Charles W. Fluharty President & CEO Rural Policy Research Institute

Transcription

1 Presented to the Prosperous Places: Building Economic Competitiveness in Rural Regions and Small Communities Conference Salt Lake City, Utah March 26, 2013 Charles W. Fluharty President & CEO Rural Policy Research Institute

2 I. Recalibrating the rural/urban dialogue and paradigm II. The global rationale for a Regional Rural Innovation strategy III. Is there a rural commitment in current U.S. domestic policy? IV. Rural imperatives, and signs of hope and progress! V. Final reflections: Why your work is so critical

3 I. Recalibrating the rural/urban dialogue and paradigm

4 U.S. Census Bureau Urban and Rural Areas Office of Management and Budget Core Based Statistical Areas Metropolitan and Nonmetropolitan Areas

5 The U.S. Census Bureau defines urban areas: Core blocks and block groups with population density of 1,000 people per square mile. Surrounding blocks with overall density of 500 ppmi 2 Range in size from 2,500 people to nearly 2 million people. Rural is everything that is not urban. Based on the 2010 Decennial Census: 59 million people live in rural areas (19%) 249 million people live in urban areas (81%) 5

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7 New York-Newark Population 1.8 million Hermann, MO Population 2,515

8 These boundaries are only defined every 10 years. Urban area boundaries don t align with boundaries of cities and towns. There is no governmental jurisdiction over Census defined urban areas. Very limited sub-county data challenges more granular understanding, and resource targeting. The most comprehensive data is at the county level. All would agree that some urban places are really much more rural in character.

9 Defined by the Office of Management and Budget. Designed to be functional regions around urban centers. Classification is based on counties. Three classifications of counties: Metropolitan, Micropolitan, Noncore Based on size of urbanized area/urban cluster in central counties and commuting ties in outlying counties.

10 Core Based Statistical Areas Metropolitan Micropolitan Noncore

11 Usually, metropolitan is equated with urban and nonmetropolitan is equated with rural. So, if metropolitan is urban, then

12 This is urban: Los Angeles, California Population 1.2 million

13 And so is this: Armstrong County, Texas Population 2,071 Part of the Amarillo Texas Metropolitan Area

14 And if nonmetropolitan is rural, then

15 This is rural: Loving County, Texas Population 55

16 And so is this: Paducah, Kentucky Population 48,035

17 Most Counties are Both Urban and Rural! Coconino County, Arizona Population 127,450 Flagstaff Metro Area

18 Most metropolitan areas contain rural territory and rural people. In fact 54% of all rural people live in metropolitan counties!

19 Distribution of U.S. Population by Urban and Rural Areas, and Core Based Statistical Areas, 2010 Urbanized Area Urban Cluster Rural Total Metropolitan 219,677,256 10,766,879 32,007, ,452,132 Micropolitan 228,950 13,852,786 13,072,477 27,154,213 Noncore 15,917 4,711,483 14,411,793 19,139,193 Total 219,922,123 29,331,148 59,492, ,745,538 Urbanized Area Urban Cluster Rural Total Metropolitan 99.9% 36.7% 53.8% 85.0% Micropolitan 0.1% 47.2% 22.0% 8.8% Noncore 0.0% 16.1% 24.2% 6.2%

20 II. The global rationale for a Regional Rural Innovation strategy

21 The OECD New Rural Paradigm (2006) Old Paradigm New Paradigm Objectives Key target sector Equalization. Focus on farm income Sector based Competitiveness of rural areas Holistic approach to include various sectors of rural economies Main tools Subsidies Investments Guarantee an adequate attention to rural issues And empower local communities and governments Key actors National governments, farmers Multilevel-governance Rural is not synonymous with agriculture Rural is not synonymous with economic decline

22 NRP and ahead: Modernising the rural economy Identification toward a set of principles Differentiation based on rural characteristics Low density sparsely populated Long distances Lack of critical mass Need to enhance competitiveness Rural areas integrated in global world Differentiated but integrated Rural regions are complex territories Non-core urban areas Innovation and Modernising the Rural Economy Urban to Rural Linkages Project Promoting Growth in all Regions

23 Promoting Growth in all Regions and Rural Development Enrique Garcilazo Regional Development Policy Division Directorate for Public Governance and Territorial Development OECD NACO WEBINAR Washington, 15 th January 2013

