A. Firms, jobs, and capital

Firms’ location decisions are shaped by multiple forces. In many sectors proximity to customers is all-important, as goods or services do not travel well or have to be supplied face-to-face. Other sectors, such as natural-resource intensive sectors, locate close to raw materials. In sectors not dominated by these forces, location decisions depend on factors including wages, productivity, the supply of suitably skilled labor, and ease of access to customers and to suppliers of intermediate goods and services.

These factors have a spatial dimension, particularly as firms derive advantages from proximity to other firms and to households—”agglomeration economies”. Agglomeration effects reflect the economies of scale that arise between firms, and also between firms, households, and workers (Duranton and Puga 2004, 2020; Puga 2010; Rosenthal and Strange 2004). Some of these benefits arise simply from cost saving. If your customers and suppliers are close by, they can be reached at low cost; just-in-time operation requires both frequent and reliable deliveries, easier to secure if suppliers are nearby. Other benefits arise as there are often knowledge spillovers between firms.⁹ These effects are manifest particularly in the tendency of firms in R&D-intensive sectors to cluster together.

Agglomeration benefits also arise because of scale and specialization. Larger and denser markets allow for scale, scope, and specialization. Specialist suppliers and workers represent a good example. The larger the market, the more likely that a firm or worker will find it worthwhile to specialize and hone skills in producing a particular good or service. This specialization creates high productivity. And, while customers pay for the product, they are likely to also receive some net benefit, over and above what they pay. This creates a positive feedback. Customers will be attracted to a place with multiple suppliers, thereby growing the size of the market, and making it attractive for further and more specialized suppliers to set up operations. This is the classic process of growing a ‘business ecosystem’ and of cluster formation.¹⁰

The agglomeration process operates at several different levels. In the supply of intermediate goods between firms, it is the basis of the ‘linkages’ discussed in an old development economics literature, and in the ‘new economic geography’ research (Fujita et al. 1999). Between firms and final consumers, it is the basis of Krugman’s ‘core-periphery’ model (Krugman 1991). And in the labor market, it takes the form of thick market effects that allow for better matching of firms to workers. In some contexts these agglomeration economies are based on overall economic activity in an area—the size and diversity of the labor force, and the level of demand for goods and services. In others they involve sector-specific knowledge spillovers, specialist labor skills, and demand and supply linkages in related sectors. The strength of different effects varies widely across sectors.

Agglomeration implies spatial differences in productivity. There is significant research on the extent to which firm productivity varies with access to economic size. Economic size typically refers to an area such as a city or travel-to-work area, and is measured in different ways, such as urban population, or more sophisticated measures of market access or the ‘effective density’ of a city or region. A consensus view is that, after controlling for variation in labor-force characteristics (skills, age, and in some cases occupation), the elasticity of productivity with respect to economic size is around 3–6 percent in advanced economies (Combes and Gobillon 2015, Rosenthal and Strange 2004). This means that each doubling of economic size raises productivity by around 5 percent, so that a city of 5 million has productivity 20–30 percent higher than one of 200,000, numbers that align well with casual observation of London or New York as compared to smaller towns and cities. Of course, these are average numbers, and the productivity advantage of urban areas will show up in different degrees in different sectors, and affecting different types of labor. For example, in advanced countries regional disparities in the wages of skilled labor have increased much more in recent years than has been the case for unskilled labor.

Agglomeration effects are possibly much larger in developing countries. There, weaknesses and wide variation in the provision of physical infrastructure (such as transportation, communications, and power), in education, and in provision of public services, significantly reduce the attractiveness of lagging places for investment unless offset by correspondingly large wage differentials (World Bank 2009). Estimates based on variations in productivity across urban areas in developing countries suggest an elasticity of productivity with respect to city size of around 8 percent, twice that in developed economies (Chauvin et al. 2017, Glaeser and Xiong 2017). Regional productivity and earnings differentials are amplified further by the presence of informal sectors and traditional agricultural activities, whose productivity may be four or five times lower than that of modern sector urban activities (Gollin et al. 2014).

