Do Jobs-Follow-People Or People-Follow-Jobs?
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RUG1 | 2 Do jobs-follow-people or Overview › Motivation ›Theoretical debate people-follow-jobs? › Dutch context › Results Meta-analysis 64 empirical studies of Jouke van Dijk, based on joint work with Gerke Hoogstra and Raymond Florax the Carlino-Mills model for jobs-follow-people Professor of Regional Labour Market Analysis, University of Groningen, versus people-follow-jobs Faculty of Spatial Sciences, Chair Department Economic Geography › Conclusion and discussion President/director Waddenacademie-KNAW Email: [email protected] Website: www.joukevandijk.nl Presentation Seminar in Geospatial Science, UCL, London, UK, March 18, 2014 4 Classis question about regional growth still in debate Literature: do “jobs-follow-people or people-follow-jobs” Do jobs-follow-people or do (Borts and Stein 1964; Steinnes and Fisher 1974) or related people-follow-jobs? “chicken-or-egg” (Muth 1971). Later The Determinants of County Growth by Carlino and Mills (1987) with lagged adjustment framework. The question relates to questions like: A. No interaction › Do people move for amenities and quality-of-life factors or economic factors (e.g. Lowry, 1966; Partridge 2010). B. People-follow-jobs › Is the residential location decision made before or after the C. Jobs-follow-people job location decision (e.g., Deding et al. 2009). › Are employment locations really exogenous to residential D. Dual causality locations? Or vice-versa (as assumed in the monocentric city model. | 6 Duelling theoretical models Policy relevance › The question what determines growth plays a central role › New Economic Geography (Krugman, 1991): falling in policy discussions as to whether catering to the wishes transport cost lead to concentration of firms and improving the business climate of a place is › Amenity migration (Graves, mid1970s): people or a better strategy than catering to wishes of people and moving to nice places, warm climates improving the people climate of a place when aiming to › Agglomeration effects, attractiveness of (big) cities stimulate local or regional growth. (Gleaser et al, 2001 etc., Florida, 2003) › Core – periphery debate in The Netherlands: is the › Storper & Scott (2009): people only move to nice places Randstad area with Amsterdam/Rotterdam the engine of with suitable employment national growth or an area at risk with (too) high cost? Partridge (2010): for the US, Graves is the winner! › Changing policy focus from only economic goals like GDP, income and (un-)employment to broader goals like well-being and quality of life 1 Well-being – Quality of life - Happiness People’s Well-being: changing preferences › The problem of short term: emotional definition Objective measures Subjective measures feelings of happiness › Life expectancy › Health perception › Mortality rates › Access to services › Many terms for more or less the same thing (how long term: ›Poverty › Material deprivation well one’s life is going) life satisfaction ›Crime › Safety and trust ›Income › Life satisfaction - Quality of life ›Un-/employment › Happiness - Welfare / Well-being ›Education › Capabilities -Health ›Gender balance › Equal opportunities - Happiness ›Working hours › Work life balance | 10 Resilience of cities/regions Social resilience Dutch context Bearable Equitable Sustainable Environmental Viable Economic resilience resilience Groningen 11 12 16 million inhabitants 300 kilometer 2 Regional development: European Economic space 14 Employment rate 2010: dark is better (jobs per inhabitants 20- 64 years) The world is spiky: concentration of people and economic activities. BUT big cities have higher initial GDP, but NOT higher growth rates! (Broersma & Van Dijk, 2008 and OECD, Regional Outlook, 2011) 15 The Role and Value of (Big) Cities from pure Share of economic and broad well-being perspective part time workers: › ECONOMIC: (Big) cities have higher productivity, generate more knowledge outcomes (patents, dark is innovations, copyrights, licenses), have higher human more capital – both stocks and inflows parttime › But also: higher land and housing prices › WELL-BEING: (Big) cities have high quality services work and amenities like universities, musea, concerts › But also: more traffic jams, more air pollution, more crime, higher risk of being the target of war and terrorist attacks Agglomeration and growth Lineair unfinite growth? Growth Finite growth? Source: OECD, Regional Outlook, 2011 Size Big cities have higher initial GDP, but NOT higher growth rates! Trade off between agglomeration Opportunities for growth are observed in all type of regions! benefits vs congestions cost? 3 Changes in the employment rates 1973-1995 vs 1995-2010 Regional unemployment differences are narrowing 19 Source: Bureau Louter, 2011 21 Regional Population Development 2010-2025 22 Unemployment rate by Total population Population age 15-64 municipality PES-data Dec 2012 Aging problem!! 