firm-level productivity in bangladesh manufacturing industries ana m. fernandes the world bank...
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Firm-Level Productivity in Firm-Level Productivity in Bangladesh Manufacturing IndustriesBangladesh Manufacturing Industries
Ana M . FernandesAna M . Fernandes
The World Bank (DECRG)The World Bank (DECRG)
““Bangladesh: A Strategy for Growth and Employment” Bangladesh: A Strategy for Growth and Employment” Workshop Workshop
Dhaka, December 12-13Dhaka, December 12-13thth 2005 2005
MotivationMotivation
In 1990s GDP growth in Bangladesh strong In 1990s GDP growth in Bangladesh strong and sustainedand sustained
But productivity growth low and Bangladesh’s But productivity growth low and Bangladesh’s good performance has fallen below potentialgood performance has fallen below potential
Our study focuses on performance of Our study focuses on performance of manufacturing sector (increasingly important manufacturing sector (increasingly important for domestic value-added and for exports)for domestic value-added and for exports)
We examine trends and determinants of We examine trends and determinants of productivity based on new firm-level survey productivity based on new firm-level survey datadata
Why Does Productivity Matter?Why Does Productivity Matter? ““Productivity isn't everything, but in the long Productivity isn't everything, but in the long
run it is almost everything.” P. Krugmanrun it is almost everything.” P. Krugman
Differences in GDP growth across countries Differences in GDP growth across countries are largely due to differences in productivity are largely due to differences in productivity growthgrowth
Improvements in productivity are crucial to Improvements in productivity are crucial to raise living standards and wealth of nationsraise living standards and wealth of nations
Concept of Total Factor ProductivityConcept of Total Factor Productivity
TFP:TFP:– Is amount of output produced per unit of Is amount of output produced per unit of
all inputsall inputs– Reflects overall efficiency with which Reflects overall efficiency with which
inputs are transformed into output inputs are transformed into output – Linked to technology but also to general Linked to technology but also to general
knowledge, management techniques, knowledge, management techniques, government policies, reallocation of government policies, reallocation of resources to more productive uses, etc resources to more productive uses, etc
Data Data New firm-level survey conducted by world New firm-level survey conducted by world
Bank in 2004-2005Bank in 2004-2005
Eliminating data problems and outliers, final Eliminating data problems and outliers, final sample includes: sample includes: – 51 firms in pharmaceuticals industry51 firms in pharmaceuticals industry– 88 firms in food industry 88 firms in food industry – 276 firms in garments industry 276 firms in garments industry – 24 firms in leather/footwear industry 24 firms in leather/footwear industry – 136 firms in textiles industry136 firms in textiles industry
Survey includes production (output/inputs) Survey includes production (output/inputs) data for 1999-2003 + firm characteristicsdata for 1999-2003 + firm characteristics
Sample Characteristics – Firm SizeSample Characteristics – Firm Size
Small (<10
workers)
Medium (10-50
workers)
Relatively Large (50-
150 workers)
Very Large (150-500 workers)
Extremely Large (> 500
workers)
Pharmaceuticals 5.9% 15.7% 45.1% 33.3%Food 1.1% 12.5% 44.3% 33.0% 9.1%Garments 0.4% 0.7% 48.6% 50.4%Leather/Footwear 4.2% 20.8% 33.3% 29.2% 12.5%Textiles 2.2% 16.9% 44.1% 36.8%
Total 0.4% 4.0% 13.9% 44.0% 37.7%
Industry
Size Distribution (% of Firms)
