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320 Spinning and weaving of cotton & wool 0.0340134 0.049388 0.031043 323 Leather and leather products 0.0953683 0.050376 0.0288 These results are further corroborated by the declining mean values of the geographic concentration levels. Table 4.14 reports the mean values of industrial concentration across 3-digit industries in Punjab. The mean value of EG index remained roughly constant from 1995-96 to 2000-01, but the index drastically fell by about 33% in the next five years. The decline in industrial concentration is mainly explained by the decline in raw concentration measure (Gini index), and the change in average plant size measured by the Herfindahl index is less important in explaining Table 4‐14: Mean values of industrial concentration measures overtime Concentration measure Concentration in Punjab 1995-96 2000-01 2005-06 Ellison-Glaeser index 0.1833 0.1789 0.1189 Gini index 0.2794 0.2656 0.2186 Herfindahl index 0.1465 0.1406 0.1374 Survey Year 2000-01 0.8626 Correlation of EG index 2005-06 0.7820 0.7873 the decline in industrial concentration. The correlation coefficient of the EG index further corroborates these results, which indicates a declining trend in the dynamic industrial concentration levels in Punjab across industries. It reveals that the correlation coefficient of EG index between 1995-96 and 2000-01 was 0.86, which fell to 0.79 between 2000-01 and 2005-06. It suggests that the agglomeration of industries followed a declining trend overtime. 4.3.6 Localization versus Urbanization Externalities Localization and urbanization externalities are related to local scale externalities that arise from local information spillovers linked with input and output markets and local technological developments. If firms in a district learn from local firms in their own industry, this is called localization externalities; if firms learn from all firms in the 337
district, it is termed as urbanization economies [Henderson et al. (2001)]. While several urban areas dominate in Pakistan, the relative strength of “localization economies” versus “urbanization economies” is not known. In the present age, there is a greater role for information spillovers leading to greater cross-industry learning economies. These relationships and bonding may explain presence of mega industries around large cities. Moreover, if these externalities are dynamic, then one may expect that presence of industry at a location in the past would affect productivity today. In these cases, industry would be unwilling to move to far off regions where there is no “built-up stock of knowledge” that makes diversification of industries more and more difficult. We follow Henderson et al. (2001) to measure the scale of local externalities by a diversity index written as ∑ ( ) ( ) 2 s N i = n= 1 in i − n g ⎡⎣ E E E E ⎤⎦ where i and n index district and industry, respectively, g is the index of localization and urbanization economies in ith district, E n is for employment in industry n, E is for total national manufacturing employment, and Ei is for employment in ith district and Ein is for employment in ith district in nth industry. A lower value of s i s g i (minimum value is zero) would imply that the city is non-specialized (high diversity) while a higher value (approaching two) would indicate complete specialization. In other words, as s gi goes up specialization increases and the diversity tends to fall. Henderson et al. (2001) find a negative relationship between s gi and productivity in Korea. As before, we use CMI data of Punjab for 1995-96, 2000-01 and 2005-06 and calculate localization and urbanization index of 3-digit industries for 29 districts of Punjab. In Table 4.15 we show localization versus urbanization externalities across districts. Our results suggest that localization economies are much greater in magnitude than urbanization economies since the diversity index has higher values for most of the districts with a mean of 0.253 in 1995-96. It shows that there is a greater role for within- 338
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INDUSTRIAL POLICY, ITS SPATIAL ASPE
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Table of Contents List of Tables ..
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3.3.13 Fisheries Sector ...........
