Principal Component Analysis (PCA): A Multivariate Approach to Macroeconomic Indicators from Vizcarra to Sagasti During the Covid-19 Pandemic in Peru

Abstract

This study analyzes the impact of the political crisis in Peru during the transition of the governments of Martín Vizcarra and Francisco Sagasti in the context of the COVID-19 pandemic, focusing on key macroeconomic indicators. Using Principal Component Analysis (PCA), twelve relevant macroeconomic variables, such as Gross Domestic Product (GDP), exchange rate, and capital flows, were examined to identify the main underlying dimensions that affected the Peruvian economy between March 2020 and July 2021. The results reveal four main components that explain 90.60% of the total variance, highlighting the interrelationship between economic activity, foreign trade and capital flows in a context of political instability. The study emphasizes the resilience of economic institutions and their role in mitigating the effects of the crisis. The findings offer implications for public policymaking in multidimensional crisis situations, highlighting the importance of preserving institutional autonomy in adverse environments.