Productive entrepreneurship, technology and innovation

Mark Dutz, Innovation and Growth, PRMED

April 2011

Outline

I. Concepts• WHAT is innovation

• WHY important

• HOW support innovation – incentives, skills, information & finance

II. Productive entrepreneurship • Transformational vs subsistence

• Alternative measures of entrepreneurship

III. Organizational innovation• Decentralization

• Management practices

I.1 WHAT is innovation

• Innovation = technology + entrepreneurshipCommercialization of new ways to solve problems by combining:

- technology: improvements in product, process, organization & marketing

- entrepreneurship: turning ideas into wealth

• A continuum of non-replicative activities• New-to-the-world

• New-to-the-market

• New-to-the-firm

• Focus• Catch-up: diffusion & adaptation of existing technologies across all sectors

• Entrepreneurship facilitation as important if not more so than technology

I.1 WHAT is innovation

Private Requiring subsidies/PPPs

Radical

Integrated circuit

Personal computer

Tata’s $2,000 Nano car

Internet

Psoriasis treatment:

$100 vs $15,000 per patient

IncrementalIntel transistors upgrading:

# purchased for $1 – 5 bn % rise 1968-2003

Boeing 747 into 777

Bharti Airtel business model:ARPU to gross profits, outsource functions

Aravind Eyecare Hospital: cataract surgery for $30 rather than $3,000 per patient

Aakash Ganga(“river from sky”) rainwater harvesting system(Lemelson-MIT prize winner)

Green Revolution

I.2 WHY important: to promote growth

• “Differences in measured inputs explain less than half of the enormous cross-country differences in per capita GDP”– Countries are poor because use their inputs less efficiently

0

2000

4000

6000

8000

10000

12000

14000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Real

GD

P p

er

cap

ita (

2000 U

S$)

South Korea

IDA

Difference in output due to

growth in labor and capital

Difference in

output due to

TFP growth

I.2 within-firm innovation often the most important driver of productivity growth

+ India: “productivity growth among formal manufacturing plantsstarting in mid 1990s driven by within-firm productivity growthof larger plants rather than reallocation across plants”(Bollard, Klenow, Sharma 2011)

I.3 HOW: Levers for innovation policies

• Incentives for productive entrepreneurship• Level-playing-field investment climate (rule of law, rewards, competition)

• Protection of IPRs

• Skills• “Absorptive capacity” within firms

• Responsiveness of training to market demands

• Problem solving skills

• Information• Access (ICT; trade, FDI, IP, diaspora; rural-urban relocation)

• Knowledge intermediaries (MNCs/buyers, alliances, TTOs, bus. services)

• Finance• Mix of instruments and institutions to select & support talent

Innovation inputs

Incentives Skills Information Finance

Rule of Law

Closing a

Business

Tertiary

Students

Internet

Users Trade

Use of

banks to

finance

investment

Country

Rating

(0 - 5)

Recovery

rate (cents on

the dollar)

% Gross

Enrollment

Rate

Per 100

Citizens

X+M

(% GDP) % of firms

India 2.6 13 13.5 4.5 51 47

China 2.2 35 22.1 22.5 65 29

Turkey 2.6 20 37.1 34.4 52 52

Brazil 2.2 17 30.0 37.5 29 28

Malaysia 3.0 39 29.7 55.8 110 49

South Korea 3.3 82 96.1 75.8 107 40

Source: WDI, Rule of Law from WB World Governance Indicators; latest year available (2004-2008).

Incentives Skills

0.00 2.00 4.00 6.00 8.00 10.00 12.00

Brazil

China

India

Philippines

Turkey

South Korea

Informal payments as % of sales

0% 20% 40% 60% 80% 100%

India

South Korea

Turkey

Malaysia

Brazil

China

% of firms training workers

Source: World Bank/IFC Enterprise Surveys, 1999-2008

Information Finance

0.00 20.00 40.00 60.00 80.00 100.00

Turkey

South Korea

Brazil

India

Malaysia

China

% firms using foreign technology average % investments financed externally

0% 5% 10% 15% 20% 25%

India

Brazil

Philippines

Turkey

China

Source: World Bank/IFC Enterprise Surveys, 1999-2008

Innovation outputs: IPRs

Country

Patents

Granted by

USPTO +

Patent

Filings

National

Office++

of which

by

Residents

Trademark

Filings Natl

Office++

Industrial

Design

Filings++

Utility

Model

Filings++

South Korea 5,433 172,469 127,114 141,289 54,362 21,084

China 758 245,161 153,060 661,358 267,432 181,324

India 444 28,940 5,314 103,419 5,521 0

Brazil 141 24,074 3,810 105,320 5,929 2,984

Malaysia 112 2,372 670 25,894 1,920 0

Turkey 22 2,021 1,810 72,444 6,868 3,011

+ Source: World Bank KAM Database, 2009. Value is average over 2003-2007.