Agglomeration economies imply that regional disparities may prove persistent. There is a ‘first-mover’ or coordination problem: no firm wants to leave an existing cluster and forego the associated productivity benefits. Coordinated movement by many firms might be collectively profitable, but the market mechanism cannot achieve this. This is because, while each firm creates benefits for other firms, these do not enter its decision taking. It follows that even large wage differences between regions may be insufficient to induce firms to locate in a lagging region, rather than in an established center. A further implication is that there are threshold effects and ‘tipping points’. Policy changes below some threshold may be wholly ineffective, while a ‘big-push’ of policy across a range of actions may stand a greater chance of success (Murphy and Shleifer 1989).

Agglomeration effects also imply that transport and infrastructure improvements, and ‘connectivity’ more broadly, have ambiguous effects—but at some point are likely to reduce disparities. Reducing the cost of shipping goods and services—globalization—enables clusters of activity to form, since production no longer has to take place close to consumption. This allows regional disparities to develop, particularly if clusters are associated with high productivity. But in the limiting case where connectivity is perfect, and goods, services, capital, and knowledge are equally accessible from all places, then geography is immaterial—the ‘death of distance’. We are back in the textbook model of firms moving to the lowest-wage places, thus removing regional wage disparities and securing factor price equalization (Fujita et al. 1999). This ambiguity makes it difficult to generalize about the effects of improving connectivity.

Moreover, the effects are highly sector-specific. In finance and some creative sectors, improved information and communications connectivity has promoted the concentration of activity. A few centers can supply services to much of the world, while at the same time benefiting from the agglomeration economies of thick local labor markets and a cluster of providers of specialist services. In other sectors, the emergence of global value chains means that value added in production of a final product has become more dispersed, helping reduce inequalities across countries. Yet different stages of production (’tasks’ or functions such as R&D and inputs of financial and legal services) have become more spatially concentrated, sometimes in just a few cities, so creating disparities within countries. While these global changes in connectivity will affect different regions in different ways, it is nevertheless likely that a lagging region is more likely to be an attractive destination for inwards investment, the better connected it is.

In summary, the potential movement of jobs and capital does not imply equalization of productivity, but does place bounds on spatial productivity differences. In an advanced economy with good connectivity and little variation in public capital, productivity in booming areas may be up to 60 percent higher than in lagging regions (as in Figure 1, top panel). In developing countries connectivity is probably weaker, variation in public capital is much greater, and agglomeration effects may be more powerful, yielding larger productivity variation (Figure 1, bottom panel).

B. Migration and labor

The second mechanism that should act to equalize real incomes across regions is the migration of workers to places with higher real income. Returns to mobile factors will then tend to be equalized and productivity differences will show up in the returns to immobile factors. For example, suppose that labor is perfectly mobile while land and housing is immobile and fixed. Labor mobility then tends to equalize real incomes (utility), because people leave a low wage region until the price of land and housing has fallen to a low enough level to compensate for low nominal wages. At the same time, the price of land and housing is bid up in the destination region (Combes et al. 2019), and it is landowners who capture much of the agglomeration benefits of booming cities.

But migration may fail to iron out spatial differences in real incomes. First, the gains from moving to higher productivity areas vary across individuals. Spatial wage differentials are much higher for some skill types, often skilled as opposed to unskilled workers, so migration tends to change the skill and occupational mix of different places. Second, migration is costly, financially and also because of social networks and other amenities that are lost in migration. These costs vary widely across individuals in the population. Migration from lower- to higher- wages areas is therefore income-equalizing for the marginal worker but, across the population at large, leaves spatial variation in productivity, wages, and real income. Those left behind in lower productivity areas, for whom moving costs exceed the expected present value of gains from relocation, are likely to be older and less skilled workers.

Declining areas are often subject to a vicious circle of further decline. As young, skilled workers migrate away, the local tax base and hence tax revenues diminish. In turn, this implies a deterioration in public services, such as schools, public safety, and cultural amenities (Florida 2014), and/or an increase in local tax rates (Pallagst et al. 2014). A shrinking local market may reduce any local agglomeration benefits; for instance, the “brain drain” of skilled workers decreases the region’s ability to attract clusters of skilled, innovative activities (Davis and Dingel 2020, Berry and Glaeser 2005). Falling land and property prices may lock-in older residents (as owner-occupiers are unable to finance moves, particularly if capital markets are imperfect), but also cause a deterioration in standards of property maintenance and upgrading. Under these circumstances it becomes even harder to retain or attract skilled workers (including public sector employees, such as teachers) and inward investment by firms. The region may become locked in a downward spiral (Holmes and Ohanian 2014, Weaver et al. 2018), characterized by persistent urban decline (Glaeser and Gyourko 2005).

C. Spatial equilibrium

Spatially uneven outcomes may represent a “spatial equilibrium”. Because of agglomeration effects, productivity is higher in a cluster or booming region than in a poorly connected lagging region. If wages are correspondingly higher in the high productivity area, then no individual firm has an incentive to move. Workers and households may have little incentive to move either, if land and property prices are low enough in the lagging region to compensate for lower nominal wages.

The nature of the spatial equilibrium poses several problems. First, this equilibrium is not generally efficient. There are multiple externalities; for example, growing a city brings positive externalities from agglomeration, and negative ones from congestion and pollution. Coordination failures mean that efficient outcomes are not achieved (see examples below). Second, as we have noted, real incomes are not fully equalized across space, for several reasons. Most importantly, migration is slow, causes adverse changes in the skill and age structure of places experiencing substantial out-migration, and creates large social costs for the ‘left-behind’. In addition, there are limits to the extent to which low land and property prices can compensate for low wages—once such prices fall far enough, then housing is left vacant as the place depopulates.

D. Growth and regional disparities in developing countries

It is almost inevitable that a process of rapid growth and structural change starts in a few places, rather than uniformly across a country. Agglomeration forces are likely to be strong, as firms, skilled workers, large markets, and the network of supplier firms that support agglomeration are concentrated in a few large centers. This is likely to be reinforced by the spatial distribution of public capital. Transport infrastructure, power grids, and other utilities are all expensive and lumpy investments that will initially serve some regions better than others. It is efficient to concentrate them in areas of high population density and incipient, if not actual, economic activity. In addition, political institutions and policies may encourage over-concentration in excessively large cities, through a skewed allocation of public services and underinvestment in inter-regional transport and communications (Davis and Henderson 2003). In such circumstances the first-mover problem is acute, meaning that firms and workers will concentrate in the economic center, even if spatial wage differences are large. This is manifest in, amongst other things, the growth of developing country mega-cities and the problem of ‘excess primacy’, that is the dominance of the largest city in the overall urban hierarchy (World Bank 2009, Henderson 2002).

From these beginnings, how is convergence likely to be achieved? Jobs are likely to spread out of central areas, as costs in these areas increase. Wages and land rents increase, and so too may costs of congestion and pollution. This spread of activity can be promoted by provision of transport and other infrastructure. At the same time, there will be movement of people towards prosperous areas, further boosting the mega-cities, and possibly creating demographic and social problems in places experiencing out-migration. It is unsurprising that countries should want to manage the balance of these two different processes, but doing so is difficult. Direct controls of population movement—the Chinese hukou system—may be effective, but are viewed as impractical or undesirable in many countries. Appropriate measures will be country-specific, but should generally support the growth of secondary cities, while at the same time accepting that some regions are likely to face population decline.

