metadata: authors: 0: author: Grover,Arti Goswami
1: author: Lall,Somik V.
count: World
docna: 0: docna: Jobs and land use within cities : a survey
            of theory, evidence, and policy
docty: Policy Research Working Paper
subtopic: Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Labor Markets,Roads & Highways,Inter-Urban Roads and Passenger Transport,Roads and Highways Performance,Business Cycles and Stabilization Policies,Transport Services
teratopic: Urban Development,Environment,Transport,Communities and Human Settlements
abstracts: cdata!: Over the last century, the urban spatial
            structure of cities has transformed dramatically from the
            traditional monocentric configuration to varying forms of
            decentralized organization. This paper reviews the theory
            and empirical evidence to understand the urban morphology of
            jobs and land use within a city. This survey highlights four
            broad insights: (i) The evolution of monocentric to
            polycentric centers has been accompanied by structural
            changes in the city. (ii) The internal geography of a city
            is an outcome of the trade-off between the pull from
            agglomeration economies and the push from congestion. (iii)
            The presence of externalities implies that the equilibrium
            spatial organization achieved by profit-maximizing firms may
            not necessarily be optimal. This justifies the role of
            public policy in addressing the associated market failures.
            (iv) The productive edge and competitiveness of a city can
            be enhanced by introducing policies that increase the
            overall connectivity to take advantage of economic
            opportunities across the metropolitan area. The survey also
            puts together a wide range of policy instruments that are
            useful in closing the gap between equilibrium urban spatial
            structure and the optimal outcome.
repnme: repnme: Jobs and land use within cities : a survey
            of theory, evidence, and policy
display_title: Jobs and land use within cities : a
            survey of theory, evidence, and policy
listing_relative_url: /research/2015/10/25191272/jobs-land-use-within-cities-survey-theory-evidence-policy
topicv3: Manufacturing Sectors m1326521 1281,Transport m1326661 135,Highways m1326916 1809,Transport Infrastructure m1327632 1803,Jobs m1503931 2670
publishtoextweb_dt: 2015-10-22T00:00:00Z
historic_topic: Urban Development,Environment,Transport,Communities and Human Settlements
no_of_pages: 43
author_keys: 0: author_key: 1066720
1: author_key: 124534
model_extractions: WPS7453 Policy Research Working Paper 7453 Jobs and Land Use within Cities A Survey of Theory, Evidence, and Policy _Arti Grover Goswami Somik V. Lall_ Social, Urban, Rural and Resilience Global Practice Group October 2015
Policy Research Working Paper 7453

# **Abstract**

Over the last century, the urban spatial structure of cities has transformed dramatically from the traditional monocentric configuration to varying forms of decentralized organization. This paper reviews the theory and empirical evidence to understand the urban morphology of jobs and land use within a city. This survey highlights four broad insights: (i) The evolution of monocentric to polycentric centers has been accompanied by structural changes in the city. (ii) The internal geography of a city is an outcome of the trade-off between the pull from agglomeration economies and the push from congestion. (iii) The presence of externalities implies that the equilibrium spatial organization achieved by profit-maximizing firms may not necessarily be optimal. This justifies the role of public policy in addressing the associated market failures. (iv) The productive edge and competitiveness of a city can be enhanced by introducing policies that increase the overall connectivity to take advantage of economic opportunities across the metropolitan area. The survey also puts together a wide range of policy instruments that are useful in closing the gap between equilibrium urban spatial structure and the optimal outcome.

This paper is a product of the Social, Urban, Rural and Resilience Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at agrover@worldbank.org and slall1@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Jobs and Land Use within Cities: A Survey of Theory, Evidence, and Policy**

_Arti Grover Goswami and Somik V. Lall_ _JEL Classification:_ R12, R13, R14, R3, R52 _Key words:_ Agglomeration, spatial, monocentric, polycentric, land use regulations.

**Acknowledgements** : This paper is a part of a World Bank Regional study on the Spatial Development of African Cities. We are grateful to the World Bank Multi‐donor Trust Fund on Sustainable Urbanization and UK DFID for financial support. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors, they do not necessarily represent the views of the World Bank Group, its Executive Directors, or the countries they represent and should not be attributed to them.  The authors can be contacted at <u>agrover1@worldbank.org</u> and <u>slall1@worldbank.org.</u>
# **I. Introduction**

The internal geographies of cities around the world have been dramatically transformed over the last century. Traditional monocentric organization where jobs are concentrated in the Central Business District of cities has been replaced by a variety of decentralized configurations. In this paper, we survey theory and empirical evidence to understand the pattern of urban morphology of jobs and land use within a city. We focus on studying the evolution of a city’s spatial structure, the extent and nature of agglomeration economies and the adjustments in functional specialization of economic centers within cities. Such an investigation is central to answering a range of economic and policy questions on land use, location of jobs, entrepreneurship and innovation, alongside congestion costs. This also has bearing on public policy interventions, such as urban development and taxation policies and transport infrastructure investments.

The theoretical and empirical literature on the spatial distribution of economic activities across cities and regions points to the existence of agglomeration economies, both within sectors (localization economies) and across sectors (urbanization economies) in developed countries and developing countries.<sup>1</sup> Although the distribution of economic activities and jobs within a city has been the focus of a limited set of contributions, nonetheless the literature on the internal structure of cities has made clear that depending on the relative strengths of push and pull factors determining agglomeration, a metropolitan area can take many spatial forms. This includes monocentric, polycentric, and dispersed spatial forms. Theory particularly assigns these push and pull forces in the form of the cost of commuting, population size, cost of congestion and the rate of spatial attenuation of production externalities.<sup>2</sup> Evidence reveals that the forces that drive agglomeration of firms and jobs at a sub‐city level may be quite different from those that drive clustering of activities across different cities. The empirical literature on urban form indicates that most large cities in developed countries have multiple centers. Just as cities prove the existence of agglomeration economies, these multiple nodes of employment within metropolitan areas strongly suggest that agglomeration economies work at different strengths and scopes within a city. The limited research that focuses on smaller spatial scale highlights a series of fundamental issues pertinent to policy makers.<sup>3</sup> These studies elucidate that urban configuration is shaped by the quality and coverage of transport infrastructure and the ensuing cost of commute, population size, proximity to ports, human capital and other inputs critical to production. Most importantly, the literature raises questions on the optimality of allocation of land within a city across residential, commercial and other uses. Our review of economic theory and empirical evidence on how employment clusters and economic specialization emerge suggests that in the presence of externalities, the equilibrium urban form generated by profit maximizing firms is unlikely to be the most efficient spatial structure, often creating a

> 1 For surveys on works across cities, see Duranton and Puga (2004) and for that across regions, see Ottaviano and Thisse (2004). For empirical works on developed countries see Rosenthal and Strange (2004), Henderson (2005), Combes et al. (2011) and that on developing countries see Overman and Venables (2005), Henderson (2010) and Venables (2010)

> 2 See for example Fujita (1988), Lucas and Rossi‐Hansberg (2002), Berliant et al. (2002), Berliant and Wang (2008), Fujita and Ogawa (1982) and Chatterjee and Eyigungor (2014).

> 3 See Picard and Tabuchi (2013) for a study that presents a formal model of urban spatial structure based on a microeconomic foundation of forward and backward linkages as it has been discussed in the framework of new economic geography.

2
wedge between the preference of businesses and broader societal welfare. In this context, we also review urban form shaping policies and infrastructure investment.

We highlight four broad insights:

1. Large cities in today’s developed economies have evolved from monocentric structures to polycentric spatial forms. In the late nineteenth‐century, for example, four‐fifths of Chicago’s jobs were compactly located within four miles of State and Maddison streets. By 1970, Chicago had 9 employment subcenters which increased to 15 in 1990 and 32 in 2000.

2. The internal geography of a city is an outcome of the trade‐off between the pull from agglomeration and the push from congestion and the cost of commute. The presence of production externalities arising from agglomeration justifies the role of public policy in addressing the associated market failures.

3. Rapidly growing cities need multiple employment sub‐centers to harness localized production externalities and reduce congestion. There is a role for government in assisting sub‐center formation because social gains from developing new sub‐centers exceed the private gains.

4. The productive edge and competitiveness of a city can be enhanced by introducing policies that increase overall citywide connectivity permitting speedier and longer commuting to take advantage of metropolitan‐wide economic opportunities.

The rest of this survey is organized as follows. Section II discusses the literature on the internal structure of cities, mainly dealing with the theory and evidence on forces agglomerating firms and workers at the level of a city or finer spatial scales. This section also describes the evolution of historic cities to monocentric forms followed by the emergence of polycentricism or multiple employment centers. Although most evidence in the field relates to developed countries, we introduce examples from developing countries whenever possible. The idea is to draw lessons from both types of experiences for building sustainable cities in Africa. The analytical insights from section II highlight the importance of addressing externalities and hence call for government intervention in aligning the market equilibrium with social welfare maximizing outcomes. These policy options are discussed in section III. The survey ends with concluding comments in section IV with special emphasis on how urban spatial development policies may help accelerate urban transformation in African cities.<sup>4</sup>

> 4 While misallocation of other inputs such as labor could be equally important, our survey focuses mainly on the impact of urban form on land use within a city.

3
# **II. The Internal Structure of Cities**

The analytic underpinnings of examining the industrial development within cities originate with Harold Hotelling’s linear city model where firms agglomerated in the city center to seize the largest possible market. In the 1960s and 1970s models of the monocentric city were augmented by William Alonso, Edwin Mills, and Richard Muth to include endogenous land rents and locations of city limits.<sup>5</sup> The historical location of all US cities can be understood through heterogeneity in land use that these models portray. The basic premise of these models is that the production structure and land use vary significantly between urban and non‐urban areas and between urban areas of different size. Since it is more productive for all firms to locate on the piece of land they value the most due to proximity to highways, proximity to their markets and suppliers, the monocentric city is a natural outcome.

Economists have identified a variety of factors that lead to ''agglomeration economies”. The most important and best articulated of these factors is increasing returns to scale. This leads to agglomeration, not only of the activity in question, but also of other activities vertically related to it. Increasing returns can be derived from various sources, including sharing a large indivisible good such as a public good in the form of a highway or rail network<sup>6</sup> or a large indivisibility in production activity.<sup>7</sup> These models propose that once the large fixed cost associated with the “indivisible” good is incurred, consumers only have to pay a constant marginal cost per use.<sup>8</sup> The consumer must, however, commute between their home and this indivisible good. This creates a trade‐off between the cost of commute and the cost of crowding the land near the location around the public good and facing higher land rent. Equilibrium configuration is an outcome of such a trade‐off where households and firms that value the good most locate in proximity to this public good.

