Regional Economic Development Planning

rwp Regional Economic Development Planning Structural Economic Analysis Michael Kiehl Department of Urban and Regional Economics Stefano Panebianco Research Institute for Regional and Urban Development of the Federal State of North Rhine-Westphalia (ILS NRW) L4. Structural Economic Analysis 22-11-2004: 9.30 h 10.15 11.00 11.15 13.00 h h h h Background / Data Basic Structural Analyses Coffee Break Exercises with MS Excel End 23-11-2004: 9.15 h 10.15 11.15 11.30 13.00 rwp Shift-Share-Analysis Portfolio-Analysis Coffee Break Presentation and discussion of results End h h h h Insights from lectures 1-3. The dependent variable: regional economic growth L1: Economics, regional economic development and planning - Ten principles of economics - What is regional economic development? - Why regional economic development planning (and policy)? - REDP: strategies, trends, challenges regional economic development: “…economic processes and resources that result in the sustainable development of, and desired economic products/outcomes for a region” (Stimson et al. 2002:7) ? ? How do we achieve these outcomes? Which are the “drivers” of growth? rwp Insights from lectures 1-3. The role of production factors L2: Introduction to economic analysis - Circular-flow diagram of the economy - Participants in the economic process - Production factors - Land price formation production factors: labour (wages, formal qualification, skills, age, mentality) capital (financial / technical assets) land (building land, natural resources) knowledge (technical knowledge, information) ? ? rwp Growth can be explained by the availability / prices of production factors What else explaines economic growth? Insights from lectures 1-3. Account and employment based methods (1) L3: Overview of (intra-reg.) methods for reg. economic analysis - Account and employment based methods - Resources based methods - Settlement / location based methods - Product / enterprise based methods Account and employment based methods: Growth can be explained by - strong exporting activities (? balance of payment) - the concentration on specific econ. activities (? location coefficient) - strong intra-regional linkages (? econ. base analysis, input-output analysis, cluster analysis) rwp Insights from lectures 1-3. Resources based methods (1) L3: Overview of (intra-reg.) methods for reg. economic analysis - Account and employment based methods - Resources based methods - Settlement / location based methods - Product / enterprise based methods Resources based methods: Growth can be explained by - the availability of natural resources (? potential and demand assessment) rwp Insights from lectures 1-3. Resources based methods (2) Example: Resources potential matrix Demand (potentials) Resources (potentials) Sector of primary production Current utilization Goods and services Current demand Potential for expansion Natural resource 1642 ha Volume 821 tons, plus current surplus of 650 tons Labour High underemployment rate in agricultural sector … 1,956 tons no imports, demand potentials in neighbouring provinces Rice cultivation 5,208 ha (2,600 tons) … … … rwp Insights from lectures 1-3. Settlement / location based methods (1) L3: Overview of (intra-reg.) methods for reg. economic analysis - Account and employment based methods - Resources based methods - Settlement / location based methods - Product / enterprise based methods Settlement / location based methods: Growth can be explained by - the existance of well-functioning cities (? settlement function scalograms) - a high accessibility (? analysis of transport infrastructure / travel times) rwp Insights from lectures 1-3. Settlement / location based methods (2) Example: Settlement functional scalogram Urban places 1 Town A Town B Town C Town D Town E Town F X X X 2 X X X X X X X X X 3 X Urban functions 4 X X X X 5 X 6 X 7 X X 8 X rwp Insights from lectures 1-3. Product / enterprise based methods (1) L3: Overview of (intra-reg.) methods for reg. economic analysis - Account and employment based methods - Resources based methods - Settlement / location based methods - Product / enterprise based methods Product / enterprise based methods: Growth can be explained by - performant forward and backward linkages (? production linkage investigation) - the business structure (? analysis of business / entrepreneur