metadata: authors: 0: author: Kleineberg,Tatjana Karina
1: author: Murray,Sally Beth
2: author: Tang,Yulu
3: author: Kaw,Jon Kher
count: Jordan
docna: 0: docna: The Welfare and Productivity Effects of
            Transit Improvements in Amman
docty: Policy Research Working Paper
theme: Urban Infrastructure and Service Delivery,Mitigation,Municipal Institution Building,Job Creation,Economic Policy,Economic Growth and Planning,Environment and Natural Resource Management,Private Sector Development,Public Sector Management,Urban Planning,Climate change,Urban and Rural Development,Jobs,Adaptation,Spatial Growth,Public Administration,Urban Development
abstracts: cdata!: This paper studies the long-run welfare
            and productivity effects of transit improvements in the
            Greater Amman Municipality. The paper builds a rich
            quantitative spatial model that includes many aspects of the
            economic geography of Amman. It studies the effects of new
            bus rapid transit lines that improve the connection of more
            peripheral areas to the city center, in two phases: phase 1
            (approximately) connecting the north-eastern and
            north-western regions, and phase 2 adding the southern and
            south-westerns regions. It finds that the bus rapid transit
            increases output by 4.4 to 5 percent in phase 1 and 7.2 to
            7.6 percent in phase 2. Workers in manufacturing benefit the
            most, and they also lived farthest from the city center
            before the bus rapid transit was established. Welfare in all
            neighborhoods increases, with the largest increases at the
            outer ends of the new bus rapid transit lines. Phase 1
            generally promotes densification and welfare in already
            dense locations, while phase 2 encourages additional
            densification to the south. Our preliminary analysis of the
            interaction of zoning restrictions with the bus rapid
            transit suggests that legal zoning limits are binding in a
            few locations where excess demand for real estate after the
            expansion of bus rapid transit is expected to be large.
display_title: The Welfare and Productivity Effects
            of Transit Improvements in Amman
listing_relative_url: /research/2024/06/34340219/welfare-productivity-effects-transit-improvements-amman
topicv3: Urban Land Supply and Markets m1326023 868,Urbanization and Growth m1326437 796,Urban Transport m1327133 788,Urban Development m1327371 699,Urbanization and Jobs m1503883 2875
publishtoextweb_dt: 2024-06-13T00:00:00Z
dois: 10.1596/1813-9450-10802
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 46
author_keys: 0: author_key: 1232204
1: author_key: 1594541
2: author_key: 2157908
3: author_key: 1275935
model_extractions: Policy Research Working Paper 10802 The Welfare and Productivity Effects of Transit Improvements in Amman _Tatjana Kleineberg Sally Murray Yulu Tang Jon Kher Kaw_ Urban, Disaster Risk Management, Resilience and Land Global Practice & Development Research Group June 2024
Policy Research Working Paper 10802

# **Abstract**

This paper studies the long-run welfare and productivity effects of transit improvements in the Greater Amman Municipality. The paper builds a rich quantitative spatial model that includes many aspects of the economic geography of Amman. It studies the effects of new bus rapid transit lines that improve the connection of more peripheral areas to the city center, in two phases: phase 1 (approximately) connecting the north-eastern and north-western regions, and phase 2 adding the southern and south-westerns regions. It finds that the bus rapid transit increases output by 4.4 to 5 percent in phase 1 and 7.2 to 7.6 percent in phase 2. Workers in manufacturing benefit the most, and they also lived farthest from the city center before the bus rapid transit was established. Welfare in all neighborhoods increases, with the largest increases at the outer ends of the new bus rapid transit lines. Phase 1 generally promotes densification and welfare in already dense locations, while phase 2 encourages additional densification to the south. The preliminary analysis of the interaction of zoning restrictions with the bus rapid transit suggests that legal zoning limits are binding in a few locations where excess demand for real estate after the expansion of bus rapid transit is expected to be large.