# **_Endogenous Urban Configuration_**<sup>9</sup>

Endogenous economic agglomeration can emerge under three alternative conditions.<sup>10</sup> First, _heterogeneity in space_ could result in endogenous CBD formation due to comparative advantage among locations. The rise of Chicago, for example, is attributed to location specific production of lumber, grains, and livestock.<sup>11</sup> Second, imperfectly competitive markets also explain endogenous CBD formation because they generate aggregate increasing returns because of the productive advantages of sharing a wider variety of differentiated inputs. Finally, _externalities from non‐market interactions_ affect agglomeration

> 5 Hotelling (1929), Alonso (1964), Mills (1967) and Muth (1969)

> 6 They are the subject of a voluminous literature referred to as club theory (or theory of local public  goods when the spatial dimension is explicitly taken into account

> 7 This corresponds to the idea of a factorytown, where large fixed costs create internal increasing returns in a production activity that employs the workforce of an entire city whose size is bounded by crowding.

> 8 There is in fact a long tradition of modelling cities as the outcome of large indivisibilities in production (Koopmans, 1957, Mills, 1967, Mirrlees, 1972)

> 9 The study of monocentric city that assumes a predetermined city center is widely known as “New Urban Economics” (see Fujita and Ogawa, 1982).

> 10 These conditions are not mutually exclusive; several models combine two or more features.

> 11 See Schweizer et al. (1976) and Berliant and Konishi (2000) for theoretical foundations and Cronon (1991) for Chicago case.

4
in a central location. Agglomeration theories are based on the assumption that spatial clustering generates positive externalities. These externalities in turn promote greater efficiency, productivity and/or innovation. Positive externalities may result from clustering of firms within the same sector (localization economies) or may even be generated by agglomeration of firms across sectors (urbanization economies).<sup>12</sup> Firms gain from spatial clustering due to the ease of communication, increased knowledge sharing and spillovers, increased scale of markets, access to human capital and other inputs and outputs, and from sharing a common urban infrastructure.<sup>13</sup> The presence of production externalities implies that a firm’s productivity at any site is governed not only by internal factors, but also by the concentration of jobs (and firms) at neighboring sites. The central business district of a city illustrates this phenomenon in the most obvious way where firms agglomerate to take advantage of such externalities. However, agglomeration raises workers’ wages and land rents and thus discourages further concentration. In contrast, decentralization of jobs increases commute time and costs for workers and draws them to the center.<sup>14</sup> When the cost of commuting to the city center is high, the proximity of firms and workers is mutually beneficial and therefore the city is more decentralized. This decentralization could be in the form of mixed land use and dispersed jobs all over the city or, alternatively, in the form of few concentrated sub‐centers of jobs. However, when the commute costs are low, a traditional monocentric city emerges.<sup>15</sup> In fact, for many models, polycentricity and dispersed land use are the result of the interplay between the CBD’s agglomeration diseconomies and transport costs related to transport infrastructure.

Models explaining non‐monocentric urban land use were pioneered by Masahisa Fujita and Hideaki Ogawa via the introduction of production externalities.<sup>16</sup> Their models suggest that when commuting costs are low, a Mills‐like monocentric city prevails, while a polycentric city with multiple business districts emerges when the cost of commute rises.<sup>17</sup> These models also suggest that the larger is the commuting 12 Marshall (1890) argued that the clustering of specialized manufacturing firms increased knowledge sharing through processes such as shared labour markets. Such spillovers are even more significant in the service dominated knowledge economy of the 20<sup>th</sup> century. Knowledge sharing and specialized labor markets are therefore central to productivity. Henderson et al. (1995) show that agglomeration effects for mature industries are related to Marshall scale economies, while newer industries benefit from diversity akin to Jacobs (1969) economies. Externalities associated with sources such as geographic concentration of human capital which explains clustering of firms based on labor pooling is explained in Rauch (1993) and Ciccone and Peri (2006).

13 Duranton and Puga (2004) summarize the gains from agglomeration in terms of sharing, matching, and learning effects. Sharing effects include the gains from a greater variety of inputs and industrial specialization, the common use of local indivisible goods and facilities, and the pooling of risk; matching effects correspond to improvement of either the quality or the quantity of matches between firms and workers; learning effects involve the generation, diffusion, and accumulation of knowledge. Agglomeration economies explain the existence of cities. This is particularly important given the growing evidence about the importance of such agglomeration economies. For a more recent survey on the evidence on agglomeration economies, see Combes and Gobillon (2015). For a more detailed exposition of the implications of introducing agglomeration economies in a monocentric city model, see Duranton and Puga (2014) and Behrens and Robert‐Nicoud (2015). 14 See Ogawa and Fujita (1980a, 1980b) and Imai (1982).

15 Many studies reveal that the degree of decentralization is strongly related with the spread of automobiles (e.g. Anas et al., 1998, Glaeser and Kahn, 2004; White, 1976; Steen 1986 and Sullivan, 1986)

> 16 These include Fujita and Ogawa (1982), Ogawa and Fujita (1979, 1980a, 1980b).

17 The Polycentric City included six main elements: a traditional business core; a secondary business core; a tertiary business core or inner‐city edge city; an outer edge city; outermost edge cities; and specialized concentrations. See Fujita and Ogawa (1982), Imai (1982) and Lucas and Rossi‐Hansberg (2002) for more details. Also see a more recent paper by Chatterjee and Eyigungor (2014). Duranton and Puga (2015) present an excellent exposition of these models.

5
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Although theoretical models provide the foundations for examining the equilibrium spatial configuration of polycentric cities, they are not immediately applicable to producing empirically testable comparative static predictions. Recent empirical works at smaller spatial scales show that it is very important to understand a firm’s location choice at a given zip code within the same metro city. A general conclusion of these studies is that firms may agglomerate at zip code or county level for usual reasons such as input sharing and labor pooling in a given location. Evidence on the US counties suggests that agglomeration due to input sharing is only present at the state level and not at county or zip code level while the idea of labor pooling makes firms agglomerate at all levels. By contrast, knowledge spillovers significantly affect agglomeration at the zip‐code level but not so much at county or state level. Theory suggests that the benefits of agglomeration diminish rapidly with distance and empirical research seems to hint that this decay function varies by the source of agglomeration economies. Particularly, evidence on the US counties reveals that the decay of knowledge spillovers with distance occurs much more rapidly vis‐à‐vis that of input sharing.<sup>19</sup> One paper that elegantly ties theory with empirics is that by Daniel McMillen and Stefani Smith.<sup>20</sup> Their study derives tractable predictions from the Fujita and Ogawa (1982) model regarding the relationship between an urban area’s population, commuting costs, and its number of sub‐centers. Using 1990 data on large US urban areas, the authors test the predictions of Fujita and Ogawa, whose simulations suggest that the equilibrium number of sub‐centers is likely to increase with population and the unit cost of commuting. Controlling for other variables affecting urban form, such as the median income in the urban area and the age of the central city, McMillen and Smith find very strong support for theory, with population and commuting costs accounting for nearly 80% of the variation in the number of sub‐centers across the urban areas.<sup>21</sup> 19 Studies at higher spatial level include Glaeser et al. (1992), Henderson et al. (1995), Rosenthal and Strange (2004) while a recent study by Agarwal et al. (2012) makes a descriptive attempt to understand agglomeration at sub‐city level in Los Angeles. There are few examples of studies at zip code level by Rosenthal and Strange (2001, 2003); Kolko (2010); De Silva and McComb (2011). Besides, spatial decay in externalities and spillovers, Redfearn (2007b) notes that the stability in subcenter employment in Los Angeles may be associated with historical path dependence. However, path dependence cannot entirely explain the rise of subcenters in the last few decades.

20 McMillen and Smith (2003) is an empirical application of Fujita and Ogawa (1982). The analysis also brings to light the fact that several theoretical papers have highlighted the role of commute costs (such as Lucas and Rossi‐Hansberg, 2002) and population size (e.g. Fujita and Mori, 1997) in determining the urban form.

21 Much of the recent literature actually suggests there is a lot of persistence in urban patterns. Bleakley and Lin (2012) document the consistent and persistent development of cities in the US along a fall line. Similarly, Redfearn (2009) finds that the most important predictor of clusters of de‐centralized jobs in Los Angeles in 2000 in a location is the presence of decentralized jobs in the same location in 1980. Thus, history has much to determine the current state of land use in a given city. For instance, the existence of a number of subcenters for a port city may well be explained by its evolution. Starting from the initial port site, expansion of the port results from technological innovations in maritime engineering and improvements in cargo handling. This marks the beginning of changing spatial relationships between the port and the urban core, as docks are built further away from the CBD due to congestion and space limitation. In the later stages of port development, increased specialization of cargo handling, growing sizes of ships, and ever increasing demands for space for cargo‐handling and storage results in port activity being concentrated at sites far removed from the oldest facilities. Such models of de‐concentration in port cities have been exemplified by metropolises in the developed countries such those in Europe and the US. In developing countries, on the other hand, studies suggest an increasing level of port concentration as certain hinterland routes develop to a greater extent vis‐à‐vis others. The urban system evolves from an initial pattern of scattered, poorly connected ports along the coastline to a main network consisting of corridors between gateway ports and major hinterland centres. See Taaffe et al. (1963), Bird (1980), Barke 7
In general, theory suggests that a city’s population and its physical size play a pivotal role in determining the extent of concentration and sub‐center formation. Large population leads to high congestion cost that motivates firms to locate outside the CBD. For the USA as a whole, evidence confirms that jobs became increasingly concentrated; however, when considering only metropolitan areas, it appears that there has been de‐concentration of jobs.<sup>22</sup> This suggests that the USA witnessed de‐concentration across large counties, and increased concentration across smaller‐sized counties, a pattern akin to the rise of sub‐ centers in congested cities.<sup>23, 24</sup> Developing countries may appear to be different, partly reflecting their early stage of development. For instance, India is observing increased concentration in already dense clusters. Although the costs of congestion in India's mega‐cities seems huge, nonetheless, these mega‐cities may still benefit from relatively large agglomeration economies, vis‐à‐vis intermediate‐sized cities that may have problems with market access, supply of better quality intermediate inputs and connectivity to basic infrastructure. By contrast, in developed countries, these issues are less of a constraint in intermediate sized cities. Although this phenomenon is not common across all emerging economies, particularly China, in general, however, it seems that constraints such as access to skilled labor<sup>25</sup> and telecom network are curbing the spread of urban growth in second tier cities.<sup>26</sup> The factor that has received substantially large attention in explaining the decentralization of jobs and sub‐center formation is the role of physical infrastructure and transportation.<sup>27</sup> Here, theory suggests that a decline in transport costs tends to untangle the location of business and residential areas and can lead to employment concentration of high value activities at the center.<sup>28</sup> Further, cheaper commute costs also make the CBD accessible to firms located in farther locations. Thus, when transport costs fall, some firms that do not need to be centrally located for their day to day operations can easily move out of CBD because the CBD would still be accessible to them even from farther locations. In sum, a decline in transport costs facilitates the movement of households from central locations and leads to concentration of business activities, while within businesses it aids the movement of non‐core activities to remote locations. What do empiricists have to say on the effect of decline in transportation cost on the location of firm activity?