24 OECD Territorial Reviews: A series of case studies of regional policy Among 34 member countries : 18 National Territorial Reviews ( +2 in process) 22 Metropolitan Reviews (+1 in process) 2 National Urban Policy Reviews (+1 in process) 6 Regional reviews (+2 in process) 5 review s on regional innovation systems 9+2 National rural Policy Reviews(+1 in process) Alemania, Mexico (2006) Finlandia, Holanda, Escocia (2007) China, Italia, España (2008) Quebec, Canadá (2009) Inglaterra (2010) 24

25 Thematic Reviews -- Rural Factors of regional competitiveness (1) Empirical evidence -- General trends (2) Case studies Field analysis Questionnaires, Peer reviewers, experts Linking Renewable Energy to Rural Development (15) RURAL-URBAN Partnerships Project (16) Policy implications: (3) Implementation Governance

26 OECD Regional Data-Base (RDB) The RDB includes regional statistics on 5 major topics: Demographic, Regional accounts, Labour, Social and environmental indicators, Innovation To facilitate comparability, regions are: Classified in 2 Territorial Levels (TLs): TL2 Territorial Level 2 (337 regions) TL3 Territorial Level 3 (1708 regions) New regions: China, Brazil, South-Africa, Chile etc.. Classified by regional type OECD definition: (PU, I, PR) Extended regional classification (PU, INC, INR, PRC,PRR) Database can be directly accessed from the OECD Statistical portal: OECD explorer: OECD MDB:

27 Promoting growth in all regions Is broader based growth economically viable? Does growth potential exist in some regions? Does it matter for national and aggregate growth?

28 There is no single/unique path to growth

29 Convergence forces in rural regions

30 Convergence forces in intermediate regions

31 The most dynamic OECD regions over pop and GDP growth pop density and GDP growth pop and GDPpc growth average rank (1== highest) population pop density

32 GDP per capita growth in PPP GDP per capita growth in PPP GDP per capita growth in PPP GDP per capita growth in PPP Dynamism in rural regions and population trends 10.0% Intermediate 9.0% 8.0% 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% Population growth, Rural 15% 14% 13% 12% 11% 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% -1% -2% -4% -3% -2% -1% 0% 1% 2% 3% 4% Population growth, Rural close to a city 15.0% 14.0% 13.0% 12.0% 11.0% 10.0% 9.0% 8.0% 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% Population growth, Rural remote 12.0% 11.0% 10.0% 9.0% 8.0% 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% Population growth,

33 NAPLES DEAGU BERLIN MONTREAL VANCOUVER LILLE TAMPA BAY FUKUOKA MANCHESTER LEEDS VALENCIA BIRMINGHAM ANKARA SEOUL KRAKOW MIAMI PHOENIX OSAKA RHINE-RUHR ST.LOUIS PITTSBURGH TORONTO IZMIR ISTANBUL PUEBLA MELBOURNE AUCKLAND BUSAN COPENHAGEN GUADALAJARA BALTIMORE SYDNEY RANDSTAD-HOLLAND TURIN DETROIT PORTLAND MEXICO CITY HANBURG BARCELONA CLEVELAND ZURICH TOKYO DUBLIN AICHI LOS ANGELES FRANKFURT LYON BRUSSELS HELSINKI CHICAGO LISBON OSLO SAN DIEGO STUTTGART MADRID VIENNA PHILADELPHIA ATHENS ATLANTA MILAN MONTERREY MUNICH ROME PRAGUE LONDON BUDAPEST STOCKHOLM DALLAS MINNEAPOLIS NEW YORK DENVER SEATTLE HOUSTON WARSAW PARIS BOSTON SAN FRANCISCO WASHINGTON Concentration high levels of GDP pc GDP per capita national GDP per capita % 79%

34 Initial GDP per worker in PPP but not necessarily faster growth Only 45% of metro--regions grow faster than the national average. Metro-regions appear to have entered in a process of convergence II Atlanta San Francisco Washington I Detroit San Diego Phoenix Osaka III Prague Berlin Dublin Monterrey Busan Budapest Ankara Istanbul Deagu Naples Izmir Puebla Krakow -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% Average annual growth rates in GDP per capita Warsaw IV signs of inefficiencies appear in significant number of metro-regions