23 | 24 Migration by age 2000-2006 Migration: the escalator model (sorting) 15-20 year 20-25 year 4 Education index population 25 Dreaming of the countryside 15-64 year: result of a spatial sorting process Darkred: > 2,4 Darkblue < 1,6 Source: Pau/Louter, 2010 Index 1-5 Population density 28 Very high Rural – urban typology: Residential no real rural areas in preferences The Netherlands! Municipality of Haren nr.1 in The Very low Country sites transforms Netherlands from production space (agriculture) to However recently: consumption space “Massive Facebook (residential and leisure) party Project X Haren Source: EU-Commision (November 2010), Investing in Europe’s in sleepy Dutch town future, 5-th Report on Economic, turns into riot” Bron: Bureau Louter, 27Social and Territorial Cohesion Waar willen we wonen 2012 29 30 Landprices per m2 Scores Residential Preferences Rural area / City Neighbourhood + - Basic services - + Plus services - + Safety & Crime + - Landprices reflect the quality of the Preferences differ! environment both in Source: Stad en But also prices! terms of economic Land, CPB, 2010 Bron: Bureau opportunities and Louter, amenities 5 31 32 Landprices per m2 and population density Landprices per m2 and lotsize Source: Stad en Land, CPB, 2010 Source: Stad en Land, CPB, 2010 Amsterdam, Groningen en Maastricht are consumer cities: besides wages also urban and natural amenities matter for explaining land prices! Source: OECD, Regional Outlook, 2011 Source: Stad en Land, CPB, 2010 Net migration 35 The city wins, but Migration by type of village / town flows in the there is a compex Netherlands: underlying spatial process of sorting! 1948/1952 but also: birds 1958/1962 Drenthenieren of a feather flock 1973/1977 together! 1996/2000 Bron: SCP, Dorpenmonitor, 2013. 6 37 | 38 Groningen: gasextraction causes serious earthquakes Dissertation Rixt Bijker (January 2013): There are also many migrants to the less popular rura areas! Also important: quick connections to nearby city + fast ICT Broadband access Commuting distances increase, especially for higher educated. Do ‘jobs follow people’ or ‘people follow jobs’? A meta-analysis of Carlino-Mills studies New working arrangements: change form daily face-to-face contact to Gerke Hoogstra, Raymond Florax a frequency 1-2 days en Jouke van Dijk (2014) per week ICT Broadband! Source: Stad en Land, CPB, 2010 | 41 | 42 Modelling do ‘jobs follow people’ or ‘people follow jobs’? Innovative features of the Carlino-Mills models: › Late 1960s variety of techniques were put forward, but › First, US nationwide analysis of population–employment in a small and fragmented group of studies. interactions at a very detailed spatial scale (county level). › Late 1980s, the number of research studies has rapidly › Second, and even more importantly, it was the first study grown and there has been relatively little disagreement to investigate these interactions by using a about the choice of methodology due to the publication simultaneous equations model similar to the one of The Determinants of County Growth by Carlino introduced by Steinnes and Fisher (1974), but with a and Mills (1987), which marked a radical departure lagged adjustment framework built in. from previous causality studies in two respects. › Criticism: the identification of the simultaneous › To illustrate the importance of the publication: it was equations system is often problematic because of the lack the most cited regional science article of 1987. of good instruments and that the results may therefore Isserman (2004) not be reliable (see, e.g., Rickman 2010). 7 | 44 43 Carlino-Mills model structures | 45 | 46 Taxanomy of Carlino-Mills model specifications Meta-analysis Table 1.levels Taxonomy vs changes of Carlino–Mills with/without model specificationscross/spatial autoregressive lags / (LHS) / RHS) 1 2 ›“The application of statistical techniques to δ1/δ2* δ1/δ2* δ3** δ4*** Introduced by: collections of empirical findings from previous a 0 0 0 0 Carlino & Mills (1987) b 1 0 0 0 Mills & Carlino (1989) studies for the purpose of integrating, c 1 1 1 0 Boarnet (1992) synthesising, and making sense of them” (Wolf, d 0 0 1 0 Luce (1994) e 0 0 0 1 Vias (1998) 1986) f 1 1 1 1 Henry et al. (2001) g 1 0 0 1 Carruthers & Mulligan (2008) › We will use a multinominal logit model and h 1 1 1 1 Kim (2008) base the interpretation on the marginal effects Note: LHS (RHS) refers to variables on the left-hand-side (right-hand side) of the equations. * 0 = population/employment levels and 1 = population/employment changes. ** 0 = without spatial obtained from this model cross-regressive lags and 1 = with spatial