Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/210825 
Authors: 
Year of Publication: 
2018
Series/Report no.: 
CBM Working Papers No. WP/03/2018
Publisher: 
Central Bank of Malta, Valletta
Abstract: 
This study extends the flow approach to forecasting unemployment, as carried out by Barnichon and Nekarda (2013) and Barnichon and Garda (2016), to the Maltese labour market using a wider number of estimating techniques. The flow approach results in significant improvements in forecast accuracy over an autoregressive (AR) process. Particular improvements to forecasting accuracy are returned over shorter time horizons. When including flows, forecast improvements over both an AR process and non-flow forecasts are found when applying VECM methods. Bayesian and OLS VARs also show strong improvements over an AR, with or without the inclusion of flows. For Maltese data, the use of flows computed using aggregate data in these two latter methodologies does not bring about a significant improvement over the forecasts which exclude them.
JEL: 
E24
E27
J64
Document Type: 
Working Paper

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