HOW CAN PRODUCTIVITY GAINS

BE SHARED AND INCLUSIVE

ACROSS SPACE

Global Productivity Forum, Budapest Rudiger Ahrend Head of Urban Programme Centre for Entrepreneurship, SMEs, Local Development and Tourism

• Productivity – Productivity across regions and cities

– Productivity performance / catching up

– Drivers of catching-up

– Territorial aspects of, and strategies for developing the tradable sector

• Inclusiveness – Inclusiveness in regions and cities

– Productivity-inclusiveness nexus across space

• Conclusion: Trade / GVC integration

Productivity across regions and cities

Productivity differs widely within countries

5

Bigger cities are more productive

City productivity increases with city size

even after controlling for sorting

6

• Productivity increases by 2-5% for a doubling in population size

Administrative fragmentation is correlated

with lower city productivity

7 7

Productivity Performance /

Catching up

OECD economies have converged -

Within countries, regions have diverged

The productivity gap between frontier

and lagging regions has increased

Notes: Average of top 10% and bottom 10% TL2 regions, selected for each year. Top and bottom regions are the aggregation of regions with the highest and lowest GDP per worker and representing 10% of national employment. 19 countries with data included.

Averages of top 10%

(frontier), bottom

75%, and bottom

10% (lagging) regional GDP per worker,

TL2 regions

50 000

60 000

70 000

80 000

90 000

100 000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

USD PPP per employee

Frontier regions Lagging regions 75% of regions

1.6% per year

1.3% per year

1.3% per year

60% increase

Geography of

productivity

convergence

relative to

national

frontiers in

European

regions

ITA DEU DNK AUT BEL CAN GRC NLD NZL FIN FRA ESP PRT USA AUS GBR SWE IRL SVN HUN CZE KOR POL SVK-2%

-1%

0%

1%

2%

3%

4%

5%

Catching up Diverging Keeping pace Frontier Country average productivity growth

Productivity growth of the region

National labour productivity growth depends

on the performance of regions

Annual average growth in real per worker GDP between 2000-2013 (or closest year available).

Regional catching-up can play an

important role for national productivity growth

Contribution to national labour productivity growth, 2000-12

13

Productivity and “catching up” in Hungary

Percentage contribution to national GDP growth, 2000-2012

Note: Difference between national labour productivity growth as calculated with and without the indicated region.

Note: The contribution is the product of a region’s GDP growth rate by its initial share of GDP.

Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages.

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

Central Hungary WesternTransdanubia

CentralTransdanubia

Northern Hungary Southern Great Plain SouthernTransdanubia

Northern Great Plain

%-points

Frontier Catching up Keeping pace Diverging

Contribution to national labour productivity growth, 2000-13

14

Productivity and “catching up” in Austria

Percentage contribution to national GDP growth, 2000-2013

Note: Difference between national labour productivity growth as calculated with and without the indicated region.

Note: The contribution is the product of a region’s GDP growth rate by its initial share of GDP.

Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages.

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

Central Hungary WesternTransdanubia

CentralTransdanubia

Northern Hungary Southern Great Plain SouthernTransdanubia

Northern Great Plain

%-points

Frontier Catching up Keeping pace Diverging

The drivers of regional

productivity catching-up

Good or bad productivity performance can

be found for all types of regions

0

10

20

30

40

50

60

70

80

90

100

Frontier (41) Catching-up (65) Diverging (76) Keeping pace (107)

%

Mostly Urban (127) Intermediate (62) Mostly Rural (100)

In which: 70% of mostly urban frontier

regions contain very large cities

in which: 75% of diverging mostly urban

regions contain very large cities

# regions in ( )

Labour productivity of remote rural areas

has recently declined

88%

89%

90%

91%

92%

93%

94%

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Total RURAL

RURAL CLOSE TO CITIES

RURAL REMOTE

Productivity levels of Predominantly Urban regions = 100

Stronger intensity of tradable sectors is

associated with productivity catching-up

All tradable sectors, TL2 regions

Notes: Tradable sectors are defined by a selection of the 10 industries defined in the SNA 2008. They include: agriculture (A), industry (BCDE), information and communication (J), financial and insurance activities (K), and other services (R to U). Non tradable sectors are composed of construction, distributive trade, repairs, transport, accommodation, food services activities (GHI), real estate activities (L), business services (MN), and public administration (OPQ).