profiles) rwp Insights from lectures 1-3. Product / enterprise based methods (2) Example: Production linkage investigation Boats Planks Furniture Wood/timber Poles Fences Housing frames Paper Shavings Construction boards rwp Insights from lectures 1-3. Data check list Location aspects Business profile Spatial distribution, transport access etc. Formal/informal status, membership in association, age of business, availability of business plan, employment structure, wages, net income, capitalization (assets less liabilities), technology gender, age, educational attainment type of raw materials, quantity, from where and how delivered, adequacy, kind of use, suppliers and prices (including the major factors determining prices) Entrepreneur profile Input to production process (backward production linkages) Outputs of production process (forward production linkages) Assistance and support What are the specific outputs, what are they used for, how are they marketed, what are their prices, in what quantities, how and to where are they marketed Marketing, infrastructure, policy, input supply, training/technical assistance, technology/product design Which data sources did you find in your countries? rwp Background. Which factors drive regional economic growth? Factors related to the LOCATION: “hard” factors: resources, accessibility, wages, land prices, human capital, public funding “soft” factors: image, quality of life, business networks/linkages, political stability Factors related to the ECONOMIC STRUCTURE: sectoral distrubution: -economic branches functional distrubution: - research/production administration/consulting business structures: - size/age of businesses rwp Background. Why do we need structural analyses? Structural analyses help to answer inportant questions of regional economic development planning. sectoral distrubution: - Which are the strongest industries? - Which industries are “missing”? functional distrubution: - How is the economy of regionx positioned with regard to higher functions? (e.g. research&development) business structures: - What is the size distribution of my business population? - Who is the typical entrepreneur of regionx (age, eduction..)? rwp Data. Which data do we need for structural analyses? Value added data - value added per economic sector Sources: national account statistics Employment data - no. of employees per sector / branches - functional employment Sources: Federal Institute for Employment; various national statistics Business data - data on size / no. of employees / turnover / main customers of businesses Sources: regional/national business surveys rwp Data. Methodological concerns - Are the data available at city or regional level? - Are the data reliable? (share of illicit work, procedures of collection) - Who is included in the data? (employees? self-employed? public officials? family workers?) - How recent is the data set? Have changes occurred in the meantime? - Are employees counted at their place of residence or place of work? - Are time series available? - Have the definitions changed over time? (e.g. unemployment?) -… rwp Data. The Value Added Data Value Added Value Added is a measure of the additional value created by a process of production. It can be measured as gross or net. Gross Value Added is defined as the value of output less the value of intermediate consumption. output = + = intermediate consumption gross value added taxes less subsidies on products gross domestic product 3 754.5 1 840.0 1 914.5 213.7 2 128.2 The example of Germany (2003) rwp Data. Critique of the Value Added Data several welfare-relevant activities are not included in the value added concept, namely: - housework - self-help activities (e.g. repair services) - subsistency production - illicit work the consumption / pollution of natural resources is not adequately mirrored (externalities) difficulties in separating intermediate consumption and outcome the methods of calculating the value added change over time - rwp Data. The German Employment Data (1) Employees subject to social insurance Definition: all employees who are subject to health insurance, pension insurance and long-term care insurance contributions … or for whom employers are required to contribute pursuant to the employment promotion legislation. (http://www.destatis.de/basis/e/erwerb/erwerbinfo1.htm) Additional information: - 27,8 Mio. (W-Germany: 22,1 Mio. / E-Germany: 5,7 Mio.) - self-employed, public officials and family workers are NOT included - generally counted by place-of-work - 11 industries, 66 economic branches - differentation available at level of the 97 planning regions and 440 counties/cities rwp Data. The German Employment Data (2) Persons Engaged in Economic Activity in National Accounts Definition: Persons engaged in economic activity, as used in national accounts, include all persons performing within Germany some gainful activity as employees (wage earners, salaried employees, public officials, marginal part-time workers, soldiers), as self-employed persons or as unpaid family workers, irrespective of the scope of such activity. (http://www.destatis.de/presse/englisch/abisz/erwerbstaetige.htm) Additional information: - 36,2 Mio. (W-Germany: 29,8 Mio. / E-Germany: 6,3 Mio.) (2003) - generally counted by place-of-residence - generated out of 45 different sources (!) - available at the level of the 97 planning regions and 440 counties/cities rwp Data. The German Employment Data (3) Economic sectors (11 categories) agriculture energy mining manufacturing construction whole sale / retail transport financial / insurance activities business orientated services household orientated services state / other organisations Business orientated Services 10% Financial/ Insurance Activities 4% Transport 5% Household orientated services 21% Wholesale/ Retail 14% State; other Organisations 9% Construction 6% Agriculture 1% Energy 1% Manufacturing 29% Mining 0% West-Germany 2002 rwp Data. The German Employment Data (4) Economic branches (66 categories) rwp Data. The German Employment Data (5) Function of employees (8 Categories) fabrication / production storage / transport research & development other technical services top management other administration corporate planning social and other activities Other Administration 23% Corporate Planning 5% Social and other activities 23% Fabrication/ Production 30% Storage/ Transport 9% Research & Development 3% Other Technical Services 5% Top Management 2% West-Germany 2002 rwp Data. The German Employment Data (6) Formal qualification of employees (8 Categories) academics A-levels (Abitur) secondary school and vocational training secondary school without vocational training others academics in corporate planning and top management without vocational training West-Germany 2002 rwp Data. The spatial units: 97 planning regions Dortmund Cologne rwp agglomerations urbanised areas rural areas Data. What can the employment data tell us? Task for the Seminar Participants: Analysis of two German regions The “Metropolis of Westphalia” (Dortmund) versus The “Metropolis of the Rhine” (Cologne) 1) Status quo: How does the economic structure look like? 2) Change: Which major changes occurred between 1985 and 2002? 3) Comparison: How did the region(s) perform in comparison with the national development / with other urban areas in West-Germany? 4) Conclusions: How should REDP intervene? rwp L4. Structural Economic Analysis 22-11-2004: 9.30 h 10.15 11.00 11.15 13.00 h h h h Background / Data Basic Structural Analyses Coffee Break Exercises with MS Excel End 23-11-2004: 9.15 h 10.15 11.15 11.30 13.00 rwp Shift-Share-Analysis Portfolio-Analysis Coffee Break Presentation and discussion of results End h h h h Why economic analysis? rwp Principles of „basic“ structural analysis • 4 major principles of “basic“ structural economic analysis: – Need of Regional Comparison/ Values to qualify Data – Calculation of shares (absolute/ relative) – Time series analysis (in comparison to national average) – Sectoral/ Functional differentiation rwp Principles of „basic“ structural analysis • 4 major principles of “basic“ structural economic analysis: – Need of Regional Comparison/ Values to qualify Data – Calculation of shares (absolute/ relative) – Time series analysis (in comparison to national average) – Sectoral/ Functional differentiation rwp Value added in the Ruhr Area - 2000 Value added in 2000: - Ruhr Area: 95 Billion € - Germany: 1800 Billion € - Dortmund: 22 Billion € Size of region does matter: => reference or scale basis is missing (denominator)! rwp Value added in the Ruhr Area - 2000 in 1.000 € 60 53 Ruhr Area 51 Germany 40 20 0 Value added/ labour force rwp Value added/ population Stralsund Kiel Rostock