> (1986), Hayuth (1981) for general models; see Kuby and Reid (1992), Notteboom (1997), McCalla (1999) and Hayuth (1988) for empirical studies.

> 22 Carlino and Chatterjee (2001, 2002)

> 23 See Desmet and Fafchamps (2006). This is broadly in agreement with models of a monocentric city with dispersed non‐CBD employment, agglomeration economies lead to a small number of employment subcenters in these models (e.g. Brueckner, 1979).

> 24 Glaeser and Kohlhase (2004). Other explanations for the decline of central cities in the United States have focused on a variety of social and material ills that have afflicted central cities such as crime (Cullen and Levitt, 1999), the degradation of the housing stock (Brueckner and Rosenthal, 2009), racial preferences (Boustan, 2010), and related changes in the school system (Baum‐Snow and Lutz, 2011)

> 25 Agglomeration due to human capital and knowledge spillovers is motivated in, for example,  Simon (2004). In addition, the existence of human capital externalities is also evident from that fact that the proximity to educated workers is associated with a higher wage. See for example, Glaeser and Mare (2001), Rauch (1993), Moretti (2004).

> 26 Desmet et al. (2015).

> 27 See Anas et al. (1998), and Glaeser and Kahn (2004), for a review of this literature, and Burchfield et al. (2006) for a recent empirical study of urban sprawl in the United States.

> 28 Fujita and Ogawa (1982) and Lucas and Rossi‐Hansberg (2002), Glaeser and Kohlhase (2004)

8
Empirical work supports the theory that decentralization and suburbanization of jobs benefit non‐central locations near the transport infrastructure. Evidence supports that suburbanization was encouraged by a well‐developed railroad system and/or the freeway network in the US, Spain and Japan.<sup>29</sup> Evidence on developing countries also suggests a somewhat similar pattern. In the case of China, data confirm that each railroad ray displaced 25% of core city industrial GDP and 16% of 1990 core city total GDP to suburbs. For China, however, radial highways do not seem to play an important role in explaining de‐concentration of production from the CBD. Highways, on the other hand, seem to matter for India where the movement of formal sector manufacturing from urban regions to rural parts of a district is explained by the Golden Quadrilateral highway. A similar case is observed in Indonesia where the process of decentralization of industrial production from the urban CBD has been facilitated by the building of a highway linking the city to nearby hinterlands.<sup>30</sup> Although there are no studies on the impact of improvements in transport infrastructure on the spatial organization of economic activity within African cities, limited available evidence available on cross‐city work in Africa suggests that there could be considerable potential for an expansion of transit networks. For instance, in Zambia, only 5% of all trips are longer than 10 km, while for the U.S. 5% of trips are longer than 50km, implying that people in African cities are unable to take advantage of a full range of job opportunities.<sup>31</sup> Further, cross‐city evidence in Africa indicates that periphery cities with better road connection to port cities grew faster vis‐à‐vis cities with poor road connection, suggesting that an efficient transport network in Africa is likely to enhance city productivity in the same way as in most cities around the world.<sup>32</sup> Similar to improvements in physical infrastructure, advances in communication and computing technologies have facilitated the fragmentation of tasks and activities of firms across various sites. Such separation of tasks is expected to occur when the cost of disintegration and the possible loss of agglomeration benefits is more than offset by lower production costs at a cheaper location. Innovations in electronic infrastructure largely explain the migration of back‐office jobs to suburbs of a city or to smaller cities while the management or headquarter activity that is a personal or face to face communication intensive task is being retained in the CBD.<sup>33</sup>

> 29 For the impact of roads and highways within cities, see, Baum‐Snow (2007), Duranton & Turner (2011) for US; Hsu and Zhang (2014) for Japan; Garcia‐López et al. (2013) and Garcia‐López  (2010b) for Spain.

> 30 See Baum‐Snow et al. (2012), Roberts et al. (2012) and Deng et al. (2008) for China; Ghani et al. (2012, 2014) for India; Henderson and Kuncoro (1996) for Indonesia. Highways in China tend to explain the decentralization in population, Baum‐Snow et al. find that with each increment of radial road capacity causing a 3 to 5.5 percent decline in central city population from 1990 to 2010. This finding corroborates with Baum‐Snow (2007) results for the US, though the magnitudes are much larger, given the higher income and incidence of auto commuting in the country. In addition, Baum‐Snow (2014) finds that the new radial roads on US inter‐state highways had a much larger effect on residential decentralization vis‐à‐vis employment decentralization. For more on the effects of railroads in China, see Banerjee et al. (2012), Baum‐Snow et al. (2012) and for India, see, Donaldson (2014). 31 Schafer (2000).

> 32 See Storeygard (2012)

> 33 Duranton and Puga (2005), Ota and Fujita (1993), RossiHansberg et al. (2009), Anas et al. (1998)

9
Finally, research has also unveiled that urban form in several developing country cities has been critically shaped by regulations on land use.<sup>34</sup> For instance, spatial distortion in Moscow is explained by Marxist ideology while a morbid cult of design explains the urban morphology in Brasilia and the policy relating to apartheid or land use regulations discouraging the division of land parcels explains the spatial allocation of land in Johannesburg. All these cities do not fit the “standard” urban model but density gradient in these cities rises as one moves away from the city center. Nonetheless, evidence is almost positive that regulation is only a transmission mechanism and that changing regulations over time can change the form of the city.

# **_Evolution of Urban Spatial Structure: From Monocentricity to Polycentricism and More_**

In an attempt to understand the internal structure of cities, our review of theory reveals that monocentric cities are untenable. Studies suggest that decentralization is normal and the declining role of central business districts is a fact of life in modern cities (e.g. Mills, 1972). In Alain Bertaud’s words, the relationship and evolvement of monocentric and polycentric cities is described as follows: “ _As they [cities] grow in size, the original monocentric structure of large metropolises tends with time to dissolve progressively into a polycentric structure. The CBD loses its primacy, and clusters of activities generating trips are spreading within the built‐up area. Large cities are not born polycentric; they may evolve in that direction. Monocentric and polycentric cities are animals from the same specie observed at a different time during their evolutionary process”_ .<sup>35</sup> The evolution of a monocentric city can be traced back to the history of development of transportation routes. Prior to the 1840s, most cities were tied to waterways such as harbors, rivers, and canals or railway networks. Locating closer to these terminals created accessibility advantages and favored the growth of a single manufacturing district. The high cost of within city communication motivated concentration of manufacturing within the CBD of cities such as New York.<sup>36</sup> Similarly, in the late nineteenth‐century, four‐ fifths of the Chicago’s jobs were compactly located within four miles of State and Maddison streets.<sup>37</sup> The advent of horse carriage and electric street cars at the end of the 19<sup>th</sup> century gave rise to a spatial structure consisting of a CBD surrounded by residences concentrated around mass transport spokes. The invention of the internal combustion engine, telephone and assembly line production in the early 20<sup>th</sup> century eased transport and communication and increased the attractiveness of locations where land was cheap.

After the World War II, large scale construction of inter‐state highways and the creation of suburban rail terminals reduced the cost of trucking and travel. These changes weakened the necessity of locating near transport networks and enabled manufacturing to move out from the CBD to the suburbs. Manufacturing

> 34 Bertaud and Malpezzi (2014)

> 35 Bertaud (2003)

> 36 Chinitz (1960)

> 37 Fales and Moses (1972)

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||City reside|ntsworkin|g in the su|burbs|Suburban re|sidents Wo|rking in th|e cities|
|---|---|---|---|---|---|---|---|---|
||1960|1970|1980|1990|1960|1970|1980|1990|
|Chicago|6.6|16.1|18.4|22.5|34.6|27.1|22.5|25.6|
|Cleveland|7.7|24.4|28.6|30.3|52.4|43.5|34.8|32.5|
|Detroit|17.3|32.1|34.3|36.4|33.5|24.6|16.9|19.4|
|Minneapolis-St. Paul|6.6|19.7|24.5|29.8|52.1|43.5|31.2|30.5|
|St.Louis|8.3|21.1|24|35.9|36.7|30|25.4|27.9|
gradients across developed and developing countries suggests that (i) density functions tend to be flatter in countries with higher incomes.<sup>44</sup> For example, Japan and the Republic of Korea had similar population densities in 1970s, yet the average 1970 gradient for Korean urban areas was 0.670, whereas the average for Japanese urban areas was 0.391. (ii) Although the tendency for gradients to decline as time passes is present in both groups, nonetheless it is more pervasive and persistent in the case of developed countries. For instance, the average density gradient for Japanese urban areas declined to 0.46 in 1965 to 0.39 in 1970 while for urban areas in Korea it declined from 0.70 to 0.67 during the same period. In the case cities in Ghana, this gradient did not decline at all over the mentioned period. In fact, in developing countries, there are also some exceptions to this downward trend in density gradients, such as the smaller urban areas in Mexico and in India during the early years of the post‐World War II period.<sup>45, 46</sup> The standard monocentric model predicts that land prices fall with distance from the CBD. This has been found to be true, for instance, in the case of New York starting from 1835 when the land price gradient was ‐0.65 implying that land values declined by 65% per mile from the CBD of New York. The fit of this semi‐log standard Mill’s type monocentric urban land values model was 0.71. Contrarily, by 1900, the land price gradient had declined to ‐0.14 and the fit of the monocentric model had fallen to 0.06.<sup>47</sup> In the case of Chicago, evidence on land values reveals a similar story suggesting that the explanatory power of the standard monocentric model has declined over time.<sup>48</sup> In general examples from cities in the developed world suggest that the shape of cities evolves over time where a monocentric shape is replaced over time by a polycentric form with multiple sub centers. In the case of developing countries, this transition could be slower or even perverse as observed in the case of Moscow, Brasilia and Johannesburg.<sup>49</sup> Although the monocentric model is very useful, it is difficult to apply it to suburban regions of cities such as New York, Chicago and San Francisco with multiple nodes of employment and where distance from CBD does not monotonically determine employment density and land values.<sup>50</sup>

> 44 See Mills and Tan (1980) for earlier evidence presented here and also see Bertaud and Malpezzi (2014) for more recent analysis. The latter study suggests that cities such Shanghai, Guangzhou, Singapore, Toulouse show the steepest slope (negative) of the density gradient while at the other extreme are cities such as Mumbai, Johannesburg, St. Petersburg and Moscow that show a positive gradient.

