The inextricable nature of space and economy

ABSTRACT

Space has always been essential within the economy, yet its importance in economics has been downplayed in several ways. This editorial introduces the seven papers comprising this issue of Spatial Economic Analysis (SEA) and shows that while the classics of economics acknowledged the importance of the location of economic activities, for many years the study of space was left to heterodox economics scholars and geographers. This is despite the established tradition of learned societies, such as Regional Science International and the Regional Studies Association, which are placed at the intersection of these fields. Space finally became mainstream in economics again due, on the one hand, to the introduction of the new economic geography some 30 years ago and, on the other, to the fact that several different economic sub-disciplines have come to understand and consider space as essential for the processes they study. This was facilitated by methodological advancements, such as in spatial econometrics.

The seven papers in this issue henceforth illustrate some of the situations and approaches which make space relevant to contemporary economic questions. Essential are, in particular, the interactions between different locations and the interactions between individuals and geographical features.

KEYWORDS:

• spatial economics
• regional economics
• urban economics
• spatial interaction
• location of economic activities

JEL:

• R1
• R3
• R2
• R5

In contrast to planning and geography, economics is not commonly considered a spatial science. Introductory economics textbooks seldom include aspects related to space or location and many degrees in economics can be obtained without any specific course on regional or urban economics. While international economics is more often present in academic curricula, its treatment of space (an intrinsic element to the existence of several countries) does not necessarily focus on truly spatial aspects. Yet, economics is indeed a topic in which space plays a paramount role and space and economy are inextricably linked: the spatial consequences of economic phenomena are very important as the location of economic processes plays a fundamental role in how they evolve.

Any introductory microeconomics course includes the notion of scale economies, which make larger plants more efficient than smaller ones. However, it often forgets to mention that firm concentration is not the only fundamental consequence because with it comes a spatial concentration of economic activities that in turn promotes concentration of jobs and ultimately, in the end, of human beings on Earth. Furthermore, invariably overlooked are firm co-location and localised external economies.

Similarly, the study of monopolies is an integral part of studies in microeconomics textbooks. However, little consideration is given to the fact that monopolies, and imperfect competition in general, are often facilitated by the distance between firms and between firms and markets.

All economic phenomena take place somewhere and where economic activities take place has a huge influence on their success. Among the economic factors that are unevenly distributed in space, we can mention commodities which, from being the cornerstone of national development in the 19th century, were gradually demoted to being something that poor countries with little industry and no advanced services could sell in order to get some exports. Recently matters have swung full circle and in more recent years an increased global competition for limited resources has made evident again the dependence of advanced economies on these commodities, as shown by the interest and strategies of global players (e.g., the European Open Strategic Autonomy).

Similarly, production factors are not uniformly distributed across space, either quantitatively or qualitatively. Labour is either abundant or not-abundant depending on location. (Consider how the slowing down of population growth is expected to impact China’s growth rates.) Qualitatively, labour is even more spatially heterogeneous, since with advanced economies comes the need of more specific competences and these are found in different individuals residing in different places, so that the competition between global cities comes to focus on the attraction of talents.

Capital is considered to be inherently mobile and financial capital is certainly the most mobile of assets. However, once capital is invested, it becomes much more difficult to move. Premises, machinery, offices, and even industrial complexes and centres of provision of services cannot be moved without great expense, which often makes it convenient to stay in places that have become sub-optimal because of the high relocation costs. Hence the rush to attract the mobile capital part, that is, new investments. Due to several rigidities however, such as the difficulties of information flows and of monitoring investments, even financial capital is not available everywhere in the same way. Interest rates may differ between regions inside the same country and obtaining seed funding might be easier for start-ups that are located closer to venture capitalists.

The demand for goods and services is also localised. It depends, quantitatively, on the purchasing power of potential buyers, which is related to the very inhomogeneous levels of income per capita. Whereas qualitatively, despite several waves of globalisation, people in different countries tend to buy and consume different bundles of goods and services and this will even occur within the same country.

Finally, innovation has been shown to be a very localised phenomenon. The level of technology is very different between and within countries. Indeed, most global innovations come from a few forerunner countries and within these countries, from a few specific places where the concentration of firms, universities, research centres, human capital and facilitating institutions make it possible to sustain innovative processes over time.