++ Source: WIPO World Intellectual Property Indicators, 2009 (latest year)

South Asia: impact of policy levers on innovation

0 10 20 30 40 50 60

Physical Infrastructure

Knowledge Spillovers

Finance

Skills & Labor Regulations

Incentives

***IMPACT ON INNOVATION***

Percent Impact

Source: Dutz, O’Connell and Tan (2011), based on Enterprise Surveys across 8 SAR countries

South Asia: marginal effect of innovation & training on TFP, employment growth and wages

Effect of innovation larger when jointly estimated• pay 26% higher wage levels; experience 5% higher employment growth

Innovation even more important for firms that train workers• have twice as high productivity; 8% higher employment growth; pay double wages

105%

26%

102%

5%

8%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

0%

20%

40%

60%

80%

100%

120%

Innovation effect, endogenous choice

treatment regression

Effect of innovation + training, jointly determined

Pe

rce

nt

Effe

ct o

n e

mp

loym

en

t gr

ow

th

Pe

rce

nt

Imp

rove

me

nt

in T

FP &

Wag

e

Effect on TFP Effect on Wage Effect on Emp Growth

Source: Dutz, O’Connell and Tan (2011), based on Enterprise Surveys across 8 SAR countries

II. Two types of entrepreneurs

Subsistence Transformational

Share of high-growth enterprises & gazelles (employment)

0% 5% 10% 15% 20%

Southkorea

China

Malaysia

India

Brazil

Turkey

% High Growth

% Gazelles

Source: World Bank Investment Climate Surveys, 1999-2008

Plant productivity over the life-cycle: Following a cohort of plants over time, no change in India, less than 2x increase in TFP in Mexico, more than 7x in U.S.

(underlying data by Chang-Tai Hsieh (Chicago) and Peter Klenow (Stanford), at October 21, 2010 World Bank DEC presentation)

Young transformational entrepreneurs grow faster in US than Europe

(underlying data by Nicolas Veron, Bruegel)

40 30 20 10 0 10 20 30 40

1976-2000

1951-1975

1926-1950

1901-1925

1876-1900

1851-1875

1826-1850

1801-1825

1776-1800

Before 1775

Number of Firms

Ye

ar o

f Es

tab

lish

me

nt

Age Pyramid of European and U.S. Firms in FT Global 500

Europe U.S.

Based on FT Global 500 ranking of the world largest listed companies, September 30, 2007, published on www.ft.com

Sub-national: R&D intensive firms agglomerate in a few cities0

510

15

20

Nu

mbe

r o

f C

itie

s

0 10 20 30Percent R&D Intensive Firms

R&d intensive firm = R&D expenditure of at least 5% of total expenditure

Source: India Enterprise Survey

2004

Distribution of R&D Intensive Firms Across Indian Cities

010

20

30

40

Nu

mbe

r o

f C

itie

s

0 5 10 15 20 25Percent R&D Intensive Firms

R&d intensive firm = R&D expenditure of at least 5% of total expenditure

Source: China Enterprise Survey

2004

Distribution of R&D Intensive Firms Across Chinese Cities

III.1 Decentralization as an innovative technology

• Survey data on 4 questions – 4,000 firms across 12 countries:

• How much capital investment a plant manager could undertake without prior authorization from corporate headquarters

• Extent of real authority of plant manager (vs corporate headquarters):

• Hiring a new full-time permanent shop-floor employee

• New product introduction

• Marketing decision

Source: Bloom, Sadun and Van Reenen (NBER WP 15129, July 2009)

-1 -.5 0 .5mean of zorg

Sweden

US

UK

Germany

Italy

Portugal

France

Poland

China

India

Japan

Greece

-1 -.5 0 .5mean of zorg

Sweden

US

UK

Germany

Italy

Portugal

France

Poland

China

India

Japan

Greece

Decentralization varies across countries

Most centralized

• Asia

• Southern Europe

Least centralized

• Anglo-Saxon countries

• Northern European countries

Decentralization measure

Decentralization can improve TFP

• Rule of law & trust facilitate delegation by improving cooperation

• Competition & non-hierarchical religions (not Catholicism, Eastern Orthodox & Islam) also associated with more decentralization