> 45 Spatial development of African cities in Ghana also witnessed a similar evolution of urban form as those in other developing countries (see Asabere and Owusu‐Banahene, 1983). Work on 5 cities in Ghana reveals that although the average density gradients in these cities are relatively higher than those found for western and Latin American cities, they are nonetheless lower than those found for Korean and Indian cities.

46 Clark (1951) was perhaps the first to show negative association between population density and distance from CBD. However, a high R‐square in such models is not necessarily supportive of the monocentric model because it results mainly due to the inherent smoothing associated with the ring approach. In fact, the R‐square associated with the regression of density in small areas within a city, such as tracts, on their distance to the CBD is much lower because there indeed are areas of fairly high density that are located relatively far from the main centre (see Duranton and Puga, 2014, 2015) 47 Atack and Margo (1998) 48 Mills (1969) 49 Bertaud and Malpezzi (2003, 2014) 50 Duranton and Puga (2015) describe that the monocentric city model explains patterns of residential land use and commuting within a city but not why individuals wish to be in a city to begin with. Neither does this model explain the complex pattern of division of land between residential and commercial uses within a city. Nonetheless, Bertaud and Malpezzi (2003) argue that the negative‐exponential parameterization of the monocentric model can hold so long as there is “a higher density of employment at the center than elsewhere”.

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Empirically, the definition of a sub‐center is often complex, case dependent and ambiguous because suburban employment tends to be highly dispersed. The literature has applied two criteria to identify sub‐ centers. One, a sub‐center is defined as an area with significantly higher employment densities than surrounding areas. Two, a sub‐center should be large enough to have a significant effect on the overall spatial structure of the urban area, leading to local rises in population density, land prices, and perhaps housing prices. Early urban empiricists applied these definitions and extended the usual empirical expression of a monocentric city to its multi‐nodal counterpart but not without drawbacks.<sup>51</sup> Alternative empirical methods for capturing the internal distribution of economic activity in a polycentric setting include clustering models and nonparametric models.<sup>52</sup> Clustering method bunches together adjacent tracts to build sub‐centers based on ad hoc definitions of employment density cut‐offs and total job thresholds. For example, a cut‐off that has been used in the literature defines two types of centers: “10– 10” and “20–20.” The former is an agglomeration of contiguous tracts having a minimum job density of 10 jobs per acre combined with a total number of jobs of at least 10,000 while the latter is a tract with at least 20 jobs per acre and 20,000 total jobs in each sub‐center.<sup>53</sup> These models are criticized for the arbitrary nature of the density and total employment cutoffs implying that the number of sub‐centers can be increased by decreasing the threshold and vice versa.<sup>54</sup> The technique proposed in the above research have been applied to identify sub‐centers in a number of large US cities, including Atlanta, Baltimore‐Washington, Boston, Dallas, Houston, Indianapolis, Los

> 51 E.g. the model requires a priori specification of the candidate subcenters implying that the gradient from each center contributes to employment density at every point in the metropolitan area. This complicates estimation especially if there are a larger number of subcenters. (See, Gordon et al.,1989 and Gordon and Richardson,1996).

> 52 The most critical challenge associated with studying urban morphology is the difficulty in obtaining data at fine spatial scales. Cities chosen to study this model have based on the ease of collecting this data and these are notably the ones with strong priors on their urban forms. For instance, not many cities have population and employment data available at the level of a tract. Land registry or any other source that is able to identify parcels is far less available. Thus, issues such as cross‐city heterogeneity within a country or the behavior of density gradients over time have been largely ignored (See Combes et at., 2012 for a comparison of land price gradients across cities in France and McMillen, 1996 for the dynamics of price gradient over 150 years in Chicago). Secondly, there have been measurement issues relating to not just identifying subcenters but also when making predictions for land parcels based on area density gradient. Thirdly, what we want to ask the literature is not whether cities are monocentric or not, a hypothesis that can be rejected in nearly all cities, but exactly how monocentric is a city. The key difficulty with this analysis is that the R2 of gradient regressions do not provide a good metric by which to measure this and reasonable methods in this field are yet to be developed (Duranton and Puga, 2015). Similarly, the predictions of the monocentric model on various aggregate need not be taken literally, but generally, empirical methods must be developed to measure how different is reality from such predictions. Monocentric model makes a number of predictions about some aggregate quantities and land rent at the centre (e.g. proportionality between total land rent and total commuting costs). One study that makes such an assessment is by Combes et al. (2012) who examine the proposition that land rent at the centre is proportional to city population.

> 53 Giuliano and Small (1991), Small and Song (1994), Bogart and Ferry (1999), Anderson and Bogart (2001), Giuliano et al. (2007). 54 Daniel McMillen along with his co‐authors has sought to address the misspecification of monocentric models and the lack of statistical tests for the clustering methods through nonparametric regression‐based models (McMillen, 2001a; McMillen and Smith, 2003; McMillen and McDonald, 1997, 1998). These models look at the deviations from general spatial trends in employment density and identify outliers relative to a spatial average that uses half of all the observations. This, however, substantially obscures the topography of local employment. Recently, methods have been devised such that the estimation of nonparametric employment density surface occurs locally— with a subsample that is kept sufficiently small to keep intact the structure of local employment density. This is necessary in order to identify subcenters, as the general spatial trends in employment density using a larger window size largely mask independent local concentrations of employment. Local maxima on the density surface become candidate centers (Redfearn, 2007a).

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Angeles, New Orleans, New York, Philadelphia, the San Francisco Bay Area, and St. Louis.<sup>55</sup> Depending on the exact methodology used, the exact number of sub‐centers varies but, in general all studies agree on multiple sub‐centers for a relatively large city.<sup>56</sup> For instance, the city of Los Angeles is found to have 41 sub‐centers when the more flexible non parametric technique of relying on the local maxima of each candidate sub‐center is used while there are 48 sub‐centers using the “10–10” definition and 10 sub‐ centers using the “20–20” thresholds for density and total employment in the clustering method.<sup>57</sup> In contrast, some small cities such as Austin in Texas, Buffalo in New York and Nashville in Tennessee do not have any sub‐centers at all.<sup>58</sup> Similar evidence exists for cities in other developed countries such as Barcelona or other metro cities in Spain as well as Paris in France. Even in the case of a developing country, large cities such as Bogota (Colombia), has evolved to generate 10 sub‐centers.<sup>59</sup> Besides the monocentric and polycentric models, recent advances in urban economics propose three other theoretical forms of spatial organization of cities. (i) Maximum Disorder model, where workers’ homes and their jobs are randomly distributed in the city. (ii) The Constrained Dispersal model, where a small number of sub‐centers exist outside the CBD and attract workplaces to each other or to shared public infrastructure and amenities. In this form, both workers and firms adjust their locations to remain within a tolerable commuting range of each other. (iii) The Mosaic of Live‐Work Communities, where workers and firms are all within walking or bicycling distance of each other. Of the 40 American cities examined in a recent study, evidence suggests that an average of 25% of jobs is located in sub‐centers and CBD while the remaining 75% are scattered throughout metropolitan areas. This suggests that while the polycentric model dominates over the monocentric one, it is the constrained dispersal model that appropriately describes the urban spatial structure among American cities.<sup>60</sup>

# **_Structural Changes with Urban Spatial Evolution: From Manufacturing to Tradable Services_**

As urban spatial structures have evolved from a monocentric organization to that of multiple centers of economic activity, so has the structural composition of the CBD. Since the World War II, manufacturing activity is de‐concentrating while services are increasingly agglomerating in central locations.<sup>61</sup> Research

> 55 Anderson and Bogart (2001) identify subcenters in Cleveland (9 sub centers), Indianapolis (11), Portland (11) and St. Louis (10); Bogart and Ferry (1999)  also study Cleveland and found 9 subcenters; Cervero and Wu (1997, 1998) analyze the San Francisco Bay Area; Giuliano and Small (1991) identify 35 subcenters, Redfearn (2007a) study Los Angeles and found 41 subcenters in 2000; and McMillen and McDonald (1998) identify 15 subcenters in the Chicago metropolitan area. McMillen (2001a) identifies 13 subcenters in Chicago, and reasonable subcenters in Dallas, Houston, Los Angeles, New Orleans, and San Francisco. This analysis is extended in McMillen and Smith (2003) to cities such as Atlanta (4 subcenters), Baltimore (5) Washington DC (10), Boston (11), New York (38), and Philadelphia (4). Others have focused on identifying points of peak density and estimating density gradients to formally test for polycentricity, for example, Small and Song (1994) for Los Angeles and Craig and Ng (2001) for Houston. 56 For example, using non‐parametric technique, Redfearn (2007a) finds 7 subcenters in orange county of Los Angeles city. Although the number of subcenters in Los Angeles county of the city is 28, orange county itself is also polycentric. 57 See Redfearn (2007a) and Giuliano et al. (2007)

> 58 McMillen and Smith (2003)

> 59 See Garcia‐López (2010a, 2010b), Holl and Viladecans‐Marsal (2011) Duarte et al. (2011), Mu ̃niz et al. (2008) for ci�es (particularly Barcelona) in Spain; Gilli (2005) for Paris in France; Avendaño and Enríquez (2012) for Bogota in Colombia; 60 See Angel and Blei (2015a)

> 61 Dumais et al. (2002), Kim (1995). Kolko (1999) finds that there has been a growing concentration of manufacturing in small and medium‐sized cities and of business services in larger cities.