It is indeed rather surprising to see this insufficient interest by casual learners and certain practitioners because the importance of space for economics was already acknowledged at the birth of economics as a science, a full strand of spatial economics has developed in time and, finally, many fields in the discipline have come to understand that the phenomena they study are as they are because they are inextricably linked to where they take place.

As Camagni (2023) noted, Adam Smith, was never associated with regional aspects, space or geography. Yet, in his very extensive corpus, there are many aspects anticipating themes that are now considered crucial in regional science, such as the origin and role of the city and its relationship with the country, the theory of land rent, spatial monopoly, the income distribution in space and the theories of growth and innovation.

The name of Alfred Marshall is more directly associated with space, thanks to his studies on districts and illustration of the spatial concentration of industries (especially in chapter 10 of book 4) (Marshall, 1890). The study of the location of industries, however, has always remained important within economics, from Weber (1929) to the most recent advances. Indeed, that the study of the location of economic activities has often had a specific urban focus, from Lösch (1954), to the very wide range of urban economics theorisations (see, e.g., Fujita, 1989).

The role of space within economics, however, was most explicitly acknowledged after the Second World War with Walter Isard (1960) and the birth of regional science where economics served as the most important, but not the only, discipline through which this new field developed. Several ‘heterodox’ (i.e., not neoclassical) economists also made compelling cases for considering space in economic processes (e.g., Hirschman, 1958; Kaldor, 1970; Myrdal, 1957).

While spatial economics thrived in its regional science/regional studies niche and urban economics received more recognition in economics due to the interest in cities and real estate, it wasn’t until the birth of the so-called new economic geography that space returned to mainstream economics. The first editorial of Spatial Economic Analysis (SEA) (2006) acknowledges this and, while the conceptual evolution of the study of agglomeration earned such great interest that it contributed to Paul Krugman winning the Nobel Prize, the semantic/epistemological development was even more important. This is because it allowed economists to address spatial issues without being labelled by their peers as heterodox or, even, non-economists (whose research was made to belong to geography and other sciences).

The modelling of increasing returns by the new economic geography models was a fundamental (r-) evolution because, while it was clear to those interested in space that agglomeration was spontaneously happening because of self-reinforcing mechanisms, this could remain anecdotical until explicitly and analytically modelled in an optimising framework (as in the seminal Krugman, 1999, paper). Even within mainstream economics space had therefore become heterogeneous and without assuming any intrinsic difference between places, nor because of institutional or social constructs limiting the equilibrating powers of markets. Rather, it was illustrated as existing in a fully rational setting with optimising agents interacting in the markets.

In parallel, and with the economists now explicitly interested in spatial mechanisms, several other strands of studies have come to acknowledge that crucial role of space. The economics of innovation, following the development of evolutionary theories (Boschma & Frenken, 2006; Nelson & Winter, 1982), has learned that innovation is a path-dependent and highly uncertain game, whose chances of success heavily depend on where potential innovators are located. This happens because innovation is the outcome of interactions between different pieces of knowledge usually possessed by different agents, not just firms or individuals, and is often collectively owned by local communities. Rationality is bounded, knowledge exchange requires interactions, and these are made simpler by direct contacts. For this reason, innovation economics nowadays does not just study how innovation takes place but also where since this is an important determinant of the outcomes.

Business studies have also come to acknowledge the importance of space for economic processes. Porter's famous diamond, originally developed at the firm level (which included the contexts of firms) was soon extended to nations and, from there, competitiveness became central in studies of regional growth. At the same time, locational aspects were never again detached from the investigation of firm success.

Competitiveness and regions therefore will never be separated again as concepts because the competitiveness of firms depends on the region where they are located and the success of regions depends on the firms located within their boundaries (Huggins & Thompson, 2017).

