A Vector Autoregression Analysis of Corruption, Unemployment, and Foreign Direct Investment Outflows in Sudan

Abstract

This study examines the dynamic interrelationships between corruption, unemployment, and foreign direct investment FDI outflows in Sudan using a Vector Autoregression (VAR) model. The objective is to explore how corruption influences both unemployment and FDI outflows, and the combined impact of these variables on Sudan's economic performance. The importance of this research lies in its potential to address economic policy and institutional reforms in Sudan, a country marked by ongoing political instability and economic challenges. The study draws upon existing literature that shows how corruption increases transaction costs, deters foreign investment, and misallocates public resources, thus contributing to higher unemployment. The VAR model is applied using time-series data from 2003 to 2023, focusing on key variables such as the Corruption Perceptions Index (CPI), unemployment rates, and FDI outflows. The results reveal that corruption significantly contributes to FDI outflows and has a long-term negative impact on unemployment. The study emphasises the critical role of governance in shaping both investment behaviour and labour market outcomes. The findings advocate for stronger institutional frameworks and anti-corruption measures to create a more attractive business environment, reduce unemployment, and prevent further capital flight. These insights offer valuable guidance for policymakers and international organisations seeking to promote sustainable economic development in Sudan.