E. Lagging regions in advanced economies

International competition and technical change have created large and persistent regional disparities in a number of advanced economies. The shocks are typically sector- and place-specific, hitting a sector in which some areas have had a traditional comparative advantage, such as textiles, shipbuilding, extractive industries and, in some cases, the automobile industry. That is, regional disparities are relatively more likely to be symptomatic of negative shocks in advanced economies than in developing countries. How do places adjust to these shocks, and how is it that, in some cases, the impacts are so persistent?¹¹

In this context, adjustment mechanisms may fail for several reasons. We have already discussed some of these issues, and two further points need to be made. First, there may be downwards rigidity in nominal wages, arising from both institutional frictions and the setting of national, rather than regional, norms. This has resulted in high levels of unemployment in many affected regions (Figure 2). More fundamentally, even with wage flexibility and full employment, there remains the question of what sectors are likely to replace those that have been lost. Many of the traditional industries that have been hit by these changes involved highly sector-specific skills that are not attractive to potential inward investors. And, fundamentally, agglomeration economies often operate at the sectoral level (“economies of localization”). This means that sectoral clusters form (for instance, in finance, technology, and the creative industries), and that the first-mover problem is strong in such sectors. Those areas that have lost traditional tradable sectors do not offer an internationally competitive environment for these new sectors. These areas do however, if wages are low enough, offer an environment for non-tradable sectors supplying the domestic economy—for instance, back-office operations, warehousing, local food processing, and public sector administration. Such areas have therefore tended to fill up with these non-tradable sectors, often offering low-skill and low-wage jobs. The difficulty of setting up new tradable sectors (especially those with localization economies) means that it is possible for a country to end up both with regional disparities and with an inefficiently small tradable goods sector. This is a low-level equilibrium trap, brought about by the first-mover problem.

A. Spatially blind, spatially connective, and spatially targeted policies

The geography of economic activity within countries has changed fundamentally in recent decades, in particular in advanced economies. Following a long period of regional convergence, international economic integration and technological progress that favors economies of scale and agglomeration have triggered deep structural changes within national economies, including an increasing concentration of value creation in a number of metropolitan areas. Is it possible to withstand the forces of skill-biased technological change, globalization, and agglomeration that have driven regional disparities in recent decades? Moreover, is it desirable to do so, as these same forces have also been key drivers of overall economic growth and prosperity? Hence, is there an inherent tradeoff between economic efficiency and regionally inclusive growth, or are there effective policies that can revive economic activity in declining areas without jeopardizing aggregate growth and welfare?

Traditional economic orthodoxy suggests that governments should care about people rather than places. Economic policy should focus on macroeconomic stability and building strong economic institutions that allow an efficient allocation of resources and smooth adjustment to shocks through free flows of labor and capital, while ensuring the provision of public goods and affordable access to basic services such as primary health care, education, sanitation, and security. Policy makers should focus on attaining spatial inclusiveness by promoting equality of opportunity rather than even economic activity across regions. Progressive taxation systems and social protection could help achieve more equal outcomes in terms of disposable real incomes and living standards.

As a result, spatially blind, people-based policies would generally be the first choice to address regional disparities in countries where labor and capital are mobile (World Bank 2009). These are universal policies applied on a national level, which do not explicitly focus on lagging regions, but which can nevertheless assist them by assisting lagging households. Such policies could include measures to:

• Strengthen public services such as health, education, and utilities (for instance, rural electrification).

• Ensure that interregional transfers, stemming for instance from a progressive tax system and social protection, as well as nationwide economic regulations, all assist lagging households.

Spatially connective policies could complement spatially blind policies, by connecting peripheral areas to markets, facilitating the movement of goods, services, people, and ideas, integrating lagging and leading areas, and thereby promoting interregional convergence. Such measures could include:

• Infrastructure investment in highways, railroads, ports, airports, and public transportation, as well as in information and communication networks. The return to these policies will be especially high where lagging regions nevertheless enjoy relatively high economic density.

• Efforts to facilitate the movement of people from lagging regions to more prosperous ones (“mobility towards opportunity”).

