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 Bigger cities are more productive

5 City productivity increases with city size even after controlling for sorting

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

6 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

Frontier regions Lagging regions 75% of regions

USD PPP per employee 100 000 Averages 1.6% per year of top

90 000 10% (frontier), 60% increase bottom 80 000 75%, and bottom 10% 1.3% per year 70 000 (lagging) regional 1.3% per year GDP per 60 000 worker, TL2 regions 50 000 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 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. Geography of productivity convergence relative to national frontiers in European regions National labour productivity growth depends on the performance of regions

Catching up Diverging Keeping pace Frontier Country average productivity growth Productivity growth of the region 5%

4%

3%

2%

1%

0%  Regional catching-up can play an -1% important role for national productivity growth

-2% ITA DEU DNK AUT BEL CAN GRC NLD NZL FIN FRA ESP PRT USA AUS GBR SWE IRL SVN HUN CZE KOR POL SVK Annual average growth in real per worker GDP between 2000-2013 (or closest year available). Productivity and “catching up” in Hungary

Frontier Catching up Keeping pace Diverging

%-points 0.5 Contribution to national labour Percentage contribution to productivity growth, 2000-12 national GDP growth, 2000-2012 0.4

0.3

0.2

0.1

0

-0.1 Note: Difference between national labour productivity Note: The contribution is the product of a growth as calculated with and without the indicated region’s GDP growth rate by its initial share of -0.2 region.Central Hungary Western Central Northern HungaryGDP.Southern Great Plain Southern Northern Great Plain 13 Note: See http://www.oecd.org/regional/oecdTransdanubia Transdanubia-regional-outlook-2016-9789264260245-en.htmTransdanubia for country pages. Productivity and “catching up” in Austria

Frontier Catching up Keeping pace Diverging

%-points 0.5 Contribution to national labour Percentage contribution to productivity growth, 2000-13 national GDP growth, 2000-2013 0.4

0.3

0.2

0.1

0

-0.1 Note: Difference between national labour productivity Note: The contribution is the product of a growth as calculated with and without the indicated region’s GDP growth rate by its initial share of region.-0.2 GDP. Central Hungary Western Central Northern Hungary Southern Great Plain Southern Northern Great Plain 14 Note: See http://www.oecd.org/regional/oecdTransdanubia Transdanubia-regional-outlook-2016-9789264260245-en.htmTransdanubia for country pages.

The drivers of regional productivity catching-up

Good or bad productivity performance can be found for all types of regions

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

100

90 In which: 70% of mostly urban frontier regions contain very large cities

80 # regions in ( )

70

in which: 75% of diverging mostly urban 60 regions contain very large cities

50

40

30

20

10

0 Frontier (41) Catching-up (65) Diverging (76) Keeping pace (107) Labour productivity of remote rural areas has recently declined

94%

RURAL CLOSE TO CITIES 93%

92%

Total 91% RURAL

90% Productivity levels of Predominantly Urban regions = 100 89% RURAL REMOTE

88% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Stronger intensity of tradable sectors is associated with productivity catching-up

All tradable sectors, TL2 regions

2013 2000 % 50

45

40

35

30

25

20 Frontier Catching-up Diverging Frontier Catching-up Diverging Tradable GVA share Tradable employment share

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). Productivity gains in tradables are mainly within sectors 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 % 5

4

3

2

1

0

-1 19 ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA Productivity gains in non tradables are associated with sectoral shifts 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 % 5 Only in Eastern Europe does the non-tradable 4 sector contribute by improving productivity significantly; in some countries non-tradable 3 productivity is even declining

2

1

0

-1 20 ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA

Territorial aspects of, and strategies for developing the tradable sector Mostly urban Mostly intermediate Mostly rural Music and Sound Recording Communications Equipment and Services Video Production and Distribution Share of total Biopharmaceuticals Financial Services employment in Insurance Services Marketing, Design, and Publishing Business Services clusters by type Aerospace Vehicles and Defense Tobacco of TL2 region Information Technology and Analytical Instruments Performing Arts Oil and Gas Production and Transportation Downstream Chemical Products Mostly urban Distribution and Electronic Commerce Recreational and Small Electric Goods Education and Knowledge Creation regions are those Printing Services TOTAL with at least 70% of Local clusters (non-traded) Hospitality and Tourism its population living Environmental Services Upstream Chemical Products in Functional Urban Medical Devices Transportation and Logistics Areas or part of its Upstream Metal Manufacturing Production Technology and Heavy Machinery population living in a Construction Products and Services Metal Mining large metro area Plastics Metalworking Technology with at least 1.5 Paper and Packaging Downstream Metal Products Vulcanized and Fired Materials million inhabitants. Food Processing and Manufacturing Lighting and Electrical Equipment Mostly rural regions Automotive Electric Power Generation and Transmission have less than 50% Textile Manufacturing Wood Products of their population Jewelry and Precious Metals Water Transportation living in FUAs Furniture Coal Mining Livestock Processing Appliances Source: OECD Nonmetal Mining Agricultural Inputs and Services Regional Statistics Apparel Fishing and Fishing Products and Ketels and Leather and Related Products Forestry Footwear Protsiv (2016) 0 10 20 30 40 50 60 70 80 90 100 Share of FTE employment in the cluster, % Urban areas attract more knowledge- intensive firms

