A Comparative Analysis of GDP Growth: Manmohan Singh vs. Narendra Modi — Part 1
The debate surrounding the economic performance of different governments often takes center stage in political discourse. In India, the administrations of Manmohan Singh and Narendra Modi have been pivotal in shaping the country’s economic landscape. To shed light on this debate, I conducted an analysis comparing GDP growth during the UPA regime (2004–2014) under Manmohan Singh and the NDA regime (2014–2022) under Narendra Modi.
Analyzing the Data
My analysis began by gathering GDP data from the World Bank for the years 2004 to 2022. I calculated GDP growth (GDP percentage change between two consecutive years) rates for each year within these two regimes, aiming to offer an objective comparison.
Simulated GDP Scenarios
To provide a unique perspective, I simulated two scenarios: one where the GDP growth rates during the UPA regime followed those of the NDA regime and vice versa. The results were intriguing.
I found that the actual GDP at the end of 2012 and not 2014 (since there are only 8 years of GDP data for NDA regime 2014–2022) was 55 percent higher than the simulated GDP if it had followed the growth rate of the NDA government. Conversely, the actual GDP at the end of 2022 was 35 percent lower than the simulated GDP if it had followed the growth rate of the UPA government. These findings raise important questions about the true impact of these two regimes on India’s economic growth.
Accounting for Extraordinary Events
Critics argue that both governments faced unprecedented economic challenges. The Manmohan Singh government grappled with the global economic recession of 2008, while the Modi government faced the COVID-19 pandemic in 2022. To address these concerns, I employed bootstrapping (non-parametric) and Monte Carlo simulations (parameteric).
Bootstrapping involves creating multiple random samples from the existing data without assuming any underlying distribution (let the data speak for itself). I generated 1000 simulations to account for potential economic catastrophes conservative scenario. This approach was valuable because it allowed me to account for the uncertainty and variability in the data. Economic growth is influenced by numerous factors, and bootstrapping helps capture the range of possible outcomes, including those influenced by unforeseen events like recessions or pandemics.
In addition to utilizing bootstrapping, I also utilized Monte Carlo simulations as a conservative approach. Monte Carlo simulations entail the generation of multiple random scenarios, relying on presumed probability distributions. In this particular instance, I made an assumption of a Gaussian distribution for GDP percentage changes. However, it’s worth noting that I assigned limited significance to this assumption, as the growth rate of the gross domestic product (GDP) typically exhibits characteristics such as heteroscedasticity, asymmetry, and fat-tails [Hassan, 2016].
The simulations produced interesting outcomes. In both scenarios, although the GDP trajectory during the UPA regime slightly exceeded expectations, the actual GDP at the end of 2022 (3.39 T USD) fell below what was anticipated: 3.77 T USD from bootstrapped simulations and 3.84 T USD from Monte Carlo simulations.
Hypothesis Testing
To rigorously test the hypothesis that GDP growth during the Modi regime was better than that during the Manmohan Singh regime, I performed hypothesis testing. However, even with bootstrapped hypothesis testing and two-sampled t test, I failed to reject the null hypothesis, as the p-value were 0.87, 0.27 respectively. This indicates that there is not enough evidence to conclude that one regime’s GDP growth was significantly better than the other’s.
Conclusion
Comparing the economic performance of the Manmohan Singh and Narendra Modi regimes is a complex task. My analysis, which considered both actual GDP data and simulated scenarios, suggests that while the UPA government may have had a slightly better GDP trajectory, the Modi government faced significant challenges that impacted the final GDP figures.
It is important to acknowledge that numerous factors, including global economic conditions and domestic policies, influence GDP growth. The COVID-19 pandemic and the 2008 recession are just two examples of external shocks that can have profound effects on an economy.
Also it is important to compare India’s GDP growth to the global economy during the Manmohan Singh and Narendra Modi governments as it would provide insights into economic alignment, stability, investor confidence, and policy effectiveness. It helps assess whether India’s performance was in sync with global trends and informs policymakers about the impact of their decisions on the international stage. I present this analysis in the next article.
Ultimately, a comprehensive evaluation of economic performance should consider a wide range of factors beyond GDP growth alone. It is crucial to engage in nuanced discussions that take into account the complexities of economic governance and the unique challenges each government faced during its tenure.
You can find the analysis notebook here .
References:
Ul Hassan, M., & Stockhammar, P. (2016). Fitting probability distributions to economic growth: a maximum likelihood approach. Journal of Applied Statistics, 43(9), 1583–1603.