Rouatu, L.2010-06-042004https://hdl.handle.net/10182/2006The main objective of this study is to try to understand how money affects real output. Despite the long history of this subject and the existence of several theories that try to explain how the monetary effect is transmitted to real output, there is still no consensus on how the transmission actually works. To put it in a more practical context, there is still a knowledge gap between the time the monetary policy is implemented and the time the effects are felt on real output (or inflation). In the literature this interim is dubbed the 'black box'. Using the various tool kits of the VAR system, such as the impulse response function, the forecast error variance decomposition and Granger-causality test, this study hopes to open the lid of this so-called 'black box' and see what goes on inside. In operational terms, this involves examining and evaluating the different transmission mechanisms with particular focus on the bivariate relationships within each theoretical model. Furthermore, in an attempt to follow the sequence of the causal relationships as indicated in the different monetary transmission models, two transmission modes are used: a 'serial' and a 'parallel' transmission mode. And in order to compare the overall performance of the different transmission models, composite or summary measures pertaining to the responsiveness, the explanatory power and the Granger-causal effect of each model are used-but these are still based on the bivariate relationships within each model. The analysis is initially carried out using New Zealand data but in order to see whether the results hold in other countries, the analysis is extended to Australia. One important reason why Australia is chosen is because of the divergence of the output paths of the two countries since the mid 1980s when New Zealand undertook major economic and financial reforms-before then, the outputs of the two countries seemed to move together. Because the interest is generally on money and its real effect, the empirical analysis started off with the monetary neutrality and superneutrality tests using Fish and Seater (1993) framework. The results of the empirical analysis show fairly interesting and important insights. On the neutrality tests, the monetary long run neutrality proposition is not rejected however money superneutrality is decidedly rejected. There is also evidence from the impulse response analysis of monetary non-neutrality. This provided the logical basis for carrying out the monetary transmission analysis. The results show that each transmission model propagates the monetary impulse differently-at least there is evidence to suggest that the effects on output, in terms of timing and magnitude, are different. The importance of the credit channel, in particular the credit-consumption channel, is also evident from the analysis. Furthermore, the use of the interest rate instead of the money supply as the source of monetary impulse changes the responsiveness or the effectiveness of the transmission models. In Australia the money supply shows a fairly dominant effect on output while in New Zealand the interest rate seems to have more influence on output path, especially in the long run. This finding supports the contention that 'money matters'. Another useful insight is the lower response of fixed investment to interest rate shock in New Zealand compared to Australia. The exchange rate response to interest rate shock however is higher and more persistent in New Zealand than in Australia. The result of the counterfactual analysis in which New Zealand interest rate is modified as to follow that of Australia in the 1985-90 period shows that New Zealand would have got a higher output had it followed Australia's interest rate movements in the period indicated. These results, needless to say, have important policy implications. The introduction of the serial and parallel transmission concept and the use of the summary measures greatly facilitated the analysis.enimpulse response functionsvector autoregressionforecast error variance decompositionlong run multipliersmonetary transmission mechanismsserial transmissionparallel transmissiondirect transmissionbivariate relationshipunit rootsstabilityGranger causalityThesisQ112860232