DefinePK

Abstract

This study aims to explore the impact of various socioeconomic factors on Pakistan's exchange rate using ARIMA (AutoRegressive Integrated Moving Average) modeling, a time-series forecasting technique. The results of this study suggest that socioeconomic variables, with GDP and broader development indicators, play a meaningful role in explaining fluctuations in the exchange rate. The findings from this study will offer valuable insights into the specific socioeconomic conditions that are most influential in shaping the Pakistani rupee's value. This study seeks to contribute to the existing literature by applying ARIMA modeling to measure the combined effect of these socioeconomics variables on the country's currency market. ARIMA (1, 1, 0) was identified as the most suitable based on model selection criteria including AIC, SIC, adjusted R-squared, and the significance of coefficients. The ARIMA model provides insights into underlying factors that contribute to fluctuations in exchange rates and highlights the importance of integrating macroeconomic fundamentals when designing exchange rate policies