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List of Tables Chapter 2 Table 2‐
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List of Figures Chapter 2 Figure 2
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Figure 4‐12: Spatial inequality i
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Acronyms and Abbreviations ADR Alte
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Acknowledgements This study has bee
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percent average GDP growth rate, th
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Development Fund and a Skill based
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knowledge based industries such as
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Therefore, we recommend specific ty
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manufacturing industries is widespr
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• Expansion of the tax base by in
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• In special economic zones, scie
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which could cross from Iranian to P
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• Provide infrastructure of the p
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transaction cost of smuggling and r
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Accordingly, the government should
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information flows between the train
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etc., that operate outside the form
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In view of the credit problems face
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• Establishment of testing and ce
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the interim period the Ministry sho
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growth of downstream industries esp
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• Strictly enforce the Tariff-bas
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• New courses in systems design m
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• Allow long-term subcontracting
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in KP. The total production of the
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• Keep on supporting PHDEC to imp
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Sports Goods Sports Goods industry
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• Ensure that the ceramics centre
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• Allow free import at 0-5% for 3
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• Operationlaise the planned marb
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• Support provision of market inf
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In order to improve the competitive
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• Advocate the use of pre-fabrica
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diversification which has been a ma
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gives a brief synopsis of the compe
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The 1980s brought a major shift in
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the costs of entry for a pioneer fi
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macro level investigation of indust
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on its own. The Government of Pakis
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Source: IMF, 2008 However, in the p
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2.1.2 Structural Rigidity & Inadequ
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share in formal non-agriculture emp
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Breaking down the analysis of manuf
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Moreover, during the 1990s, total f
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Figure 2‐13: Output per Worker Gr
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of world exports increased on avera
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More so, the product concentration
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The underlying reason for South Asi
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Source: Felipe and Lim, 2008 2.1.5
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order to bring about technological
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sector. The role of the government
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eforms in particular trade liberali
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07. In the last two years, the priv
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from 12% to 24% of total investment
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2005-07 controlling for the size of
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skewed away from the manufacturing
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sustained growth and wide spread em
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interest rate remained stable in th
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45.00 40.00 35.00 30.00 25.00 20.00
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Source: Felipe and Lim (2008). Rece
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increased as a premium for being a
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The government faces an immediate n
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services, TRIPs (Trade Related Inte
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most of the burden, for e.g., those
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that it comes second only to Bangla
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Box 2‐2: Energy in Comparison wit
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Hydel or Hydropower While the gener
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announced at least two months in ad
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network. Road linkages connecting m
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Ministry of Industries and Producti
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According to the World Bank (2004),
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Absence or weakness of skills in th
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and Nazli (1998)]. In Balochistan,
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Source: PIHS (2001-02 and 2005-2006
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Pakistan do not consider inadequate
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curricula, poor quality of instruct
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also to enhance information flows b
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shortage of qualified textile profe
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Figure 2‐36: growth in lending by
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the average value of the collateral
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The procedural requirements such as
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2.3.3.6 Policy Recommendations: The
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approving the certification bodies,
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Balochistan Sindh Punjab NWFP Small
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of manufacturing the tyre. Such ina
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Cost (% of Claim) Source: World Ban
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Due to the tax rates and complicate
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are: import duties, import surcharg
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Competitiveness & Industry Stagnati
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egional competitors like India and
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the overall TFP growth rate to 0.9
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aiding hidden sugar stocks. This il
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Second, a science park captures the