However, the experience of recent decades raises some doubts as to whether these standard policy prescriptions are sufficient to overcome regional divides and promote opportunity. While spatially blind and connective policies may help many skilled, young, and ambitious people in lagging regions move toward better opportunities in booming regions, the majority of the population is less mobile and may remain stuck in their declining home regions. In some (mostly developing) countries, inter-regional mobility is inherently hindered by geographic, social, cultural, or ethnolinguistic divisions. Moreover, mobility is not always towards opportunity: while mobility in most OECD countries is indeed towards urban metro centers (OECD 2018), for the United States a much higher share of moves has been between lagging (’low-vitality’) regions rather than from less to more dynamic regions (Nunn et al. 2018). In many advanced economies, the declining demand for lower-skilled labor and steep increases in housing costs in booming regions have further reduced migration from lagging regions (Nunn et al. 2018, Bayoumi and Barkema 2019, Hsieh and Moretti 2019). This limited mobility has contributed to high and persistent non-employment rates in some regions that have experienced deindustrialization and economic decline (Austin et al. 2018). In this context, unemployment is a far more important determinant of discontent than low earnings—increasing social strains in economically depressed regions are linked to a lack of jobs rather than of disposable income (Austin et al. 2018, Neumark 2018).

All this suggests a case for spatially targeted, place-based policies that make lagging regions more attractive places in which to create jobs, for instance by supporting local demand and improving business conditions, as opposed to people-based redistributive policies that aim to address skewed economic outcomes. Regionally focused incentives could encompass:

• Location-specific favorable tax treatments, investment subsidies, special regulations, and investment climate reforms.

• The targeted location of public employment, and public funding of research and higher education facilities or local infrastructure.

Economists have traditionally been skeptical about the effectiveness of spatially targeted policies, and concerned about their distortionary side-effects. The conventional wisdom is that such policies have at best mixed effects (Neumark and Simpson 2015). Their impacts have often been limited and not sustainable. Sometimes, they largely amount to beggar-thy-neighbor policies that shift activity and employment from one place to another (Ehrlich and Overman 2020). That said, infrastructure policies seem to work better than tax exemptions, or employment and investment subsidies. For instance, in the United States, the Tennessee Valley Authority generated significant improvements in that region’s infrastructure, with a lasting impact on its development. But even in this case, the local manufacturing agglomerations it engendered were offset by losses in the rest of the country (Kline and Moretti 2014). The fiscal costs of interventions can be high, and favoring some regions over others generates horizontal-equity concerns (Gbohoui et al. 2019). Other possible side-effects include distorted migration and the capitalization of the benefits into housing costs (Austin et al. 2018). Moreover, the case for place-based policies was historically weak against the backdrop of a long period of regional convergence and high inter-regional mobility.

Nevertheless, spatially targeted policies never completely fell out of policymakers’ favor, and the case for them has strengthened over time, given persistently high and/or widening regional disparities, lower inter-regional mobility, and the social and political costs of the deindustrialization and economic decline of entire regions. Some market failures may be best addressed at the local level—for instance, localized productivity spillovers, or when not-working rates and employment elasticities are both comparatively large in distressed regions (Austin et al. 2018). Even where efficiency arguments for such policies are weak, they could help insure individual regions against place-based shocks, and address equity concerns (Gaubert et al. 2021).

B. Firms, jobs, and capital

We now examine the case for some of these policies in greater detail. We focus first on measures to boost job creation, including both spatially connective policies, and place-based policies such as the localization of public investment and public employment, tax or spending benefits for businesses and/or individuals, and regulatory relief measures. Policy measures can be explicitly spatial (such as the U.S. Appalachian Regional Commission, the Mezzogiorno tax credit for Italy’s South, or the solidarity surcharge for East Germany) or implicitly spatial, for instance sectoral support for an industry that is highly concentrated in specific regions.

Public capital: infrastructure and connectivity. Spatially connective infrastructure, for instance highways, railroads, and metropolitan transit networks, can promote mobility, either by facilitating long-distance moves or by reducing economic distance, allowing commuters from further afar to participate in the economic activity of a leading region (Neumark 2018, Smith 2018). In the latter case, a metropolitan area enlarges by integrating its hinterland. A good example of a spatially connective policy initiative that goes beyond mere transport infrastructure is the concept of “rural-urban integrated cities” developed in South Korea. Launched in the mid-1990s, the policy aimed at reducing rural-urban disparities by integrating rural counties with cities in a unified spatial framework. Such frameworks encompass joint planning of transport links, land use, public service provision, and local administration (World Bank 2009).