20

25

30

35

40

45

50

Frontier Catching-up Diverging Frontier Catching-up Diverging

Tradable GVA share Tradable employment share

2013 2000

%

19

Productivity gains in tradables are

mainly within sectors

-1

0

1

2

3

4

5

ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA

%

Tradable sectors - contribution to productivity growth

Employment shifts to faster growing sectors Employment shifts to initially more productive sectors

Sectoral productivity growth Productivity growth in tradable sectors

20

Productivity gains in non tradables are

associated with sectoral shifts

Only in Eastern Europe does the non-tradable sector contribute by improving productivity significantly; in some countries non-tradable productivity is even declining

-1

0

1

2

3

4

5

ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA

%

Non-tradable sectors - contribution to productivity growth

Employment shifts to faster growing sectors Employment shifts to initially more productive sectors

Sectoral productivity growth Productivity growth in non-tradable sectors

Territorial aspects of, and strategies for developing the tradable sector

Share of total

employment in

clusters by type

of TL2 region

Mostly urban

regions are those

with at least 70% of

its population living

in Functional Urban

Areas or part of its

population living in a

large metro area

with at least 1.5

million inhabitants.

Mostly rural regions

have less than 50%

of their population

living in FUAs

Source: OECD

Regional Statistics

and Ketels and

Protsiv (2016)

0 10 20 30 40 50 60 70 80 90 100

Footwear

Forestry

Leather and Related Products

Fishing and Fishing Products

Apparel

Agricultural Inputs and Services

Nonmetal Mining

Appliances

Livestock Processing

Coal Mining

Furniture

Water Transportation

Jewelry and Precious Metals

Wood Products

Textile Manufacturing

Electric Power Generation and Transmission

Automotive

Lighting and Electrical Equipment

Food Processing and Manufacturing

Vulcanized and Fired Materials

Downstream Metal Products

Paper and Packaging

Metalworking Technology

Plastics

Metal Mining

Construction Products and Services

Production Technology and Heavy Machinery

Upstream Metal Manufacturing

Transportation and Logistics

Medical Devices

Upstream Chemical Products

Environmental Services

Hospitality and Tourism

Local clusters (non-traded)

TOTAL

Printing Services

Education and Knowledge Creation

Recreational and Small Electric Goods

Distribution and Electronic Commerce

Downstream Chemical Products

Oil and Gas Production and Transportation

Performing Arts

Information Technology and Analytical Instruments

Tobacco

Aerospace Vehicles and Defense

Business Services

Marketing, Design, and Publishing

Insurance Services

Financial Services

Biopharmaceuticals

Video Production and Distribution

Communications Equipment and Services

Music and Sound Recording

Share of FTE employment in the cluster, %

Mostly urban Mostly intermediate Mostly rural

23

Urban areas attract more knowledge-

intensive firms

Birth shares by sector (births by sector/total regional births)

TL3 regions (15 OECD countries) 2014

Strategies for developing the tradable sector

To remain competitive in Tradable sectors there are mainly three

main options:

1. Continued specialisation in Natural resources. This is typically

an option for remote rural regions

2. Be integrated in Global Value Chains. Integration between

manufacturing and service sectors is needed. Connectivity and

proximity may favour low-density areas close to cities. Without a

territorial strategy it may be difficult to benefit from GVCs for

regional development. Forward and backward linkages (re-

bundling) are critical to maximize value-added of FDI and

creation of a network of local suppliers.

3. Develop Territorially differentiated products & services

through mobilisation of local assets. Consumers may express

preferences for local or traceable products, without subsidies or

some form of protection.

Inclusiveness in regions and cities

26

Gini index of disposable income (after tax and transfers), 2013

Disparities of household income are large

within regions, mainly in capital cities

Source: OECD Income Distribution Database and OECD Regional Well-being database

Eastern Slovenia

Capital

Oslo and

Akershus

Åland

Prague

Brussels Capital Region

Bratislava Region

Central Hungary

Vienna

Stockholm

North Holland

Hesse

Ile-de-France

Central Region

Hokkaido

Ticino

Southern and

Eastern

Ontario

Sicily

Western Australia

Ceuta

Attiki North Island

South East

England

Estonia

Jerusalem District

District of

Columbia Northeastern

Anatolia West

Santiago Metropolitan

Oaxaca

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

#REF!

