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Forecasting with a Global VAR model

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The Bank assesses the impact of international conditions on the New Zealand economy using a range of models. Among them, is the Global Vector Autoregressive model (GVAR), which is designed to analyse economic and financial interdependencies between countries. The GVAR is primarily used by the Bank to examine the transmission of global shocks or disturbances to the New Zealand economy. This Analytical Note examines to what extent the GVAR can also forecast macroeconomic conditions in New Zealand and its main trading partners. We test several specifications of the GVAR and calculate out-of-sample forecasts for GDP, inflation, interest rates, exchange rates and equity prices for New Zealand, U.S., China, Australia, Canada and the euro area. We then evaluate whether GVAR forecasts are more accurate than other statistical models and whether the model’s GDP forecasts can outperform economists’ forecasts published by Consensus Economics. We find that forecasts obtained from simple specifications of the GVAR tend to outperform other simple statistical models of inflation and GDP. The GVAR also outperforms economists’ GDP growth forecasts from Consensus Economics. These results emphasise the benefits of incorporating international linkages to improve forecast accuracy and suggest that the GVAR is a useful addition to the range of models used by the Reserve Bank to forecast the international economy.

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  • Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Forecasting with a Global VAR model," Reserve Bank of New Zealand Analytical Notes series AN2019/03, Reserve Bank of New Zealand.
    • Handle: RePEc:nzb:nzbans:2019/03
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    1. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    2. Annari De Waal & Rene頖an Eyden & Rangan Gupta, 2015. "Do we need a global VAR model to forecast inflation and output in South Africa?," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2649-2670, May.
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