Economic geography and misallocation in Pakistan’s manufacturing hub


In this article, we explore whether localization of industries can reduce economic distortions and dispersion in total factor productivity (TFP) among firms in Punjab, Pakistan’s largest province economically. We consider two types of misallocation: (i) dispersion in the distribution of output-based TFP (TFPQ), in particular the survival of low productivity firms in the left tail; and (ii) dispersion in revenue-based TFP (TFPR), indicative of allocative inefficiency. The results are mixed: On the one hand, we find that the distribution of TFPQ is less dispersed in more agglomerated areas, measured by the localization quotient, local productive concentration, and average firm size. At the same time, we find that average TFPQ is also positively related to localization, especially the presence of small firms in the same sector, even though own-firm TFP is lowest for small firms. On the other hand, we do not find evidence that agglomeration improves allocative efficiency measured as deviations in TFPR from the sector average, concluding rather that greater localization of small firms is associated with firms being more output and capital constrained.

This is a preview of subscription content, log in to check access.

Fig. 1

Source: Authors’ calculations based on CMI Punjab, 2005–2006, trimmed data

Fig. 2

Source: Authors’ calculations based on CMI Punjab, 2005–2006, trimmed data


  1. 1.

    Migration restrictions, such as those facing both labor and firms in China, can lead to firms losing out from scale and agglomeration economies (Au and Henderson 2006).

  2. 2.

    TFPR is proportional to a ratio of output and capital distortions (see Hsieh and Klenow 2009, p. 1410).

  3. 3.

    The findings of the existing empirical literature on agglomeration have largely documented that agglomeration, in the form of localization and/or urbanization, enhances the productivity of firms (Andersson and Lööf 2011; Ehrl 2013; Henderson 1986, 2003; Hu et al. 2015; Henderson et al. 1995; Hansen 1990; Hanson 1996, 1997). On the other hand, other aspects of agglomeration might lower productivity, for example, if congestion sets in, or if firms in agglomerated sectors remain small and, due to their large number, are unable to achieve economies of scale. According to Shaver and Flyer (2000), localization economies disproportionately enhance the competitiveness of weak firms possibly at the expense of stronger firms, leading the latter to avoid concentrated areas. Folta et al. (2006) find diminishing returns to agglomeration as a cluster grows. Spatial proximity, by facilitating communication among firms, may even enable non-competitive behavior such as collusion. Evidence from Chinese manufacturing firms reveals non-competitive pricing in industrial clusters (Brooks, Kaboski and Li).

  4. 4.

    Duranton (2015) survey of the current literature does not identify any strong evidence to date that productivity growth in urban areas is responsive to higher rates of entry and exit.

  5. 5.

    We lack the panel data for firms in Pakistan required to apply semiparametric methods such as Olley and Pakes (1996) and Levinsohn and Petrin (2003), or generalized methods of moments (GMM) dynamic panel models.

  6. 6.

    Discussions with the agency responsible for collecting the data indicate that the sample is skewed toward smaller units in the sampling frame. After dropping cotton-ginning activities (as it is no longer considered a manufacturing activity according to most international studies), the raw data set is left with just over 3000 firms.

  7. 7.

    According to Hsieh and Klenow (2009), an output distortion is observed where the labor share is different from the elasticity of output with respect to labor and a capital distortion is observed where the ratio of a plant’s wage bill to its capital stock differs from the ratio of the respective output elasticities.

  8. 8.

    The data requirements include labor compensation, nominal output (revenue), expenditures on input materials and energy, book value of capital, and the industry level cost shares for labor and capital. Details of calculations of the firm-level TFPQ and TFPR in Pakistan can be found in Haseeb and Chaudhry (2014).

  9. 9.

    Punjab’s districts were ranked by their location quotient and divided into quartiles. The firms in those districts in each quartile of agglomeration were included in the distribution. For example, the firms in districts considered most agglomerated were included in the distribution for “very highly agglomerated” areas.

  10. 10.

    That dispersion in TFPR is in general less than that for TFPQ is an expected result since firms that are more productive (with higher \(A_{si}\) or TFPQ), should be producing more output at lower prices (Hsieh and Klenow 2009).

  11. 11.

    Like our Eq. (12), Kalemli-Ozcan and Sørensen (2014) have used the log value of the Hsieh and Klenow capital distortion in a regression analysis, but they were not examining the role of agglomeration but rather institutional failures in Africa.

  12. 12.

    For example, the small firm location quotient is defined as (employees of small firms in region x and industry y)/(total employees in industry y). Small firms are defined as firms with less than 10 workers, medium size as firms with 10–49 workers, and large firms having employment level greater than 49 workers.

