Agglomeration Economies and Manufacturing Practices

Bloom, N. et. al. (ongoing). Manufacturing Practices in the Manufacturing Sector in Pakistan. International Growth Centre.

http://www.theigc.org/project/management-practices-in-the-manufacturing-sector-in-pakistan/
Recent literature shows surprising differences between and within developing and developed countries in firm level performance. Poor management practices are an important factor behind lower levels of development in Asia, Africa and Latin America, hampering the manufacturing sector’s ability to innovate, exploit new technologies and react to the challenges and opportunities of globalization. In partnership with the State Bank of Pakistan and the Pakistan Bureau of Statistics, the project undertakes the first rigorous empirical analysis of the determinants of management practices in a developing country by extending the large scale US Census Bureau Management and Organizational Practices Survey (Bloom, Brynjolfsson, Foster, Jarmin, Saporta-Eksten, and Van Reenen 2013) to Pakistan. The study aims to collect management data in 2,000 firms in Punjab, Pakistan. The focus is to document how firms are managed in Pakistan and whether their management practices vary with size, industry type, financials particulars and performance indicators. An analysis of firms in Pakistan will (1) identify the strengths and weaknesses in management practices in Punjab and explore ways in which firms in Pakistan can potentially emulate the development paths of firms in other Asian middle income countries, and (2) understand the mechanisms of firm upgrading through improved management quality and suggest stronger research and policy recommendations for stimulating growth.

Burki, A. A., & Khan, M. A. (2013). Agglomeration Economies and their Effects on Technical Inefficiency of Manufacturing Firms: Evidence from Pakistan. International Growth Centre.

http://www.theigc.org/project/agglomeration-economies-and-their-effects-on-productivity-and-efficiency-of-manufacturing-firms-evidence-from-pakistan/
The researchers suggest that different sectors respond differently to agglomeration economies. The textile and leather industries benefited from localization economies (that is, learning from other local firms in their own industry, also known as intra-industry spillovers), other sectors including food, beverage, tobacco, chemical, rubber and plastics were much more likely to benefit from urbanization economies (that is, learning from all firms in a district, regardless of sector, also known as inter-industry spillovers). Inter-industry learning includes information transfers, availability of infrastructure, and access to specialized business, information technology or financial services. The findings suggest that localization economies had previously been more prevalent in Pakistan, suggesting that firms did not adequately value the importance of technology spillovers and inter-industry learning, this pattern was changing. Over time a decrease in the value of localization economies was observed. The research uses the translog stochastic frontier and technical inefficiency effects model combined with cross-section data from Pakistan’s Census of Manufacturing Industries for 1995-96, 2000-01 and 2005-06 and provides evidence for industry agglomeration significantly benefiting firms. The research finds that 73.5% of industries in Pakistan are either highly or moderately agglomerated. The most highly concentrated industry is the ship-breaking industry, with the second most highly concentrated industry being the sports and athletic goods industry.

Gardezi, N. Z. (2013). Labor Pooling as a Determinant of Industrial Agglomeration. Center for Research in Economics and Business.

http://www.creb.org.pk/uploads/file/5fc29f0a5585da206c994d09b7c61c6eWorking Paper Series No. 04-13 Complete.pdf
This paper analyzes the agglomeration behavior exhibited by manufacturing firms and examines the sources of differences in Punjab, Pakistan. Drawing on an extensive and unique dataset comprising information on the location of manufacturing firms in Punjab, the authors construct an industry-specific measure of agglomeration by computing the geographical distance between pairs of firms. Such a distance-based framework has not been used in Pakistan and the recent literature confirms its superiority over measures based on discrete spatial units. The M-function computed in this study is based on the theoretical model proposed by Marcon and Puech (2009), and provides empirical evidence on the extent of agglomeration exhibited by each industry. The M function—the industry-level measure of concentration—is regressed on a number of industry characteristics that measure the presence of positive externalities. As a preliminary contribution, this paper provides evidence on the location pattern of industries in the Punjab. Using data on the names and addresses of all manufacturing firms in the 32 districts of Punjab, the authors compute the geographical coordinates of each firm. This allows them to map the firms in an industry and thus show cross-industry variations in the level of agglomeration or dispersion. In particular, a measure of each industry’s potential for labor pooling is used to determine whether firms that experience greater fluctuations in employment are likely to be more concentrated. The results provide evidence of the importance of labor pooling in explaining the high level of concentration within industries

Haroon, M. (2013). The Effects of Agglomeration on the Formation and Scale of Operation of New Firms. Center for Research in Economics and Business.

http://www.creb.org.pk/uploads/file/5fc29f0a5585da206c994d09b7c61c6eWorking%20Paper%20Series%20No.%2003-13%20complete.pdf
The formation of new firms is an important determinant of economic and regional development. The literature on industrial organization highlights agglomeration as one of the main factors enhancing the formation and scale of operation of new firms. The study’s aim is to analyze, first, whether the presence of similar manufacturing activity in a district fosters new firm formation; and, second, whether a concentration of different industries leads to the entry of new firms into a particular district. Using data from the Directory of Industries, this study estimates a model that determines the effect of local conditions on new firms’ formation and scale of operation in the manufacturing sector in Punjab, Pakistan. The findings indicate that firms derive benefits by locating in agglomerated regions, which induces firm entry to gain the benefits of agglomeration. Localization has a significant and positive impact on new firm formation, and this holds at all levels of localization. Additionally, new firm formation is higher in areas of medium-scale urbanization. The scale of operations of new entrants increases where large- or medium-scale firms belonging to the same industry are present. The scale of operations also tends to increase in areas of medium-scale urbanization. The authors find that average income has a significant and positive impact on arrival as well as on the scale of operations.

Nasir, M. (2013). Agglomeration and Firm Turnover. Center for Research in Economics and Business.

http://www.creb.org.pk/uploads/file/5fc29f0a5585da206c994d09b7c61c6eWorking%20Paper%20Series%20No.%2002-13%20Complete%20Final.pdf
The geographic and industrial concentration of firms affects firm turnover, as highlighted in research on industrial organization. This study conducts a firm-level analysis to determine the impact of agglomeration on firm entry and exit in domestic industries in Punjab, Pakistan for the year 2005-06. The authors use data from the Punjab Directory of Industries (available for 2002, 2006, and 2010) to analyze firms’ entry and exit rates. The study thus aims to contribute to the existing literature on industrial organization in Pakistan by assessing the impact of spatial and industrial concentration on the entry and exit rates of manufacturing firms in Punjab. The results conform to the existing literature, which finds that firm entry and exit is higher in more agglomerated industries, ceteris paribus. The study also illustrates how some industries exist in clusters while others are highly dispersed.