Regional value National average

Larger cities are more unequal

27

Metropolitan population and income inequality, circa 2014

Metropolitan size and inequality, once controlled for income levels and country effect

Brussels

Antw erpen

Liège

Red Deer

Calgary

Lethbridge

Thunder Bay

Québec

Trois Rivières

Montreal

Sherbrooke

Toronto

Brant

Windsor

Iquique

Antofagasta

Calera

San Antonio

Rancagua

Linares

Temuco

Osorno

Punta Arenas

Paris

Toulouse

Saint-Etienne

Rouen Roma

Milano

Napoli

Tijuana

Hermosillo

Rey nosa

Torreón

León Guadalajara

Pachuca de Soto

Mex ico City

Toluca

Oslo

Malmö

Portland

Buffalo

Albany

Boston

Clev eland

Omaha

New York

Philadelphia

Denv er

Cincinnati

Washington

San Francisco

Fresno

Las Vegas

Albuquerque

Memphis

Los Angeles

Atlanta

Dallas

Houston

Miami

McAllen

0.05

0.1

0.15

0.2

0.25

10 11 12 13 14 15 16 17

Gin

i coeffi

cie

nt

(com

ponent plu

s r

esid

uals

)

City population (natural logarithm)

What do we know about the nexus between productivity and inclusiveness across space

Towards a topology for regions and cities*

*This section is based on preliminary work that has been prepared by the Program for Local Economic and Employment Development (LEED) and discussed by its Committee.

Variables Weight

Unemployment

Equal weighting

was selected after PCA assigned

similar weights to all

indicators

Long-term unemployment

Low-work intensity household

Deprivation rate

Poverty rate

NEET rate

Educational attainment: primary education

Designing the Inclusiveness Composite

Indicator (Work in Progress)

Designing the Inclusiveness Composite

Indicator

What it does

• Reduce the data from a multidimensional frame to a single dimension, simplifying its interpretation

• Concentrate on the inclusion of the most disadvantaged individuals in society

• Provide a way to measure regional differences within the same country and across countries

What it does not do

• Provide a measure of income inequality

• Act as an indicator of overall well-being

• Include data on access to basic services (future development)

Praha

Severozápad

Hovedstaden

Syddanmark

Helsinki-Uusimaa

Etelä-Suomi

Southern and Eastern

Trento

Veneto

Lazio

Molise

Puglia

Sicilia

Bratislavský kraj

Západné Slovensko

País VascoMadrid

Cataluña

Andalucía

Ceuta

Stockholm

Sydsverige

-2-1

01

23

Lab

ou

r p

rod

uctivity

-2 -1 0 1Inclusiveness Composite Indicator

Czech Republic Denmark Finland Ireland

Italy Slovakia Spain Sweden

Comparing 70 regions across 8 OECD

countries

• Following the evidence presented by the other panellists,

integration of regions and cities into global value chains

improves various inclusiveness outcomes for them,

improving inclusiveness within territories

• This is coherent with the evidence that by and large

productivity and inclusiveness seem to be correlated across

space

• However, it is typically cities and regions sufficiently close to

larger urban centers that get integrated into GVCs, given

the obvious importance of good transport links

• For remote (rural) regions such an integration is more

difficult, implying that the emergence of GVCs may have

contributed to widen spatial gaps between territories

Conclusion: Can integration into global trade

(and into GVCs) further spatial inclusiveness?

References

Ahrend, Farchy, Kaplanis and Lembcke (2017) “What Makes Cities More Productive? Agglomeration Economies & the Role of Urban Governance: Evidence from 5 OECD Countries”, Journal of Regional Science, Vol. 57(3).

Ahrend and Schumann (2014) “Does Regional Economic Growth Depend on Proximity to Urban Centres?”, OECD Regional Development Working Papers, 2014/07.

Bachtler, Oliveira Martins, Wostner & Zuber (2017) “Towards Cohesion Policy 4.0: Structural Transformation and Inclusive Growth”, Regional Studies Association Europe Paper for the 7th EU Cohesion Forum

Boulant, Brezzi and Veneri (2016) “Income levels and inequality in OECD metropolitan areas. A Comparative Approach in OECD Countries”, OECD Regional Development Working Papers, 2016/06.

OECD (2015) The Metropolitan Century: Understanding Urbanisation and its Consequences,

OECD (2015) Governing the City

OECD (2016), Regions at a Glance.

OECD (2016), Making Cities Work for All: Data and Actions for Inclusive Growth.

OECD (2016), Regional Outlook: Productive Regions for Inclusive Societies.

OECD (2017) “Analysing the Local Dimension of Productivity and Inclusiveness: Untangling the Nexus”, Background Document, Spring Meeting of the Local Economic and Employment Development (LEED) Committee

Veneri and Ruiz (2016), “Rural-to-urban population growth linkages: evidence from OECD TL3 regions. Journal of Regional Science, Vol. 56(1).

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