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on the US suggests that most services, particularly, wholesale retail, finance, insurance and real estate (FIRE) and other services have become more concentrated while most other sectors, such as ‘manufacturing’ and ‘farming’, have exhibited de‐concentration and are located on lower cost urban periphery or in small cities and towns, perhaps to take advantage of lower rents and wages. Evidence suggests that nearly all agglomerated services industries are highly urbanized, whereas many manufacturing industries agglomerate in smaller cities or rural areas. Studies on US and French services firms suggest that service industries are localized at very short distances and are primarily situated in the heart of a few big cities and strongly benefit from highly localized technological spillovers.<sup>62</sup> What explains this sort of structural change in urban form where central locations are increasingly being replaced by services rather than manufacturing firms? Some services require close proximity with consumers (e.g. professional services) while others can be transmitted over the internet. Services that rely on ICT can substitute for proximity, and are less likely to agglomerate even in the same county. Services and manufacturing agglomerate for different reasons: while manufacturing agglomerates for reasons related to labor pooling due to occupational specialization, services agglomerate because of knowledge spillovers. The important difference in explaining urbanization across the sectors, however, is the share of output going to consumers, which is positively correlated with urbanization for manufacturing industries and negatively correlated with urbanization for services industries. Thus, the cost of transporting goods to customers could affect location decisions differently for manufacturing and for services.<sup>63</sup> Furthermore, innovations in communication technologies fragments a firm’s activities – when the front‐unit activity needs to be in touch with other firms’ headquarters, it will agglomerate in the CBD, while the back‐unit activity will be located in the suburbs.<sup>64,65</sup> The shift from sectoral to functional specialization also implies that service focused business centers are few and large whereas manufacturing centers are more numerous and smaller in size. Such structural changes are not unique to the US; German and Chinese data also reveal a similar pattern of spatial development of activities.<sup>66,67</sup> Other reasons explaining such structural changes include the maturity of the industry. In a mature industry the localization economies have been mostly exploited, and knowledge spillovers have lost much of their

> 62 See Glaeser and Kohlhase (2004), Desmet and Fafchamps (2006), Arzaghi and Henderson (2008) and Desmet and Rossi‐ Hansberg (2014) for the case of US and Barlet et al. (2013) for the study on France. The theoretical argument for this observation is explained in Desmet and Ross‐Hansberg (2009, 2014).

> 63 See Glaeser and Kohlhase (2004) and Kolko (2010) for more details on the effect of these factors as well as the differences in the two sector with respect to co‐agglomeration forces.

> 64 Ota and Fujita (1993), Duranton and Puga (2005). Henderson and Ono (2008) provide a very comprehensive evidence related to the spatial separation of firm headquarters and production facilities.

> 65 See Duranton and Puga (2005). Using data from micro data set on auxiliary establishments in the US from 1977 to 1997, Davis and Henderson (2008) find that headquarters of firms agglomerate in the CBD of large metro areas to take advantage of services and production externalities (which decline with distance) in the form of the availability of differentiated local service input suppliers and the scale of other headquarter activity nearby.

> 66 We know of only one study, that is, by Rossi‐Hansberg et al. (2009), that examines the within city sectoral pattern of urban development. They document an increase in the share of employment, and establishments in the suburbs or city edges. They find that the shift in employment from CBD to suburbs in the case of US was not driven by any one particular industry. During 1980‐ 1990, the average employment share at the center declined from 0.42 to 0.38 in manufacturing and from 0.47 to 0.43 in services. That is, average employment shares declined by about the same percentage in both sectors. This information is, however, not indicative of whether the share of services relative to manufacturing increased at the city center.

> 67 Example of such accounts on San Francisco bay area is found in Walker (2004) and on Pittsburg is described in Muller (2001).

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importance.<sup>68</sup> This makes agglomeration in such an industry expensive if land is a critical factor of production. Hence, as spillovers weaken, mature industries such as those in the manufacturing sector tend to move out of CBD. Contrarily, services industry has relatively recently been affected by a major GPT in the form of ICT and many firms in the industry have not fully adapted to the new technological paradigm.<sup>69, 70</sup> A recent study by Jed Kolko suggests that services do not agglomerate as much at a county level vis‐à‐vis manufacturing but more so at a zip code level (with zip codes being much smaller than counties). This trend is in contrast to that of manufacturing firms that tend to agglomerate in the same county to save on transport costs and also access to similar resources (natural or labor) but they do not need to co‐locate within the same the zip code (and thus economize on land rents).<sup>71</sup> It is noteworthy that the observed trends in the developed world may not necessarily be mirrored in a developing country context. In fact, there are similarities between the current developing country trends and that of the U.S.A. in the late 19th and early 20th centuries. Manufacturing facilities in developing countries often locate in large cities, perhaps because learning and adaptation are critical to the successful transfer of technology from abroad. However, as the industry matures and technology standardizes, higher land rents are likely to push the firms out to peripheral locations. Such a process is in the beginnings in China and Indonesia. However, in India, both services, and to a certain extent manufacturing, are increasingly concentrating in high‐density clusters.<sup>72</sup> Based on the theoretical explanations, this suggests that services in India are “young", whereas manufacturing is not as “mature" as in the developed world. This should not be surprising though. Nonetheless, there are differences even across manufacturing. Research shows that organized manufacturing is moving to rural areas, away from city centers while the reverse is true for unorganized manufacturing. Thus, it seems that unorganized sector seems to be driving the overall results for Indian manufacturing.<sup>73</sup>

# **III. Is the Market Equilibrium Optimal? Some Policy Options**

In the presence of externalities, equilibrium urban form generated by profit maximizing firms and utility maximizing workers may not be the most efficient spatial structure. For instance, in a polycentric environment, where urban sub‐centers are formed from the tension between centripetal and centrifugal forces in the form of production externalities versus congestion or commute costs, there are distinct

> 68 Duranton and Puga (2001)

> 69 Hobijn and Jovanovic (2001)

> 70 See Desmet and Ross‐Hansberg (2009). The increased geographic concentration of services has also been studied by, Glaeser and Ponzetto (2010), who suggest that this phenomenon may be driven by lower transport and communication costs.

> 71 Specifically, the average Ellison‐Glaeser county level agglomeration index for services industries at the six‐ digit North American Industry Classification System (NAICS) level is 0.0068, while that for manufacturing is 0.0132.

> 72 Desmet et al. (2015). India's experience is not common to all fast‐growing developing economies. The spatial growth pattern of China looks more similar to that in the U.S. than to that of India. See Baum‐Snow et al (2012) for China and Rothenberg (2013) for Indonesia.

> 73See Ghani et al. (2012). One of the factors that could be leading to de‐concentration of Indian manufacturing includes delicensing that took place in the 1990s (Fernandes and Sharma, 2012).

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challenges. Although production externalities encourage clustering but if private incentives to join an agglomeration is inadequate, an equilibrium with excessive dispersion may emerge. On the other hand, if production externalities are very strong, then excessive concentration leads to excess congestion. Since different externalities operate at different scales, the spatial pattern of economic activity may turn out to be too concentrated in the CBD while too decentralized at the sub‐center level.

In sum, the presence of externalities creates a wedge between the market equilibrium outcome and the socially optimal one. This section discusses the policy issues in the urban spatial development and the related instruments that can help bring the market equilibrium closer to an optimal outcome.<sup>74</sup> Annex table A.1 presents a summary of the research discussed in this section.

The few models that compare the equilibrium configuration with an optimal one<sup>75,76</sup> contend that business land and employment should be more concentrated in the optimal allocation relative to their equilibrium structure. In the optimum allocation, mixed areas tend to disappear because workers’ location decision also takes into account the effect of employing an extra worker on the production of other firms in the city. This, in turn, changes the gains from using a given location for business purposes. Thus, for no value of cost of employing an extra worker in a given location are the conditions necessary for the existence of a mixed area satisfied.

There are two policy issues for cities in developing countries in the current context: One, how can cities transform into productive hubs by integrating labor markets with productive firms and channelizing resources into tradable activities? Two, not all density profiles are compatible with an efficient transit system. Specifically, when residential densities are dispersed throughout the city, there is a role for government in creating conditions for the mass public transit system to work efficiently. This section discusses some of the available policy options, such as zoning, urban growth boundary, regulations on density (e.g. floor area ratio) and so on for aligning the equilibrium allocation of land use with the optimal outcome.

One of the most important policies known to influence land use corresponds to zoning laws whereby a central planner can assign land use in different sections of the city. For example, some areas can be

> 74 By optimal outcome we mean the one that maximizes welfare.

> 75 Early models that studied the optimal allocation of workers within a monocentric city include: Borukhov and Hochman (1977), Dixit (1973) and Hochman and Pines (1982) while Stull (1974) and Helpman and Pines (1977) obtain an endogenous size of business district. These models exogenously impose the land use structure and assume that workers commute to the CBD rather than their actual work places. This is sort of a restrictive condition because the problem of firm and household location cannot be determined endogenously.

> 76 Rossi‐Hansberg (2004); this section mainly discusses the results of this model. More recently, Kyriakopoulou and Xepapadeas (2013) present a model incorporating not only agglomeration economies but also pollution externality. Their results are throughout consistent with Rossi‐Hansberg (2004). Arnott et al. (2008) build a model with pollution externalities where the spatial layout results from a balance between two opposing forces: one is the repulsion of households from industry that is the source of the pollution and the other is the attraction between households and industry caused by increasing‐with‐distance commuting costs. Other papers that compare market outcomes with socially optimal outcomes on the basis of land use mixing include ‐ Wheaton (2004) and Zhang and Kockelman (2014). The former study suggests that agglomeration in CBD is associated with longer commute and worsened congestion, while employment decentralization entails shorter commuting distance and lower congestion levels while unlike Rossi‐Hansberg (2004), the latter study models congestion externalities as well.

