Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/33384
Title: | Forecasting unemployment rates in Malta : a labour market flows approach |
Authors: | Ellul, Reuben |
Keywords: | Unemployment -- Forecasting -- Malta Unemployment -- Mathematical models Labor market -- Malta Regression analysis |
Issue Date: | 2018 |
Publisher: | Central Bank of Malta |
Citation: | Ellul, R. (2018). Forecasting unemployment rates in Malta : a labour market flows approach. Central Bank of Malta WP/03/2018. |
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. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/33384 |
Appears in Collections: | 2018 |
Files in This Item:
File | Description | Size | Format | |
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Forecasting_unemployment_rates_in_Malta_a_labour_market_flows_approach_2018.pdf | 1.14 MB | Adobe PDF | View/Open |
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