At the same time, physical and digital infrastructure helps connect different regions, improving the access of entrepreneurs and firms in lagging areas to the larger and thriving markets of leading areas. While better access to a large and growing market may boost some economic activity in the lagging area, it also allows companies from leading areas to compete in the periphery. Furthermore, firms from the lagging area may be lured to relocate to the leading area themselves. Thus, better infrastructure links could also further increase the concentration of economic activity. Most likely, industries that exhibit agglomeration economies would relocate to the center, while those that do not might benefit from the lower labor costs in the periphery.

Spatially targeted public investment projects are generally the most popular tool for promoting local economic development. Empirically, their record is mixed. Generally, they have been successful when they identified and targeted regional interventions with high returns, such as the electricity supply capacity created by the Tennessee Valley Authority. Such projects produced durable employment impacts and agglomeration economics, serving as incubators for private investment. However, public investment programs have failed to make a lasting impact where they did not target high return interventions, their scale was too modest, or their scope too broad. Moreover, there are risks that political pressures, limited local ownership, and the lack of thorough cost-benefit analysis produce white elephant projects with marginal benefits and possibly high follow-up costs for operation and maintenance. Policymakers can mitigate such risks through close coordination and collaboration with local authorities, businesses, and citizens, together with rigorous cost-benefit and impact analyses. The European Union’s Smart Specialization Strategy is a promising approach in this regard.

To some extent, governments can also support structurally weak regions through the targeted location of government agencies, public research institutions, technology parks, or military installations. Some developing and emerging economies have gone as far as relocating the country’s administrative capital in an effort to both develop the hinterland and to reduce congestion in the traditional center (for instance, Brazil, Indonesia, Kazakhstan, Myanmar, Egypt). While proximity to federal or state capitals may be important for some government agencies, others are quite insensitive to location (Yglesias 2016). Stable public or publicly funded white-collar employment could serve as a solid demand base for local economies that lack agglomeration economies and other competitive advantages. Moreover, colleges, universities, research institutions, and technology parks can also have substantial local externalities in terms of symbiotic public-private training and research partnerships, entrepreneurial start-ups, and the diffusion of knowledge, ideas, and technologies to local firms (Baron et al. 2018, Link and Scott 2018). The broad distribution of federal and state government agencies as well as research institutions has in many cases successfully contributed to the mitigation of regional disparities in Germany, sustaining the local economies of small- and mid-sized cities and creating symbiotic partnerships. Examples are the network of Fraunhofer Gesellschaft research institutes or Baden-Württemberg’s universities of cooperative education, with their close links to regional small and medium enterprises.

The regional targeting of corporate tax incentives and subsidies could be attractive if there are large regional differences in unemployment (for instance owing to the decline of a localized industry), and measures supporting employment promise to have a high return in lagging places. Many developing countries have introduced special export processing zones, some of which have been very successful as incubators for broader industrial development (such as the Special Economic Zones in China). Policymakers in advanced economies have introduced corporate investment and employment incentives in the form of tax credits, subsidies, preferential credit, or funding for workforce training to support disadvantaged regions (Neumark 2018). Examples include the United Kingdom (Enterprise Zones), United States (Empowerment Zones and Opportunity Zones), France (Zones Franches Urbaines), and the European Union’s Cohesion Policy. Their results have been mixed, with both the size and the sustainability of impact being very sensitive to the time period and individual approach (Austin et al. 2018, Busso et al. 2013, Ham et al. 2011, Neumark and Kolko 2010, Greenbaum and Engberg 2004, O’Keefe 2004, Bondonio and Engberg 2000). Case studies suggest that interventions are more likely to prove successful if they build on existing comparative advantages, focus on innovative and high value-added activities, and display close coordination between national and regional authorities and the private sector.

