Central bank research hub - Papers by K. Barhoumi
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Research hub papers by author K. BarhoumienShort-Term Forecasting of GDP Using Large Monthly Datasets: A Presudo Real-Time Forecast Evaluation Exercise
http://www.lb.lt/wp2008_no_1
Bank of Lithuania Working Papers by G. Rünstler, K. Barhoumi, S. Benk, R. Cristadoro, A. Den Reijer, A. Jakaitiene, P. Jelonek, A. Rua, K. Ruth, C. Van NieuwenhuyzeShort-Term Forecasting of GDP Using Large Monthly Datasets: A Presudo Real-Time Forecast Evaluation Exercise2008-10-30T17:32:00ZThis paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best.Short-Term Forecasting of GDP Using Large Monthly Datasets: A Presudo Real-Time Forecast Evaluation ExerciseFull texthttp://www.lb.lt/wp2008_no_1 G. RünstlerChristophe Van NieuwenhuyzeK. BarhoumiA. RuaP. JelonekR. CristadoroS. BenkArd den ReijerK. RuthA. Jakaitiene G. Rünstler, K. Barhoumi, S. Benk, R. Cristadoro, A. Den Reijer, A. Jakaitiene, P. Jelonek, A. Rua, K. Ruth, C. Van Nieuwenhuyze2008-10Bank of Lithuania Working PapersC53E37Short-term forecasting of GDP using large monthly datasets - A pseudo real-time forecast evaluation exercise
http://www.nbb.be/doc/ts/publications/wp/wp133En.pdf
National Bank of Belgium Working Papers by K. Barhoumi, S. Benk, R. Cristadoro, A. Den Reijer, A. Jakaitiene, P. Jelonek, A. Rua, G. Rünstler, K. Ruth, C. Van NieuwenhuyzeShort-term forecasting of GDP using large monthly datasets - A pseudo real-time forecast evaluation exercise2008-06-30T12:37:00ZThis paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best.Short-term forecasting of GDP using large monthly datasets - A pseudo real-time forecast evaluation exerciseAbstracthttp://www.nbb.be/pub/06_00_00_00_00/06_03_00_00_00/06_03_05_00_00/WP_133.htmFull texthttp://www.nbb.be/doc/ts/publications/wp/wp133En.pdfG. RünstlerR. CristadoroP. JelonekK. BarhoumiK. RuthA. RuaA. JakaitieneS. BenkChristophe Van NieuwenhuyzeArd den ReijerK. Barhoumi, S. Benk, R. Cristadoro, A. Den Reijer, A. Jakaitiene, P. Jelonek, A. Rua, G. Rünstler, K. Ruth, C. Van Nieuwenhuyze2008-06-17National Bank of Belgium Working Papers