17
designated as purely business or entirely residential areas while others can be assigned for mixed land use. Although zoning is inevitable for providing the essential public facilities such as roads, public buildings and so on, it is also implemented to mitigate the distortive effects of externalities generated by the proximity of “incompatible” uses like a residence and a noxious factory, the need to contain urban sprawling via green belts as well as curbing congestion in central areas of the city. In the early half of the 20th Century, zoning was perceived to be a first‐best policy instrument that could mitigate the effects of distortive externalities.<sup>77</sup> The problem with such zoning restrictions, however, is that it does not internalize the externality, and hence is not optimal. Nonetheless, it could still take advantage of higher external effects caused by proximity of firms to each other which would push the overall output of the city.<sup>78</sup> Another policy option available to governments is the use of urban growth boundary (UGB), which is a regional boundary circumscribing an urban area, fixed with the objective of controlling urban sprawl and land use. For instance, the area inside a UGB can be mandated for use of higher density urban development, while the area outside could be reserved for lower density development. UGB could be an effective guide to zoning and land use legislation for controlling the extent of mixed land use among cities in developing countries. Some researchers argue that regulations on urban growth boundary (UGB) and building size, if properly chosen, may be an effective second‐best substitute for the first‐best land use policy. This is because the shadow price of land is less than its market value at the region’s edge in a congested and monocentric setting.<sup>79</sup> Nevertheless, some other studies in a monocentric framework suggest that UGBs may achieve far lower welfare levels vis‐à‐vis the strategies of first‐best tolling.<sup>80</sup> By contrast, the efficiency and welfare effect of the UGB policies in a polycentric framework is found to be mixed. UGBs seem to reduce travel costs and distances, and city size, but without significantly changing equilibrium job levels.<sup>81</sup> A series of recent works in urban economics explores density regulations, such as lot size zoning as well as floor area ratio (FAR) regulation to control urban sprawl and the population density over space. Floor area ratio refers to the ratio of the total floor area of the building relative to the aggregate size of the plot on which they are built. In contrast, lot size zoning fixes the minimum or the maximum size of the lot in a given part of the city. Lot size zoning is imposed in the peripheral area of the city to control the size of each lot containing one household, whereas FAR regulation is imposed in the urban area to control the

> 77 Pines and Sadka (1985); Wheaton (1998)

> 78 The problem with the equilibrium with zoning restrictions is that land rents are not be continuous at the boundary between business and residential sectors which motivate some land owners to lobby for changes in the zoning restrictions. Zoning has the advantages that it entails relatively low transactions costs and is well‐established. But, it is inflexible and unresponsive to market signals, and the private gains from rezoning invite rent‐seeking behavior and corruption. Alternatives include pricing policies (such as differential property tax rates or impact fees on developers), government creation of previously absent markets (such as that for transferable development rights), or the redefinition of property rights (such as the use of restrictive covenants in Houston). 79 Arnott, (1979); Pines and Sadka (1985)

> 80 Brueckner (2007); Kono et al. (2012)

> 81See Zhang and Kockelman (2014). For similar results on US cities see Anas and Rhee (2007); Anas and Pines (2008); Staley et al. (1999); Cho et al. (2008).

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size of buildings containing many households, such as apartment buildings, condominiums, etc.<sup>82</sup> While lot size zoning can be a first‐best policy as it directly impacts population density, FAR regulation is a second‐best policy because it only controls the total floor supply of a building without controlling the per‐ capita floor space consumption.<sup>83</sup> To manage population density at the desired amount, an extremely low FAR may have to be implemented, which in turn generates a deadweight loss in the building size market<sup>84</sup> When implementing FAR regulations, policy makers could also take advantage of minimum FAR (as opposed to maximum FAR, that is widely used) to increase population density in the context of urban expansion.<sup>85</sup> Finally, the concept of dynamic FAR would be more relevant in a world where cities have a high population growth rate because the level of externality at a location can change remarkably over time.

Regulation on building height is another formulation of FAR that aids in restricting population and employment density in urban areas. For instance, FAR in cities such as New York; Hong Kong SAR, China; and Singapore ranges from 5 to 15 in CBD to 0.5 or below in suburbs and is dynamically increasing over the years as per changes in population and infrastructure network. At the other extreme is the city of Mumbai in India where population density is inefficiently regulated by imposing a maximum FAR of close to 1 since 1991, without much consideration to geographic locations or dynamic changes.<sup>86</sup> Studies on the efficiency of regulations on building size reveal that the welfare cost from building height restrictions could be non‐trivial and one study estimated this cost to be about 2% of the household income in a monocentric city model. Welfare costs emerge from the additional commute costs incurred by the residents living at the edge of the city.<sup>87</sup> Alain Bertaud suggests a host of policy options ranging from general land use regulations and planning including those that re‐evaluate the status of buffer zone between formal and informal settlements, the ones that allow densification of high income area or the policy instruments that offer to develop low income housing based on clusters rather than on individual plots. Policies that allow and actively promote the concentration of employment and calls for investment to upgrade and increase the amenities in the central parts of cities would also go a long way in reducing the extent of employment dispersion throughout the city.

Although some cities such as, Brasilia offer subsidized low cost housing programs to ease congestion in the city center, they are often unmindful of the trade‐offs that poor households face. Households prefer to locate closer to their work place while providers mandate higher infrastructure standards at distant

> 82 Lot size zoning can control only the plot size, not the building size. Therefore, in an area that mainly consists of buildings that accommodate multiple households, lot size zoning is not as effective as FAR regulation to control population externalities. 83 Wheaton (1998)

> 84 Also see, Pines and Kono (2012)

> 85 Sakashita (1995); Kono et al. (2010); Joshi and Kono (2009). Some cities such as Oregon City, City of Buffalo, and Colorado Springs have been practicing minimum FAR regulation in designated areas to prevent underdevelopment. 86 See Bertaud (2011).

> 87 Direct density regulations such as building height restrictions (Arnott and MacKinnon, 1977; Bertaud and Brueckner, 2005; Kono et al., 2012) city limits determined in the sphere of politics (Brueckner, 2000a) constitute land‐use regulations which invoke distortions that may be associated with large welfare costs.

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locations where land is cheap. Thus, the government ought to make subsidies “portable” and allow low income households to make the trade‐off between land use standards, transport costs and location. Similarly, emphasis on minimum floor space (or FAR) and infrastructure and not on minimum land consumption should help correct the distortion in land consumption.<sup>88</sup> Land use policies can be strengthened with complementary transport policies to reach spatially optimal outcomes. A reduction in the cost of commute brings the equilibrium allocation closer to the optimal one through, (i) a direct reduction in workers costs per mile commuted and (ii) an indirect effect via the concentration of business areas. Policies to bring workers closer to job, such as those on road construction and improving public transportation should also consider this latter indirect additional gain in their cost‐ benefit analysis.<sup>89</sup> Esteban Rossi‐Hansberg’s model suggests that policies on parking lots construction, highway investments which reduce the costs of working at business centers, are much needed to align the city structure with optimal allocation of land use.<sup>90</sup> These transport related policies are in essence similar to a government subsidy that lowers the labor costs for firms and motivates them to hire more workers has a positive impact on wages and rents.<sup>91</sup> In response to increases in rents, workers move out of prime locations, thereby making equilibrium allocation more concentrated and hence an optimum one.

In contemporary cities in the USA, about three quarters of the jobs are dispersed outside the sub‐centers and the CBD. Studies on developed countries conclude that agglomeration economies are possibly metropolitan in scale.<sup>92</sup> Thus, the continued productive edge of cities is largely dependent on the ready availability of public transit and private automobiles that allow workers to reach out better and more productive economic opportunities available throughout metropolitan area. Such a model of dispersed employment may be acceptable in developed countries where car ownership rates are high and public transit systems are efficiently placed. However, for cities in low income countries, dispersion in employment is actually counter‐productive because of lack of a well‐organized public transit system, extremely low car ownership rates and poor road infrastructure. Developing countries may want to focus on policies that promote concentration of economic activity at the center or sub‐centers and build infrastructure connectivity to and from such centers. Policies promoting metropolitan‐wide connectivity and those that permit speedier and longer commuting would to aid agglomeration of firms and relocation of workers within tolerable commute range.<sup>93</sup> Once zoning regulations, UGBs and transport policies can mitigate the problem of dispersed employment, agglomeration among firms is likely going to raise the productivity of the city as a whole and perhaps even attract more productive economic opportunities. At some point, congestion externalities would kick in

> 88 Bertaud (2009)

> 89 Rossi‐Hansberg (2004)

> 90 Studies that evaluate the cost of congestion and the policies for reducing such costs include ‐ Anas and Xu (1999); Wheaton (1998). Such policies may have similar effects.

> 91 We find similar suggestions in Kyriakopoulou and Xepapadeas (2013) as well.

> 92 See Burger et al. (2009); Gordon and McCann (2000); Johansson and Quigley (2004) and Angel and Blei (2015a) 93 Angel and Blei (2015b)

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and necessitate the formation of multiple sub‐centers of employment. Sub‐center formation, however, may not be automatic. At a low population level, equilibrium and optimum coincide, however, as the population expands, the ‘excessive’ population must move away to form a new sub‐center. Given that the social gains from relocation exceed the private gains, the second center is not formed until later. Thus, there may be a role for government in assisting sub‐center formation, through the provision of infrastructure, the regulation of developers, or subsidization of developer activity or firm location.<sup>94,95</sup> At the other extreme to concentrated employment sub‐centers is the case of edgeless cities documented by Robert Lang.<sup>96</sup> An edgeless city is characterized by the development of isolated office and business space separated by large distances between each other. Such business areas are neither pedestrian friendly, nor easily accessible by public transit, and do not lend themselves to mixed use. Policies for curbing sprawl is motivated by the desire to foster agglomeration economies, reduce the cost of providing public services and infrastructure, and reduce the dependence on the automobile and the externalities associated with its use (e.g. air pollution and congestion). Development taxes and congestion tolls seem to be effective in reducing the spatial size of the city. Several anti‐sprawl policies such as UGB, taxes on residential development, property taxes and fuel taxes have been proposed in the literature.<sup>97</sup> Once the urban land use pattern comprises of multiple centers of economic activity and begins to look similar to the congested cities of developed countries, there is a separate set of policy instruments for dealing with congestion externalities. These include ‐ tax on urban auto travel,<sup>98</sup> congestion pricing in the form of cordon charges, area‐wide pricing, and variable‐rate highway tolling (such as that in Singapore, London and in several of U.S. metropolitan areas).<sup>99</sup> Congestion pricing is expected to reduce congestion, thus lessen the associated negative externalities such as like traffic delays, air pollution, and greenhouse gas emissions etc. and also offer revenue to help fund transport system improvements, including public 94 The same issues have been raised on a larger scale in the debates on France’s poles de croissance, Britain’s New Towns Policy, and LDC policies to control growth of primate cities.