Region-specific tax incentives or subsidies for individuals are less common than for corporations. They are generally regressive (with benefits accruing mostly to higher-income earners), poorly targeted for regional redistribution, and may result in distorted migration to subsidized areas without incentivizing concomitant job creation. Moreover, horizontal equity concerns are likely to be more serious for individual than for corporate subsidies. That said, spatially blind national tax policy can have implicit spatial effects, as with the 2017 U.S. tax reform, which combined lower individual tax rates with caps on the deductibility of home mortgage interest, thus penalizing coastal high-tax states.

In numerous cases, spatially targeted regulatory relief measures have been combined with corporate employment subsidies in special enterprise zones. They include relaxed zoning and environmental regulations, one-stop permitting, and other simplified bureaucratic procedures. In other cases, stringent urban zoning and building regulations, such as minimum lot sizes, maximum lot occupancy rates, height and unit restrictions, or historic preservation districts have contributed to an inelastic housing supply with steep housing cost increases, restricting the population growth in booming areas (for instance the San Francisco Bay area or London).

C. Migration and labor

Several factors have negatively affected interregional labor mobility, often rooted in policies that have created market distortions. The most important are housing costs and social benefits (Bayoumi and Barkema 2019, Hsieh and Moretti 2019, Nunn et al. 2018, Ganong and Shoag 2017). Sometimes, discriminatory policies and residential segregation along ethnic/racial lines have contributed to and manifested inequalities on the regional or local levels (Hardy et al. 2018, Pietila 2010). Moreover, there are also social costs to moving and leaving family and friends behind, and these costs are likely rising given ageing societies and the high cost of elderly care and childcare.

Housing costs. In some countries, stringent municipal zoning regulations, building codes, and land-use conversion rules have contributed to an increasingly constrained and inelastic housing supply in booming areas (Hsieh and Moretti 2019). The resulting steep increases in housing cost have made it unaffordable for many people to move from lagging to leading regions.¹² Disincentives from high housing costs dominate the incentives from higher potential earnings, especially for people in lower-wage professions (Bayoumi and Barkema 2019). In many developing countries, insecure property rights, high transaction costs due to the lack of titles and cadasters, and limited access to credit are additional deterrents to regional mobility (World Bank 2009). Consequently, strengthening property rights and making land use, zoning, and building regulations more flexible could help make housing supply more elastic, transactions smoother, and housing more affordable. Support for investment in social housing could help increase the availability and affordability of housing in booming urban areas.¹³ Finally, some cities rely on rent-control regulations; these may limit the cost of existing living space, but are also likely to deter investment in new housing units.

Social benefits. Non-portability of state and local social benefits is a major deterrent to labor mobility. Public pension schemes, often explicitly designed to incentivize long-term job commitment, create strong incentives for public employees not to leave (Economist 2017). Municipal-level social benefits, such as housing vouchers, as well as federal social programs that are administered at local or regional levels (for instance, Medicaid in the United States) equally encourage people to stay put, as they may lose or have to reapply for the benefits when they move between counties or states (Austin et al. 2018). Lower living costs in lagging regions may motivate people that rely on fixed social benefits, such as unemployment insurance, not to relocate. The granting of a universal basic income could have a similar effect, reducing labor supply in booming regions (Waldman 2016). On the other hand, it would also help support demand in lagging regions. That said, both effects are likely modest.

D. Choice of measures and implementation considerations

There are trade-offs between spatially connective policies that strengthen mobility, and spatially targeted policies that directly support local economies. Measures that improve mobility reinforce regionally unbalanced growth and geographical concentration, withdraw the most productive workers from lagging regions, and thereby further diminish the economic prospects of the less skilled and mobile workers that are left behind. In contrast, place-based policies foster more balanced economic activity across regions, but may hamper overall economic growth by inhibiting an efficient spatial allocation of capital and labor. This is because the same forces that lead to a concentration of economic activity and inequality are important drivers of growth: technological progress has favored economies of scale and agglomeration, while international economic integration has created opportunities but also brought about structural change and dislocation in many local and regional economies. Misguided place-based policies could result in unproductive capital investment, and discourage efficiency-enhancing labor mobility by distorting workers’ incentives to move towards opportunity. Thus, policy makers need to strike the right balance between fostering rapid but regionally uneven growth on the one hand, and promoting more inclusive regional development outcomes on the other.

