Flows associated with travel-to-work patterns in Metropolitan regions

Metropolitan areas involve intense interactions with neighboring regions. The industries and households located in a metropolitan region import various products to satisfy their input needs for intermediate or final consumption and export many of their production to other regions or abroad. The high intensity of commuting flows between these neighboring regions is another important characteristic of dense urban areas, like the metropolitan ones, with important consequences on both the regions where people live and where people work. Accordingly, the study of commuting requires the analysis of the economic (and other) interdependencies within a given geographical area. The Multi-Regional Input-Output (MRIO) modelling framework allows for the analysis of inter industrial and inter regional spill overs. But, there is a gap on modelling regarding the incorporation of flows associated with commuting, either in terms of the travel-to-work journey (by private or public transports), or in terms of corresponding differences in shopping and expenditures made in the region where people work and in the region where they live, as well as regarding the housing market and corresponding rents. Indeed, commuting activities in metropolitan areas have been ‘often-ignored’ in regional and urban economic studies. Accordingly, the main aim of this article is to present a proposal for the creation of a “Commuting Satellite Account”, as well as a discussion on the corresponding incorporation into a MRIO framework, in order to allow for an improved (regional and national) impact assessment of changes in urban forms and commuting patterns. This is supported with an illustrative example, considering the case of the Lisbon metropolitan area (a Portuguese NUT II region, divided in two region NUT III areas: Great Lisbon – which includes the Lisbon municipality - and Peninsula de Setubal).Two main steps are followed to accomplish the goals of this research: the derivation of the Multi-Regional data framework, with details on how the interdependencies between economic agents in the regions considered are integrated in the MRIO model; and the proposal for the design and compilation of a “Satellite Account” for Commuting. The application of the proposed modelling framework to the illustrative case of the Lisbon metropolitan area departs from the MULTI2C - multi-sectorial and multi-regional - approach, a general flexible procedure, developed by a group of researchers from the University of Coimbra, Portugal, that allows for the adoption of different geographic configurations. The basis of the MULTI2C model is the Portuguese 2010 “National Supply and Use Table” (with a disaggregation level of 431 products and 125 industries), complemented with the 2011 Population Census. MULTI2C uses non-survey methods to regionalize IO tables (for the 30 Portuguese NUTS III) and takes advantage of the very detailed set of information provided by the Portuguese National and Regional Accounts, combining it with several other detailed statistical sources (beyond Population Census, also Households Expenditure Survey, Agricultural Census, National Forest Survey). Further, the method used to determine each industry structure of primary products, by region, uses very detailed information from the Social Security database. The adoption of the geographical configuration suitable to model the Lisbon metropolitan area requires the consideration of a tri-regional model (Great Lisbon, Peninsula de Setubal, and the ‘Rest of the Country’). The method to derive this tri-regional model involves two steps. Firstly, splitting the country into “region A” (the Great Lisbon Metropolitan Area) and the “Rest of the Country”. Then, region A is split into A1 (Great Lisbon) and A2 (Peninsula de Setubal), such that A1 and A2 exhaust A. Then, the recommendations in SEC-2010 for the design and compilation of “Satellite Accounts2 are followed for the implementation of the proposed extension of the ‘standard’ MRIO framework to incorporate the specificities of commuting. For this there is the need to explore supplementary information that allows for the consideration of three main features associated with commuting: firstly, commuters and non-commuters have different consumption patterns (e.g. the share of expenditure in fuel, cars, insurance); secondly, each industry’s income distribution between different types of households (commuters, non-commuters and landlords) differs from region to region; and, finally, there are important relations between economic agents, their movements in space, and the renting activities. Firstly, the estimation of the distinctive household’s consumption patterns – between commuters and non-commuters – is based on data from the Households Expenditure Survey and uses econometric methods to identify what are the most relevant products associated with commuting activities. Secondly, as different industries have different commuters ‘attractiveness’, the share of income distributed among the region where the industry is located and the other regions is estimated, based on the 2011 Census. Finally, taking into account information from the Household Regional Accounts, renting activities are treated as a monetary flow between firms and households, in order to estimate the regional distribution of the total rents paid/received by firms/households.The estimated inter-regional database makes clear the existence, in the Great Lisbon region, of a large deficit in terms of international trade compensated by a large surplus in terms of inter-regional trade. Otherwise, the Peninsula de Setubal region presents deficits both in terms of international and inter-regional trade. These deficits are very likely offset in its “balance of payments” by the income inflows associated with the commuting phenomenon. Concerning each of the industries, net exports from the Great Lisbon region are associated mainly with the wholesale trade activities, financial services, passenger air transport and the manufacture and provision of gas. Many of these net exports can be explained by the location of many of the Portuguese firm’s headquarters in the municipality of Lisbon. In terms of population and commuting activities, the Lisbon municipality has been losing population, while the number of inhabitants living in the surrounding areas has largely increased. This trend has contributed to the extended increase of the commuting phenomenon. Indeed, this metropolitan area is the Portuguese region where the commuting activities are more significant, with approximately 1.250.000 workers (almost a quarter of the Portuguese workers) and more than 540.000 daily travelling between municipalities in order to work. Among these commuters, more than 110.000 travel between the two NUT III regions (Great Lisbon and Peninsula de Setubal) and 40.000 workers have their residence in the “Rest of the Country”. The modelling framework used made possible to confirm that different industries have different commuters ‘attractiveness’ and reveals that the share’s distribution of the workers residence influences the distribution of induced effects in the three regions considered. With such data, the wages and income earned by employed and self-employed workers can then be distributed among the regions, taking into account these industries’ asymmetries. These results also influence the share of household’s consumption regarding non-commuters and commuters in each one of the three regions considered. Indeed, preliminary results reveal that household’s living near the most relevant employment centers spend more in housing rents and local services and less in fuel and other commuting related products (e.g. cars, maintenance, tolls, and insurance). Further, almost half of the income directly distributed to households that live in the Peninsula de Setubal are directly distributed by firms located in the Great Lisbon region. This fact highlights the existence of important spill-over effects associated with income distribution. Finally, having estimated the origin-destiny matrices for the renting activities flows, per region, it is possible to better describe the impact of changes in the prices of house renting or in the demand for housing that occurs in a specific urban region. The final aim of this research is to apply the “commuting satellite account” in the MRIO framework, in order to assess the multidimensional impacts of (hypothetical or real) major changes in the structure of economic activities and of households/industries location. E.g., one possible application (which is part of our research agenda) regards the assessment of the impacts of commuting patterns’ changes in metropolitan areas assuming scenarios, such as: the maintenance of the trend on residential location’s movements from the center to the periphery; or, in contrast, cases in which inhabitants return (from the suburbs) to the Central Business District. Further, this framework can be applied simultaneously with other satellite accounts, allowing for the consideration of a modeling framework that integrates the three fundamental dimensions of sustainability: economic, social and environmental.