Sample Characteristics – Firm AgeSample Characteristics – Firm Age
< 5 Years Old
5-10 Years Old
10-20 Years Old
20-40 Years Old
> 40 Years Old
Pharmaceuticals 15.7% 11.8% 29.4% 29.4% 13.7%Food 26.4% 10.3% 35.6% 25.3% 2.3%Garments 27.5% 27.5% 35.9% 8.3% 0.7%Leather/Footwear 8.3% 25.0% 54.2% 12.5%Textiles 29.4% 27.2% 27.2% 11.0% 5.2%
Total 25.6% 22.7% 32.8% 15.3% 3.7%
Industry
Age Distribution (% of Firms)
Sample Characteristics – LocationSample Characteristics – Location
DhakaDhaka Export
Proc. ZoneChittagong
Chittagong Export
Proc. ZoneKhulna Other
Pharmaceuticals 72.6% 5.9% 21.6%Food 28.4% 39.8% 4.6% 27.3%Garments 62.3% 4.7% 15.9% 9.8% 7.3%Leather/Footwear 87.5% 4.2% 4.2% 4.2%Textiles 29.4% 1.5% 9.6% 3.7% 55.9%
Total 51.3% 2.8% 16.7% 5.6% 0.7% 23.0%
Industry
Location (% of Firms)
Measurement of ProductivityMeasurement of Productivity
Firm-level TFP not observed but can be Firm-level TFP not observed but can be estimated as residual from a production estimated as residual from a production functionfunction
Estimate production function coefficients using Estimate production function coefficients using Olley and Pakes (1996) methodology that Olley and Pakes (1996) methodology that corrects for endogeneity of inputs corrects for endogeneity of inputs
Use firm-level price indexes to deflate sales Use firm-level price indexes to deflate sales (output measure) and materials (materials (output measure) and materials (materials input measure)input measure)
Capital constructed by perpetual inventory Capital constructed by perpetual inventory methodmethod
ititkitmitlit akmly
Trends in TFP across IndustriesTrends in TFP across Industries
Two Approaches:Two Approaches:
Industry-level TFP: weighted average of firm- Industry-level TFP: weighted average of firm- level TFP (weights=sales shares)level TFP (weights=sales shares)– Look at evolution over timeLook at evolution over time– Problem: emphasizes movements in TFP for larger Problem: emphasizes movements in TFP for larger
firmsfirms
Median firm-level TFP in each industry Median firm-level TFP in each industry – Look at evolution over timeLook at evolution over time– Gives same weight to each firmGives same weight to each firm
Industry-Level TFPIndustry-Level TFP
9000
9500
1000
010
500
1100
011
500
Ind.
Avg
. Lab
or P
rod.
(19
99 U
SD
)
1.74
1.76
1.78
1.8
Ind.
Wei
ghte
d A
vg. T
FP
1999 2000 2001 2002 2003
TFP Labor Prod.
Pharmaceuticals Industry
2000
030
000
4000
050
000
6000
070
000
Ind.
Avg
. Lab
or P
rod.
(19
99 U
SD
)
3.5
3.6
3.7
3.8
3.9
4In
d. W
eigh
ted
Avg
. TF
P
1999 2000 2001 2002 2003
TFP Labor Prod.
Food Industry
2000
2500
3000
3500
Ind.
Avg
. Lab
or P
rod.
(19
99 U
SD
)
1819
2021
22In
d. W
eigh
ted
Avg
. TF
P
1999 2000 2001 2002 2003
TFP Labor Prod.
Garments Industry
Industry-Level TFP (cont’d)Industry-Level TFP (cont’d)
7500
8000
8500
9000
9500
Ind.
Avg
. Lab
or P
rod.
(19
99 U
SD
)
1.04
1.06
1.08
1.1
1.12
1.14
Ind.
Wei
ghte
d A
vg. T
FP
1999 2000 2001 2002 2003
TFP Labor Prod.
Leather/Footwear Industry
5600
5800
6000
6200
6400
Ind.
Avg
. Lab
or P
rod.
(19
99 U
SD
)
.404
.405
.406
.407
.408
Ind.
Wei
ghte
d A
vg. T
FP
1999 2000 2001 2002 2003
TFP Labor Prod.
Textiles Industry
In pharmac., food, leather/footwear TFP In pharmac., food, leather/footwear TFP increases, then declines and recovers in 2003increases, then declines and recovers in 2003
TFP declines then stagnates in garments TFP declines then stagnates in garments TFP increases until 2002 then sharply declines TFP increases until 2002 then sharply declines
in textiles in textiles
Median Firm-Level TFPMedian Firm-Level TFP-1
0-5
05
10P
erce
ntag
e G
row
th R
ate
2000 2001 2002 2003
Med. TFP Gr. Med. Sales Gr.Med. Employment Gr. Med. Materials Gr.Med. Capital Stock Gr.
