A structural VAR analysis of electricity consumption and real GDP : evidence from the G7 countries

In this paper, we depart from the literature on electricity consumption–real GDP in that for the first time we examine the reaction of real GDP to shocks in electricity consumption. To achieve this goal, we use the structural vector autoregressive (SVAR) model and examine the impact of electricity consumption shocks on real GDP for the G7 countries. We find that except for the USA, electricity consumption has a statistically significant positive impact on real GDP over short horizons. This finding implies that except for the USA, electricity conservation policies will hurt real GDP in the G7 countries.

Does monetary policy matter in a less developed economy? Evidence from Bangladesh

This paper explores the role of monetary policy in the context of a less developed economy. Monetary transmission mechanisms in less developed economies can be quite different from an industrialized economy, as unlike industrialized countries, these economies are characterized by the small size of organized financial markets, limited substitutability between money and other assets and weak fiscal and monetary institutions. We utilize the Structural VAR approach to analyze the monetary transmission process and impacts of monetary policy on different macro variables in Bangladesh. Monetary policy shocks are identified using non-recursive contemporaneous restrictions, which are based on the Central Bank's reaction function and the structure of the economy. We found strong evidence for the interest rate channel of monetary policy in Bangladesh. Our findings indicate that monetary policy shocks are important sources of fluctuations in the rate of interest, output and prices. Expansionary monetary policies are found to be harmful for achieving price stability in Bangladesh, as they not only increase the prices permanently, but also make the price level more volatile. We also found the evidence of a long lasting effect of monetary policy on output, which suggests that contractionary policy measures may create sustained recession in Bangladesh.

Impacts of monetary policies on housing affordability in Australia

Housing affordability has become a major policy issue in many countries across the world since the rapid inflation of house prices. This paper empirically investigates how monetary policies affect housing affordability in Australia from 1998 to 2009. Three primary variables associated with the housing sector and monetary policy, which are money supply, interest rates and house prices, are studied for all eight capital cities in Australia in this research. Shocks of such variables are identified by a structural vector autoregression (SVAR) model with restrictions that are consistent with economic theoretical framework. Based upon the analysis using the structural decomposition of impulse response on quarterly data, it can be discovered that the monetary policy plays an active role in housing affordability via adjustments of money supply and interest rates during the observed period in Australia. The empirical results from this research may be used for decision makers to determine money supply and interest rates from the perspective of housing affordability.

An analysis of Fiji's monetary policy transmission

Purpose – The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

Design/methodology/approach – The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short-term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

Findings – The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre-shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

Practical implications – The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

Originality/value – For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

Investigating the housing market fluctuation under an expansionary monetary policy in Australia

This research empirically investigates the impact of monetary policy on the housing market in Australia from 1996 to 2009. Three primary variables associated with the housing sector and monetary policy, including interest rates, money supply and house prices, are estimated by a structural vector autoregression (VAR) model. Depending upon the analysis using the impulse response function, it can be identified that monetary policy significantly affects the housing market in Australia by the adjustments in interest rates and money supply. The empirical results from this study may be useful for policy makers to enact appropriate policies in relation to the infrastructure planning.

Vector autoregressions and macroeconomic modeling: an error taxonomy

In this article we investigate the theoretical behaviour of finite lag VAR(n) models fitted to time series that in truth come from an infinite order VAR(∞) data generating mechanism. We show that the overall error can be broken down into two basic components, an estimation error that stems from the difference between the parameter estimates and their population ensemble VAR(n) counterparts, and an approximation error that stems from the difference between the VAR(n) and the true VAR(∞). The two sources of error are shown to be present in other performance indicators previously employed in the literature to characterize, so called, truncation effects. Our theoretical analysis indicates that the magnitude of the estimation error exceeds that of the approximation error, but experimental results based upon a prototypical real business cycle model and a practical example indicate that the approximation error approaches its asymptotic position far more slowly than does the estimation error, their relative orders of magnitude notwithstanding. The experimental results suggest that with sample sizes and lag lengths like those commonly employed in practice VAR(n) models are likely to exhibit serious errors of both types when attempting to replicate the dynamics of the true underlying process and that inferences based on VAR(n) models can be very untrustworthy.