Scholarlink

<p>The study investigates the various reasons for the persistent firms’ agglomeration in Punjab to understand if technological advancement and other external economies are driving such clustering. We first quantify agglomeration through the Ellison-Glaeser (EG) index and find evidence that firms choose to cluster in a select few districts only. However, the existing literature lacks comprehensive analysis on the specific microeconomic factors and natural advantages driving this agglomeration, particularly in developing regions such as Punjab. Our results indicate that <i>knowledge spillovers</i> significantly increase industrial concentration with a coefficient of 0.0033. <i>Labor pooling</i> also shows a significant effect, where a unit increase in labor force concentration decreases the EG index by 0.0152. <i>Scale economies</i> exhibit a notable impact with a coefficient of − 0.2496. We find evidence that a key factor for narrow clustering is the <i>natural advantages</i> of energy, resources, and water available in select areas. However, evidence on input sharing is weak, and transportation costs show mixed results in affecting agglomeration. We also find that the past pattern of industrial agglomeration has an important influence on the current location decisions of firms; one reason for this is that the spatial diversification policies of the government on manufacturing location have not been successful rather they have contributed to agglomeration. The study adds to our understanding why manufacturing clusters in a few districts in Punjab, offering lessons for other developing economies with similar geography or industrial policies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Knowledge Spillovers, Labor Pooling, and Firms’ Agglomeration: A Case Study of Pakistan

  • 期刊论文

  • 发表日期：

    2025年1月10日

查看全文
  • Asim Iqbal,
  • Anjum Siddiqui

摘要

The study investigates the various reasons for the persistent firms’ agglomeration in Punjab to understand if technological advancement and other external economies are driving such clustering. We first quantify agglomeration through the Ellison-Glaeser (EG) index and find evidence that firms choose to cluster in a select few districts only. However, the existing literature lacks comprehensive analysis on the specific microeconomic factors and natural advantages driving this agglomeration, particularly in developing regions such as Punjab. Our results indicate that knowledge spillovers significantly increase industrial concentration with a coefficient of 0.0033. Labor pooling also shows a significant effect, where a unit increase in labor force concentration decreases the EG index by 0.0152. Scale economies exhibit a notable impact with a coefficient of − 0.2496. We find evidence that a key factor for narrow clustering is the natural advantages of energy, resources, and water available in select areas. However, evidence on input sharing is weak, and transportation costs show mixed results in affecting agglomeration. We also find that the past pattern of industrial agglomeration has an important influence on the current location decisions of firms; one reason for this is that the spatial diversification policies of the government on manufacturing location have not been successful rather they have contributed to agglomeration. The study adds to our understanding why manufacturing clusters in a few districts in Punjab, offering lessons for other developing economies with similar geography or industrial policies.