This paper is a product of the Urban, Disaster Risk Management, Resilience and Land Global Practice and the Development Research Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at smurray2@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
# **The Welfare and Productivity Effects of Transit Improvements in Amman**<sup>*</sup>

Tatjana Kleineberg Sally Murray Yulu Tang World Bank World Bank Harvard University Jon Kher Kaw World Bank

## JEL Classification: R13; R32; R40; R52

Keywords: Urban Transport; Urban Land; Urban Productivity; Urban Jobs; Amman; Jordan; Spatial Computable General Equilibrium Model

> *We would like to thank Hogeun Park, Myriam Ababsa, and the World Bank transportation team for data and their expert reviews and comments. 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 and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Contact: Development Research Group, World Bank, 1818 H Street NW, Washington, DC 20433. Email: smurray2@worldbank.org; tkleineberg@worldbank.org.
# **1 Introduction**

In developing countries, urbanization is a key driver of economic productivity growth. Through their scale, density, and connectivity, cities offer economies of scale and agglomeration, and facilitate knowledge spillovers, which together drive efficiency gains in production and services. To create thriving cities, urban planning, infrastructure, and service provision must enhance connectivity, through productive density and strong transportation, while offering high living standards to workers. Transport system must provide workers access to the most productive jobs and places within cities.

This paper analyzes the welfare and productivity effects of transit infrastructure improvements in Amman, the capital of Jordan.

We collect rich microdata at a very granular level to characterize the city structure of Amman. We observe the neighborhoods in which people live and work and their sectors of employment. We further observe locations’ residential and commercial floor space and the legal zoning restrictions. Data on the transportation network and travel speeds allows us to calculate the travel times between all neighborhood pairs of the city. We use this data to calibrate a quantitative urban model in which workers make residential, commuting, and employment decisions (including where to live and work, what sectors to work in, and how to commute), and developers make decisions about housing supply, following Ahlfeldt, Redding, and Sturm (2016), Redding and Rossi-Hansberg (2017) and others. Structural parameters and elasticities are calibrated to values from the literature. Based on these parameters and the data described above, the model derives baseline amenities, productivities, wages, and rents for each neighborhood.

After thereby describing the city at baseline, we then use the estimated model to simulate counterfactual policy scenarios. In particular, we analyze how investments in Bus Rapid Transit (BRT) systems affect aggregate and distributional outcomes. The spatial model sim2
ulates effects of the BRT investment on aggregate output and welfare, sectoral output, and on the distribution of population and economic activity across neighborhoods within Amman. The model further analyzes the extent to which Amman’s zoning restrictions can limit the development of new residential or commercial real estate which can lower potential productivity gains.

Despite the richness of the model, there are some caveats that should be kept in mind. Especially, we cannot measure or distinguish informal employment and unemployment in the data, so we focus our analysis only on formal employment. The total employment and total population of Amman are fixed in our model; this means we cannot capture any impact that the BRT may have on drawing workers or residents into the city, or inactive residents into the labor force. It also does not capture exogenous population, income, and output growth over time. We keep amenities (i.e. neighborhood attractiveness) fixed in our policy counterfactuals, so we do not capture potential responses in the attractiveness of neighborhood characteristics due to changes in the population composition or density. It is, for example, possible that neighborhood become less attractive as they become denser or alternatively the might become more attractive through additional resources or investments as more educated and higher-income residents move in.

The remainder of the paper is organized as follows. Section 2 describes the context of the Greater Amman Municipality and the BRT expansion. Sections 3 and 4 describe the model and data, respectively. Section 5 describes the calibration. Section 6 presents the results of our policy counterfactuals, and Section 7 concludes and suggests directions for future research.

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# **2 Context and Transit Infrastructure in Amman**

Jordan is an upper middle-income economy, with GDP per capita of USD4,400 in 2021. Its capital and economic hub, Amman, is a primate city, hosting 42 percent of the national population (3.7 million people in the latest 2015 census).

Amman has been continually inhabited since the 8th century BC, but its population has grown exponentially in the past century, from just 5,000 in 1906 to 1.8 million by 1999, and over 4 million today (Ababsa and Ahmad (2020)). This growth was driven in part by large successive waves of refugees from fragile regional neighbors, most recently from the war in the Syrian Arab Republic.

