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Monetary Condition Index: Empirical Evidence from Pakistan

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The study focuses on assessing the Monetary Condition Index (MCI) in Pakistan, which measures the tightness or easiness of the country's monetary policy. It analyzes the impacts of interest rates and exchange rates on inflation and GDP growth, using time series data from 1975 to 2020. Monetary Condition Index is calculated by using time series data, employing annual data set from 1975 to 2020. Two different methods are applied to find the weights of interest rate and exchange rate, the one is the Principal Component Analysis and the other is co-integration method employing the Autoregressive Distributed Lag model. The research aims to provide valuable insights for policymakers, planners, and economists to optimize monetary policies and understand the transmission mechanism in the economy. The study also explores the historical impacts of interest rates and exchange rates, with potential implications for other economies. The Monetary Condition Index is introduced as a useful policy locator and an indicator of the monetary policy stance. Additionally, the research seeks to validate the MCI's reliability as a policy indicator and address certain research gaps related to its effectiveness, dynamics, and generalizability. The study concluded that the MCI is sensitive to variations, and its calculation and methodology are essential. The monetary stance in Pakistan remained tight from 2017 to 2020, representing the highest trend in history. However, the effectiveness of using interest rate tools to control inflation in Pakistan was questioned, suggesting that changes in monetary policy tools might be necessary to achieve the objectives of the State Bank of Pakistan in line with Islamic economics principles.
Title: Monetary Condition Index: Empirical Evidence from Pakistan
Description:
The study focuses on assessing the Monetary Condition Index (MCI) in Pakistan, which measures the tightness or easiness of the country's monetary policy.
It analyzes the impacts of interest rates and exchange rates on inflation and GDP growth, using time series data from 1975 to 2020.
Monetary Condition Index is calculated by using time series data, employing annual data set from 1975 to 2020.
Two different methods are applied to find the weights of interest rate and exchange rate, the one is the Principal Component Analysis and the other is co-integration method employing the Autoregressive Distributed Lag model.
The research aims to provide valuable insights for policymakers, planners, and economists to optimize monetary policies and understand the transmission mechanism in the economy.
The study also explores the historical impacts of interest rates and exchange rates, with potential implications for other economies.
The Monetary Condition Index is introduced as a useful policy locator and an indicator of the monetary policy stance.
Additionally, the research seeks to validate the MCI's reliability as a policy indicator and address certain research gaps related to its effectiveness, dynamics, and generalizability.
The study concluded that the MCI is sensitive to variations, and its calculation and methodology are essential.
The monetary stance in Pakistan remained tight from 2017 to 2020, representing the highest trend in history.
However, the effectiveness of using interest rate tools to control inflation in Pakistan was questioned, suggesting that changes in monetary policy tools might be necessary to achieve the objectives of the State Bank of Pakistan in line with Islamic economics principles.

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