95 Developers and large firms (non‐competitive) are sometimes critical in promoting subcenter formation. Edge cities”, as they are popularly known, are subcenters created by large‐scale land developers. See for instance, Henderson and Slade (1993), Henderson and Mitra (1996) and Fujita et al. (1997). Also see Anas et al. (1998) for a survey on subcenters from both the theoretical and empirical points of view. Takashaki (2014) finds that strategic interactions among firms could result in equilibrium with either agglomeration in the city center or decentralization where firms locate at either ends of the city. Higher commuting cost vis‐à‐vis shopping travel costs results in agglomeration, otherwise there is maximum dispersion in firm location decision. Another view is that employment centers emerge as a result of the decision making of local governments, including tax policy and land‐use policy (Fujita, 1989; Sullivan, 1986; Zhang and Sasaki, 1997, 2000) 96 Lang (2003) 97 See for instance, Brueckner (2000b, 2001) who finds that development taxes and congestion tolls seem to be effective in reducing the spatial size of the city. Bento et al. (2006) find that, from an overall efficiency perspective, development taxes and UGB are equivalent instruments and the most effective anti‐sprawl policies. By contrast, gasoline tax and the property tax are substantially less effective in combating sprawl. In an endogenous land use model, Anas and Rhee (2006) find that congestion tolls eliminate excess travel or excess sprawl by making the job and residence distribution of the city more compact while UGBs result in a substantial efficiency loss. Also see Anas and Rhee (2007) that makes a careful discussion on the reasons why UGB is not always a second‐best policy option relative to congestion tolls.

98 Although this may lead to excessive decentralization and perhaps over‐investment in highways such as that in the US in 1950s, see, Wheaton (1978) 99 Santos (2005); Gao (2012) 21
transit. Empirical work suggests that congestion tolls may catalyze land development around tolled roads, and perhaps also have a somewhat negative effect on the city center’s economy.<sup>100</sup> Alternatively, to reduce congestion, many innovative policies have been deployed. These policies range from adding carpool lanes, which is common in the United States, to rationing driving by allowing only certain license plate numbers to enter heavily congested areas on certain days or at certain times, which is common in Latin America. Even transit investment and ridership have shown signs of reversing long declining trends. Urban planners could encourage further concentration of jobs in sub‐centers and then use public transit to link the sub‐centers with population groups in need of better access to employment. Land‐use and zoning policies might also be used in combination so as to induce a reduction in the use of the private automobiles and thereby reduce traffic congestion.<sup>101</sup> The spatial structure of a city can be modified by a consistent action involving a close coordination between transport infrastructure investments, modification of land use, housing and planning regulations, taxation and distribution of subsidies. Nonetheless, spatial modification is a difficult task not only because of historical persistence but also due to the complexity of factors that determine urban spatial structure. Alain Bertaud argues that the consistency across the three tools is a hard find because they are often designed at different administrative levels of government and in most cases for very different objective, perhaps completely unrelated with city spatial structure.<sup>102</sup> We conclude this section with three caveats. One, with the exception of zoning regulations, most policy prescriptions offered in this section do not directly affect urban form, but the effect on spatial organization comes through changes in density and land prices.<sup>103</sup> For instance, regulations on FAR does not directly determine whether land use in a given area would be allocated for business, residential or mixed purposes but it could potentially sway the density of a given area in the aimed direction. Specifically, stipulating a minimum FAR in a central region increases the supply of land and could potentially ease the transition from mixed land use area to a primarily business area. This effect may, however, depend on the several other factors such as the efficiency of transport networks, cost of communication, sectoral composition of the industry and the strength of agglomeration economies and so on.<sup>104</sup>

> 100 See Gupta et al. (2006) for Austin; Santos and Shaffer (2004) for London

> 101 See Cervero (1989) and Downs (1992) for a discussion on the policy for the development of subcenters in the US. 102 Bertaud (2003)

> 103 Zoning regulations can directly impact the land use pattern by designating areas for certain purposes. For instance, to reverse the chaotic growth of the city the government of the Federal District of Mexico issued a decree called Bando2 that established the main guidelines for urban development in the city for the next six years. Three zoning areas for housing development were created within the city:  One, a re‐densification zone that offered incentives to promote low cost housing and thereby achieve high density housing area; a second zone where restrictions were imposed on large housing developments that made high demands on water supply and infrastructure; and a third zone were zoning regulations were not changed (see Naranjo and Quintero, 2011).

> 104 Similarly, UGBs, which are instituted with the objective of containing urban sprawl, typically drive land prices higher in the inner city area. UGBs are, therefore, likely to promote concentration of firms in the central regions while they hope to settle residences in the surrounding outer region. See Venkataraman (2014) for the impact of UGBs on land prices in Bangalore and Jun (2004) for an impact of UGBs in Portland on urban  development  patterns,  transport  choices  and  mobility.

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Two, most available policies for affecting the pattern of land use are possibly only a second‐best solution. For instance, zoning is agreeably not the first‐best policy to influence land use because it does not completely internalize the externality. Similarly, it is argued that UGBs can easily yield undesirable outcomes, because they are not directly linked to the underlying market failures responsible for sprawl.<sup>105</sup> Regulations on maximum FAR are also considered to be at most a second‐best policy because they only control the total land supply but that may not have the desired impact on actual per‐capita consumption of space. Thus, before implementing the suggested policy, officials need to weigh the dead weight loss ensuing from such a change against the expected benefit it may have.

Three, our review of the literature points to several instances where the necessary policy‐mix could be far more complex than assumed by economic models. We offer three such examples here: (i) Strategies for coping with urban issues in a monocentric region should be distinct from those of polycentric settings because they face different issues on land use. Analysis from both theoretical as well as empirical findings, however, remains inconclusive regarding policy effects.<sup>106</sup> (ii) The equilibrium urban form arising from, say, _imperfectly competitive markets,_ such as that in intermediate inputs, à la Chamberlin (1933) style, could be far from optimum due to differences in demand conditions.<sup>107</sup> (iii) Research in this field has only partially shed light on several questions pertaining to the economies of agglomeration and welfare. Firms agglomerate based on a variety of factors, including increasing returns and Smithian specialization, idiosyncratic matching, production externalities, and innovation. If such reasons motivate firms to agglomerate, the market cannot perhaps efficiently deal with all of them. Given our limited understanding of agglomeration economics at finer spatial scales, the policy implications of their incomplete internalization is not clear.

# **IV. Conclusions**

This paper surveys the existing literature on the theory and evidence of jobs and firm location and land use changes within a city. The theoretical foundations of urban spatial organization suggest that both centrifugal and centripetal forces are at work. Agglomeration economies in the form of production externalities, urbanization economies or localization forces tend to enable clustering of firms while the cost of commute, congestion externalities, and the higher rates of decay of production externalities tend to disperse firm location. The equilibrium outcome is the result of a trade‐off between these forces.

The survey illustrates that in the presence of externalities, equilibrium urban form generated by profit maximizing firms and utility maximizing workers may not be the socially optimal spatial structure. This

> 105 Brueckner (2000b)

> 106 . For example, in a city or region with only congestion externalities, marginal cost pricing is acceptably the first‐best policy because it reflects the gap between marginal social and marginal private costs of each trip while this may not necessarily be true in a polycentric framework. See Pines and Sadka, (1985); Wheaton, (1998); Kono and Joshi, (2012). Also see, Giuliano and Small (1991); Crane and Chatman (2004)

> 107 Abdel‐Rahman and Fujita (1990), Henderson (1974).

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calls for government action in preparing the city to take the most efficient spatial form that facilitates agglomeration of firms. Such policy options include changes to FAR, Urban growth boundary, congestion taxes, zoning regulations also help in defining the land use in central and peripheral locations. Further, increasing citywide connectivity through investments in transit networks and/or highways that reduce the costs of working at business centers is also likely to align the equilibrium outcome with the optimal solution. However, given that most of these are second best policy options, their merits need to be carefully weighed against the objective of changing the urban spatial structure.

Policies on urban spatial organization could be useful in accelerating structural transformation in cities such as those in Africa. Although traditionally urbanization was considered to be synonymous with structural transformation, studies on Africa reveal a perverse pattern. For instance, rapid urbanization in Ghana and Côte d’Ivoire in the past few decades has not been accompanied by an industrial or service revolution. Research shows that boom in the export of cash crops such as cocoa and coffee in African countries is responsible for the rise of “consumption” cities where spillover and linkage effects are lower.<sup>108</sup> Thus, even though the problem of Africa’s urbanization without structural transformation may seem unique, the solution to this problem may, however, partly be found in urban spatial organization policies.

Finally, as a way forward to future research, our survey reveals that most empirical studies have not worked in tandem with the theoretical predictions provided. The future course of research in this area should align with the forces that have been identified in the literature as affecting the pattern of land use, returns to scale in production, spatial inhomogeneity, linkages, product variety, spatial interaction, traffic congestion, automobile pollution, and so on. Further, empirical work has largely focused on the trends in firm location and land use for developed countries. Much less is known about such patterns of industrial evolution in developing countries. The World Bank is responding to the lack of such studies through the “Spatial Development in Africa” program, which aims to understand the pattern of urban development in African cities and investigate how growing densities in Africa need to be supported by proactive policies and by appropriate infrastructure— including appropriate transport modalities, public transport, and so on. These countries remain widely unexplored. Finally, policy implications in this field are largely based on theoretical models and numerical simulations. Thus, there is more scope, in principle, to offer concrete policy lessons from studies on industrial evolution within cities once the theory and empirics are better aligned.