Its role as a safe harbor has spurred Amman to become an important regional hub for banking, business, and tourism, but has also put urban services and labor markets under intense strain, as populations have soared almost overnight during waves of refugees crises. Most recently, at the height of the Syrian refugee crisis, water demand rose by 40 percent and unemployment by 30 percent (100 Resilient Cities, 2017).

A hilly topography, population pressures, and insufficient investment in public transport have exacerbated traffic congestion in Amman in recent years. The city is built around nineteen hills, forcing a reliance on bridges or tunnels to connect many major city roads. The density of buildings, population, and cultural heritage sites has also limited the scope for road widening as the population has boomed. In response, the Greater Amman Municipality (GAM) began constructing a Bus Rapid Transit (BRT) system in 2015, to improve the efficiency of the road network. The first BRT routes were opened in 2021 and 2022, with a third (connecting Amman to Zarqa) expected to open in 2023.

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# **3 Model Outline**

The spatial model that we use to study the effects of the BRT investments is based on recent work in the urban literature such as Ahlfeldt, Redding, and Sturm (2016); Redding, Sturm, and Heblich (2018); Tsivanidis (2019). The full model is specified in Appendix B. Here, we describe the model set up, workers’, residents’, firms’, and developers’ choices, market clearing and the equilibrium conditions of the model.

**Production.** We consider three economic sectors: manufacturing, tradable services, and non-tradable services. Tradable services are defined as typically higher-end services that can be traded across neighborhoods within the city (such as finance, marketing, or accounting), while non-tradable services are those that require face-to-face interactions (such as grocery stores, coffee shops, and hair dressers). Sectoral prices for goods and services are assumed to be the same across the city, reflecting the assumption that all goods and services (but not workers) can be freely traded across Amman’s neighborhoods. Within each sector and each city neighborhood, perfectly competitive firms use labor (efficiency units) and commercial floor space as inputs, to produce a homogeneous output good. Due to perfect competition, firms make zero profit in each location and sector, so that their revenues equal total wages paid to workers plus total rent paid for commercial floor space.

**Geography.** We model 152 neighborhoods in the Greater Amman Municipality. Each neighborhood is characterized by residential amenities (which make locations more or less desirable for residents), sectoral productivities, and residential and commercial housing supply (floor space). Each neighborhood pair is separated by a bilateral commuting time, which depend on the city’s road and public transit infrastructure. The new BRT investments improve these commuting times.

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**Individuals’ Choices.** Average welfare in the model depends on residential amenities (factors affecting the attractiveness of the neighborhood in which each person lives) and real incomes. Individuals choose a location in which to live and a location and sector in which to work, optimizing their utility which depends on residential amenity and real income. These decisions define workers’ commuting routes between their residence and work locations. Each worker’s income depends on the efficiency units that she or he supplies to her or his job and on the wage rate per efficiency unit that is offered by her or his sector and work location. Workers’ efficiency in each job depends on their location-and-sector choice, and is reduced by commuting times, since workers can work longer times when spending less time in transit. Workers spend their income on consumption goods from all three sectors and on residential housing, which they rent at local unit-prices in their chosen residence location.

**Developers’ Choices.** Residential and commercial floor space is characterized by a fixed and a variable component. The fixed component captures limits in land availability. The variable component allows floor space to increase in response to rents, capturing the fact that real estate developments can increase the housing supply if local housing demand and rents increase. The housing supply elasticity captures how strongly housing supply responds to changes in local rents. We include zoning restrictions in our model, which provide a legal upper limit to residential and commercial housing supply in each neighborhood.

**Market Clearing and Equilibrium.** The model is characterized by a set of structural parameters and regional characteristics. The structural parameters describe individuals’ preferences, the responsiveness of individual choices to neighborhood or job characteristics (elasticities), the production technology, and the housing supply elasticity. The regional characteristics are residential amenities, sectoral productivity, the fixed component of residential and commercial floor space, and commuting costs.