Hamburg Value added by region - 2000 Berlin Schwerin Bremen Hannover Magdeburg DO E Dü Erfurt Bonn Frankfurt Mainz Halle Leipzig Dresden Chemnitz Value added/ labour force in 1.000 <= 30,0 60,0 <= 40,0 80,0 <= 50,0 100,0 <= 60,0 120,0 <= 70,0 140,0 <= 100,0 200,0 München Nürnberg Saarbrücken Stuttgart rwp Value added in the Ruhr Area - 2000 in 1.000 € 60 53 Ruhr Area 56 51 Agglomerations 40 Germany 26 20 20 22 0 Value added/ labour force rwp Value added/ population Development of „Value added“ in the Ruhr Area 1976 – 2000 Change in % +250% +200% 160% +150% +100% +50% +0% 139% 116% Ruhr area Agglomerations 195% 14% -9% -50% Value added/ labour force rwp Value added Labour force (Employment) Need of regional comparison/ other values - Conclusion - Regional comparison is indispensable for the interpretation of your results => Choose regions carefully, as choice of region has major influence on your results - Regional comparison demands standardization by other values/ denominator => Denominator affects results (i.e. labour force vs. Population); => and change rates rwp Principles of „basic“ structural analysis • 4 major principles of “basic“ structural economic analysis: – Need of Regional Comparison/ Values to qualify Data – Calculation of shares (absolute/ relative) – Time series analysis (in comparison to national average) – Sectoral/ Functional differentiation rwp Absolute Shares i.e.: Employment in one sector/ Total employment Ruhr area Energy/ Mining Production Construction Wholesale/ Retail/ Logistic Other Services State/ Non-profit 2,6 13,4 4,9 23,7 30,3 26,4 Agglomerations 1,2 17,3 4,4 20,2 31,5 24,6 Germany 1,0 24,5 6,0 19,5 24,0 22,7 rwp Relative Shares (i.e. location quotient) - Location quotient as measure for relative specialisation of a region - Idea: Identification of sectoral specialisation in relation to national average Calculation: Location quotient = National Employment in Sector X Total National Employment Employment in Sector X in Region Total Employment in Region rwp Location quotient II Interpretation: Location quotient <1: lower than national concentration location quotient =1: equal concentration location quotient >1: higher than national concentration rwp Principles of „basic“ structural analysis • 4 major principles of “basic“ structural economic analysis: – Need of Regional Comparison/ Values to qualify Data – Calculation of shares (absolute/ relative) – Time series analysis (in comparison to national average) – Sectoral/ Functional differentiation rwp Development between 2 dates 10 8 6 4 2 0 -2 -4 -6 -8 -10 -12 Germany Germany Agglom. Ruhr Area Growth 80-03 Agglom. Ruhr Area Growth 85-03 => Choice of dates with significant influence on result => Might shroud change of development tendencies rwp Thus: Time Series Analysis Change since 1976 +25% +20% +15% +10% +5% 0% -5% -10% -15% 1976 1981 1986 1991 1996 Munich Rhein-Main Stuttgart Hamburg ABL Düsseldorf Ruhr area 2001 rwp Time series analysis standardized by national development Change in comparison to national average Munich +15% +10% +5% 0% -5% -10% -15% -20% -25% 1976 rwp Rhein-Main Stuttgart Hamburg Germany Düsseldorf Ruhr area 1981 1986 1991 1996 2001 Calculation Growth rate (in %): Employment Region 2004/ Employment in year 1985 (*100-100) Growth rate standardized by national development (in %): = (Employment Region 2004/ Employment National 2004) (Employment Region 1976/ Employment National 1976) Advantages of standardization by national development: National trends are excluded Regional disparities/ cohesion as focus Idea of future development ? rwp Principles of „basic“ structural analysis • 4 major principles of “basic“ structural economic analysis: – Need of Regional Comparison/ Values to qualify Data – Calculation of shares (absolute/ relative) – Time series analysis (in comparison to national average) – Sectoral/ Functional differentiation rwp Sectoral Differentiation - employment development standardized by national average 120 100 Other Services (-112%) 80 60 State/ Non Profit (13,2%) Wholesale/ Retail/ Logistic (-26,9%) Construction (-43,8%) Production (-50,5%) 40 Energy/ Mining (-57,5%) 20 1976 rwp 1980 1984 1988 1992 1996 2000 Functional/ Occupational Data 0% -10% -20% Administration Research and Development -30% -40% -50% 1990 rwp Technical Staff Total Employment Production Storage/ Transport 1992 1994 1996 1998 2000 2002