OECD URBAN-RELATED WORK

Rudiger Ahrend, Head of Urban Programme Public Governance and Territorial Development Brussels, DG Regio & Urban 16/11/2016

• Internationally comparable cities

• Urbanisation and its consequences

• Productive Cities

• Metropolitan Governance

• Rural-Urban linkages

• Inequality / inclusive growth

• Well-being

• Land use

• National Urban Policy

OUTLINE

2

INTERNATIONALLY COMPARABLE CITIES

3

Administrative boundaries are not the

answer

4

• Definition of Functional Urban Areas based on population density in 1km2 cells that are matched to municipal boundaries and connected via commuting patterns.

• Urban centres are identified by aggregating densely populated 1km2 cells. Urban centres with at least 50,000 inhabitants are kept.

• They are matched with the boundaries of the lowest administrative level for which statistical data is typically available (NUTS5/LAU2)

• Urban centres and the less densely populated municipalities in the commuting zone are combined into Functional Urban Areas based on commuting flows (>15%).

• More info: OECD (2012) Redefining Urban

• http://measuringurban.oecd.org

A functional definition for cities

(EU/OECD)

5

6

Looking at economic agglomerations:

15 Megacities and a different “top 20”

FUAs Statutory cities

City Population (millions) City Population (millions)

Shanghai 34.0 Shanghai 22.3

Guangzhou 25.0 Beijing 18.8

Beijing 24.9 Chongqing 15.7

Shenzhen 23.3 Tianjin 11.1

Wuhan 19.0 Guangzhou 11.1

Chengdu 18.1 Shenzhen 10.4

Chongqing 17.0 Wuhan 9.8

Tianjin 15.4 Dongguan 8.2

Hangzhou 13.4 Chengdu 7.4

Xian 12.9 Foshan 7.2

Changzhou 12.4 Nanjing 7.2

Shantou 12.0 Xian 6.5

Nanjing 11.7 Shenyang 6.3

Jinan 11.0 Hangzhou 6.2

Haerbin 10.5 Haerbin 5.9

Zhengzhou 9.7 Shantou 5.3

Qingdao 9.6 Jinan 4.3

Shenyang 7.7 Zhengzhou 4.3

Wenzhou 7.6 Changchun 4.2

Nanchang 7.4 Dalian 4.1

Source: OECD Urban Policy Report China, based on clculations of NBS data, via IPLE/CASS for the FUAs; NBS data from the China Statistical Yearbook 2010.

FUAs and statutory cities, 2010 – total population

URBANISATION AND ITS CONSEQUENCES

7

8

The 21st century is witnessing urbanisation on an unprecedented scale

9

Urbanisation alone is not enough for economic development

• Large cities have benefits and costs…

• Overall, individuals generally benefit from living in well-functioning cities, and millions even choose to live in poorly functioning ones.

10

Are cities good for their residents?

PRODUCTIVE CITIES

11

12

Why do we care about productivity

in cities?

• A country’s productivity is, in large part, determined by the productivity of its cities.

• Large urban agglomerations account for over 50% of total GDP while taking up less than 5% of total surface area.

• GDP per capita increases with city size: for a doubling of city size by roughly 16%.

• This is in part a result of higher participation rates in cities. Another part comes from sorting, as better educated individuals have a tendency to live and work in larger cities.

• However, productivity also increases even when controlling for sorting.

13

Bigger cities are more productive

• Sources of agglomeration from Marshall (1890); reviews by Rosenthal and Strange (2004), Puga (2010); concepts already present in Marshall (1890).

• Thicker labour markets: labour market pooling; better matching

• gain from reduced labour acquisition and training costs in thick local labour markets with abundant specialised labour force

• Sharing facilities, inputs, gains from specialisation

• firms may face lower costs for specialised non-traded inputs that are shared locally in a geographical cluster.

• Knowledge spillovers

• face-to-face contact can enable tacit knowledge spillovers through increases in the intensity of the interactions with other firms or individuals

• Probably also : Connectivity, Knowledge based capital

14

Sources of agglomeration benefits

City productivity increases with city size

even after controlling for sorting

15

Heterogeneity: bigger is better

16

Spain

United States

Heterogeneity: borders matter(ed)

17

Germany

Mexico

Heterogeneity: distance matters

18

Netherlands

United Kingdom

Netherlands

Heterogeneity: distance matters

19 excluding FUAs that border a metropolitan area (light blue)

United Kingdom

Distance matters - Productivity differentials and distance to London

20

Scotland

• The productivity increase associated with increasing a city’s population are in the order of 2-5.0% for a doubling in population size.