Ultimately, the choice of policies must be country- and context-specific. One-size-fits-all policy interventions are not appropriate for vastly different regional economies, and there is merit in ‘place-sensitive’ policies tailored to particular locales. The right mix of measures may differ between advanced and developing economies, or between higher- and lower-income regions. Spatially blind and spatially targeted policy strategies can complement or counteract each other, depending on the context. The goal is always to release the development potential of all regions, and counter the under-utilization of skills and resources (Iammarino et al. 2016). To this end, “economic development policy should be both sensitive to the need for agglomeration and the need to occur in as many places as possible”, to foster dynamic efficiency and maximize the aggregate economy’s future innovation potential.

The appropriate policy mix will depend on the characteristics of a country’s leading and lagging regions, and the key drivers of regional disparities. Sparsely populated lagging areas may be best served by people-based policies focused on providing basic public services. In contrast, large-scale infrastructure investment would likely generate low returns, and spatially targeted policies aimed at attracting business investment would be handicapped by the limited market size and shallow local labor markets. Densely populated lagging areas, on the other hand, could benefit from spatially connective infrastructure if there are no significant structural impediments to mobility, and otherwise from spatially targeted incentives and local infrastructure investment (World Bank 2009). In this context, policymakers should consider to what extent disparities reflect strong agglomeration economies, low interregional mobility, or weak interconnectedness of regional markets. Policy should also take into account the specific regional economic structures, resource endowments, and employment elasticities, as well as the presence of positive or negative externalities, and any regional targeting challenges. More broadly, in advanced regions, policies should focus on maintaining the innovative edge to keep abreast with the routinization, imitation, and geographic spread as technologies mature. In lagging lower-income regions suffering from limited skill pools and productive capital, policies should exploit wage competitiveness, and boost local capacity through active labor market policies, education reforms, and university-industry linkages to foster skill development and innovation absorption. Policy makers must also bear in mind the potential for reforms to trigger out-migration of the skilled and young, resulting in negative demographic dynamics that further undermine economic and social creativity.

Authorities should also consider fiscal costs, policy space, and implementation capacity and quality of governance at both the national and regional level (EBRD 2019). Large-scale infrastructure projects and spatially targeted policies to boost local markets, business investment, and employment are costly. They must be weighed against the expected social returns, using thorough cost-benefit analysis. This is all the more important where fiscal policy space is constrained and spending needs to be prioritized. Even where the economic returns from spatially connective or place-based policies are in principle high, if the quality of governance and the government’s implementation capacity are weak, then actual outturns will likely suffer from delays, wasteful spending, rent-seeking behavior, or outright corruption. In such contexts, the focus should be first on strengthening governance and institutions, including property rights, land regulations, economic management, and planning and implementation capacity at the national and subnational level. Related considerations include the design of intergovernmental financial relations, the presence of vertical fiscal imbalances, and the level of fiscal and political decentralization, which will determine which level of government should be responsible for the design, implementation, and monitoring of policy measures (Bartolini et al. 2016, Gbohoui et al. 2019).

Governments must also take into account political economy considerations, including society’s preferences regarding interregional redistribution. Where the public’s appetite for spatial redistribution is low in general, or limited by the existence of cultural, ethnic, or political divisions between regions, the focus should be on spatially blind national policies with the potential to assist disproportionately lagging regions. These could be complemented by spatially connective measures to help reduce regional divisions over time.

E. Case studies: German reunification, and the Italian Mezzogiorno

We now illustrate the arguments through two case studies of place-based policies. The first, German reunification, proved relatively successful. The second, the Italian Mezzogiorno (South), less so.