Conditional on this set of parameters and neighborhood characteristics, the equilibrium of 6
the model is defined by sectoral prices, local rental rates for commercial and residential housing, and location- and sector-specific wage rates, which ensure that:

1. Workers maximize their utility by optimally choosing their consumption, the location in which they want to live, and the location and sector in which they want to work.

2. Firms in each location and each sector maximize their profit by making optimal input choices over labor and commercial floor space, making zero profits in equilibrium due to perfect competition.

3. Good markets clear in each sector, equating firms’ production with workers’ consumption.

4. Labor markets clear in each location and each sector, equating workers’ labor supply with firms’ labor demand.

5. Commercial and residential floor space markets clear in each location, equating each respective housing supply with firms’ demand for commercial floor space and with consumers’ demand for residential floor space.

# **4 Data**

This section describes the data and patterns of the spatial distribution of residents and employment in the Greater Amman Municipality. Our analysis is at the neighborhood level and covers 152 neighborhoods and 20 mantiqas. We analyze economic activity in three sectors: manufacturing, non-tradable services, and tradable services. We gather the following data at the neighborhood level: total employment and residents by sector, commuting times between all neighborhoods, total floor area for residential and commercial use, and zoning restrictions (i.e., maximum allowed floor space area). Appendix A provides more information on the data construction and data sources.

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**Population.** We retrieve population data for each neighborhood from the Housing and Population Census (2015). Figure 1 describes the distribution of population across neighborhoods and the relationship between population density and neighborhoods’ distance from the center. The first panel shows a scatter plot relating population density and distance. The plot shows a negative relationship, suggesting that people concentrate in the center of the city. The second plot confirms this finding by grouping neighborhoods into deciles according to their distance to the center. The third plot is a map which shows the population density for each neighborhood. The map show that some of the neighborhoods in the outskirts also have high population density, suggesting that Amman has some resemblance to a poly-centric city.

**Employment.** We use employment data by sector at the matiqa level from the Establishment Census (2018). We impute this data to the neighborhood level based on the withinmatiqa distribution of building volume. Figure 2 shows the distribution of employment across neighborhoods and the relationship between employment density and neighborhoods’ distance from the center with three plots that are analogous to Figure 1. We see that the highest employment density is in the center of the city, with a particular concentration in the center-west.

Figure 3 shows the distribution of the employment density separately for each sector: we see that jobs in tradable services are most spatially concentrated, with a clear cluster in the center-west of the city. Non-tradable service jobs are somewhat more dispersed: they have high density in the same areas (center/center-west), but they additionally have higher density in the southern and eastern parts of the center. Manufacturing is less centralized, with distinct clusters in the east, south, and west.

**Housing Volume and Zoning Restriction.** We collect data on total built floor space in each neighborhood from satellite data from the European Space Agency. In addition, we

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obtain shapefiles with land use typologies from the municipal government, which allows us to approximately classify floor space in each location as either commercial or residential. We further obtain the Amman zoning restriction rules, which assign to each building type the percentage of the plot that can be used for construction and the maximum number of floors that can be constructed (among other constraints not modeled here). We merge the land use typology of each plot to the relevant building categories from the zoning rules to calculate the maximum floor space that can legally be developed in each location. We perform this step separately for commercial and residential building types.

**Travel Times with Road Travel.** To compute average travel times between all locations, we use the road network for Amman and assign average travel speeds to different types of road segments based on estimates from the World Bank Transportation Unit. Specifically, we assign a speed of 35 km/hour for primary roads, 20 km/h for secondary roads, 10 km/h for tertiary roads, 8 km/h for other road types, and 5 km/h for walking. For metro lines we assign a speed of 35 km/h and for monorail 45 km/h. In the counterfactual, we compute commuting times with the new BRT routes to which we assign a traveling speed of 25 km/h.