• account for 4/5 of variation in decentralization

• Allows more efficient firms to grow in scale

• Fosters higher returns from IT

• While info technologies (ERP for plant manager, CAD/CAM for plant workers) increase decentralization, communication technologies (data networks) increase centralization:

increase in ERP usage by 60% (avg diff in ICT b/w US & Europe) equiv to a large increase in S of human capital (=1990-2000 rise in US college grads)

III.2 Management as an innovative technology

• Survey data in medium & large manufacturing firms on 18 practices:

• Monitoring: collection & processing of production information

• Target setting: coherent & binding e.g. operations, inventory, quality control

• People incentives: merit-based pay, promotion, hiring & firing

Source: Bloom and Van Reenen, QJE 2007

2.6 2.8 3 3.2 3.4mean of management

US

Germany

Sweden

Japan

Canada

France

Italy

Great Britain

Australia

Northern Ireland

Poland

Republic of Ireland

Portugal

Brazil

India

China

Greece

23

Overall management is worse in developing countries

Average country management score, manufacturing firms 100 to 5000 employees(monitoring, targets and incentives management scored on a 1 to 5 scale

using the methodology developed in Bloom & Van Reenen (QJE 2007))

69533627012234431218876238292231102140

524171

620559

# firms

24

Firm-Level Management Scores

0.2

.4.6

.8

Dens

ity

1 2 3 4 5management

0.2

.4.6

.8

Dens

ity

1 2 3 4 5management

US manufacturing, mean=3.33 (N=695)

Indian manufacturing, mean=2.69 (N=620)

India’s low score is due to a tail of badly managed firmsD

ensi

tyD

ensi

ty

Firm-level histograms underlying the country averages from the previous figure

Family-owned & managed, founder and government firms have the largest tail of badly-managed firms

Impact of management innovation:Evidence from large Indian textile firms

Randomized experiment:

• treatment plants: 5 mths extensive consulting

• control plants: 1 mth light diagnostic consulting

Causal impact of adopting better management technologies:

• Raised average productivity by 11% in first year– annual profitability increases of $230,000 per firm

(at consulting cost of $250,000, profitable in 16 months given cost of capital of 15%)

• Increased decentralization of decision-making

– better flow of information enabled owners to monitor and delegate more decisions to middle managers

• Increased use of computers

– necessitated by data collection & analysis

Source: Bloom, Eifert, Mahajan, McKenzie and Roberts (mimeo 2010)

Poor quality meant 19% of manpower went on repairs

Workers spread cloth over lighted plates to spot defectsLarge room full of repair workers (the day shift)

Defects lead to about 5% of cloth being scrappedDefects are repaired by hand or cut out from cloth

28

Mending recorded only to cross-check against customers’ rebates claims

Defects log with defects not recorded in an standardized format. These defects were recorded solely as a record in case of customer complaints. The data was not aggregated or analyzed

05

01

00

15

0

-20 -10 0 10 20 30 40timing

Quality defects index for treatment and control plants

2.5th percentile

Control plants

Treatment plants

Weeks after the start of the intervention

Qu

alit

y d

efec

ts in

dex

(h

igh

er s

core

=lo

we

r q

ual

ity)

Start of Diagnostic

Start of Implementation

Average (+ symbol)

97.5th percentile

Average (♦ symbol)

2.5th percentile

97.5th percentile

End of Implementation

Notes: Average quality defects index, which is a weighted index of quality defects, so a higher score means lower quality. Plotted for the 14treatment plants (+ symbols) and the 6 control plants (♦ symbols). Values normalized so both series have an average of 100 prior to the startof the intervention. Confidence intervals from plant block bootstrapped.

Why are so many firms badly managed?

• Limited competition

– 50% tariff on fabric imports insulates textile firms from foreign pressure

– bankruptcy not a threat given low weaver wage of $5/day

• Constrained managerial span of control linked to poor rule of law

– unwillingness to delegate & limited promotion opportunities for middle managers in family-owned firms prevents expansion of good firms, allowing bad firms to survive

– motivated by fear that managers would steal with greater autonomy, given inability to punish without effective legal system, so every decision requires owner sign-off

• Labor regulations constrain hiring/firing & re-assignment

• Insufficient training about management practices

• Worker skills: adaptation easier when workforce more knowledgeable

• Lack of information: too little benchmarking against MNCs

• Finance: hard to borrow for management training (intangible investment difficult to collateralize); lack of financing stifles new entry