Birth shares by sector (births by sector/total regional births) TL3 regions (15 OECD countries) 2014

23 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 Disparities of household income are large within regions, mainly in capital cities Gini index of disposable income (after tax and transfers), 2013 #REF! Regional value National average

0.55

Oaxaca Santiago 0.5 Metropolitan District Northeastern of Anatolia Columbia West 0.45 Jerusalem District South Ceuta East England 0.4 Western Brussels Australia Sicily Capital Estonia North Attiki Ticino Central Region Region Island North Southern Vienna 0.35 Holland Ontario and Hokkaido Ile-de-France Hesse Eastern Stockholm Central Oslo and Hungary Prague Akershus 0.3 Bratislava Capital Region Åland Eastern Slovenia 0.25

0.2

26 Source: OECD Income Distribution Database and OECD Regional Well-being database Larger cities are more unequal

Metropolitan population and income inequality, circa 2014 Metropolitan size and inequality, once controlled for income levels and country effect Calgary 0.25 McAllen Brussels Miami Albuquerque ​ Toronto Houston ​ ​ Osorno New York Fresno Dallas ​ Los Angeles ​ Clev eland Philadelphia ​ Toluca ​ San Francisco Pachuca de​ Soto​ ​ ​ ​ Atlanta Paris ​ Las Vegas Malmö ​ Napoli​ 0.2 ​ ​ Temuco ​ Memphis​ ​ ​ ​ ​ ​ Boston​ Milano ​ Toulouse ​ Red Deer​ Rouen Oslo Roma ​ Torreón Iquique​ ​ Liège León ​ ​ ​ Windsor​ ​ Cincinnati​ Guadalajara Mex ico City ​ ​ Saint-Etienne​ ​ Denv er Montreal Lethbridge ​ ​ ​ ​ Tijuana​ Portland ​ ​ Antofagasta Hermosillo​ ​ ​ Antw erpen ​ ​ ​ ​ ​ Thunder​ Bay​ ​ Omaha ​ Brant Rancagua ​ Washington 0.15 ​ ​ Buffalo Rey​ ​ nosa Punta​ Arenas ​ ​ ​ ​ San Antonio Sherbrooke Linares Trois Rivières Albany ​

Québec Gini coefficient Gini coefficient (component plus residuals)

0.1 Calera

0.05 10 11 12 13 14 15 16 17 27 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. Designing the Inclusiveness Composite Indicator (Work in Progress)

Variables Weight Unemployment Long-term unemployment Equal weighting Low-work intensity household was selected after PCA Deprivation rate assigned Poverty rate similar weights to all NEET rate indicators Educational attainment: primary education Designing the Inclusiveness Composite Indicator

What it does What it does not do • Reduce the data from a multidimensional frame to a • Provide a measure of income single dimension, simplifying its inequality interpretation • Act as an indicator of overall • Concentrate on the inclusion of well-being the most disadvantaged individuals in society • Include data on access to basic services (future development) • Provide a way to measure regional differences within the same country and across countries

Comparing 70 regions across 8 OECD

countries 3

Stockholm

Southern and Eastern Hovedstaden 2

Helsinki-Uusimaa Syddanmark

1 MadridPaís Vasco Lazio Trento Bratislavský kraj Cataluña Veneto Sydsverige Etelä-Suomi

0 Ceuta Praha Andalucía

Labourproductivity Sicilia Molise

Puglia -1

Západné Slovensko

Severozápad -2 -2 -1 0 1 Inclusiveness Composite Indicator

Czech Republic Denmark Finland Ireland Italy Slovakia Spain Sweden Conclusion: Can integration into global trade (and into GVCs) further spatial inclusiveness?

• 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 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). THANK YOU