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This should be done while preservin
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• Pilot projects that help demons
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ecome too costly for more developed
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inputs/raw material by the domestic
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Table 3‐1: Demand for Petrochemic
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products is reasonable (import of e
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3.1.2 Steel Industry Steel is a cri
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scrap and serviceable engineering g
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sector. Investments in improved fer
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Figure 3‐5: Comparison of Pakista
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3.2 Value Added Knowledge Based Ind
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About 75% of the firms supply to th
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Electronics is one of the largest m
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3.2.2.1.2 Lack of Technological Kno
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3.2.2.1.4 Trade through Illegal Cha
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new patent laws under the TRIPs whi
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Figure 3‐8: Broad Comparison of P
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• Income Tax: The advanced income
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3.3 Value Added Skill & Engineering
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• Adequate human resource with gr
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etween 5-10 years. Sales are also f
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3.3.2.1.1 Low levels of productivit
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etc are fetching much higher export
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• Strongly advocate with State Ba
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The above composition suggests that
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Out of this 70% of the cost is for
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• Similarly, grinding is done usi
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The industry seems to be doing reas
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Another major area that has restric
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for such industry already exists in
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Chinese products fetch (US$0.35 - i
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more than the producer. The mean re
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US$0.26 billion in 2009 from a high
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Figure 3‐21: Typical Value of Han
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3.3.6.3 Policy Recommendations: Sin
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Source: UN Commodity Trade Statisti
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• Ensure that the Ceramics Indust
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level of quality control, inefficie
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Figure 3‐25: Key Challenges in Pa
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Another issue faced by the furnitur
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3.3.8.4 Policy Recommendations: It
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675 tanneries in the formal sector,
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• Limited availability of modern
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3.3.10 Gems & Jewellery Sector Paki
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Raw Mat erial Waste is 7% Filing &
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3.3.10.2 Policy Recommendations: Ca
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3.3.11.1 Value Chain Analysis Value
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capable of processing stone in acco
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Figure 3‐29: Traditional Quarryin
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of the NEEDS. Below we have summari
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3.3.12.1.9 Levy of Federal Excise D
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production assets and technology. T
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Source: ‘Pakistan: Growth and exp
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• Explore possibility of increasi
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3.3.12.12 Electrical Fittings The e
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scale commercial fishing vessels. I
Page 311 and 312: overtime, we freeze the district bo
Page 313 and 314: The phenomenon of localized versus
Page 315 and 316: 4.3 Mapping Measures of Regional an
Page 317 and 318: Source: GoP (2001) Khan (2003) disc
Page 319 and 320: Log of population 2005-06 13 14 15
Page 321 and 322: Log of population growth from 1981-
Page 323 and 324: Ghaus-Pasha and Jamal; 1996-97 Jafr
Page 325 and 326: FBS 2550 calories -- -- 26.6 29.3 2
Page 327 and 328: eginning; it has remained constant
Page 329 and 330: Figure 4‐5: Poverty headcount in
Page 331 and 332: a ratio equal to twice the area bet
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Page 335 and 336: 4.3.3 Evidence on Spatial Dispariti
Page 337 and 338: system in each district. Since thes
Page 339 and 340: Intermediate college size -0.047 0.
Page 341 and 342: Table 4‐10: Most and least develo
Page 343 and 344: eporting of data. However, district
Page 345 and 346: Figure 4‐10: Industry clusters an
Page 347 and 348: 4.3.4 Market Access and Spatial Ine
Page 349 and 350: Figure 4‐12: Spatial inequality i
Page 351 and 352: indicates that Peshawar, Abbottabad
Page 353 and 354: Moreover, we also present evidence
Page 355 and 356: Table 4‐11: Change in concentrati
Page 357 and 358: Next, we discuss the geographic con
Page 359 and 360: 313 Beverage industry 32 36 16 -0.0
Page 361: Table 4‐13: Geographic concentrat
Page 365 and 366: Table 4‐15: Localisation versus u
Page 367 and 368: 5 Poverty Impacts of Public Investm
Page 369 and 370: landholding and the incidence of po
Page 371 and 372: ijt household and individual level
Page 373 and 374: individual characteristics. Column
Page 375 and 376: Financial assets owned by household
Page 377 and 378: Mardan =1 if individual belongs to
Page 379 and 380: Survey year 1992-93× Punjab 0.073
Page 381 and 382: Table 5‐4: Effects of household a
Page 383 and 384: is roughly similar, except that mal
Page 385 and 386: Pseudo R 2 0.131 0.131 Notes: All r
Page 387 and 388: Survey year 1996-97 0.139 0.346 0 1
Page 389 and 390: status dummies and province-year fi
Page 391 and 392: unchanged until 1996-97. This is re
Page 393 and 394: the whole country, f ( yi ) is the
Page 395 and 396: Province× year fixed effects inclu
Page 397 and 398: Individual level controls included
Page 399 and 400: We take corresponding data from Pak
Page 401 and 402: second five year period, industry a
Page 403 and 404: oads density variable is positive a
Page 405 and 406: complete set of sub-industry (3-dig
Page 407 and 408: The two time dummies reflect produc
Page 409 and 410: 0.125) in road density of a distric
Page 411 and 412: Fourthly, the literature tells us t
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References Ahmad, H., M. Mahmud, N.
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Competitiveness Support Fund (2010)
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Gelman, A., J.B. Carlin, H.S. Stern
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Henderson, J. V., Todd Lee, Yung J.
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Levine, Ross and Renelt, David (199
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Shabbir, T., A.H. Khan (1991). Minc
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World Development Report (2000). En
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