35 Contributions to aggregate growth depend on few hub regions the fat tail is equally important -- if not more -- to aggregate growth 35

36 Contribution tooecd growth Contributions to growth OECD TL3 regions 5% 27% of growth driven by 2.4% (or 20) regions... 4% Tokyo 3% 2% 1% Gyeonggi-do Seoul Madrid London West Roma Milano Aichi Barcelona Attiki Miasto Warszaw Dublin Hauts-de-Seine Stockholms län Inner London -- East Chungcheongnam-do Gyeonsangbuk-do Paris München Gyeonsangnam-do...and 73% of growth by the remaining y = x % 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75 % 80% 85% 90% 95% TL3 regions 36

37 Lagging regions contribute to national growth Lagging Regions Contribution to Aggregate Growth lagging leading Australia 29% 71% Austria 53% 47% Canada 26% 74% Czech Republic 62% 38% Finland 35% 65% France 68% 32% Germany 27% 73% Greece -16% 116% Hungary 34% 66% Italy 26% 74% Japan 27% 73% Korea 23% 77% Mexico 44% 56% Netherlands 49% 51% Norway 61% 39% Poland 44% 56% Portugal 54% 46% Slovak Republic 67% 33% Spain 48% 52% Sweden 58% 42% Turkey 47% 53% United Kingdom 57% 43% United States 51% 49% average unweighted 43% 57% average weighted 44% 56% Overall, they contributed to 44% of aggregate OECD growth in In eight OECD countries lagging regions contributed more to national growth than leading regions. Bottom line: support for lagging regions need not be merely a social policy. They contribute a large share of national growth. 37

38 Analytical approach: Compare indicators relevant for regional growth b/w growing and underperforming group Population density GDP density Employment rate Unemployment rate Youth unemployment rate Patent applications Patent intensity Business R&D to GDP Government R&D to GDP Higher education R&D to GDP Primary attainment rate Tertiary attainment rate Connectivity in global network Economic mass/thickness of market economies of agglomeration Labour utilisation Innovation related indicators Human capital Geography/NEG Productivity Infrastructure

39 Performance of all growing regions associated Growth factor Productivity Productivity (GDP per employee) 31,612 29,728 55,832 50,728 72,551 59,824 Infrastucture Motorway density Primary educational attainment (% of LF) 42% 46% 26% 22% 25% 29% Human capital Labour market Innovation Agglomeration and connectivity Indicator Regions w ith large catching up potential Grow ing above av. Grow ing below av. Regions w ith catching up potential Grow ing above av. Grow ing below av. Advanced regions Grow ing above av. Grow ing below av. Teritiary attainment (% of LF) 21% 19% 26% 25% 31% 26% PISA score mathematics PISA score reading Employment rate 57% 55% 71% 68% 71% 66% Unemployment rate 9% 8% 5% 7% 5% 6% Long-term unemployment rate 4% 5% 2% 2% 2% 2% Youth unemployment rate 21% 22% 13% 16% 12% 15% Participation rate 62% 60% 73% 72% 74% 69% ln (patent application) Patent applications per million ln (patent application copatents) Co-invention within region Co-inventions within ctry Co-inventions foreign R&D expenditure total (as % of GDP) 1.06% 1.03% 1.50% 1.41% 2.21% 1.51% BERD % GDP 0.35% 0.42% 0.90% 0.86% 1.35% 1.00% GERD % GDP 0.33% 0.22% 0.23% 0.20% 0.42% 0.16% High and medium HTM % empl. 3.3% 4.8% 5.2% 6.1% 5.3% 6.4% KIS (as % of total employment) 22.5% 28.2% 33.3% 32.8% 36.7% 32.2% Population density GDP density Degree of openness Clustering coefficient Centrality Productivity Human capital Density

