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  -