Pharmaceuticals Industry
-10
-50
5P
erce
ntag
e G
row
th R
ate
2000 2001 2002 2003
Med. TFP Gr. Med. Sales Gr.Med. Employment Gr. Med. Materials Gr.Med. Capital Stock Gr.
Food Industry
-50
5P
erce
ntag
e G
row
th R
ate
2000 2001 2002 2003
Med. TFP Gr. Med. Sales Gr.Med. Employment Gr. Med. Materials Gr.Med. Capital Stock Gr.
Garments Industry
Median Firm-Level TFP (cont’d)Median Firm-Level TFP (cont’d)
Median TFP growth is negative until 2001 in Median TFP growth is negative until 2001 in pharmac. and garmentspharmac. and garments
Median TFP growth positive in food, leather/ Median TFP growth positive in food, leather/ footwear and textilesfootwear and textiles
Until 2002 median sales growth is negative in all Until 2002 median sales growth is negative in all but pharmac. industrybut pharmac. industry
Empl. growth positive but capital growth negativeEmpl. growth positive but capital growth negative
-10
-50
5P
erce
ntag
e G
row
th R
ate
2000 2001 2002 2003
Med. TFP Gr. Med. Sales Gr.Med. Employment Gr. Med. Materials Gr.Med. Capital Stock Gr.
Leather/Footwear Industry
-10
-50
5P
erce
ntag
e G
row
th R
ate
2000 2001 2002 2003
Med. TFP Gr. Med. Sales Gr.Med. Employment Gr. Med. Materials Gr.Med. Capital Stock Gr.
Textiles Industry
Efficient Allocation of Resources?Efficient Allocation of Resources? TFP in industry may increase because :TFP in industry may increase because :
– All firms become more productive All firms become more productive - Output reallocated towards more productive - Output reallocated towards more productive
firms firms
Decompose industry-level TFP into: Decompose industry-level TFP into: – Unweighted average TFPUnweighted average TFP– Covariance between TFP and sales shareCovariance between TFP and sales share
Inefficient allocation in pharmac., leather/ Inefficient allocation in pharmac., leather/ footwear and textiles in 1999-2003footwear and textiles in 1999-2003
Determinants of TFPDeterminants of TFP What explains higher firm TFP and higher firm What explains higher firm TFP and higher firm
TFP growth ? TFP growth ?
Five sets of policy-relevant factors:Five sets of policy-relevant factors:– Human capitalHuman capital– Integration into world marketsIntegration into world markets– TechnologyTechnology– FinanceFinance– Business environmentBusiness environment
Framework and Potential ProblemsFramework and Potential Problems Regressions of TFP levels or TFP growth on Regressions of TFP levels or TFP growth on
variables covering 5 factorsvariables covering 5 factors
Estimation problems Estimation problems – Endogeneity of factors/reverse causality Endogeneity of factors/reverse causality
Solutions: - include year, industry and location Solutions: - include year, industry and location
dummy variables + size and agedummy variables + size and age
- include industry-location averages - include industry-location averages of of
business environment variables business environment variables – Multicollinearity given many variables includedMulticollinearity given many variables included
Solution: regressions with 1 determinant at a timeSolution: regressions with 1 determinant at a time– Most determinants of TFP available for 2003 onlyMost determinants of TFP available for 2003 only
Main Obstacles to Operations/GrowthMain Obstacles to Operations/Growth
0 10 20 30 40 50 60 70
Crime, Robbery and Disorder
Skills and Educ. of Available Workers
Frequent Changes in Gov. Regul./Regul. Policy
Environmental Permits/Certifications
Roads
Access to Financing
Business Licensing and Operating Permits
Tax Rates
Cost of Financing
Ports
Power from Public Grid
Tax Administration
Customs
Corruption
