RDP 2005-08: Declining Output Volatility: What Role for Structural Change? 1. Introduction
October 2005
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The past 25 years has been an era of significant reforms affecting the institutional features and operation of monetary and fiscal policies, as well as of product and labour markets across a range of industrialised countries. Over the same period, there has also been a considerable decline in the volatility of real output around the developed world. Figure 1 shows that, on average, across 20 selected OECD countries,[1] the standard deviation of the annual growth rate of GDP has fallen by more than 1 percentage point since the 1970s. Not surprisingly, there is a growing literature seeking to disentangle the varied (and interrelated) causes of this general decline, and to determine the explanatory role, if any, for structural reforms.
Four factors that could explain the decline in the volatility of GDP have been proposed: changes in both the composition of GDP and the behaviour of its various components; the efficacy of monetary and fiscal policies; structural reforms in markets; and plain good luck, reflecting smaller and/or less frequent shocks.[2] Explanations related to the first three factors typically emphasise their role in reducing the responsiveness of an economy to exogenous shocks. In addition, these factors may have had some role in directly reducing the magnitude of shocks themselves. The fourth factor, good luck, may have led to a decline in the magnitude of the shocks globally over this period, regardless of any effect from the first three factors. The relative contribution of these four factors to the decline in output volatility is important since it has implications for future output volatility.
By their nature, the first three structural factors are likely to have a more permanent effect on output volatility, while a decline in global shocks (irrespective of structural factors) may only be temporary.
Surprisingly, there has been little consensus regarding the relative contribution of these four factors to the reduction in output volatility. A variety of approaches have been used to determine their empirical relevance. One approach examines changes in the make-up and behaviour of various components of GDP for a given country.
A second approach examines the effectiveness of monetary policy as a tool of macroeconomic stabilisation. For example, Cecchetti, Flores-Lagunes and Krause (2004) estimate movements towards an efficiency frontier for inflation and output variability and movements in the frontier itself (by using estimates of simple structural equations for aggregate demand and supply). They find that better monetary policy (that is, a move towards the efficient frontier) accounts for most of the improvement in macroeconomic stability across a wide range of countries.
A third approach also uses estimates of structural models for given countries, but with the aim of decomposing changes in output volatility into two parts, that which is due to changes in the magnitude of shocks and that which is due to changes in the transmission of shocks (that is, model parameters). Changes in transmission are taken to reflect structural change, broadly defined to incorporate behavioural changes, the efficacy of macro-policies and structural reforms in markets. In stark contrast to the results of the aforementioned studies, Ahmed, Levin and Wilson (2004) and Stock and Watson (2004) find that most of the decline in output volatility in the United States is due to a decline in the magnitude and frequency of global shocks. For Australia, Simon (2001) also finds that most of the decline in output volatility is due to smaller shocks, with little role for structural factors. However, this approach implicitly assumes that shocks are independent of the structure of the economy. Simon acknowledges this limitation, noting that the decline in productivity shocks may have been related to structural factors, such as the shift towards more skilled workers and serviced-based industries, and financial liberalisation. Similarly, Clarida, Galí and Gertler (2000) argue that monetary policy (by better anchoring expectations) can reduce shocks arising from shifts in expectations for reasons unrelated to macroeconomic fundamentals.
A fourth, atheoretic, approach is based on cross-country panel data models with output volatility as the dependent variable and various measures of structural change as independent variables. Implicitly, coefficient estimates on these measures of structural change will jointly capture their effect on the responsiveness of an economy to shocks and the size of those shocks. Using G7 panel data, Barrell and Gottschalk (2004) find a significant role for indirect measures of monetary policy effectiveness and regulatory reform in explaining the decline in output volatility.
The aim of this paper is to re-examine the significance of a wide range of variables in explaining the decline in output volatility using this atheoretic approach, though with a few notable innovations. First, we use a larger panel (with 20 OECD countries). Second, we use direct measures of structural reforms which are less likely to suffer from possible endogeneity. Specifically, for monetary policy we construct a crude, but apparently effective, dummy variable that identifies two possible types of regimes according to the relative strictness with which policy-makers pursue the goals of low and stable inflation. For product markets we use a ‘synthetic’ indicator which allows a comparison of regulatory frameworks across countries and over time (Nicoletti et al 2001). Third, unlike existing studies of this type, we show that our results are relatively robust to trends in common global shocks that are unrelated to structural change.
The structure of this paper is as follows. Section 2 provides a more detailed discussion of the mechanisms linking output volatility to the explanatory factors identified above; paying particular attention to the role of product and labour market reforms, which have received less attention in the literature. Section 3 describes the data in detail, and outlines the basic estimation methodology. Section 4 presents the results, considers an extension that controls for trends in common shocks, and provides a number of robustness checks. Section 5 concludes.
Footnotes
These are: Australia; Austria; Belgium; Canada; Denmark; Finland; France; Germany; Ireland; Italy; Japan; the Netherlands; New Zealand; Norway; Portugal; Spain; Sweden; Switzerland; the United Kingdom; and the United States. [1]
See Bernanke (2004) and Stock and Watson (2004) for discussions of the literature. A fifth factor that has received attention is the possibility of a reduction in measurement error, though at least for the United States, this has been discounted (see Dynan, Elmendorf and Sichel 2005 for a discussion). [2]