figure 4: Investment shares in selected OECD countries 1980–2017 Source: IMF World Economic Outlook Database. Figure 5: Labour productivity Source: OECD. 3 The major exception is Spain where during the boom years in the late 1990s and early 2000s growth was strongly biased towards the construction sector and thus extremely labour intensive. This process reversed in the years following the financial crisis, leading to a strong recovery of productivity during the recession and in the beginning of the upturn. 10 15 20 25 30 35 1980 1985 1990 1995 2000 2005 2010 2015 DE FR JP UK US Investment share in percent of GDP. percent -4 -2 0 2 4 6 8 10 1971 1976 1981 1986 1991 1996 2001 2006 2011 2016 DE JP UK US percent Annual growth of GDP per hour worked, constant prices. 8 Potential explanations for the productivity slowdown While the slowdown of productivity growth has been accentuated by the Global Financial Crisis and their repercussions, econometric evidence suggests that the slowdown started already well before the Great Recession and the sovereign debt crisis in the euro area (Cette et al. 2016). The weakness of productivity came as a surprise to many observers who had expected more dynamic productivity growth as a result of the sweeping improvements in technology, including digitization, artificial intelligence, and robotics. The coincidence of the productivity slowdown and the availability of new technologies is labelled “productivity paradox” or “productivity puzzle”.4 A number of explanations have been suggested to reconcile technological innovations with poor productivity performance (Crafts 2018; Freund 2018). One strand of the literature argues that problems with accurately measuring new technology output would help solving the productivity puzzle. It is true that serious challenges in estimating GDP exist, including collecting data on the sharing economy, taking account of digital services that are not priced directly, and adjusting for the quality improvements associated with technological advances and new goods and services entering the market (IMF 2018). However, these problems should primarily affect the level of productivity growth, while in order to explain changes in productivity growth they would need to have become increasingly important over time. This, is, however, according to a number of recent studies not the case. Thus, mismeasurement cannot account for a large share of the observed slowdown in labour productivity in advanced economies. For example, IMF (2018) estimates that for the US 10-20 percent of the shortfall in labour productivity may be attributable to under-measurement of the digital sector. Barnett et al. (2016) suggest that up to 25 percent of the productivity gap in the UK could be due to measurement issues. IfW (2017) concludes that measurement problems do not significantly contribute to explaining the productivity slowdown in Germany. Another strand of literature argues that the impact of the recent wave of new technologies on productivity is relatively low, or that the positive effect on productivity will materialize only with a long lag. According to Robert Gordon (2014), digitization does not have the potential to raise productivity in a similar way that the industrial revolution did in the first half of the 20th century. An alternative explanation of the productivity paradox argues that the productivity enhancing impact of the new digital technologies needs more time to be realized (Brynjolfsson et al 2017). Investment in new equipment and necessary complementary tangible and intangible capital to reap the full benefits of digitization will need considerable time as will the associated restructuring of production processes and value chains. The introduction of new technology also contains an element of trial and error that may contribute to a long lag between the introduction and measured productivity increases on the macro level. The implications of the two technology explanations of the productivity paradox for future productivity growth are substantially different. While productivity growth will remain sluggish according to the first explanation, productivity growth will recover according to the second explanation. Other explanations of the productivity slowdown are not directly related to new technologies. The role of structural change may be important as productivity growth on the macro level is not only affected by the development of productivity in each sector but also by the fact that the 4 The term productivity paradox goes back to Robert Solow’s 1987 notion that “you can see the computer age everywhere, but in the productivity statistics” (see also Brynjolfson 1993 for a discussion of the productivity paradox of the 1980s). The term “productivity puzzle” has been coined in the discussion about surprisingly weak productivity growth in Britain (see e.g. Office for Budget Responsibility 2012). 