– This implies, e.g., that moving from a city of roughly 50000 inhabitants to the Paris agglomeration – on average - increases productivity by an order of magnitude of 20%.

• Smaller cities can “borrow” agglomeration benefits

• Human capital (spill-overs)

– 10 percentage point increase in university graduates increases productivity by 3% through human capital externality

– Direct effects are even a lot larger

21

What makes cities rich?

• Adequate governance structures with administrative functions carried out at the “right” level – Low fragmentation at metropolitan level; governance bodies

• Position of hub for trade or financial flows or status as national capital can facilitate rent extraction – Port cities 3% more productive

• Specialization in certain types of activities – Cities with higher share of manufacturing, finance and business

services (or high tech) have higher levels of productivity.

– Potential trade-off specialisation vs. resilience (especially for smaller cities)

• Good (in particular) public transport infrastructure prevents fragmented labour markets

22

What makes cities rich?

23

Percentage of Sydney jobs reached in

60 minute journey by public transport

Source: Kelly / Mares 2013

24

Percentage of Sydney jobs reached

in a 45 minute journey by car

Source: Kelly / Mares 2013

Higher productivity comes with higher prices

25

– Overall, gains from agglomeration, but local purchasing power does (on average) not increase with city size

Agglomeration benefits and local price levels in Germany

• Local purchasing power varies widely around the average, and amenities can explain a significant share of the variation

• Residents are willing to pay for local amenities – Proximity to large bodies of water (coast or lake), cultural attractions

(theatres/operas/etc.) and UNESCO World heritage sites make cities relatively more expensive

• Disamenities require compensation – PM10 air pollution reduces local price level relative to productivity

benefits

• More educated individuals appear to be willing to pay more for amenities; also, the share of university educated workers seems to be a local amenity in itself.

Differences in local purchasing power are partly driven by amenities

26

METROPOLITAN GOVERNANCE

27

Metro governance reforms in the OECD

have accelerated in recent decades

Number of metropolitan governance structures created or

reformed in the OECD, by decade

0

5

10

15

20

25

30

35

40

45

50

1951-1960 1961-1970 1971-1980 1981-1990 1991-2000 2001-2010

Recent country-wide metro governance

reforms across the OECD

Turkey: creation of metropolitan provinces

Australia: regional-led initiatives to create metro governance bodies

France: new governance structures for the 14 biggest urban areas

United Kingdom: “city deals” incentivise cities to improve metro cooperation

Italy: 10 provinces become metropolitan cities (città metropolitane)

• Growing recognition that administrative boundaries are often outdated and don’t match the functional realities in Metropolitan areas

• Evidence that excessive municipal fragmentation hampers metropolitan economic performance and wellbeing

What are the drivers of metropolitan

governance reforms?

30

Why do we care about Metropolitan governance?

Horizontal administrative fragmentation is common as cities outgrow their historic boundaries (more than 10 local governments in 75% of OECD Metropolitan Areas; more than 100 in 22%).

This may lead to undesirable outcomes due to lack of cooperation and negative externalities.

Evidence from case studies points to administrative fragmentation indeed having negative effects.

This is confirmed by more systematic econometric evidence:

Ahrend, Farchy, Kaplanis and Lembcke (2014), “What Makes Cities More Productive? Agglomeration Economies & the Role of Urban Governance: Evidence from 5 OECD Countries”, forthcoming in Journal of Regional Science

Urban areas are highly fragmented

32

Degree of administrative fragmentation

in large OECD Metropolitan areas

33

City productivity & administrative

fragmentation

34

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

• Productivity falls by 6% for a doubling in number of municipalities

(for given population size)

35

Less fragmented urban agglomerations have experienced higher economic growth

Higher administrative fragmentation is associated with higher

segregation of people in different municipalities

36

Hypothesis: Fragmented metropolitan governance can facilitate segregation at the level of local units.

