Business location research often focuses on evaluating specific policies or explaining outcomes for a particular region. Further, the micro-foundations of random profit maximization supporting manufacturing location analysis often lack the intuitive nature of demand thresholds. While this article maintains these micro-foundations, it introduces a unifying concept of profit pools and examines how proximate supply/cost factors determine potential local manufacturing size. The approach avoids a number of limitations associated with other locational choice models. Restricted-access establishment-level data from the Longitudinal Business Database along with secondary data sources produce a model to estimate county-level contributors to outcomes of manufacturing establishment growth and consolidation. The analysis offers improved methods and accuracy for modeling establishment location outcomes, including accuracy in measuring industry size and methods for choosing among various count data distributions. The locational factors associated with county-level potential for manufacturing vary in magnitude and significance depending on the type of manufacturing, while affirming the importance of agglomeration across manufacturing types.

营业地点研究通常侧重于评估特定政策或解释特定地区的结果。此外，支持制造位置分析的随机利润最大化微观基础往往缺乏需求阈值的直观性。虽然本文保留了这些微观基础，但它引入了利润池的统一概念，并研究了近似供应/成本因素如何决定潜在的本地制造规模。该方法避免了与其他位置选择模型相关的许多限制。来自纵向业务数据库的受限访问企业级数据以及辅助数据源生成了一个模型，用于估计县级对制造业企业增长和整合结果的贡献者。该分析为建立场所结果建模提供了改进的方法和准确性，包括测量行业规模的准确性以及在各种计数数据分布中进行选择的方法。与县级制造业潜力相关的区位因素因制造业类型而异，但同时肯定了跨制造业集聚的重要性。