Image de Google Jackets
Vue normale Vue MARC vue ISBD

Introduction

Par : Type de matériel : TexteTexteLangue : français Détails de publication : 2005. Ressources en ligne : Abrégé : This research paper explores the role of unemployment in improving gross domestic product (GDP) growth forecasting reliability by using vector autoregressive (VAR) models, with a particular focus on mixed frequency Bayesian VAR (MF-BVAR) models. It also examines how key economic variables, which are largely employed by central banks, are included, such as GDP, money supply (M1), inflation, short-term interest rates, and unemployment. By incorporating unemployment data, the study aims to improve the accuracy of GDP forecasts. The findings highlight the significant impact of unemployment on economic indicators and the overall accuracy of the forecasting models. This research contributes to economic forecasting literature by demonstrating the value of considering labor market dynamics in predictive models and offers valuable insights for policymakers and economists. JEL classification: C53, E24, E58.
Tags de cette bibliothèque : Pas de tags pour ce titre. Connectez-vous pour ajouter des tags.
Evaluations
    Classement moyen : 0.0 (0 votes)
Nous n'avons pas d'exemplaire de ce document

83

This research paper explores the role of unemployment in improving gross domestic product (GDP) growth forecasting reliability by using vector autoregressive (VAR) models, with a particular focus on mixed frequency Bayesian VAR (MF-BVAR) models. It also examines how key economic variables, which are largely employed by central banks, are included, such as GDP, money supply (M1), inflation, short-term interest rates, and unemployment. By incorporating unemployment data, the study aims to improve the accuracy of GDP forecasts. The findings highlight the significant impact of unemployment on economic indicators and the overall accuracy of the forecasting models. This research contributes to economic forecasting literature by demonstrating the value of considering labor market dynamics in predictive models and offers valuable insights for policymakers and economists. JEL classification: C53, E24, E58.

PLUDOC

PLUDOC est la plateforme unique et centralisée de gestion des bibliothèques physiques et numériques de Guinée administré par le CEDUST. Elle est la plus grande base de données de ressources documentaires pour les Étudiants, Enseignants chercheurs et Chercheurs de Guinée.

Adresse

627 919 101/664 919 101

25 boulevard du commerce
Kaloum, Conakry, Guinée

Réseaux sociaux

Powered by Netsen Group @ 2025