Academic Projects:
Exploring Total Factor Productivity: Constructing ARMA Models for US GDP Per Capita Time Series Analysis, 2023
Abstract
This project examines the Total Factor Productivity (TFP) of the USA using an ARMA (Auto-Regressive Moving Average) model to analyze and forecast its time series behavior. The objective is to determine the best-fitting ARMA model that captures the underlying trends and cyclical components in the data. Using GDP per capita (constant 2015 US$) from 1960 to 2022, the analysis follows a structured approach involving data extraction, filtering, visualization, and model estimation. Stationarity tests confirm the presence of a unit root, necessitating detrending through the Hodrick-Prescott (HP) filter. Autocorrelation and partial autocorrelation functions reveal seasonality in the residuals, guiding the selection of model parameters. Through an iterative approach, the ARMA(0,5) model is identified as the best fit based on the Akaike Information Criterion (AIC). The results provide insights into the long-term growth patterns of the U.S. economy and highlight the effectiveness of time series modeling in understanding productivity trends.
The Redistribution, Selection, and Trade by Miriam Kohl, 2023
Abstract
This project replicates the theoretical model from The Redistribution, Selection, and Trade by Miriam Kohl using Mathematica, under the guidance of Dr. Dibyendu Maiti at DSE (2023). The study analyzes the distributional effects of international trade and welfare policies, with a particular focus on how progressive income taxation shapes occupational choices and redistribution. By evaluating its impact on welfare and income inequality, the research offers insights into the broader implications of taxation for economic outcomes and social equity
Impact of awareness and financial stability on mental health treatment, 2022
Abstract
This study examines the impact of awareness and financial stability on mental health treatment, conducted under the guidance of Dr. Devesh Birwal at DSE (2022). A primary research survey was conducted using Google Forms, collecting responses from over 500 participants. A Logistic Regression Model was developed and implemented to assess the relationship between financial stability, awareness, and mental health treatment among students. The model demonstrated a 93% explanatory power, identifying pandemic-induced loneliness and traumatic events as key factors affecting student mental health. The findings highlight the critical role of these variables in shaping mental health outcomes, emphasizing the need for targeted interventions to address mental health challenges in academic settings.
Predicting the Auction Price of a Player (IPL), 2022
Abstract
This study examines the key factors influencing the auction price of IPL players, conducted under the guidance of Dr. Devesh Birwal at DSE (2022). Analyzing the past performance data of 149 batsmen, a Linear Regression model was developed to predict auction prices. The study identified runs scored and strike rate as significant determinants, emphasizing franchises' preference for high-scoring and aggressive players. A robustness check was performed by evaluating the role of numerologist ideology in player selection. The findings provide insights into the valuation of cricketers in professional leagues and the strategic considerations of IPL franchises.
Comparison between India and China, the two fastest-growing economies, 2022
Abstract
This project compares the economic and social trajectories of India and China, the two fastest-growing economies, using 25 years of data (1997–2021) from the World Bank. The research examines GDP growth across agriculture, industry, and service sectors, unemployment rates, GDP per capita trends, and key social indicators such as health expenditure and suicide mortality rates. The objective is to analyze the structural composition of economic growth in both countries and assess the potential correlations between economic performance and public health outcomes. The findings reveal a widening gap in GDP per capita growth between India and China over time, with China experiencing sustained industrial growth while India's economic expansion remains more sectorally balanced. Additionally, a positive correlation is observed between GDP per capita and suicide mortality rates in both nations, suggesting complex interactions between economic development and mental health. While increased health expenditure does not exhibit a straightforward relationship with suicide rates, India shows a tendency toward a positive association. These results highlight the need for a holistic policy approach that integrates economic growth strategies with mental health and social welfare initiatives to ensure sustainable development.