15 Furthermore, the estimation uncertainty within a given model is very high. Beyer and Wieland (2017) show that a 95 percent confidence band for the Laubach and Williams estimates ranges from -5 to +5 percent. Kiley (2015) tries to reduce estimation uncertainty by including prior information in a Bayesian estimation framework and by including additional control variables like asset prices, fiscal policy measures, and credit spreads. He finds that the data provides relatively little information on the natural rate, because the co-movement of output, inflation, unemployment, and the real interest rate is too weak to yield precise natural rate estimates. Hence, the posterior estimates are very close to the prior assumption regarding the time series process for the natural interest rate. Accounting for additional control variables, in particular credit spreads, leads to a point estimate of the natural interest rate of 1.25 percent. Using a ten year forecast from a simple time series model, Hamilton et al. (2016) find a natural interest rate of 0.4 percent for both the US and the world (based on 17 advanced economies) with a 90 percent confidence band ranging from about -1 to +2 percent. Further, they find that in episodes, in which the real interest rate was much lower than the post-war average of about 2 percent, it remained low only temporarily. They conclude that it is not possible to seriously pin down a point estimate of the natural interest rate, that there is no evidence for permanently lower real rates, and that plausible values for the natural interest rate range from a little above zero to up to 2 percent. The approach by Laubach and Williams relies on a semi-structural model that links unobservable trends and cycles to the data. The discussion above shows that the results are highly uncertain and depend crucially on the model assumptions. Lubik and Matthes (2015) use an alternative approach based on a Vector Autoregression (VAR) that captures dynamic correlations among all considered variables (output growth, inflation, and the real interest rate) without imposing coefficient restrictions from theory. To account for secular changes over time, Lubik and Matthes allow for time-variation in the parameters of the model. To obtain an estimate for the natural interest rate, Lubik and Matthes use the estimated VAR and compute a five-year forecast for the real interest rate. This forecast is interpreted as a measure of the natural interest rate. The rationale is that the natural interest rate reflects a stable price equilibrium towards which the real interest rate eventually moves after cyclical factors have faded out. They assume that over a five-year horizon the real interest rate converges to its natural counterpart. Similar to Laubach and Williams, they find a secular decline in the natural rate over the last decades. However, their point estimate is 0.5 percent in 2015, so about 50 basis points higher than the one by Laubach and Williams. The uncertainty around the point estimate is similarly high as in the model by Laubach and Williams. The 90 percent confidence band ranges from about -2 to about +3 percent. Estimates of long-run equilibrium rates Del Negro et al. (2017) and Wieland and Wolters (2018) use fully theory-based macroeconomic models to estimate the long-run equilibrium rate. In contrast to the medium-term horizon of the semi-structural approaches discussed above, their natural rate estimates refer to a long-run concept of 20 to 30 years. The models used are Dynamic Stochastic General Equilibrium (DSGE) models as used by central banks for policy simulations and forecasting. The equations are derived from microeconomic optimization problems of households and firms, so that all 16 variables and parameters have a clear structural meaning. The models are estimated using Bayesian estimation methods. Both studies find a decline in the natural interest rate since the early 1990s. However, the size of the decline is larger in the Del Negro et al. study leading to current estimates of the natural interest rate for the US between 1 and 1.5 percent, while the ones of Wieland and Wolters are currently about 2 percent. The difference between the two studies can be traced back to differences in the definition of the natural interest rate and related methodological differences regarding its measurement. Wieland and Wolters estimate the model-implied steady state real interest rate. In order to account for slow-moving structural changes, they estimate the model based on a rolling window of 80 quarterly observations, i.e. of 20 years of data. Hence, their steady state concept refers to a situation in which all shocks including those that have highly persistent effects have faded out. Del Negro et al. compute at each point in time 20- and 30-year forecasts of the real interest rate, which they use as a measure of the long-run natural interest rate. Due to highly persistent shock processes that have not faded out after 20 or 30 years, they find time-variation in the natural interest rate. The natural rate estimates 0.5-1 percentage points lower than in Wieland and Wolters can be explained by an increased preference of investors for safe and liquid short-term assets, called the convenience yield by Del Negro et al. This shift in preferences is so persistent that it lowers the forecast-based natural rate estimates in the Del Negro et al. study. Wieland and Wolters focus instead on steady state measures, i.e. they measure the natural interest rate after all shocks have faded out including the highly persistent convenience yield shocks. Using natural rates for policy discussions Overall, it turns out that it is not possible to pin down the natural interest rate with a sufficiently high degree of precision. All studies find that the natural rate has decreased over the last two decades, but the size of the decline differs widely across studies (Table 1). Recent estimates for the US vary between 0 and 2 percent with the influential Laubach and Williams estimates marking the lower bound. However, uncertainty bands are very large and estimates vary depending on the precise concept of the natural interest rate used, being lower for medium-term and somewhat higher for long-term concepts. Further, data revisions and data becoming available in the future might lead to substantial revisions of current estimates of the natural interest rate. Such uncertainty is particularly high at the sample end where it is difficult to distinguish cyclical dynamics and trend changes in real-time. Hence, it is uncertain whether the natural interest rate has declined substantially or whether recent low estimates will be revised upwards in the future.6 Finally, most of the literature focusses on natural rate measures related to short-term safe US assets. For these, specific aspects like a global increase in the demand for safe and liquid short-term assets since the Great Recession might be relevant leading to particularly low natural rate estimates. Overall, natural rate estimates are of limited use in policy discussions (Clark and Kozicki 2005). Rather than relying on point estimates, policy should take into account imprecision in estimates (Orphanides and Williams 2007). 6 See Hamilton et al. (2016) for a discussion that periods of real interest rates being below 2 percent have turned out to be temporary in the past. 17 Table 1 : Ranges of U.S. natural rate estimates Study Last estimates Uncertainty Drop since late 1990s Laubach and Williams (2016) 0.14% (2018, Q1) -5%,+5% (95% band, Beyer and Wieland, 2017) 3% Lubik and Matthes (2015) 0.5% (2015, Q2) -1.5%,1.5% (90% band) 1.5% Kiley (2015) 1.25% (2014, Q4) 0.4%,2.1% (68% band) 0.6% Del Negro et al. (2017) 1-1.5% (2016, Q3) 0.6%,1.8% (68% band) 0.7%-1.2% Wieland and Wolters (2018) 1.2-2.2% (2017, Q1) 0.9%,4% (95% band) 1%-2% 2.4 Factors behind the natural interest rate Several factors that are associated with desired savings and desired investment can influence the level of the natural interest rate. Most frequently, the natural rate is related to potential output growth or productivity growth. Lower potential output growth (or expected consumption growth) is associated with a lower natural interest rate as investment tends to become less attractive due to lower returns on investment and as private households according to the Euler equation tend to increase their savings to smooth consumption. The more economies are financially integrated the more global factors can have an effect on the natural interest rate. For example, Bernanke (2005) and Greenspan (2005) argue that with increasing financial integration a savings glut due to high desired savings in emerging economies has contributed to the decline in real interest rates in advanced economies. However, with increasing international financial integration international investment opportunities are increasing as well so that the impact on the natural interest rate is ambiguous. International financial integration has also led to an increase in the effective demand for safe assets, which are typically supplied by advanced economies (e.g. US government bonds), and thereby may have put downward pressure on risk-free rates (Caballero et al. 2017). Furthermore, demographic factors can influence the natural interest rate. For example, a decline in the old-age dependency ratio could increase the propensity to save and thereby lower the natural interest rate. However, if a decline in the old-age dependency ratio is associated with an increase in population growth returns on investment (or the marginal product of capital) may also increase, leading to higher desired investment and thus putting upward pressure on the natural rate (Carvalho et al. 2016). Another factor that has been discussed in the literature is the downward trending relative price of investment goods implying that a declining investment share in GDP is sufficient to reach the same production path (IMF 2014). Other factors that have been discussed include a lack of investment opportunities (Gordon 2012), shifts in inequality that impact desired savings (Eggertsson et al. 2017), or shifts in risk premia that influence desired investment (CEA 2015). Recently, it has been argued that monetary policy could also be a factor influencing the natural rate, as the monetary regime may have an impact on natural interest rates (Borio et al. 2017). The question to what extend these factors have contributed to fluctuations in the natural interest rate is very difficult to address. First, many of the potential factors are interdependent, making it difficult to identify their individual impact. Second, estimates of the natural interest rate are subject to high uncertainty indicating that the data are not very informative for identifying natural rates and suggesting that they will not be very informative as well for identifying the contributions of different factors. Third, the impact of these factors may vary over 18 time and could be non-linear. Many studies that evaluate the impact of these factors are based on narrative approaches or calibrated theoretical models. Empirical studies are usually focussing only on one single factor. One exception is Borio et al. (2017) who analyse the impact of several factors at the same time (GDP growth, demographic factors, relative price of capital goods, inequality). The results in the literature are mixed. The CEA (2015) concludes that lower potential output growth, demographic factors, and the global saving glut have contributed to a decline in the natural interest rate in addition to transitory factors. The IMF (2014) stresses the importance of the global savings glut, higher demand for safe assets, and the decline in relative prices of investment goods as well as a decline in investment profitability. However, Gomme et al. (2015) find that both returns on investment as well as investment volumes are not particularly low in the US. Also in other countries, such as Germany, equity and other investment returns have not strongly declined (Deutsche Bundesbank 2017). The fact that expected equity returns did not follow the decline of “safe” asset returns indicates that it is not a lack of investment opportunities, as suggested, e.g. by the secular stagnation hypothesis, that is behind the decline in the natural interest rate, but rather increased risk-premia due to a shift of demand towards safe assets. In this regard, Del Negro et al. (2018) find that the higher demand for safe assets in addition to lower productivity growth is an important factor behind the decline in their natural interest rate estimates. However, it is very difficult to establish a robust long-run link between these factors and the natural interest rate (Borio et al. 2017). Overall, the decline in potential growth and a stronger demand for safe assets related to a savings glut, and demographic change seem to be relevant drivers behind the decline in the natural interest rate in the last decades. While some of these factors are more likely to stay in place (lower potential output growth) others are more transitory or could reverse and put upward pressure on the natural rate (e.g. higher savings due to demographic change) in the future, even though it is difficult to anticipate when these effects will set in. 4 IMPLICATIONS FOR MONETARY POLICY Potential growth and the natural interest rate have declined over the past decades. At the same time, there is high uncertainty about the level of potential output and the natural interest rate. While recently potential growth and the natural interest rate have recovered somewhat according to most estimates, it is questionable whether they will reach levels observed some decades ago. All of this has important implications for monetary policy. A lower natural interest rate makes the conduct of monetary policy more difficult, because it increases the likelihood that the Zero or Effective Lower Bound (ELB) will become binding more often in the future. The ELB can therefore restrict conventional interest rate policy so that the central bank may undershoot its inflation target. In such a situation, a central bank may turn to unconventional measures such as forward guidance (in particular the promise to keep interest rates lower than otherwise expected for an extended period of time) and outright asset purchases, 19 as observed in the aftermath of the Global Financial Crises in many advanced economies.7 However, there is a debate in the literature on how effective unconventional monetary policy is. Wu and Xia (2016) as well as Debortoli et al. (2018), using VAR models, find that there was no structural change in the Federal Reserve’s ability to affect economic activity between the period before and after the Lower Bound became binding. However, Hamilton and Wu (2012) conclude that large volumes of asset purchases may be necessary to achieve modest effects. Overall, estimates of the impact of an asset purchase programme (scaled to one trillion dollars) on inflation in the US range from zero to four percentage points across studies. On average, the peak effect (excluding one outlier) is estimated to be 0.5 percentage points. There are fewer studies for the euro area, but they also exhibit a sizeable range of estimates (cf. Fiedler et al. 2016 for an overview). Thus, very large asset purchase programmes may be required to reach a particular increase in inflation, which may not always be feasible. For example, the Eurosystem already holds close to 25 percent of all euro area government bonds making it increasingly difficult to further expand the balance sheet, especially when taking into account the limits and criteria for eligible bonds introduced by the ECB. Moreover, the impact of unconventional monetary policy might vary over time (Borio and Hofmann 2017). There is evidence that unconventional monetary policy can be particularly effective during acute crisis phases where uncertainty, financial stress, and credit constraints are elevated, but that afterwards financial imbalances built up before the crisis impairs important transmission channels of monetary policy (Hesse et al. 2018). Against this backdrop, to the extent that the natural interest rate has declined it has become more likely that central banks will undershoot their inflation targets for extended periods of time and that attempts to fine-tune inflation will be associated with considerable costs (Eichenbaum 2017). Propositions to deal with these challenges include adjusting or changing the flexible inflationtargeting framework of monetary policy within which many central banks operate. One prominent proposition is to increase inflation targets (Blanchard et al. 2010; Ball 2014). The idea behind is that higher inflation will increase the spread between nominal and real interest rates, allowing the central bank to push real rates further below zero to provide more stimulus to the economy. However, a higher inflation rate could also increase the costs of inflation (including relative price distortions, menu and shoe leather costs, the distortions due to taxation of nominal returns, etc.). Moreover, raising the inflation target could be ineffective or lead to a loss of central bank credibility and de-anchoring of expectations (Laubach and Williams 2015). This could be of particular concern as central banks have undershot their inflation targets for a longer period in many advanced economies after the Global Financial Crisis and it is not obvious that they could reach a higher inflation target in a reasonable amount of time. In addition, the high uncertainty surrounding estimates of potential output and the natural interest rate makes it more difficult for central banks to assess the appropriate monetary policy stance to reach their targets. This high uncertainty suggests that central banks should put less weight on estimates of potential output (Ehrmann and Smets 2003, Smets 2002) and the natural interest rate (Hamilton et al. 2016) and more weight on incoming data on inflation, output growth or other business cycle indicators. More generally, policy rules more robust to measurement 7 In practise, it is sometimes difficult to neatly distinguish different types of unconventional policies. For example, large-scale asset purchase programmes could be seen as a form of forward guidance because they provide a commitment for the central bank to keep interest rates low for an extended period of time. 20 errors regarding potential output or the natural interest rate are preferable when estimation uncertainty is high (Laubach and Williams 2015). In this regard, it is also important that there is some uncertainty whether standard estimates of the natural interest rate capture all relevant information. For example, estimates which take the financial cycle into account result in substantially higher estimates of the natural rate (Juselius et al. 2017). Beyond uncertainty about potential output and the natural interest rate, central banks are currently facing several additional challenges that make it more difficult for monetary policy to reach its targets compared to the past. First, the Philips curve relationship, which describes how inflation reacts to changes in the output gap, has apparently weakened (BIS 2017, IMF 2013, Blanchard et al. 2015, Lodge and Mikolajun 2016). As monetary policy usually tries to influence inflation via engineering changes in the output gap, this weaker relationship makes it more difficult for central banks to reach their inflation targets within the same time-frame as in the past. One reason for this weaker relationship might be that inflation expectations are better anchored due to a high credibility of central banks so that inflation reacts less sensitive to changes in the output gap (Bernanke 2010, IMF 2013).8 If this were the main driver of the weaker Phillips curve relationship it would not be a major concern of central banks. However, following the Global Financial Crisis, central banks in many advanced economies apparently had problems to hold inflation close to their targets indicating that well-anchored inflation expectations and a high credibility of central banks are not sufficient conditions to keep inflation close to target. Second, the impact of monetary policy on GDP and the output gap seems to be statedependent and to vary over time making it more difficult for central banks to conduct a monetary policy that stabilizes the output gap and in turn inflation. There is increasing evidence that expansionary monetary policy was particularly effective during the acute phase of the Global Financial Crisis (Ciccarelli et al. 2013, Dahlhaus 2017, Jannsen et al. 2018) but less effective subsequently in the recovery phase (Bech et al. 2014, Borio and Zabai 2016, Jannsen et al. 2018). Reasons for this could be that expansionary monetary policy helped to mitigate the high uncertainty during the acute phase of the Global Financial Crisis, while afterwards the high indebtedness of private households and the boom in the housing markets preceding the crisis made monetary transmission via the credit channel and the housing market less effective. Third, there is increasing evidence that monetary policy can have negative side-effects that harm the economy. Expansionary monetary policy leads to increasing risk-taking and thereby may lead to financial imbalances that undermine financial stability (Drehmann et al. 2012, Rajan 2005, Maddaloni and Peydro 2011). Moreover, expansionary monetary policy can contribute to the misallocation of resources. Cette et al. (2016) show empirically that a decline in the real interest rate is associated with a significant decline in productivity. Furthermore, expansionary monetary policy can contribute to the so-called “Zombification” of firms and banks, a process where firms which are not creditworthy receive further funding because banks want to avoid writing down existing loans to these firms. This phenomenon has been observed in Japan (Caballero et al. 2008, Hoshi and Kashyap 2004). In the euro area, the windfall profits for banks in the peripheral countries due to the OMT announcement have mainly led to an increase of loans to firms with below than average credit servicing ability (Acharya et al. 2015). These firms did not use the additional funding for investment or job creation so that even in the short run no 8 Other factors behind the weaker Phillips curve relationship that have been discussed in the literature are globalization and digitalization. For a discussion see e.g. Fiedler et al. (2018b). 21 stimulating effects for the economy have taken place. Finally, expansionary monetary policy, in particular in the euro area, may provide disincentives for structural reforms or financial consolidation of governments’ budget balances, e.g. because it lowers government bond yields. While these risks may be limited if monetary policy is expansionary only for some years, they could increase when monetary policy is expansionary for extended periods of time. 5 CONCLUSIONS Overall, central banks are facing several challenges at the current juncture. Potential output growth has been on a secular downward trend since the late 1970s in many advanced economies partly due to declining productivity growth. Going forward, there are indications that the downward trend in potential growth is about to reverse, but there is no strong reason to expect sudden improvement. However, estimates of potential output are subject to large uncertainty. The Global Financial Crisis does not seem to have had a persistent dampening effect on the growth rate of potential output, but it has further increased uncertainty of potential output estimates. This uncertainty translates into uncertainty about the output gap making it more difficult for central banks to assess the appropriate stance of monetary policy as the Phillips curve relationship between the output gap and inflation describes one of the most important transmission channels of monetary policy on inflation. Uncertainty about potential output growth can be also a major factor behind forecast errors (Dovern and Weiser 2011) making it even more difficult for central banks to assess the appropriate stance of monetary policy and in turn to reach their targets within a reasonable period of time. Further, the natural interest rate has most likely declined over the last decades with lower potential output growth being one important factor behind. Other potential factors include increasing savings due to demographic change and an increase in the demand for safe assets. Estimates of the natural interest rate are, however, particularly uncertain, sensitive to the methodology and econometric model specification, and subject to large revisions. Uncertainty is so large that pinning down a precise value is not possible. To the extent that the natural rate has declined, it makes it more difficult for monetary policy to stabilize economic activity and to control inflation during downturns, in particular when the Effective Lower Bound becomes binding. However, it is not obvious that an insufficiently expansionary stance of monetary policy was an important reason behind the sluggish recovery and the persistently low inflation following the Global Financial crisis. First, the sluggish recovery was in line with historical experiences of other financial crises. Second, there is increasing evidence that monetary policy (either conventional or unconventional) is less effective in the aftermath of financial crises compared to non-crisis times. Third, the relationship between the output gap and inflation has weakened, making it more difficult for central banks to control inflation. Going forward, to the extent that the natural rate has declined, central banks will rely more on unconventional policy measures as conventional monetary policy will be restricted more frequently by the Effective Lower Bound. There are concerns that unconventional monetary policy is less effective and has negative side effects, especially if it is in place for long periods of time. This implies that central banks may have to accept deviations from their inflation targets for longer periods than in the past. Moreover, given that estimates of potential output and the 22 natural interest rate are subject to high uncertainty and large revisions, central banks should put a relatively low weight on these estimates and a relatively high weight on incoming data on inflation, GDP growth as well as other business cycle indicators and allow for more inertia in adjusting their monetary policy. 23 REFERENCES Acharya, V., D. Pierret and S. Steffen (2015). Do Central Bank Interventions Limit the Market Discipline from Short-Term Debt? Working Paper. Available at: https://www.frbatlanta.org/- /media/Documents/news/conferences/2015/1119-the-role-of-liquidity-in-the-financial-system/acharyapierret-steffen-do-central-bank-interventions-limit-market-discipline-preliminary.pdf?la=en Ball, L. (2014). The Case for a Long-Run Inflation Target of Four Percent. IMF Working Paper WP/14/92. International Monetary Fund, Washington, D.C. Bank for International Settlements (BIS) (2017). Monetary policy: Inching towards normalisation. 87th Annual Report, 2016/17, Chapter 4. Available at: https://www.bis.org/publ/arpdf/ar2017e4.htm Barnett, A., S. Batten, A. Chiu, J. Franklin and M. Sebastiá-Barriel (2014). The UK productivity puzzle. Bank of England Quarterly Bulletin 2014 (2): 114–128. Barsky, R., A. Justiniano and L. Melosi (2014). The natural rate of interest and its usefulness for monetary policy. The American Economic Review 104 (5): 37–43. Baumol, W.J. (1967). Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis. American Economic Review 57: 415–426. Bech, M., L. Gambacorta and E. Kharroubi (2014). Monetary policy in a downturn: Are Financial crises special? International Finance 17 (1): 99–119. Bernanke, B.S. (2005). The global saving glut and the U.S. current account deficit. Board of Governors of the Federal Reserve System, April 14, 2005. Bernanke, B. (2010). The Economic Outlook and Monetary Policy. Speech, Federal Reserve Bank of Kansas City Economic Symposium, Jackson Hole, Wyoming, August 27. Available at: http://www.federalreserve.gov/newsevents/speech/bernanke20100827a.htm Beyer, R., and V. Wieland (2017). Instability, imprecision and inconsistent use of equilibrium real interest rate estimates. CEPR Discussion Papers 11927. Center for Economic and Policy Research, Washington, D.C. Blanchard, O., G. Dell’Ariccia, and P. Mauro (2010). Rethinking Macroeconomic Policy. IMF Staff Position Note SPN/10/03. International Monetary Fund, Washington, D.C. Blanchard, O., E. Cerutti and L. Summers (2015). Inflation and activity – two explorations and their monetary policy implications. NBER Working Papers 21726. National Bureau of Economic Research, Cambridge, MA. Borio, C. (2014). The financial cycle and macroeconomics: what have we learnt? Journal of Banking and Finance 45 (August): 182–98. Borio, C. (2017). Secular stagnation or financial cycle drag? Business Economics 52 (2): 87–98. Borio, C. and M. Drehmann (2009). Assessing the Risk of Banking Crises – Revisited. BIS Quarterly Review (March): 29–46. Borio, C. and B. Homannn (2017). Is monetary policy less effective when interest rates are persistently low? BIS Working Papers 628. Available at: https://www.bis.org/publ/work628.pdf Borio, C., and A. Zabai (2016). Unconventional monetary policies: a re-appraisal. BIS Working Papers 570. Available at: http://www.bis.org/publ/work570.pdf Borio, C., P. Disyatat, M. Juselius and P. Rungcharoenkitkul (2017). Why so low for so long? A long-term view of real interest rates. BIS Working Papers 685. Bank for International Settlements, Basel. Boysen-Hogrefe, J., N. Jannsen and C.-P. Meier (2016). A Note on Banking and Housing Crises and the Strength of Recoveries. Macroeconomic Dynamics 20: 1924–1933. Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM 36 (12): 66–77. Caballero, R.J., T. Hoshi and A. Kashyap (2008). Zombie Lending and Depressed Restructuring in Japan. American Economic Review 98 (5): 1943–1977. Caballero, R., E. Farhi and P. Gourinchas (2016). Safe Asset Scarcity and Aggregate Demand. American Economic Review: Papers & Proceedings 106 (5): 513–518. Caballero, R., E. Farhi, and P. Gourinchas (2017). The Safe Assets Shortage Conundrum. Journal of Economic Perspectives 31 (3): 29–46. CEA (Council of Economic Advisors) (2015). Long-Term Interest Rates: A Survey. Available at: https://obamawhitehouse.archives.gov/sites/default/files/docs/interest_rate_report_final.pdf 24 Cerra, Valerie and Sweta C. Saxena (2008). Growth Dynamics: The Myth of Economic Recovery. American Economic Review 98, 1, 439–457. Cette, G., J. Fernald and B. Mojon (2016). The Pre-Great Recession Slowdown in Productivity. European Economic Review 88: 3–20. Ciccarelli, M., A. Maddaloni and J.-L. Peydro (2013). Heterogeneous transmission mechanism: monetary policy and financial fragility in the eurozone. Economic Policy 28 (75): 459–512. Cieslak, A. (2015). Discussion of ‘The Equilibrium Real Funds Rate: Past, Present and Future,’ by James D. Hamilton, Ethan S. Harris, Jan Hatzius, Kenneth D. West (2015), slides from Brookings Conference. Available at: https://www.brookings.edu/wp-content/uploads/2016/07/West.pdf Clark, T., and S. Kozicki (2005). Estimating equilibrium real interest rates in real time. The North American Journal of Economics and Finance 16 (3): 395–413. Crafts, N. (2018). The productivity slowdown: is it the ‘new normal’? Oxford Economic Review of Economic Policy 34 (3): 443–460. Cúrdia, V., A. Ferrero, G. Ng and A. Tambalotti (2015). Has US monetary policy tracked the efficient interest rate? Journal of Monetary Economics 70: 72–83. Dahlhaus, T. (2017). Conventional Monetary Policy Transmission during Financial Crises: An Empirical Analysis. Journal of Applied Econometrics 32: 401–421. Debortoli, D., J. Galí and L. Gambetti (2018). On the Empirical (Ir)Relevance of the Zero Lower Bound Constraint. Barcelona GSE Working Paper 1013. Graduate School of Economics, Barcelona. Del Negro, M., D. Giannone, M. Giannoni and A. Tambalotti (2017). Safety, Liquidity, and the Natural Rate of Interest. Brookings Papers on Economic Activity, Economic Studies Program. The Brookings Institution 48 (1 (Spring): 235–316. Del Negro, M., D. Giannone, M. Giannoni and A. Tambalotti (2018). Global Trends in Interest Rates. Federal Reserve Bank of New York Staff Reports 866. New York. Deutsche Bundesbank (2017). The natural rate of interest. Monthly Report. October. Frankfurt, Main. Dovern, J., and N. Jannsen (2017). Systematic Errors in Growth Expectations over the Business Cycle. International Journal of Forecasting 33: 760–769. Dovern, J. and C. Zuber (2017). Recessions and Instable Estimates of Potential Output. Discussion Paper Series, No. 639, Department of Economics, Heidelberg University. Dovern, J., and J. Weisser (2011). Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An Empirical Comparison for the G7. International Journal of Forecasting 27(2): 452–465. Drehmann, M., C. Borio and K. Tsatsaronis (2012). Characterising the financial cycle: don’t lose sight of the medium term! BIS Working Paper 380. Available at: https://www.bis.org/publ/work380.pdf Eggertsson, G., N. Mehrotra and J. Robbins (2017). A Model of Secular Stagnation: Theory and Quantitative Evaluation. NBER Working Paper 23093. National Bureau of Economic Research, Cambridge, MA. Ehrmann, M., and F. Smets (2003). Uncertain potential output: implications for monetary policy. Journal of Economic Dynamics & Control 27: 1611–1638. Eichenbaum, M. (2017). Global secular stagnation and monetary policy. Presentation. Fiedler, S., I. Hanisch, N. Jannsen and M. Wolters (2016). Transmission Channels of Unconventional Monetary Policy in the Euro Area: Where Do We Stand? Briefing Paper for the European Parliament’s Monetary Dialogue, November. Available at: https://www.ifw-kiel.de/de/publika tionen/ policy-papers/analysen-fuer- das-europaeische-parlament/transmission-channels-of-the-unconventional-monetary-policy-in-the-euro- area-where-do-we-stand-10096/ Fiedler, S, K.-J- Gern, N. Jannsen, and M. Wolters (2018a). Growth Prospects, the Natural Interest Rate, and Monetary Policy. Briefing Paper prepared for the European Parliament, Policy Department A: Economic and Scientific Policy, Monetary Dialogue November 2018. Fiedler, S., N. Jannsen and U. Stolzenburg (2018b). An economic recovery with little signs of inflation acceleration: Transitory phenomenon or evidence of a structural change. In-Depth Analysis prepared for the Monetary Dialogue of the European Parliament, February. Available at: http:// www.europarl.europa.eu/cmsdata/138405/MD%20KIEL%20final.pdf Freund, L. (2018). The Productivity Paradox – A Survey. Available at:http://dezernatzukunft.org/2018/10/02/theproductivity-paradox-a-survey-2/ Furceri, D., and A. Mourougane (2012). The Effect of Financial Crises on Potential Output. New empirical evidence from OECD countries. Journal of Macroeconomics 34: 822–832.