40 Performance of regions with low levels of development Growth factor Productivity Productivity (GDP per employee) 31,612 29,728 55,832 50,728 72,551 59,824 Infrastucture Motorway density Primary educational attainment (% of LF) 42% 46% 26% 22% 25% 29% Human capital Labour market Innovation Agglomeration and connectivity Indicator Regions w ith large catching up potential Grow ing above av. Grow ing below av. Regions w ith catching up potential Grow ing above av. Grow ing below av. Teritiary attainment (% of LF) 21% 19% 26% 25% 31% 26% PISA score mathematics PISA score reading Employment rate 57% 55% 71% 68% 71% 66% Unemployment rate 9% 8% 5% 7% 5% 6% Long-term unemployment rate 4% 5% 2% 2% 2% 2% Youth unemployment rate 21% 22% 13% 16% 12% 15% Participation rate 62% 60% 73% 72% 74% 69% ln (patent application) Patent applications per million ln (patent application copatents) Co-invention within region Co-inventions within ctry Co-inventions foreign R&D expenditure total (as % of GDP) 1.06% 1.03% 1.50% 1.41% 2.21% 1.51% BERD % GDP 0.35% 0.42% 0.90% 0.86% 1.35% 1.00% GERD % GDP 0.33% 0.22% 0.23% 0.20% 0.42% 0.16% High and medium HTM % empl. 3.3% 4.8% 5.2% 6.1% 5.3% 6.4% KIS (as % of total employment) 22.5% 28.2% 33.3% 32.8% 36.7% 32.2% Population density GDP density Degree of openness Clustering coefficient Centrality infrastructure and innovation related activities (co-invention within regions and with other regions within countries) are critical, in addition to human capital. Advanced regions Grow ing above av. Grow ing below av.

41 As regions move into higher levels of development Growth factor Productivity Productivity (GDP per employee) 31,612 29,728 55,832 50,728 72,551 59,824 Infrastucture Motorway density Primary educational attainment (% of LF) 42% 46% 26% 22% 25% 29% Human capital Labour market Innovation Agglomeration and connectivity Indicator Regions w ith large catching up potential Grow ing above av. Grow ing below av. Regions w ith catching up potential Grow ing above av. Grow ing below av. Teritiary attainment (% of LF) 21% 19% 26% 25% 31% 26% PISA score mathematics PISA score reading Employment rate 57% 55% 71% 68% 71% 66% Unemployment rate 9% 8% 5% 7% 5% 6% Long-term unemployment rate 4% 5% 2% 2% 2% 2% Youth unemployment rate 21% 22% 13% 16% 12% 15% Participation rate 62% 60% 73% 72% 74% 69% ln (patent application) Patent applications per million ln (patent application copatents) Co-invention within region Co-inventions within ctry Co-inventions foreign R&D expenditure total (as % of GDP) 1.06% 1.03% 1.50% 1.41% 2.21% 1.51% BERD % GDP 0.35% 0.42% 0.90% 0.86% 1.35% 1.00% GERD % GDP 0.33% 0.22% 0.23% 0.20% 0.42% 0.16% High and medium HTM % empl. 3.3% 4.8% 5.2% 6.1% 5.3% 6.4% KIS (as % of total employment) 22.5% 28.2% 33.3% 32.8% 36.7% 32.2% Population density GDP density Degree of openness Clustering coefficient Centrality human capital but in addition to adequate infrastructure, efficient labour markets and innovative activity are critical to enhance their performance. Advanced regions Grow ing above av. Grow ing below av.

42 As regions approach the production possibility frontier Growth factor Productivity Productivity (GDP per employee) 31,612 29,728 55,832 50,728 72,551 59,824 Infrastucture Motorway density Primary educational attainment (% of LF) 42% 46% 26% 22% 25% 29% Human capital Labour market Innovation Agglomeration and connectivity Indicator Regions w ith large catching up potential Grow ing above av. Grow ing below av. Regions w ith catching up potential Grow ing above av. Grow ing below av. Teritiary attainment (% of LF) 21% 19% 26% 25% 31% 26% PISA score mathematics PISA score reading Employment rate 57% 55% 71% 68% 71% 66% Unemployment rate 9% 8% 5% 7% 5% 6% Long-term unemployment rate 4% 5% 2% 2% 2% 2% Youth unemployment rate 21% 22% 13% 16% 12% 15% Participation rate 62% 60% 73% 72% 74% 69% ln (patent application) Patent applications per million ln (patent application copatents) Co-invention within region Co-inventions within ctry Co-inventions foreign R&D expenditure total (as % of GDP) 1.06% 1.03% 1.50% 1.41% 2.21% 1.51% BERD % GDP 0.35% 0.42% 0.90% 0.86% 1.35% 1.00% GERD % GDP 0.33% 0.22% 0.23% 0.20% 0.42% 0.16% High and medium HTM % empl. 3.3% 4.8% 5.2% 6.1% 5.3% 6.4% KIS (as % of total employment) 22.5% 28.2% 33.3% 32.8% 36.7% 32.2% Population density GDP density Degree of openness Clustering coefficient Centrality in addition to human capital dynamism is mainly associated with innovation-related activities and their connectivity within the global network of regions and agglomeration forces. Advanced regions Grow ing above av. Grow ing below av.

