firm-level productivity in bangladesh manufacturing industries ana m. fernandes the world bank...

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


Food Industry

-50

5P

erce

ntag

e G

row

th R

ate

2000 2001 2002 2003


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


Leather/Footwear Industry

-10

-50

5P

erce

ntag

e G

row

th R

ate

2000 2001 2002 2003


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 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 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)


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%


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 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

firm-level productivity in bangladesh manufacturing industries ana m. fernandes the world bank...

Documents

industrylevel tfp slide

median firmlevel tfp

industry median firmlevel

firmlevel productivity

level tfp weights

textiles tfp

garments tfp

industrylevel tfp contd