Finally, it is important to mention environmental economics. This is not a new issue and nor are its spatial implications. However, its importance has increased with the rise in concern about climate change and environmental protection. These phenomena, while global, do not impact places in uniform fashion. Geographically, different places are affected by different challenges (e.g., floodings for some places or drought for others). In terms of economics, places differ in their preparation to the challenges. Furthermore, the global interventions to mitigate all these challenges place a different toll on to different places, largely depending on their economy (McCann & Soete, 2020).

Space, in spatial economics, is not only reflected in physical proximity (Capello, 2015). While distance and proximity are very relevant, this is because they make interactions easier, as shown by the economics of innovation (Boschma, 2005; Breschi & Lissoni, 2001). It is in fact the interactions between economic agents that make economic processes possible and viable. SEA therefore, is not just about proximity but about space in this wider meaning.

The seven papers included in this issue present several of these aspects and are hence quite representative of spatial economics.

The first paper is by Paul Elhorst. Professor Elhorst is the former Editor-in-Chief of SEA and was the main motor behind the journal’s growth in terms of contents, impact and reputation over his eight-year tenure, which ended in 2023. He was also the main author of the editorials opening each regular issue, all of them sharing the title ‘Raising the bar’ following from his earlier very successful paper bearing the same title published in this journal (Elhorst, 2010). The paper presented here (Elhorst, 2024, in this issue) takes stock of all these editorials in a critical review of the main concepts that have emerged in SEA over the past eight years to identify ‘two main laws of spatial economics: (i) units of observation cannot be treated as independent entities because they interact; and (ii) interaction causes spillovers from one unit to another’ (Elhorst, 2024, in this issue).

These two laws constitute a basis for spatial economics because it is in the interactions between different units at different scales that space finds its role. The paper by Elhorst illustrates this by referring to a number of approaches: economic theory and new economic geography, input-output modelling, spatial econometrics, gravity and origin-destination models, climate change and house prices. In each case, a number of issues emerging for the measurement of effects is presented and the conclusion is that there is still a large amount of work to be done in spatial economics since no approach is really able to fully consider the two laws at the same time.

The paper by Capello et al. (2024, in this issue) presents the fifth edition of the very successful MASST (MAcroeconomic Sectorial Social Territorial) model, whose second edition was published in this journal 12 years ago (Capello & Fratesi, 2012). This econometric model is designed to simulate scenarios for EU regions and is based on two sub-models at regional and national levels, interacting so that bifurcations happening at either level have impacts on both regional and national growth. A specific characteristic of this model is that, in contrast to CSGE models, it is specifically designed to simulate scenarios at the regional level and, as such, is not optimising but, differently from CSGE models, allows for the modelling of bifurcations and long-term trends.

In the paper published in this issue, the new edition of the model is presented with specific emphasis on two main trends, that of digitalisation, including the emergence of industry 4.0, and that of globalisation. In particular, the changes to global value chain and reshoring of economic activities. The MASST model, furthermore, is specifically one in which growth spills from one region to another, as well as between countries and regions and vice versa.

One of the issues where spatial components are not adequately considered are fiscal revenues and inequal public budgets. The literature has long been aware of the issues related to fiscal federalism and fiscal competition between jurisdictions (Oates, 1999; Wildasin, 2003) but even centralised states experience different revenues per capita due to the fact that people’s incomes are related to regional production disparities and that most tax systems are progressive. Furthermore, explicit fiscal equalisation systems between regions are present in many countries.

These issues are analysed in the paper by Malkina (2024, in this issue) which shows with Russian data that disparities in tax collection are larger than those in production. The paper, after reviewing conceptually the advantages and disadvantages of fiscal equalisation systems, decomposes fiscal revenue per capita into components, which allows for an analysis of the Russian fiscal equalisation system. Some unpleasant results also emerge. For example, the system proves to be pro-cyclical instead of anti-cyclical, there are difficulties for weak regions to levy own resources and there is a wide relevance of informal and non-transparent mechanisms, which serves as another example of the importance of institutional mechanisms in spatial economics.

The next paper by Chen et al. (2024, in this issue) provides an investigation into how institutional mechanisms work in space by looking at peer effect and political competition and in this case focusing on one very timely issue, that of eco-efficiency (i.e., producing more with fewer resources). It has in fact become fundamental to decouple growth from energy consumption and this is especially important for China, the country analysed in the paper, whose demographic size and rapid economic growth over recent decades have made it by and large the main polluter in the world.

