Research & Projects

This paper investigates whether and how employee-level factors influence firm performance across diverse industries. Drawing on firm-level survey data from multiple sectors, we employ fixed-effects panel regression models to estimate the causal impact of employee engagement, skill composition, and workplace practices on output and profitability. Our findings reveal significant heterogeneity: firms in knowledge-intensive sectors benefit disproportionately from workforce investments, while manufacturing firms show stronger returns to management practice improvements. We control for firm size, capital intensity, and market conditions, and conduct robustness checks using instrumental variable approaches. The results carry implications for human resource policy design and organizational strategy in…

This study examines the geographic distribution of productivity across regions using exploratory spatial data analysis and spatial econometric techniques. We construct a mock spatial dataset to illustrate how productivity clusters emerge, demonstrating the presence of spatial autocorrelation through Moran's I statistics and Local Indicators of Spatial Association (LISA). The analysis employs spatial lag and spatial error models to account for spillover effects between neighboring regions. Results show significant positive spatial autocorrelation, suggesting that productive regions tend to cluster together. We discuss how these spatial dependencies inform regional development policy, infrastructure investment decisions, and the design of place-based economic interventions.

This empirical note presents findings from a structured survey of student welfare demands across university campuses. Using a mixed-methods approach combining quantitative survey instruments with focus group discussions, we document the priority areas identified by students including hostel facilities, mental health support, library access, and gender-sensitive infrastructure. The analysis employs descriptive statistics and ordinal regression to identify demographic and socioeconomic predictors of welfare demand intensity. Our recommendations include establishing transparent feedback mechanisms, regular facility audits, and inclusive policy committees with student representation. The findings contribute to the growing literature on participatory governance in higher education institutions.