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0 .2 .4 .6 .8 1

Administrative fragmentation

Controlling for country fixed effects and other city characteristics (i.e. income , population, spatial structure), higher administrative fragmentation is associated to higher spatial segregation by income in different municipalities

What do we know about Metropolitan governance?

• Approximately 280 metropolitan areas with more than 500,000 inhabitants exist in OECD countries

• Two-thirds of them have some form of metropolitan authority

• Great variety in tasks and competencies

Metropolitan authorities

No metropolitan authority

31%

Metropolitan authority without

regulatory powers

51%

Metropolitan authority with

regulatory powers

18%

21.2

78

1.5

15.5

0

10

20

30

40

50

60

70

80

90

Median Budget, USD per capita Median Staff

Legislative/Regulatory Powers No Legislative/Regulatory Powers

Source: 2nd Metropolitan Governance Survey, n = 56

MGBs with regulatory powers have larger

staff and higher per capita budgets

Fields of activity of surveyed MGBs

40

78.6%

66.1%

46.4%

25.0%

23.2% 23.2% 14.3% 12.5% 12.5% 8.9%

12.5%

17.9% 39.3%

21.4%

35.71%

12.50%

32.1%

1.8% 1.8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Fields of activity of surveyed MGBs

Primary Field Secondary Field

3.9

12.0

3.4

25.4

6.4

21.2

373

0

5

10

15

20

25

30

35

40

45

50

Transfers -Subnational

level

Transfers -Government

Transfers -Municipalities

Serviceprovision fees

Chargemember fees

Othersources**

MGB can levytaxes

Source: 2nd Metropolitan Governance Survey, n = 56

Median per capita budget (USD) by source

of funding

62.5% 64.3% 42.9%

30.4% 16.1%

25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Local Governments(Municipalities)

Subnational Governments National Governments

A leading role A minor role

Source: 2nd Metropolitan Governance Survey, n = 56

Role of different levels of governments

in establishing MGBs

44.6%

23.2%

23.2%

7.1%

1.8%

Mandated by national/state law

National or State law, non mandatory

Voluntary but enforceable agreement

Entirely informal agreement

Home rule charter

Source: 2nd Metropolitan Governance Survey, n = 56

Legal basis of surveyed MGBs

What are the effects of Metropolitan governance?

• Urban sprawl creates negative externalities in Metropolitan areas (MAs)

• Cooperation is a way to internalize the externalities when making policy decisions

• -> Sprawl decreased in MAs with governance body, but increased in those without!

Governance bodies can reduce sprawl

Difference significant at the 99%-level after controlling for log-population levels and country specific trends.

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

With GovernanceBody

Without GovernanceBody

Change in Urban Sprawl

Governance bodies can increase well-being

55%

60%

65%

70%

75%

80%

With TransportAuthorities

Without TransportAuthorities

Share of Citizens Satisfied with Public Transport • Citizens are more

satisfied in MAs that have sectoral authorities for public transport

• Those MAs have also lower pollution levels (PM)

Based on European Urban Audit perception survey. Difference significant at 95% level.

• Within countries, cities with fragmented governance structures have lower levels of productivity.

– For a given population size, a metropolitan area with twice the number of municipalities is associated with 5-6% lower productivity.

• Effect mitigated by almost half when a governance body at the metropolitan level exists.

47

Governance bodies positively affect economic productivity

RURAL URBAN LINKAGES

48

Space matters: proximity to cities benefits

surrounding rural & intermediate regions

49

Sources of catching-up: proximity to

cities

50

Rural remote regions present a higher variation in productivity growth rates than other types of regions

Annual average labour productivity

growth, 2000-12 Standard deviation

Coefficient of variation

Predominantly urban

1.01% 1.02% 1.019

Intermediate 1.07% 1.09% 1.024

Predominantly rural close to

cities 1.36% 1.32%

0.972

Predominantly rural remote

0.70% 1.15% 1.641

Note: Labour productivity is defined as real GDP per employee. GDP is measured at PPP constant 2010 US Dollars, using SNA2008 classification; employment is measured at place of work. The coefficient of variation represents the ratio of the standard deviation over the mean.

Source: OECD Regional Outlook 2016

The variability of growth rates is much higher in rural areas than for the other types of region.

Part of this variability can probably be explained by looking at the role of the relationships with Urban or Intermediate regions (urban-rural linkages).

-.4

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Urban Intermediate Rural

Population growth rates (2000-2009) in OECD TL3 regions, by typology

U.S., Canada, Chile, Mexico, Israel and Iceland are excluded from the analysis for reasons of data availability

Rural regions show the highest variability in population growth and positive growth for close to a urban areas

51

Why are we interested in urban-rural partnerships?

Rural and urban areas are interconnected through different linkages (commuting, provision of amenities, transportation, economic transactions etc.)

The way these linkages are governed has an impact on the economic development and people’s wellbeing both in urban and rural communities

Better understanding of interdependencies (unit of analysis = self-contained space of relationship, functional region)

Design governance solutions to facilitate an integrated approach that improves the outcome of the rural-urban partnerships 52

• Facilitates production/sharing of public goods (good for economy & well-being)

• Helps with joint financing where adequate, as well as with exchange of information and experience. The latter exchange contributes to building up local capacity, in particular in smaller communities.

• Given their complementarity, a stronger integration between cities and their surrounding rural areas can strengthen the position in the competition among regions as well as globally.

Benefits of rural-urban cooperation

53

• Allows to reduce negative externalities between urban & rural areas. In particular, in functionally (but not administratively) integrated regions, a lack of coordination of spatial planning can have strong negative consequences, including sprawled out settlement patterns.

– drive up the cost of basic infrastructure provision & create multiple other problems (e.g. congestion).

• Large variation of situations:

– Functional regions already acknowledged formally as planning regions and endowed with planning instruments

– Functional regions acknowledged as planning regions

– Functional regions not endowed neither with management instruments nor with planning instruments

Benefits of rural-urban cooperation

54

High heterogeneity of approaches to rural-urban cooperation

The governance model of Rurban partnerships varies on the basis of different issues

a) Management oriented vs. project oriented

b) Flexibility of the boundaries

c) Main objectives and domains of intervention

d) Single purpose vs. holistic approach

e) Top down vs. bottom-up processes

f) National framework (degree of formal acknowledgment)

55

INEQUALITY AND INCLUSIVE GROWTH

56

Productivity growth of “frontier” regions

outpaces that of most regions

Notes: Average of top 10% (“frontier”) and bottom 75%/10% (“lagging”) TL2 regions in 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. OECD (2016) OECD Regional Outlook 2016: Productive regions for inclusive societies, http://dx.doi.org/10.1787/9789264260245-en

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 in the gap from

1995-2013

57

Source: Bartolini, D., S. Stossberg and H. Blöchliger (2016), "Fiscal Decentralisation and Regional Disparities", OECD Economics Department Working Papers, No. 1330, http://dx.doi.org/10.1787/5jlpq7v3j237-en.

Convergence of countries vs.

divergence of regions in the OECD

GDP per capita dispersion

is now greater within

countries than between

countries

58

Income inequalities are large within metropolitan areas and bigger

cities are on average more unequal

59

Metropolitan population and income inequality, circa 2014 (controlled for income levels and country effect)

Calera

San Fernando

Linares

Quillota

Ovalle

Melipilla

San Antonio

Punta Arenas

Calama

Curicó

Osorno

Valdivia

Copiapó

IquiqueLos Angeles

AricaChillán

Puerto Montt

Talca

AalborgOdenseRancagua

Antofagasta

Temuco

Coquimbo-La Serena

Aarhus

Toledo

Akron

Saint-Etienne

Irapuato

Venezia

Pachuca de Soto

Toulon

Bari

Gent

Durango

HarrisburgMadison

Wichita

Celaya

Linz

Little Rock

Graz

Des MoinesCharleston

Catania

Columbia

Montpellier

Richmond

Colorado Springs

Baton RougeGrenoble

Malmö

Benito JuárezRennesRouen

Albany

Providence

Genova

Grand RapidsSaltillo

Firenze

Reynosa

Oaxaca de Juárez

XalapaLiège

Tuxtla Gutiérrez

Bologna

Strasbourg

Dayton

Tampico

VeracruzHermosillo

McAllen

Acapulco de Juárez

Chihuahua

El Paso

NiceMorelia

Culiacán

Omaha

Nantes

Centro

Cuernavaca

Göteborg

Albuquerque

Concepción

Tulsa

Mexicali

Palermo

Birmingham

Aguascalientes

Valparaíso

Tucson

Buffalo

FresnoFort Worth

AntwerpenRaleigh

Norfolk-Portsmouth-Chesapeake-Virginia beach

Querétaro

Bordeaux

New Orleans

Clearwater/Saint Petersburg

San Luis Potosí

Luisville

Toulouse

JacksonvilleOklahoma city

Salt Lake City

Nashville

Memphis

Torreón

Mérida

Juárez

Lille

Pittsburgh

Tampa

Charlotte

Tijuana

León

Milwaukee

Indianapolis

Marseille

AustinCleveland

Torino

Columbus

Lyon

Toluca

Kansas CityCincinnati

StockholmLas Vegas

Copenhagen

BaltimoreSacramento/Roseville

San AntonioOrlando

Puebla

Portland

Bruxelles / Brussel

Denver

Saint Louis

WienSeattleSan DiegoBoston

Minneapolis

Philadelphia

DetroitNapoli

Roma

Phoenix

Milano

Monterrey

Atlanta

Guadalajara

Dallas

Washington

MiamiHouston

Santiago

San FranciscoChicago

Los AngelesNew York

Mexico City

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5.2

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10 12 14 16 18Ln of total metropolitan population

Top income households tend to segregate the most in

neighbourhoods, in Canada, France and US; while bottom income

households in the Netherlands

60

Spatial segregation by income, neighbourhood scale (entropy index)

WELL-BEING IN CITIES

61

Why look at well-being at local level? A framework for measuring local well-being

62

- Measures well-being where people live (the importance of the scale e.g. functional urban areas or city-regions)

- Focus on outcomes rather than output

- Multidimensionality

- Focus on distributions of outcomes

- Assess how well-being changes over time (resilience, sustainability)

- It considers that well-being can be manageable to change by citizens, governance and institutions

Main features

Well-being outcomes can be very different across

cities in the same country

Income • 33,500 USD household

income between Washington D.C. and McAllen (around 30,000 USD among OECD countries)

• Gini index of household income between Celaya and Mexico City 0.12 (around 0.24 among OECD countries)

Jobs • 17pp in the unemployment rate

of Las Palmas and Bilbao (23pp among OECD countries)

• 36pp in the employment rate between Firenze and Palermo (32pp among OECD countries)

Environment • 23 mg/m3 in the level of air

pollution (PM2.5) between Cuernavaca and Mérida (21 among OECD countries)

Differences between highest and lowest values in metropolitan areas

Education • 21pp in the share of workforce

with tertiary education between The Hague and Rotterdam (26pp among OECD countries)

Life expectancy is not homogeneous within cities Differences across municipalities within the same city-region can go up to

more than 5 years (Copenhagen)

64

GOVERNANCE OF LAND USE

65

HTTPS://YOUTU.BE/JUV3GEVERB4

• Need to find a balance between sustainability, liveability and affordability

• Formal planning instruments can be slow to respond to change and foster innovation

• Policies outside of the planning system need to be aligned with land use objectives—particularly subnational finances and tax policies

Land use policies to foster green and

inclusive growth

0

5000

10000

15000

20000

25000

30000

35000

Property(buildings,

infrastructure)

Land Machinery &Equipment

Inventories Other naturalresources

Intellectualproperty

Other nonfinancialassests

Cultivatedbiologicalresources

Land and property are by far the most

important forms of capital

Disaggregated capital stock (six-country sample) U$ billion PPP

Note: Data includes Australia, Canada, Czech Republic, France, Japan and Korea. Source: OECD National Accounts Table 9B

The amount of developed land per capita in

urban areas differs across the OECD

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Developed land per capita in urban cores (in m²) Developed land per capita in commuting zones (in m²)

Source: OECD calculations based on Corine Land Cover and National Land Cover Database

Developed land per capita in urban areas

*All data is based on the OECD definition of Functional Urban Areas (FUAs)

Land use in urban cores and commuting

zones in Europe

Urban Cores

010

20

30

0 200 600400 800 10000

10

20

30

0 200 600400 800 1000Nu

mb

er

of

metr

op

olita

n a

rea

s

Developed land per capita in m² Developed land per capita in m²

Commuting zones

Source: OECD calculations based on Corine Land Cover data

Developed land is growing everywhere…

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

Annual % growth of developed land in commuting zone Annual % growth of developed land in core