The paper builds a model in which administrators of different constituencies compete on growth and eco-efficiency at the same time by looking for the best allocation of their budget. It tries to disentangle the impacts of political competition on eco-efficiency, which is also tested in a spatial econometric setting so as to consider spatial interdependencies. Results show a U-shaped pattern in the evolution of eco-efficiency, which first decreased and then increased between 2003 and 2015. In particular, the paper shows that more political competition leads to less eco-efficiency, which could be countered with specific incentives and evaluation systems.

The units that can interact in the spatial economy are not necessarily regions because spatial economics is able to model and analyse the behaviour of smaller scale agents and individuals as the two following papers show. In particular, the choices of economic agents do not just depend on their characteristics but, largely, on their location. The paper by Castells-Quintana et al. (2024, in this issue) hence studies the effectiveness of mobility restrictions imposed by the government during the COVID-19 pandemic. Data from phone-tracked individual movements are shown to depend on socio-economic characteristics of neighbourhoods in the city of Bogotà, with a comparative analysis of pre-pandemic and post-pandemic data. The fact that mobile phones are almost universally ubiquitous allows the authors to compare the behaviour of people from rich and poor backgrounds whose reactions to the same stimuli are different. This also depends on the option to stay home, as well as job and sector of activity. With poorer zones in the city being denser and overcrowded, the possibilities for working from home are also different. Compliance with restrictions in poorer neighbourhoods is also found to be significantly lower, and also lower than in the poor neighbourhoods of richer cities elsewhere.

The next paper, by Aydinoglu and Sisman (2024, in this issue), provides an interesting example of how macro trends depend on micro-level decisions and, at the same time, individual decisions depend on macro-variables. The study of these aspects is made possible by the use of large-scale data and innovative techniques, whose presence in SEA has always been consistent and welcome. In the paper a methodology is developed for computer-assisted mass appraisal (CAMA) of real estate values with an application to Turkish districts. Mass appraisal can be a more convenient alternative to traditional individual appraisal techniques. In this case, the methodology identifies from the data, after eliminating both individual and geographical outliers, the geographical appraisal zones through network-based spatially constrained multivariate clustering analysis. In this way, more homogeneous areas can be built. Then, a very wide and encompassing set of features affecting real estate values inside each zone are investigated through the random supervised machine-learning technique. The results for both individual and site-specific characteristics show that levels of importance and the rankings of both individual and locational features differ in the geographical appraisal zones.

The last paper by Otto et al. (2024, in this issue) also has a real-estate application but it is used as a way to illustrate the advantages of the innovative methodology that it introduces. The starting point is the spatial effects in volatility, which are a very important determinant of market risks because what happens in closer areas may also impact this aspect. For this reason, simple ARCH (AutoRegressive Conditional Heteroskedasticity) models are inadequate for spatial analysis. The paper, therefore, presents a dynamic spatiotemporal ARCH model that allows for unobserved heterogeneity over time and space. In this way, it is able to consider both time and space effects on volatility as well as higher order lags. This is estimated through the generalised method of moments (GMM) and its asymptotic and finite-sample properties are studied with a Monte-Carlo analysis demonstrating why it is superior to a quasi-maximum likelihood (QML) approach. After the presentation of the estimator, its potential and usefulness is demonstrated through an application to the case of monthly condominium prices in Berlin. The analysis shows that the spatial, temporal and spatio-temporal lags of the log-squared returns have statistically significant effects on the log-volatility.

To conclude this editorial, the current editorial board, comprising both long-standing and newly appointed Co-editors,¹ wants to thank the Co-editors whose terms recently ended, including Arnab Bhattacharjee, Coro Chasco and Umed Temursho, and especially Editor-in-Chief, Paul Elhorst, for the excellent work done over the last eight years to consolidate the reputation of SEA as a pathbreaking, theoretically strong and empirically sound journal dedicated to spatial economics. We will work hard to maintain and, hopefully, grow this reputation.

Notes

1 https://twitter.com/spatialeconomic/status/1782684938715660606.