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# **Annex 1**

Table A.1: Research on Policy Options for aligning equilibrium land use with optimal allocation 40
<!-- Start of picture text --> Name of authors Context Suggested Instruments Main findings<br>government subsidy that lowers the<br>Non-monocentric labor costs, parking lots construction,<br>Rossi-Hansberg (2004) (Endogenous land use) highway investments Positively impact rents, brings equilibrium allocation closer to optimum<br>Leads to compact urban form and job decentralization, and serves as an<br>Non-monocentric effective strategy for correcting congestion externalities. First best<br>Zhang and Kockelman (2014) (Endogenous land use) Congestion toll policy policy<br>Spatially differentiated Pigouvian taxes per unit emission levied on<br>Non-monocentric industrial polluters does not support the optimum. Pigouvian taxes are<br>Arnott et al. (2008) (Endogenous land use) Congestion toll policy optimal only under special circumstances.<br>Non-monocentric In the presence of agglomeration economies, a naive optimal<br>Brinkman (2013) (Endogenous land use) Congestion toll policy congestion pricing policy may lead to welfare loss<br><!-- End of picture text -->

|Nameofauthors|Context|SuggestedInstruments|Mainfindings|
|---|---|---|---|
|||government subsidythat lowersthe||
||Non-monocentric|laborcosts,parkinglotsconstruction,||
|Rossi-Hansberg(2004)|(Endogenous land use)|<br>highwayinvestments|Positively impactrents, bringsequilibriumallocation closertooptimum|
||||Leadstocompacturbanformandjobdecentralization,andservesasan|
||Non-monocentric<br>||effective strategyforcorrectingcongestion externalities. Firstbest<br>|
|ZhangandKockelman (2014)|(Endogenous landuse)|Congestion toll policy|policy|
||||Spatiallydifferentiated Pigouvian taxesperunitemissionleviedon<br>|
||Non-monocentric||industrial pollutersdoesnot supporttheoptimum.Pigouviantaxesare|
|Arnott et al. (2008)|(Endogenous land use)|Congestion toll policy|optimal onlyunderspecialcircumstances.|
|Brinkman (2013)|Non-monocentric<br>(Endogenous land use)|Congestion toll policy|Inthepresenceofagglomerationeconomies,anaiveoptimal<br>congestion pricing policymay leadtowelfare loss|
||||Congestion tax isthe first best policyoptiontoencourage<br>|
|PinesandSadka(1985);Wheaton (1998)|Monocentric|Congestion toll policy|decentralizationaroundthecitycore.|
|Anasand Kim (1996);AnasandXu||||
|(1999);Wheaton (2004);Zhang and<br>Kockelman(2014)|Polycentric|Congestion toll policy|welfareimproving; delivers amorecompacturbanform and also<br>correctsfortheassociatedmarketfailure|
||||Alleviatecongestion externalitiesandlowertraveltimes, vehicle-miles|
||Non-monocentric<br>||traveled,andtravelcosts;butcarrycertainlossofsocialwelfareowing<br>|
|ZhangandKockelman (2014)|(Endogenous landuse)|Urban growthboundary(UGB)|<br>to landrentescalationandUGBs’ limitationsonjobdecentralization.|
|PinesandSadka(1985);Arnott (1979)|Monocentric|Urban growthboundary(UGB)|Effectivesecond-best substitute forfirst-besttolling|
||||welfaregainfromanoptimal UGBpolicyagainst unpriced congestion is<br>onlyatinyfractionofthatgainedunderthetollregime,implyingthat|
|Brueckner(2007);Konoetal.,(2012)|Monocentric|Urban growthboundary(UGB)|<br>theUGBpolicy isapoorsubstituteforthetollregime.|
|PinesandSadka(1985);Wheaton(1998)|Monocentric|LotsizeZoning|Resultsimilartoafirst-bestcongestiontoll|
|ArnottandMacKinnon (1977); Bertaud<br>||||
|andBrueckner(2005)|Monocentric|Buildingheightregulations|invokesdistortionsthatmaybeassociatedwithlargewelfarecosts|
|ArnottandMackinnon(1977);Bertaud|||onlymaximumbuildingsize regulation isconsidered, ignoring|
|andBrueckner(2005)|Monocentric|buildingsizeregulations|optimalityoftheregulation|
||||welfaregainundertheoptimalFAR policywithasuitablychosenUGB<br>makes upa significantfractionofthatachievedunderthetollregime.<br>Evenwithouta UGB,welfaregainundertheoptimal FAR policyalone is<br>alsosubstantial. Ascomparedtooptimal lotsize zoning, FAR<br>regulationscanatmostbesecondbestpolicyoptionforcontrolling|
|Konoetal.,(2012)|Monocentric|buildingsizeregulations(FAR) —|<br>populationdensity.|
||||Inaclosed city, it isoptimal toallow notonlydownwardadjustmentto<br>themarketdensityatboundary locationsusingmaximumFAR<br>|
||||regulation butalsoupwardadjustmentatcentral locations using<br>minimumFARregulation.Thecommonpracticeofimposingmaximum|
|KonoandJoshi (2012)|Monocentric|Floorarearatio(FAR)|<br>FARregulation iseffective inanopencity.*|
||||Inaclosedcity, FARregulation isthesecond-best policyandthatthere<br>|
|Konoetal., (2010);JoshiandKono|||is aneedforminimum FARregulationsinadditiontothecurrentlyused|
|(2009);Sakashita (1995);|Monocentric|Floorarearatio(FAR)|maximumFARregulations|
||||welfarecostofFARregulation increaseswithan increase inthe<br>|
|BertaudandBrueckner(2005)|Monocentric|Floorarearatio(FAR)|commutingcosts;however,onlymaximumFAR regulation is<br>considered, ignoring optimalityoftheregulation.|
||||FARoptimal regulationsrenderUGBredundantbut itcannotalways<br>replacethefiscalinstruments(e.g.spatially-variableexcisesubsidies,|
|PinesandKono(2012)|Monocentric|Floorarearatio(FAR)|<br>ortaxes,onhousing) forachievingthesecond-best utility.|
||||Developmenttaxesandcongestiontollsseemtobe effective in|
|Brueckner(2000b, 2001)|Monocentric|Anti-spraw! policies|reducingthespatialsizeofthecity|
||||Fromanoverall efficiencyperspective,developmenttaxesandUGBare|
||||equivalent instrumentsandthemosteffectiveanti-sprawl policies. By<br>|
||||contrast,gasolinetaxandthepropertytaxaresubstantially less|
|Bentoetal. (2006)|Monocentric|Anti-sprawl policies|effectiveincombatingsprawl.|
||||Congestiontollseliminatetheexcesssprawlbymakingthejoband|
||Non-monocentric||<br>residencedistributionofthecitymorecompactwhileUGBsresult in|
|Anasand Rhee(2006)|(Endogenous land use)|Anti-sprawl policies|substantial efficiency loss.|
|Notes:*Aclosedcityisdefinedastheone<br>endogenouslyforagivenutilitylevel.|whereutilityisdetermine|dendogenouslygiventhepopulations|izewhileinanopencity, thesizeofthepopulationisdetermined|

<!-- Start of picture text --> Congestion tax is the first best policy option to encourage<br>Pines and Sadka (1985); Wheaton (1998) Monocentric Congestion toll policy decentralization around the city core.<br>Anas and Kim (1996); Anas and Xu<br>(1999); Wheaton (2004); Zhang and welfare improving; delivers a more compact urban form and also<br>Kockelman (2014) Polycentric Congestion toll policy corrects for the associated market failure<br>Alleviate congestion externalities and lower travel times, vehicle-miles<br>Non-monocentric traveled, and travel costs; butcarrycertain loss ofsocial welfareowing<br>Zhang and Kockelman (2014) (Endogenous land use) Urban growth boundary (UGB) to land rent escalation and UGBs’ limitations on job decentralization.<br>Pines and Sadka (1985); Arnott (1979) Monocentric Urban growth boundary (UGB) Effective second-best substitute for first-best tolling<br>welfare gain from an optimal UGB policy against unpriced congestion is<br>only a tiny fraction of that gained under the toll regime, implying that<br><!-- End of picture text --> <!-- Start of picture text --> Pines and Sadka (1985); Wheaton (1998) Monocentric Lot size Zoning Result similar to a first-best congestion toll<br>Arnott and MacKinnon (1977); Bertaud<br>and Brueckner (2005) Monocentric Building height regulations invokes distortions that may be associated with large welfare costs<br>Arnott and Mackinnon (1977); Bertaud only maximumbuilding size regulation is considered, ignoring<br>and Brueckner (2005) Monocentric building size regulations optimality of the regulation<br>welfare gain under the optimal FAR policy with a suitably chosen UGB<br>makes upa significant fraction of that achieved under the toll regime.<br>Even without a UGB, welfare gain under the optimal FAR policy alone is<br>also substantial. As compared to optimal lot size zoning, FAR<br>regulations can at most be second best policy option for controlling<br>Kono et al., (2012) Monocentric building size regulations (FAR) — population density.<br><!-- End of picture text --> <!-- Start of picture text --> Ina closed city, it is optimal to allow not only downward adjustment to<br>the market density at boundary locations using maximum FAR<br>regulation but also upward adjustment at central locations using<br>minimum FAR regulation. The common practice of imposing maximum<br>Kono and Joshi (2012) Monocentric Floor area ratio (FAR) FAR regulation is effective in an open city.*<br>Ina closed city, FAR regulation is the second-best policy and that there<br>Kono et al., (2010); Joshi and Kono is a need for minimum FAR regulations in addition to the currently used<br>(2009); Sakashita (1995); Monocentric Floor area ratio (FAR) maximum FAR regulations<br>welfare cost of FAR regulation increases with an increase in the<br>commuting costs; however, only maximum FAR regulation is<br>Bertaud and Brueckner (2005) Monocentric Floor area ratio (FAR) considered, ignoring optimality of the regulation.<br>FAR optimal regulations render UGB redundant but it cannot always<br><!-- End of picture text --> <!-- Start of picture text --> replace the fiscal instruments (e.g. spatially-variable excise subsidies,<br>Pines and Kono (2012) Monocentric Floor area ratio (FAR) or taxes, on housing) for achieving the second-best utility.<br>Development taxes and congestion tolls seem to be effective in<br>Brueckner (2000b, 2001) Monocentric Anti-spraw! policies reducing the spatial size of the city<br>From an overall efficiency perspective, development taxes and UGB are<br>equivalent instruments and the most effective anti-sprawl policies. By<br>contrast, gasoline tax and the property tax are substantially less<br>Bento et al. (2006) Monocentric Anti-sprawl policies effective in combating sprawl.<br>Congestion tolls eliminate the excess sprawl by making the job and<br>Non-monocentric residence distribution of the city more compact while UGBs result in<br>Anas and Rhee (2006) (Endogenous land use) Anti-sprawl policies substantial efficiency loss.<br>Notes: *A closed city is defined as the one where utility is determined endogenously given the population size while in an open city, the size of the population is determined<br>endogenouslyfor a given utility level.<br><!-- End of picture text -->