شناسایی سیاست های پولی و مالی در یک ساختار VAR

Good economic management depends on understanding shocks from monetary policy, fiscal policy and other sources affecting the economy and their subsequent interactions. This paper presents a new methodology to disentangle such shocks in a structural VAR framework. The method combines identification via sign restrictions, cointegration and traditional exclusion restrictions within a system which explicitly models stationary and non-stationary variables and accounts for both permanent and temporary shocks. The usefulness of the approach is demonstrated on a small open economy where policy makers are actively considering the interaction between monetary and fiscal policies.

For any country, effective economic management depends on understanding the nature of shocks hitting the economy and their subsequent economic interactions. In particular, interactions of monetary policy shocks with fiscal policy and other variables, fiscal policy shocks with monetary policy and other variables, and macroeconomic shocks with both fiscal and monetary policy are of importance for policy makers. This paper contributes a new methodology for disentangling these effects empirically in a structural vector autoregression framework (SVAR). Empirical macroeconomic modelling is often undertaken in a SVAR, where identification of policy shocks usually occurs in one of three ways.1 The first is through traditional normalisation and restrictions on the contemporaneous relationships between variables. This is widely applied to monetary policy (for a review see Bagliano and Favero, 1998) and only recently to fiscal policy using institutional detail and calibrated elasticities as identification tools (Blanchard and Perotti, 2002, Perotti, 2002, Chung and Leeper, 2007 and Favero and Giavazzi, 2007). The second is the newer sign restriction identification method which imposes restrictions on the set of impulse responses to shocks considered acceptable from the possible choice of orthogonal systems (Faust, 1998, Canova and de Nicoló, 2002 and Mountford and Uhlig, 2008). The third approach is to take account of the longer run properties of the model, in one form as a vector error correction model (VECM), or as an extension of Blanchard and Quah (1989), or in the recognition of the correspondence between SVARs and VECMs, see Jacobs and Wallis (2007), which allows the use of cointegrating relationships as a tool of identification as in Pagan and Pesaran (2008). Here the approach is to build a model containing fiscal, monetary and other macroeconomic variables drawing on elements of these three identification methods. Short-run restrictions on the non-fiscal variables are provided via the existing traditional SVAR restrictions. The fiscal policy shocks are identified using a minimal set of sign restrictions, leaving other relationships to be data determined.2 These restrictions are applied in conjunction with information from the cointegrating relationships between the macroeconomic variables to model the long run, allowing for both permanent and transitory components and a mixture of stationary and non-stationary variables. The current paper is the first to combine these three techniques and allows us to make a more structured analysis while still adhering to the VAR tradition of letting the data determine the dynamics in the economy, particularly for the less commonly modelled fiscal policy shocks. The study of fiscal policy shocks and policy interactions in SVAR models is relatively limited but has largely built on the Blanchard and Perotti (2002) fiscal policy framework: for example Perotti (2002) for a range of OECD countries. More recently, Chung and Leeper (2007) and Favero and Giavazzi (2007) build on Blanchard and Perotti and show the importance of accounting for the level of government debt. Mountford and Uhlig (2008) use the Blanchard and Perotti fiscal variables but an alternative sign restriction based identification scheme. Canova and Pappa (2007) also utilise the sign restriction method for examining fiscal policy in a monetary union. The latter papers all focus on the US.3 The application in this paper is to the small open economy of New Zealand, one of the few countries which has coherent fiscal data available for modelling.4 New Zealand was the first country to adopt inflation targeting, in 1990, and consequently has the longest available time series for a small open economy in an inflation targeting environment. It also adopted a Fiscal Responsibility Act in 1994. Further, policy attention in New Zealand is currently focussed on the interactions between fiscal and monetary policy (Finance and Expenditure Committee, 2008). There is a well-established SVAR modelling framework for New Zealand, which has resolved many non-fiscal related model specification issues, and this is drawn on for the short-run restrictions for the non-fiscal variables; see particularly Buckle et al. (2007) and references therein. The rest of this paper proceeds as follows. Section 2 presents a coherent VAR framework in which three types of identification restrictions are simultaneously applied and illustrates how to obtain impulse response functions and historical decompositions under this structure. Section 3 outlines the variables and data properties for the New Zealand example, characterising the stationarity and cointegration results necessary to apply the modelling framework. The specification of the model is described in Section 4 and the results are presented in Section 5 in terms of impulse response functions and historical decompositions. Section 6 concludes.

This paper has contributed a new approach to the empirical estimation of the interactions between monetary policy, fiscal policy and other economic shocks using a SVAR framework. The strengths of three different identification methods were exploited within a single modelling framework with an application to a small open economy. The existing traditional short-run coefficient restrictions were used to identify non-fiscal shocks. Sign restrictions were used to separate government expenditure and taxation shocks. The third element was to formally model the long run via the cointegrating relationships between the macroeconomic variables, and account for both permanent and transitory shocks in a model with both stationary and non-stationary data. The methodology was illustrated by an application to New Zealand, the economy with the longest history of inflation targeting and a well-constructed fiscal data set. Additionally, New Zealand is currently considering the structure of its macroeconomic policy making, and specifically the interactions between monetary and fiscal policy. The model incorporated elements of previous SVAR modelling for this economy in the short-run coefficient restrictions, building on Buckle et al. (2007). New features included the incorporation of the fiscal and debt variables, and the adoption of a SVARX form, where climate and international interest rates are incorporated as exogenous variables. The important role of debt in empirical models of fiscal policy has been emphasized in the recent work of Chung and Leeper (2007) and Favero and Giavazzi (2007). An important addition to the model was incorporating the long run behaviour, where the cointegrating relationships were derived from both the empirical characteristics of the data and theoretical concepts regarding fiscal sustainability. The model characterised the behaviour of output in New Zealand over the last 20 years, and showed that in general fiscal policy shocks have been larger than monetary policy shocks. Taxation and debt policy shocks have been more substantial than government expenditure shocks. Most of the behaviour in output arising over the sample period was clearly not a result of policy shocks; in many case New Zealand has been greatly affected by internationally sourced shocks, or effects from domestically sourced demand and inflation shocks have been important. However, a decomposition of monetary policy shocks showed that it mainly responded to inflationary shocks, providing a heartening validation of the conduct of monetary policy in New Zealand.