A Singular Spectrum Analysis of Potential Output and Output Gap for the Indian Economy

Abstract

Estimating the output gap and potential output presents a perpetual challenge for policymakers. Model-based estimations can yield inconsistent results if the underlying assumptions fail to capture the economy’s true dynamics. Conversely, while statistical filters offer a rapid estimate of potential output, they can be susceptible to spurious cycles and end-of-sample bias. In this study, we employ both univariate and multivariate singular spectrum analysis (SSA) as statistical filters to estimate the potential output and output gap for the Indian economy. The output gaps estimated using both univariate and multivariate SSA methods show a strong correlation and demonstrate high co-movements in terms of directional changes with ‘capacity utilization’, the Reserve Bank of India’s survey-based measures of the sentiment of the manufacturing sector. Counterfactual potential GDP was compiled to gauge the impact of the COVID-19 pandemic and subsequent disruptions in the global supply chain. Our findings indicate that the pandemic has led to a decline in India’s potential output and potential losses as measured by the difference between estimated counterfactual potential growth and potential growth are 4.6 per cent, 3.8 per cent, 2.9 per cent and 1.8 per cent, respectively, during the financial years 2020–2021 to 2023–2024.

AMS Subject Classification: 62G05, 62H25, 62M10, 65C05, 62P20, 91B62