Perc. of Firms Identifying Factor as a "Severe" or "Very Severe" Obstacle
Smaller firms are more productive: inefficiencies, Smaller firms are more productive: inefficiencies, weak corporate managementweak corporate management
‘‘Middle-aged’ firms are more productiveMiddle-aged’ firms are more productive
Main Determinants of TFP Levels 1Main Determinants of TFP Levels 1
Specif. 3
Very Large Dummy (150 to 500 Workers) 0.040***(0.013)
Relatively Large Dummy (50 to 150 Workers) 0.233***(0.028)
Medium Dummy (10 to 50 Workers) 0.322***(0.042)
Small Dummy (Less than 10 Workers) 0.273***(0.052)
Dummy for Firms Aged 5 to 10 Years Old 0.094***(0.024)
Dummy for Firms Aged 10 to 20 Years Old 0.141***(0.026)
Dummy for Firms Aged 20 to 40 Years Old 0.154***(0.032)
Dummy for Firms Aged More than 40 Years Old 0.051(0.036)
Number of Observations 2236
Firms with better human capital have higher TFP Firms with better human capital have higher TFP
Internationally-integrated firms have higher TFPInternationally-integrated firms have higher TFP
Main Determinants of TFP Levels 2Main Determinants of TFP Levels 2
Specif. 3
Skilled Workers Share 0.120***(0.042)
Dummy for Managers with Post-Graduate Educ. 0.024(0.015)
Manager Years of Experience (log) 0.018**(0.008)
Foreign-Owned Dummy 0.102**(0.047)
Majority Exporters Dummy 0.105***(0.024)
Main Determinants of TFP Levels 3Main Determinants of TFP Levels 3 Firms with R&D staff or quality certif. are more Firms with R&D staff or quality certif. are more
productive but firms with newer machinery are notproductive but firms with newer machinery are not
Firms with overdraft have higher TFP but firms with Firms with overdraft have higher TFP but firms with loan have lower TFPloan have lower TFP
Specif. 3
Dummy for R&D Staff 0.023(0.016)
Quality Certification Dummy 0.051***(0.016)
Perc. of Machinery Less than 5 Years Old -0.001***(0.0003)
Overdraft Dummy 0.025*(0.015)
Loan Dummy -0.059***(0.015)
Main Determinants of TFP Levels 4Main Determinants of TFP Levels 4 Weak power infrastructure and crime lead to lower Weak power infrastructure and crime lead to lower
firm TFPfirm TFP
Bureaucracy and corruption are associated with Bureaucracy and corruption are associated with higher TFP: reverse causality? higher TFP: reverse causality?
Specif. 3
Days to Clear Customs for Imports (log) 0.007(0.041)
Number of Power Interruptions (log) -0.102***(0.034)
Perc. Manag. Time Spent Dealing with Regulation 0.158*(0.081)
Perc. of Sales Paid in Bribes to Get Things Done 0.023(0.015)
Protection Payments as Perc. Sales -52.823***(11.787)
Main Determinants of TFP Growth 1Main Determinants of TFP Growth 1 Very large/rel. large firms have faster TFP growthVery large/rel. large firms have faster TFP growth Young firms have faster TFP growthYoung firms have faster TFP growth Some convergence in TFPSome convergence in TFP
Specif. 3
Lagged TFP OP (log) -0.068***(0.021)
Very Large Dummy (150 to 500 Workers) 0.012*(0.007)
Relatively Large Dummy (50 to 150 Workers) 0.027**(0.011)
Medium Size Dummy (10 to 50 Workers) 0.050**(0.020)
Small Size Dummy (Less than 10 Workers) 0.024(0.019)
Dummy for Firms Aged 5 to 10 Years Old -0.018(0.011)
Dummy for Firms Aged 10 to 20 Years Old -0.014(0.012)
Dummy for Firms Aged 20 to 40 Years Old -0.023(0.014)
Dummy for Firms Aged More than 40 Years Old -0.026(0.016)
Main Determinants of TFP Growth 2Main Determinants of TFP Growth 2 Firms with better human capital exhibit faster TFP Firms with better human capital exhibit faster TFP
growth growth Internationally-integrated firms show higher TFP Internationally-integrated firms show higher TFP
growthgrowth
Specif. 3
