Analyzing Inflation Dynamics in Ghana: Evidence as of Quantile Autoregressive Model
Publish place: International Journal of Management, Accounting and Economics (IJMAE)، Vol: 7، Issue: 10
Publish Year: 1399
Type: Journal paper
Language: English
View: 141
This Paper With 22 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
JR_IJMAE-7-10_001
Index date: 1 November 2023
Analyzing Inflation Dynamics in Ghana: Evidence as of Quantile Autoregressive Model abstract
Inflation persistence (or inertia) has been a problem in many developing countries and due to the relationship between inflation and economic growth, much research has been conducted on the literature to study closely these macroeconomic variables in developing countries (Brick, 2010; Gokal and Hanif, 2004). This paper however made use of a superior method known as quantile autoregressive model proposed by Koenker and Xiao (2006) to estimate the persistence of inflation, the dynamic behavior and examine how diverse shocks may perhaps affect the rate of inflation within different quantiles. The data employed in this study is the monthly year-on-year Ghana inflation rate from January 2000 to July 2019. The result shows that Ghana inflation rates exhibits low persistence at both lower and higher quantiles and a mean reversion behavior across quantiles. Also, we observe that Ghana inflation rate is globally stationary as well as portraying non-stationary behavior in about 10% of the sampled observations. Evidently, the results again reveal that Ghana inflation rate has irregular characteristics at different quantiles in its conditional distribution. Also, there is a bidirectional relationship between Ghana overall inflation rate and its components (food and non-food inflation).
Analyzing Inflation Dynamics in Ghana: Evidence as of Quantile Autoregressive Model Keywords:
Analyzing Inflation Dynamics in Ghana: Evidence as of Quantile Autoregressive Model authors
Patrick Gbolonyo
College of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, ۳۱۰۰۱۸, China
Gideon Boyetey
College of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, ۳۱۰۰۱۸, China
Xiaorong Yang
College of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, ۳۱۰۰۱۸, China
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :