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OECD urban-relatedwork

Presentation on OECD urban-related work by Rudiger Ahrend, Head of Urban Work, Regional Development Policy Division.


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OECD urban-relatedwork

  1. 1. OECD URBAN- RELATED WORK Rudiger Ahrend, Head of Urban Programme Public Governance and Territorial Development Brussels, DG Regio & Urban 16/11/2016
  2. 2. • 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
  4. 4. Administrative boundaries are not the answer 4
  5. 5. • 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. 6. 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
  8. 8. 8 The 21st century is witnessing urbanisation on an unprecedented scale
  9. 9. 9 Urbanisation alone is not enough for economic development
  10. 10. • 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?
  12. 12. 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. 13. 13 Bigger cities are more productive
  14. 14. • 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
  15. 15. City productivity increases with city size even after controlling for sorting 15
  16. 16. Heterogeneity: bigger is better 16 Spain United States
  17. 17. Heterogeneity: borders matter(ed) 17 Germany Mexico
  18. 18. Heterogeneity: distance matters 18 Netherlands United Kingdom
  19. 19. Netherlands Heterogeneity: distance matters 19 excluding FUAs that border a metropolitan area (light blue) United Kingdom
  20. 20. Distance matters - Productivity differentials and distance to London 20 Scotland
  21. 21. • 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?
  22. 22. • 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. 23. 23 Percentage of Sydney jobs reached in 60 minute journey by public transport Source: Kelly / Mares 2013
  24. 24. 24 Percentage of Sydney jobs reached in a 45 minute journey by car Source: Kelly / Mares 2013
  25. 25. 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
  26. 26. • 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
  28. 28. 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
  29. 29. 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)
  30. 30. • 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
  31. 31. Why do we care about Metropolitan governance?
  32. 32. 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
  33. 33. Degree of administrative fragmentation in large OECD Metropolitan areas 33
  34. 34. 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. 35. 35 Less fragmented urban agglomerations have experienced higher economic growth
  36. 36. 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. -.05 0 .05 .1 .15 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
  37. 37. What do we know about Metropolitan governance?
  38. 38. • 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%
  39. 39. 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
  40. 40. 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
  41. 41. 3.9 12.0 3.4 25.4 6.4 21.2 373 Transfers - Subnational level Transfers - Government Transfers - Municipalities Service provision fees Charge member fees Other sources** MGB can levy taxes Source: 2nd Metropolitan Governance Survey, n = 56 Median per capita budget (USD) by source of funding
  42. 42. 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
  43. 43. 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
  44. 44. What are the effects of Metropolitan governance?
  45. 45. • 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 Governance Body Without Governance Body Change in Urban Sprawl
  46. 46. Governance bodies can increase well-being 55% 60% 65% 70% 75% 80% With Transport Authorities Without Transport Authorities 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.
  47. 47. • 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
  49. 49. Space matters: proximity to cities benefits surrounding rural & intermediate regions 49
  50. 50. 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
  51. 51.  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-.2 0 .2.4.6 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
  52. 52. 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
  53. 53. • 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
  54. 54. • 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
  55. 55. 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
  57. 57. 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
  58. 58. 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
  59. 59. 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 Iquique Los 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 Harrisburg Madison Wichita Celaya Linz Little Rock Graz Des Moines Charleston Catania Columbia Montpellier Richmond Colorado Springs Baton Rouge Grenoble Malmö Benito JuárezRennes Rouen 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 Nice Morelia 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 Austin Cleveland Torino Columbus Lyon Toluca Kansas City Cincinnati Stockholm Las Vegas Copenhagen Baltimore Sacramento/Roseville San Antonio Orlando Puebla Portland Bruxelles / Brussel Denver Saint Louis Wien SeattleSan DiegoBoston Minneapolis Philadelphia DetroitNapoli Roma Phoenix Milano Monterrey Atlanta Guadalajara Dallas Washington Miami Houston Santiago San Francisco Chicago Los AngelesNew York Mexico City .05 .1 .15 .2 .25 10 12 14 16 18 Ln of total metropolitan population
  60. 60. 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)
  62. 62. 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
  63. 63. 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)
  64. 64. 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
  66. 66. • 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
  67. 67. 0 5000 10000 15000 20000 25000 30000 35000 Property (buildings, infrastructure) Land Machinery & Equipment Inventories Other natural resources Intellectual property Other non financial assests Cultivated biological resources 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
  68. 68. 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)
  69. 69. Land use in urban cores and commuting zones in Europe Urban Cores 0 102030 0 200 600400 800 1000 0 102030 0 200 600400 800 1000 Numberofmetropolitanareas Developed land per capita in m² Developed land per capita in m² Commuting zones Source: OECD calculations based on Corine Land Cover data
  70. 70. 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
  71. 71. -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)
  72. 72. Car use is lower in denser regions 0.025ha0.018ha 0.14ha 1ha 0 30 60 90 120 Number 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
  73. 73. 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
  74. 74. Restrictive land use policies can lead to rising housing costs Annualchangehouseprices (2000-2012) 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%
  75. 75. 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
  76. 76. • 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
  77. 77. 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
  78. 78. 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
  79. 79. 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
  80. 80. 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
  81. 81. 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
  82. 82. 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
  84. 84. • 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.
  85. 85. • 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 85
  86. 86. 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.
  87. 87. 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)
  88. 88. 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)
  89. 89. 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 16 15 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
  90. 90. 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
  91. 91. 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 91