Skilled Workers Share 0.031**(0.015)
Dummy for Managers with Post-Graduate Educ. -0.008(0.006)
Manager Years of Experience (log) 0.006*(0.003)
Foreign-Owned Dummy 0.012(0.015)
Majority Exporters Dummy 0.015**(0.007)
Dummy for External Training Provided 0.015**(0.008)
Number of Observations 1710
Main Determinants of TFP Growth 3Main Determinants of TFP Growth 3 Firms with quality certif. exhibit faster TFP growth Firms with quality certif. exhibit faster TFP growth
but those with R&D or newer machin. exhibit but those with R&D or newer machin. exhibit lower TFP growthlower TFP growth
Firms with access to overdraft facility have slower Firms with access to overdraft facility have slower TFP growthTFP growth
Specif. 3
R&D Spending Intensity -0.074(0.145)
Quality Certification Dummy 0.007(0.007)
Perc. of Machinery Less than 5 Years Old -0.0002(0.0001)
Overdraft Dummy -0.007(0.006)
Main Determinants of TFP Growth 4Main Determinants of TFP Growth 4
More frequent power outages, more red tape and More frequent power outages, more red tape and more crime are associated with lower TFP growthmore crime are associated with lower TFP growth
Specif. 3
Number of Power Interruptions (log) -0.01(0.014)
Perc. Manag. Time Spent Dealing with Regulation -0.048(0.045)
Protection Payments as Perc. Sales -8.071(5.749)
TFP Growth Panel 1992-2003TFP Growth Panel 1992-2003
82 firms observed in 1992 World Bank survey 82 firms observed in 1992 World Bank survey and in current surveyand in current survey
Obtain growth accounting firm-level TFP growth Obtain growth accounting firm-level TFP growth measures between 1992 and 2003measures between 1992 and 2003
Average TFP Growth 1992-2003 -3.67%
Overall TFP Growth 1992-2003 -40.12%
Average Labor Productivity Growth 1992-2003 0.71%
Overall Labor Productivity Growth 1992-2003 8.15%
Average Sales Growth 1992-2003 3.24%
Overall Sales Growth 1992-2003 36.00%
Average Employment Growth 1992-2003 2.79%
Overall Employment Growth 1992-2003 30.69%
Number of Observations 82
Determinants of TFP Growth 1992-2003Determinants of TFP Growth 1992-2003 Extrem. large firms, younger firms and Extrem. large firms, younger firms and
exporters have higher TFP growth in 1992-exporters have higher TFP growth in 1992-2003 2003
Lagged TFP (log) -0.959***(0.141)
Very Large Dummy (150 to 500 Workers) -0.160(0.102)
Relatively Large Dummy (50 to 150 Workers) -0.211(0.234)
Medium Size Dummy (10 to 50 Workers) -0.023(0.233)
Dummy for Firms Aged 5 to 10 Years Old -0.066(0.214)
Dummy for Firms Aged 10 to 20 Years Old -0.278(0.193)
Dummy for Firms Aged 20 to 40 Years Old -0.453**(0.213)
Dummy for Firms Aged More than 40 Years Old -0.415*(0.238)
Skilled Workers Share -0.002(0.326)
Exporters Dummy 0.211*(0.123)
Loan Dummy 0.031(0.119)
Policy ImplicationsPolicy Implications Improvements in infrastructure are likely to Improvements in infrastructure are likely to
bring large improvements in firm TFPbring large improvements in firm TFP Policies promoting Policies promoting
– human capital formation of both workers and human capital formation of both workers and managersmanagers
– integration of firms into global markets – integration of firms into global markets – either by attracting foreign capital or by either by attracting foreign capital or by facilitating access to export marketsfacilitating access to export markets
can benefit firm TFP can benefit firm TFP
Efforts of firm-level data collection can pay off Efforts of firm-level data collection can pay off by allowing government to make informed by allowing government to make informed decisions on policies towards private sector decisions on policies towards private sector