Annual growth rates of developed land between 2000 and 2012

Source: OECD calculations based on Corine Land Cover and National Land Cover Database

-1.0%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

Annual percentage change in developed land per capita 2000 - 2012

…but per capita land use is declining in

many countries

Per capita growth of developed land in functional urban areas (cores and commuting zones combined)

Car use is lower in denser regions 0.0

25ha

0.0

18ha

0.1

4ha

1ha

Develo

ped land p

er

capita

0 30 60 90 120Number of vehicles per 100 inhabitants

European TL3 regions Estimated relationship

Source: OECD calculations based on Corine Land Cover and National Land Cover Database Note: The positive relationship between land cover and car ownership is robust to controlling for per capita GDP levels and country fixed-effects.

Regions with 10% less developed land per capita have 0.75 fewer cars per 100 inhabitants

Housing costs have risen strongly in most

OECD countries

Inflation-adjusted property prices (1995=100)

0

50

100

150

200

250

300

350

400

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Australia Belgium Canada Switzerland Germany

Denmark Spain Finland France United Kingdom

Ireland Italy Japan Netherlands Norway

New Zealand Sweden United States Average

Sweden

Japan

Ireland

UK

Germany

Norway

Restrictive land use policies can lead to

rising housing costs

An

nu

al

ch

an

ge

ho

us

e p

ric

es

(2

00

0-2

012

)

Annual change in developed land per capita (2000-2012)

• Land use regulations should aim to prevent sprawl…

• …but have to provide sufficient space to construct housing for growing populations

• Otherwise, housing costs rise

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

-1.0% -0.5% 0.0% 0.5% 1.0%

Very little densification is taking place

• Very little densification of building stock on-going since 2000

• Less than 0.01% of developed land in data has changed to a higher density class in Europe; less than 1% has changed in the U.S.

• Caveat: existing data not ideal to measure density; only two density classes for Europe; four density classes for the U.S.

Europe United States

Densified land since 2000/01

Land with constant density since 2000/01

Source: OECD calculations based on Corine Land Cover and National Land Cover Database

• Many cities have densities similar to when they were much smaller Low density neighbourhoods that were once at the urban fringe are now within urban cores without having densified

• Sufficiently high densities are needed to adapt urban form, allow for efficient public transport and build housing for greater populations

• Public spaces need to be of high quality in denser environments to ensure well-being

Sufficiently high density of high quality

is needed

How to make planning more flexible and

foster good land use?

How land is used

Public policies aimed at steering land use

• Spatial planning • Transport planning • Land use planning • Environmental regulations • Building code regulations

Public policies not targeted at land use

• Tax policies • Transport taxes and subsidies • Fiscal systems and inter-

governmental transfers • Agricultural policies • Energy policies

How land is permitted to be used How individuals and businesses want to use land

Fiscal and tax systems incentivise:

i. local governments’ planning policies

ii. land use decisions by firms and individuals

Incentives need to be better aligned with land use objectives

Aligning fiscal and tax incentives to land

use objectives

Examples: How fiscal and tax systems

influence land use

In some countries, local governments obtain a large share of revenues from business taxes

Local governments have incentives to allocate as much land as possible to commercial uses to maximise tax revenues.

In some countries, ownership of single-family homes receives

preferential tax treatment

Residents have incentives to live in low-density neighbourhoods in

sub-urban areas

Examples: How fiscal and tax systems

influence land use

Agriculture is heavily subsidised across most of the OECD

Without subsidies, agricultural land uses would change

Many countries make expenses for commuting by car tax

deductible

Lower costs of commuting provide incentives to live further from the place of work (often in peri-urban areas) and increase

car reliance

Key message: Need to pay greater attention

to incentives

• By paying greater attention to the incentives that public policy provides for land use, planning can become less restrictive and more effective

• Taxes and fiscal systems matter most

• Regulatory and economic instruments need to be combined

Effective governance mechanisms are a prerequisite for a successful implementation

Incentive-based land use policies

require monitoring and evaluation

• The use of fiscal instruments to steer land use can result in land patterns that are more desirable but at the same time less predictable

• Systematic evaluations of land use policies are lacking

• Knowledge about evaluation practices is rare

– data on land use and land use regulations is scarce

NATIONAL URBAN POLICY

83

• Most people live in cities. Governments that ‘get cities right’ can improve overall well-being.

