TY - GEN AB - The aim of this paper is to demonstrate the relative performance of combining forecasts on inflation in the case of Tunisia. For that, we use a large number of econometric models to forecast short-run inflation. Specifically, we use univariate models as Random Walk, SARIMA, a Time Varying Parameter model and a suite of multivariate autoregressive models as Bayesian VAR and Dynamic Factor models. Results of forecasting suggest that models which incorporate more economic information outperform the benchmark random walk for the first two quarters ahead. Furthermore, we combine our forecasts by means and the finding results reveal that the forecast combination leads to a reduction in forecast error compared to individual models. AU - Zardi, Souhaïb Chamseddine CY - Geneva DA - 2017 DA - 2017 DO - 10.71609/iheid-77zd-vn31 DO - doi ID - 294973 L1 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf L1 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf?subformat=pdfa L2 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf L2 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf?subformat=pdfa L4 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf L4 - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf?subformat=pdfa LK - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf LK - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf?subformat=pdfa N2 - The aim of this paper is to demonstrate the relative performance of combining forecasts on inflation in the case of Tunisia. For that, we use a large number of econometric models to forecast short-run inflation. Specifically, we use univariate models as Random Walk, SARIMA, a Time Varying Parameter model and a suite of multivariate autoregressive models as Bayesian VAR and Dynamic Factor models. Results of forecasting suggest that models which incorporate more economic information outperform the benchmark random walk for the first two quarters ahead. Furthermore, we combine our forecasts by means and the finding results reveal that the forecast combination leads to a reduction in forecast error compared to individual models. PB - The Graduate Institute of International and Development Studies, International Economics Department PP - Geneva PY - 2017 PY - 2017 T1 - Forecasting inflation in a macroeconomic frameworkan application to Tunisia TI - Forecasting inflation in a macroeconomic frameworkan application to Tunisia UR - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf UR - https://repository.graduateinstitute.ch/record/294973/files/HEIDWP07-2017.pdf?subformat=pdfa Y1 - 2017 ER -