43 The policy headache: isolated sectoral action may have unintended outcomes. Leaking by linking Infrastructure provision Problem: lack of connectivity Persistence of inequality 43

44 The policy headache: isolated sectoral action may have unintended outcomes. Brain drain with labour mobility Human capital formation Policy responses Persistence of inequality 44

45 The need for a differentiated approach Place based polices in the new regional paradigm are best suited for this task Integrated approach diagnosis is critical Right level of intervention local labour markets A match between bottom and top down information and initiative is critical Policy design and multilevel governance are key for a successful implementation 45

46 Towards a Multidimensional Response Regional growth and convergence Many countries are reforming in this direction, but implementation is still difficult. At the regional scale Innovation Business environment Human capital formation Infrastructure provision -Horizontal evidence? -Policies? -Institutions? Policy responses 46

47 III. Is there a rural commitment in current U.S. domestic policy?

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50 What policy framework will best integrate rural and urban initiatives and programs, to advantage both ag and non-ag rural constituencies, their communities and regions, and enhance their children s potential to thrive there in the 21 st century?

51 1. Greater attention to asset-based development, much more broadly defined. Placemaking, married to economic development, must be the new paradigm. 2. The building of regional frameworks, appropriately configured, of sufficient scale to leverage these geographies and bridge these constituencies. (While we need rural and urban responses, their intersection is the future of enlightened public policy.) 3. As the Federal role reduces over time, greater attention to new governance / new intermediary support by the public sector. 4. Regional innovation policies which specifically target mutually beneficial competitive advantage, that rural and urban areas share. (i.e., Regional food systems, bio-energy compacts, natural resourcebased / sustainability assets, workshed / watershed approaches, etc.)

52 5. Attention to the importance of working landscapes: Arts / heritage / culture Natural resources / tourism Bio-energy / biofuels, entrepreneurial agriculture 6. Incentives to bridge innovation / entrepreneurship support systems, from urban to rural expression 7. Opportunities to address spatial mismatch issues in workforce / training across broader geographies, via place-based community / technical college collaborations, both sister schools and research universities. 8. Innovative funding approaches which enhance collaboration across state and local governments, particularly in cross-sectoral, regional experimentation.

53 IV. Rural imperatives, and signs of hope and progress!

54 New Narratives & Networks Knowledge Networks & Workforce Collaborative Leadership Quality of Place Entrepreneu r-ship & Innovation Critical Internal Considerations Wealth Creation and Intergenerational Wealth Retention Youth Engagement and Retention Social Inclusion and Social Equity

55 V. Final Reflections: Why your work is so critical

56 Distribution of U.S. Population by Urban and Rural Areas, and Core Based Statistical Areas, 2010 Urbanized Area Urban Cluster Rural Total Metropolitan 219,677,256 10,766,879 32,007, ,452,132 Micropolitan 228,950 13,852,786 13,072,477 27,154,213 Noncore 15,917 4,711,483 14,411,793 19,139,193 Total 219,922,123 29,331,148 59,492, ,745,538 Urbanized Area Urban Cluster Rural Total Metropolitan 99.9% 36.7% 53.8% 85.0% Micropolitan 0.1% 47.2% 22.0% 8.8% Noncore 0.0% 16.1% 24.2% 6.2%

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59 What lies behind us, and what lies before us are tiny matters compared to what lies within us. --Ralph Waldo Emerson

60 Charles W. Fluharty President and CEO Rural Policy Research Institute 214 Middlebush Hall University of Missouri Columbia, MO (573)