• Cities are also complex dynamic systems, in which the actions of households and firms, as well as the interactions among different strands of public policy, typically have large positive or negative spill-over effects on others.

• Cities affect national economic, environment and social outcomes.

Cities provide opportunities for higher levels of government to address these in a coherent, integrated way.

84

National Urban Policy Frameworks: Why

are they needed?

Density of settlement and activity implies greater policy complexity and greater need for policy co-ordination, particularly in periods of dynamic change.

• National policies affect urban development

National legislation establishes the ground rules for cities.

National governments intervene directly in a large number of policy domains that affect cities – yet explicit national urban policies are often narrowly conceived.

Inter-municipal co-ordination needs support from above.

• Major domestic policy challenges require a multi-level approach:

Neither cities nor national governments alone can address the main competitiveness challenges.

Environmental policies have a strong, place-based dimension, especially in cities.

Inclusive growth requires both economy-wide and local measures.

Policy coherence across levels of

government requires national leadership

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Report for Habitat III evaluates state of

NUP in OECD countries.

• NUPs can be a key tool to support the implementation of the New Urban Agenda and other global agreements.

• OECD countries have still scope in the development of NUP.

• Only 15 OECD countries have explicit NUP (of which 5 in formulation stage) but almost 90% have partial urban policies.

• Climate change resilience and human development receive a weaker attention within the NUPs of OECD countries.

Out of the 35 OECD countries, only 15 have an

explicit national urban policy.

Figure 1.2. Urbanisation and economic development

2013

Notes: Urban Areas as defined by national statistical offices.

Source: World Development Indicators (World Bank, 2014)

• However, almost 90% of OECD counties have partial elements of NUPs in their urban landscape.

Type of National Urban Policies in 35 OECD countries

15 15

5

0

2

4

6

8

10

12

14

16

Explicit Partial No NUP

Number of countries

Source: OECD survey on National Urban Policies (2016)

Majority of countries have the NUPs in the

implementation stage (40%).

Figure 1.2. Urbanisation and economic development

2013

• Within the 14 countries in implementation stage, five have an explicit NUP.

• Among the countries with explicit NUP are 33% are in formulation stage with a similar proportion in the implementation process.

1

6

14

9

5

0

2

4

6

8

10

12

14

16

Diagnostic Formulation Implementation M&E Not applicable

Number of countries

. National Urban Policies by stage of development in 35 OECD countries

Source: OECD survey on National Urban Policies (2016)

Climate resilience receives the weakest degree

of attention by NUPs in OECD.

• Economic development is the most extensively covered sector by NUP in OECD countries. It receives strong attention by almost 55% of the countries.

19

1615

11

5

0

5

10

15

20

Economic

Development

Spatial Structure Environmental

sustainability

Human

Development

Climate resilience

Number of countries

Source: OECD survey on National Urban Policies (2016)

Areas with extensive scope in National Urban Policies

Large majority of OECD countries have a general

national planning authority to oversee NUPs.

• The majority of OECD countries chose a participatory approach to develop a NUP, which involved a wide range of stakeholders in developing a NUP.

• In most of the OECD countries, the implementation mechanism of NUPs is carried out through a process of national-local level coordination.

3

23

2

7

0

5

10

15

20

25

Specialised Urban

Agency

General National

Planning Authority

Sub-National Agency Not applicable

Number of countries

Source: OECD survey on National Urban Policies (2016)

Type of urban agency in 35 OECD countries

The presentation draws from:

Ahrend, Farchy, Kaplanis and Lembcke (2014), “What Makes Cities More Productive? Agglomeration economies & the role of urban governance: Evidence from 5 OECD Countries”

Ahrend and Schumann (2014) “Does regional economic growth depend on proximity to urban centres?”

Ahrend, Gamper and Schumann (2014) “The OECD Metropolitan Governance Database: A Quantitative Description of Governance Structures in Large Urban Areas”

OECD, OECD Regional Outlook 2016

OECD (2017), The Governance of Land Use

OECD (2016), Making Cities Work for All

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

OECD (2015) Governing the City

OECD (2012) Redefining Urban: a new way to measure metropolitan areas

Thank you

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