The Working of Monetary Policy Transmission Mechanisms in Rwanda: An Econometric Analysis Using the Equilibrium Model

Nkikabahizi, Ferdinand; Hategekimana, Veneranda; Musabanganji, Edouard

doi:10.1007/978-981-15-5046-1_4

Cited by 1 publication

(1 citation statement)

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“…The economics literature has conflicting views on the monetary policy transmission mechanism (MPTM) (Zahid et al, 2021;Nkikabahizi, Hategekimana & Musabanganji, 2020). Consequently, several studies have analyzed foreign debt with various econometric techniques on panel, cross-sectional, and time-series data (Igharo et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing Various Channels of Monetary Policy Transmission Mechanism: The Case of Pakistan

Ghauri

Hamid

Zaman

2022

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This paper analyzes Pakistan's monetary policy transmission mechanism by considering these channels: Interest rate Channel, Credit Channel, and Risk channel. In this study, an innovative channel, Risk Channel, is introduced to measure its impact on the monetary policy transmission mechanism by covering the annual time data from 1995 to 2020for Pakistan. This paper aims to examine the long-run and the short-run relationship between foreign debt, bank capital, and monetary policy transmission mechanism. To fulfill this objective, we intended to use Autoregressive Distributed Lag (ARDL) model to investigate long-run and short-run relations. As per the result, the risk channel represents that it is not following the cointegration benchmark. The coefficient is negative, but the probability is more significant than 0.05, which is statistically insignificant; therefore, there is no long-run relationship between the model variables. The interest rate channel represents that it ensures the benchmark of cointegration as the coefficient is negative, but the probability is less than 0.05, which is statistically significant; therefore, there is a long-run relationship between variables for the model. The credit channel represents that it ensures the cointegration benchmark as the coefficient is negative and statistically significant at 90%; therefore, there is a long-run relationship between variables for the model. However, the study concluded that risk channel has short-term relation and interest rate& credit channels have short-term and long-term relationships.

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Section: Literature Reviewmentioning

confidence: 99%