  13. 13.

    Reed (2015) has suggested that instrumenting current values with lagged values may be a better solution to simultaneity than using lagged values alone.

  14. 14.

    We include district dummies in most specifications to control for levels of infrastructure and human capital and proximity to markets.

  15. 15.

    Examples of where large vendor segments support clusters include electric fans in Gujrat/Gujranwala and surgical goods in Sialkot.


  1. Andersson M, Lööf H (2011) Agglomeration and productivity: evidence from firm-level data. Ann Reg Sci 46(3):601–620. doi:10.1007/s00168-009-0352-1

    Article  Google Scholar 

  2. Atkin A, Chaudhry A, Chaudry S, Khandelwal A, Verhoogen E (2015) Mark-up and cost dispersion across firms: direct evidence from producer surveys in Pakistan. Am Econ Rev Pap Proc 105(5):537–544. doi:10.1257/aer.p20151050

    Article  Google Scholar 

  3. Au CC, Henderson JV (2006) How migration restrictions limit agglomeration and productivity in China. J Dev Econ 80(2):350–388. doi:10.1016/j.jdeveco.2005.04.002

    Article  Google Scholar 

  4. Banerjee A, Duflo E (2005) Growth Theory through the Lens of Development Economics. In: Durlauf S, Aghion P (eds) Handbook of economic growth, vol 1A. Elsevier Science Ltd, North Holland, pp 473–552

    Google Scholar 

  5. Beaudry C, Schiffauernova A (2009) Who’s right, Marshall or Jacobs? The localization versus urbanization debate. Res Policy 38:318–337. doi:10.1016/j.respol.2008.11.010

    Article  Google Scholar 

  6. Brooks WJ, Kaboski JP, Li, YA (2016) Growth policy, agglomeration, and (the lack of) competition (No. w22947). National Bureau of Economic Research. doi:10.3386/w22947

  7. Cingano F, Schivardi F (2004) Identifying the sources of local productivity growth. J Eur Econ Assoc 2(4):720–744

  8. Chen K, Irarrazabal A (2015) The role of allocative efficiency in a decade of recovery. Rev Econ Dyn 18(3):523–550. doi:10.1016/

    Article  Google Scholar 

  9. Combes PP, Magnac T, Robin JM (2004) The dynamics of local employment in France. J Urban Econ 56(2):217–243. doi:10.1016/j.jue.2004.03.009

    Article  Google Scholar 

  10. Combes PP, Duranton G, Gobillon L, Puga D, Roux S (2012) The productivity advantages of large cities: distinguishing agglomeration from firm selection. Econometrica 80(6):2543–2594. doi:10.3982/ECTA8442

    Article  Google Scholar 

  11. Desmet K, Ghani E, O’Connell S, Rossi-Hansberg E (2015) The spatial development of India. J Reg Sci 55(1):10–30

    Article  Google Scholar 

  12. Duranton G (2015) Growing through cities in developing countries. World Bank Res Obs 30(1):39–73

  13. Ehrl P (2013) Agglomeration economies with consistent productivity estimates. Reg Sci Urban Econ 43(5):751–763. doi:10.1016/j.regsciurbeco.2013.06.002

    Article  Google Scholar 

  14. Folta TB, Cooper AC, Baik YS (2006) Geographic cluster size and firm performance. J Bus Ventur 21(2):217–242. doi:10.1016/j.jbusvent.2005.04.005

    Article  Google Scholar 

  15. Glaeser EL, Kallal HD, Scheinkman JA, Schleifer (1992) Growth in cities. J Polit Econ 100(6),1126–1152.

  16. Graham DJ (2009) Identifying urbanisation and localisation externalities in manufacturing and service industries. Pap Regional Sci 88(1):63–84

  17. Graham D, Melo P, Jiwattanakulpaisarn P, Noland R (2010) Testing for causality between productivity and agglomeration economies. Reg Sci 50(5):935–951. doi:10.1111/j.1467-9787.2010.00676.x

    Article  Google Scholar 

  18. Greenstone M, Hornbeck R, Moretti E (2010) Identifying agglomeration spillovers: evidence from winners and losers of large plant openings. J Polit Econ 118(3):536–598. doi:10.1086/653714

    Article  Google Scholar 

  19. Government of the Punjab (2015) Punjab Industries Sector Plan 2018: Promoting Industrial Development and Investment, Planning & Development Department, supported by International Growth Centre, UK

  20. Hansen ER (1990) Agglomeration economies and industrial decentralization: the wage–productivity trade-offs. J Urban Econ 28(2):140–159. doi:10.1016/0094-1190(90)90047-Q

    Article  Google Scholar 

  21. Hanson GH (1996) Localization economies, vertical organization, and trade. Am Econ Rev 86(5):1266

    Google Scholar 

  22. Hanson GH (1997) Increasing returns, trade and the regional structure of wages. Econ J 113–133.

  23. Haroon M, Chaudhry AA (2014) Where do new firms locate? The effects of agglomeration on the formation and scale of operations of new firms in Punjab. Economics Discussion Papers, No 2014–2021, Kiel Institute for the World Economy

  24. Haseeb M, Chaudhry TT (2014) Resource misallocation and aggregate productivity in Punjab (no. 1-2014). Centre for Research in Economics and Business, The Lahore School of Economics

  25. Henderson JV (1986) Efficiency of resource usage and city size. J Urban Econ 19(1):47–70. doi:10.1016/0094-1190(86)90030-6

    Article  Google Scholar 

  26. Henderson V, Kuncoro A, Turner M (1995) Industrial development in cities. J Polit Econ 103(5):1067–1090. doi:10.1086/262013

    Article  Google Scholar 

  27. Henderson V (2003) The urbanization process and economic growth: the so-what question. J Econ Growth 8(1):47–71. doi:10.1023/A:1022860800744

    Article  Google Scholar 

  28. Hsieh CT, Klenow PJ (2009) Misallocation and manufacturing TFP in China and India. Q J Econ 124(4):1403–1448. doi:10.1162/qjec.2009.124.4.1403

    Article  Google Scholar 

  29. Hu C, Xu Z, Yashiro N (2015) Agglomeration and productivity in China: firm level evidence. China Econ Rev 33(2015):50–66. doi:10.1016/j.chieco.2015.01.001

    Article  Google Scholar 

  30. Inklaar R, Lashitew AA, Timmer MP (2015) The role of resource misallocation in cross-country differences in manufacturing productivity. Forthcoming in Macroeconomic Dynamics

  31. Levinsohn J, Petrin A (2003) Estimating production functions using inputs to control for unobservables. Rev of Econ Stud 70(2):317–341

  32. Kalemli-Ozcan S, Sørensen BE (2014) Misallocation, property rights, and access to finance: evidence from within and across Africa. In: African Successes: Modernization and Development, vol 3. University of Chicago Press, Chicago

  33. Martin P, Mayer T, Mayneris F (2011) Spatial concentration and plant-level productivity in France. J Urban Econ 69(2):182–195

  34. Nasir M (2013) Agglomeration and firm turnover (No. 2-2013). Centre for Research in Economics and Business, The Lahore School of Economics

  35. Naveed R (2015) Relative factor abundance and relative factor price equality in Punjab. Lahore J Econ 20(1):105–133

    Google Scholar 

  36. Olley GS, Pakes A (1996) The dynamics of productivity in the telecommunication equipment industry. Econometrica 64(6):1263–1297

  37. Pakistan Bureau of Statistics (2009) Census of manufacturing industries 2005–2006: executive summary. Islamabad (industry_mining_and_energy/publications/cmi200506/Executive_Summary.pdf). Accessed 31 August 2015

  38. Shaver JM, Flyer F (2000) Agglomeration economies, firm heterogeneity, and foreign direct investment in the United States. Strateg Manag J 21(12):1175–1194.

  39. Siba E, Söderbom M, Bigsten A, Gebreeyesus M (2012) Enterprise agglomeration, output prices, and physical productivity: firm-level evidence from Ethiopia. WIDER working paper no. 2012/85

  40. Syverson C (2011) What determines productivity? J Econ Lit 49(2):326–365. doi:10.1257/jel.49.2.326

    Article  Google Scholar 

  41. Tirmazee Z (2012) Relative wage variation and industry location within districts of Punjab. Dissertation, Lahore School of Economics, mimeo

  42. Vollrath D (2009) How important are dual economy effects for aggregate productivity? J Dev Econ 88(2):325–334. doi:10.1016/j.jdeveco.2008.03.004

    Article  Google Scholar 

  43. World Bank (2009) World development report 2009: reshaping economic geography. The World Bank, Washington, DC

Download references

Author information



Corresponding author

Correspondence to Theresa Chaudhry.



See Table 8.

Table 8 Kolmogorov–Smirnov tests for the equality of distributions by level of agglomeration

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chaudhry, T., Haseeb, M. & Haroon, M. Economic geography and misallocation in Pakistan’s manufacturing hub. Ann Reg Sci 59, 189–208 (2017).

Download citation

JEL Classification

  • D24
  • R12
  • L11
  • L25
  • L6