Figure 4 shows average commuting times for each residency neighborhood to all possible work locations where we weigh travel times of each work destination by the number of jobs available in this destination. Aligned with the previous results on employment density, we see that central neighborhoods are best connected to jobs while the outskirts have larger average commuting costs to available employment opportunities. Commuting times are particularly large for the south and some of the most western and northern neighborhoods.

# **5 Calibration Results**

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# **5.1 Calibration of the Model Parameters and Regional**

# **Characteristics**

In our model calibration, we use structural parameters from the literature as shown in Appendix B. We then use these parameters, the data moments described in the previous section, and the equilibrium conditions from our model to infer regions’ characteristics, which include economic productivity (by sector) and residential welfare. The calibration procedure solves for locations’ sectoral wage rates, rental rates for commercial and residential floor space units, and prices for goods from each sector. These wages, rents, and prices are endogenously determined and they ensure that all markets clear in equilibrium. Appendix B provides more details on the calibration procedure. We now present the distribution of our regional characteristics.

**Productivity.** Figure 5 shows the distribution of productivity across neighborhoods for each sector. Consistent with the employment density by sector, the productivity of manufacturing is higher in the southeastern part of Amman (where most industries are located), while the non-tradable and the tradable sectors exhibit higher productivity in the northwestern area.

**Wage Rates.** Figure 6 shows that average wage rates are highest in the center-west, where wages are two or three times higher than the average wages.

**Amenities.** Amenities are a residual capturing how attractive neighborhoods are to residents due to unexplained factors.

**Welfare.** Figure 7 shows that welfare is highest for residents in the western part of Amman. (West Amman is an affluent part of the city, where international companies, banks,

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private schools and main Embassies are located.) In this figure, we estimate workers’ welfare from their indirect utility, which includes neighborhoods’ residential amenities, average real income, and average commuting costs for residents.<sup>1</sup>

# **6 Policy Counterfactuals**

## **6.1 BRT Investments Improve Transit Times and Job Accessibility**

We simulate two phases of BRT investments, which are shown in Figure 8. We first analyze the effects of Phase 1 of the BRT investment, which connects the eastern and western parts of the city to the center (yellow and orange lines on Figure 8). We refer to this policy as "BRT Phase 1". The yellow line was completed and opened in 2022, and the orange line is scheduled for completion in 2024. We then analyze the effects of the full planned BRT investment, which includes the former lines and adds the BRT lines to the south and southwest (pink lines on Figure 8). We refer to this full BRT investment as "BRT Phase 2". These lines are expected to be completed and opened between 2024 and 2027.

Figure 9 shows how each BRT phase affects job accessibility from each neighborhood. In particular, we calculate the (new) average commuting time from each residence neighborhood to all possible work locations, weighing each travel time by the number of jobs in the work location. For this calculation, we estimate travel speed of the BRT line to be 25 km/h, accounting for speeds as well as stoppage time.<sup>2</sup> Figure 9 shows substantial travel time reductions due to the BRT. BRT Phase 1 primarily improves the travel times from the eastern and western parts, with decreases in average travel times by up to 22 percent. BRT Phase

> 1More specifically, we average the indirect utility across all residents in each neighborhood: _Vi js = wPjs_<sup>_α_</sup> _dr_<sup>_−_</sup> _i_<sup>1</sup> _ij_<sup>1</sup><sup>_−εαi js_</sup> .)

> 2This compares to estimates of road speeds that vary between 8km/h for unfinished roads and 35 km/h for primary roads. We maintain these road speed estimates in our counterfactual with the BRT investments, which ignores additional potential travel time improvements if the BRT’s would alleviate road congestion.

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2 additionally improves travel times from the south into the center, decreasing travel times by up to 26 percent.

# **6.2 Aggregate Effects of the BRT on Productivity and Output**

Since the analysis holds total population and employment fixed, it does not capture potential gains from workers who respond to the BRT by entering formal employment in Amman from unemployment, from informal work, from outside the labor market (inactive), or from regions that are outside of our model area.

We focus on two key channels through which better commuting times increase economic output and workers’ productivity: first, workers can work longer hours since they spend less time in transit which increases workers’ effective work input. