RDP 2019-05: Cost-benefit Analysis of Leaning against the Wind 1. Introduction

‘Leaning against the wind’ is the policy of setting interest rates higher than a narrow interpretation of a central bank's macroeconomic objectives would warrant due to concerns about financial instability. This policy aims to dampen large increases in credit and asset prices. It is supported by a large literature that finds that ‘sustained rapid credit growth combined with large increases in asset prices appears to increase the probability of an episode of financial instability’ (Borio and Lowe 2002).^[1]

However, there are also costs of leaning against the wind, such as lower income and employment. Following Svensson ((2017a), though most of the literature cites earlier versions), numerous papers have extended the earlier research by quantifying and comparing both the costs and benefits of leaning against the wind. This is part of a broader trend to base economic policy on empirical cost-benefit analysis (Sunstein 2018). The main objective of this paper is to summarise the new research on leaning against the wind and discuss how it might be applied to Australia. We also discuss several concerns that have been raised regarding the research.

The new research assumes that the main benefit of leaning against the wind is avoiding financial crises, defined as episodes of substantial bank failures, such as the global financial crisis of 2008. Australia has experienced two of these crises – in 1893 and 1990. An advantage of this definition is that it enables both benefits and costs to be measured in terms of expected changes in unemployment. A debatable disadvantage of this definition is that it may be too narrow. As discussed below, the Reserve Bank of Australia (RBA) has broader objectives.

This benefit can be measured as the product of a lower probability of a financial crisis and the likely size of that crisis. Estimates of the lower probability of a crisis are based on (i) the effect of interest rates on credit growth, and (ii) the effect of credit growth on the probability of a crisis. Estimates of the effect of interest rates on credit growth are generally taken from simple regressions or vector autoregressions (VARs), while estimates of the effect of credit growth on the risk of a financial crisis are generally based on Schularick and Taylor (2012) or similar databases. The size of the financial crisis, usually measured by the expected increase in the unemployment gap, is assumed to be similar to past crises. This can then be compared with estimates of the effect of interest rates on the unemployment rate taken from, for example, a structural macroeconomic model. A quadratic loss function is typically assumed, and prudential policy is assumed to respond as it has in the past.

In many papers, this approach leads to the conclusion that some degree of leaning against the wind can raise welfare. The reason is that the conventional welfare costs of small deviations from the macroeconomic optimum are close to zero. Leaning against the wind involves incurring this negligible cost in return for a reduction in the probability of a crisis in the future, so would, on net, be beneficial. However, estimated magnitudes are tiny. Ajello et al (2016) estimate the welfare-maximising level of leaning against the wind involves raising interest rates by 3 basis points; this is ‘in line with’ the results of Aikman et al (2018); while Pescatori and Laséen (2016) estimate it to be 6 basis points. For larger, more relevant deviations, the costs of leaning against the wind increase to be substantially greater than the benefits. Pescatori and Laséen find that a 25 basis point increase in the Canadian policy rate would reduce welfare by 0.4 per cent. Svensson (2017a) finds costs exceed benefits by ‘a large margin’. In the ‘average probability’ scenario of the International Monetary Fund (Habermeier et al 2015, p 25), the welfare cost of a 100 basis point increase in the policy rate is around 30 times larger than the benefits. Gorea, Kryvtsov and Takamura (2016) estimate costs are 20 times benefits (taking midpoints of baseline ranges). Kockerols and Kok (2019, Figure 1) estimate that costs for the euro area would be three times as large as benefits. Specchia and Plank (2017) provide simple estimates for Australia, concluding that costs may exceed benefits.

The most common result of the research is that the costs of any meaningful leaning against the wind outweigh the benefits. This assessment is shared by other overviews of the research including Bernanke (2015), FOMC (2016, pp 2–3), Bank of Canada (2016, p 27), Allen, Bean and De Gregorio (2016, pp 19, 24), Constâncio (2018), Broadbent (2018) and most of the studies we survey. However, this conclusion has been contested. As we discuss below, Filardo and Rungcharoenkitkul (2016), Gerdrup et al (2017) and Gourio, Kashyap and Sim (2017) argue that leaning against the wind can be worthwhile under some assumptions. Adrian and Liang (2018) emphasise the uncertainties involved. Finally, Borio (2016) and the Bank for International Settlements (BIS 2016) argue that more complicated analysis would yield different conclusions to the currently standard approach. We discuss many of these points of controversy and sensitivity below.

The new research has two complementary strands. One focuses on empirical estimates of relationships between interest rates, credit growth, financial crises and a small number of other variables. Examples include Habermeier et al (2015), Gorea et al (2016), Pescatori and Laséen (2016), Specchia and Plank (2017) and Svensson (2017a). A second ‘structural’ strand embeds these relationships into general equilibrium models with explicit preferences and technology. Examples include Ajello et al (2016), Alpanda and Ueberfeldt (2016), Gerdrup et al (2017), Gourio et al (2017), Aikman et al (2018) and Kockerols and Kok (2019). In this paper, we focus on the first strand, which is more transparent and facilitates comparisons to other empirical research. However, the two strands substantially overlap and most of our discussion also relates to the structural models.

Our paper is narrow in focus. As noted above, the papers we survey specify the benefit of leaning against the wind as avoiding substantial bank failures. Research has focused on these financial crises for several reasons. First, in contrast to some other dimensions of financial stability, there is substantial evidence that their occurrence is affected by monetary policy. Second, they are large and frequent enough to be important. Third, despite the previous point, they used to be rare enough to be omitted from central bank modelling. The third reason ceased to be convincing after the global financial crisis (GFC). Rectifying that neglect is now a major research priority.

However, there is more to financial stability than bank failures. The RBA (2016a) and Lowe (2017a, 2017b) have justified higher interest rates on the grounds that they reduce the fragility of household balance sheets. As far as we are aware, this argument has not been quantified in the research literature, so is outside our scope. That exclusion means that we ignore some potential benefits of leaning against the wind.

We also ignore some leading criticisms. Many commentators argue that interest rates are often not the best tool for addressing financial imbalances. Stronger prudential regulation, such as capital requirements or loan-to-value limits, might reduce risky lending with less collateral damage in the form of higher unemployment. See, for example, Yellen (2014), Bernanke (2015) or Broadbent (2018); for recent formal studies see Aikman et al (2018), Kockerols and Kok (2019) and references cited therein. Again, this is a controversial issue that this paper does not explore.

These limitations mean that our paper should not be viewed as a comprehensive assessment of leaning against the wind. Rather, we focus on one specific argument – that leaning against the wind might help to avoid financial crises. Most of the papers we survey believe this argument is the central issue at stake with leaning against the wind. However, as Lowe (2017b) discusses, other considerations might be relevant in some circumstances.

Another branch of research that we do not discuss examines the effect of debt, asset prices and financial frictions on the business cycle. These variables can have substantial effects on future spending decisions – for example, through the effect of net worth on consumption. Hence a forward-looking central bank will react to them. A common research finding is that augmenting a backward-looking Taylor rule with financial variables improves performance. Although this response is sometimes called ‘leaning against the wind’ others would consider it to be ‘normal inflation-targeting policy’. Again, this debate is outside our scope. Following Bernanke and Gertler (2000), our focus is on responses to financial variables over and above their effect on near-term forecasts of activity and inflation. The issue of leaning against the financial cycle (Filardo and Rungcharoenkitkul 2016) is more relevant and we discuss it Section 6.3.

Footnote

Other prominent references include Schularick and Taylor (2012), who find that the probability of a financial crisis is positively correlated with the growth rate of real credit during the previous few years, and Drehmann et al (2010), who find that the detrended credit-to-GDP ratio is the best single predictor of financial crises. [1]