Small Stores, Big Obstacles: Understanding Constraints and Opportunities for Micro-retail Firms

Abstract

Micro and small enterprises (MSEs), particularly informal micro-retailers known as nanostores, play a vital role in developing economies but remain largely underserved by traditional financial institutions and overlooked in economic policy. In Mexico, nanostores account for more than 95% of businesses and over 10% of national employment, yet face high closure rates, low productivity, and limited access to formal credit. This thesis asks: What structural and contextual factors determine the survival and performance of nanostores, and how can policy better support high-potential firms within this segment? To answer this, the study constructs a longitudinal panel of nanostores using microdata from the Mexican Economic Census (2009, 2014, and 2019), and combines it with municipality-level contextual data including crime, infrastructure, unemployment, electricity costs, and business regulations. It applies survival models to estimate firm closure dynamics and implements a misallocation framework to quantify distortions in capital and labor usage. The results reveal that misallocation—particularly of capital—is pervasive and systematically linked to institutional weaknesses and credit access constraints. In response to the limited real-time data available for this sector, the thesis proposes the LIFT Performance Index, developed by the MIT Low-Income Firms Transformation Lab (MIT LIFT Lab), as a diffusion-based tool for monitoring micro-retailers’ business sentiments using structured operational surveys. A pilot implementation in Argentina demonstrates the index’s potential to generate timely and actionable insights for policymakers and private stakeholders. Overall, this work contributes a novel empirical foundation for understanding heterogeneity within the micro-retail sector and offers a scalable framework for designing targeted, data-driven interventions to support inclusive economic development.