Trend　in　the　producer　price　is　of　much　value　to　the　central　bank　authorities　in　identifying　the　cost-push　inflation　that　can　improve　their　understanding　of　future　directions　of　inflation　in　the　aggregate　economy　and　informulating　sound　policies　and　macroeconomic　plans.　Forecasting　of　the　producer　price　movement　is　complex;　the　popular　use　of　conventional　methods　is　fraught　with　inaccuracies　which　often　produces　misleading　results.　This　study　explored　the　reliability　and　accuracy　of　the　use　of　artificial　neural　networks　(ANNs)　for　modelling　and　predicting　producer　price　index　(PPI)　trend　in　New　Zealand.　The　study　also　compared　ANNs　results　with　those　produced　by　the　autoregressive　integrated　moving　average　(ARIMA)　as　an　alternative.　Results　showed　that　the　ANNs　model　outperformed　the　ARIMA　model　as　a　more　reliable　and　accurate　tool　for　time　series　data　prediction.　The　method　developed　could　guide　economists　and　macroeconomic　policymakers　in　making　more　accurate　forecasts.　Copyright　©　2020　Inderscience　Enterprises　Ltd.