Abstract:PurposeThis paper empirically investigates the effect of economic policy uncertainty (EPU) on the UK money demand stability during the inter-war period (1920–1938). Both a narrow definition (M0) and a broad definition (M3) of money are investigated.Design/methodology/approachThe empirical investigation is conducted by employing the autoregressive distributed lag (ARDL) bounds testing approach to cointegration.FindingsResults presented indicate a stable demand for both definitions of money only when EPU is incl… Show more
“…This implies that GDP-CPI nexus of UK is greatly vulnerable to GEPU relative to country-specific EPU but responds largely to country-specific GPR than global GPR. Knowing that uncertainty indices have a large impact also on inflation dynamics in UK [ 59 , 65 ], the stronger conditional influence of these uncertainties on the GDP-CPI nexus is not surprising. Fig.…”
“…This implies that GDP-CPI nexus of UK is greatly vulnerable to GEPU relative to country-specific EPU but responds largely to country-specific GPR than global GPR. Knowing that uncertainty indices have a large impact also on inflation dynamics in UK [ 59 , 65 ], the stronger conditional influence of these uncertainties on the GDP-CPI nexus is not surprising. Fig.…”
“…In the setting of the Markov switching VAR model, they reveal that the effect of uncertainty on money demand seems to be greater in times of high uncertainty. Choudhry (2023) finds for the UK that uncertainty is indispensable for the stability of the money demand function and negatively affects the M0 and M3 aggregates. Khan et al (2023) study the impact of different forms of uncertainty (economic uncertainty, stock market uncertainty and monetary uncertainty) on the demand for money in India using quarterly data for the period 2003-2019.…”
The aim of this paper is to investigate the long run effect of policy uncertainty on money demand for Central African Economic and Monetary Community (CEMAC) countries over the period 1985-2017. We consider a more inclusive measure of policy uncertainty that encompass uncertainty related to economic and political events. Our measure of policy uncertainty is taken from the World Uncertainty Index (WUI) developed by the Policy Uncertainty Group. To estimate the money demand function, we employs panel data estimators that address issues of cross-sectional dependence and parameter heterogeneity. The estimates establish evidence of the long-run relationship between money demand and its determinants. It appears that the demand for domestic money increases with real income meanwhile decreases with the inflation rate. And so, the opportunity cost of holding money is reflected in the rate of inflation. The results associated to the exchange rate show that currency substitution does not hold in the long-run for the sample considered. The most important result is that policy uncertainty has an adverse long-term effect on money demand for CEMAC countries. Our results are robust to alternative panel estimation approaches. Thus, increased uncertainty leads people to hold less cash, while decreased uncertainty leads them to hold more cash.
“…ARDL, by incorporating lagged values of the variables, can help address endogeneity to some extent (Voumik & Ridwan, 2023). ARDL allows for the inclusion of both I(0) and I(1) variables, meaning it can handle a mix of stationary and non-stationary time series (Choudhry, 2023). This is useful when constructing an MCI that comprises variables with different integration orders (e.g., interest rates as stationary and inflation as non-stationary).…”
Section: Theoretical Implication Of Ardlmentioning
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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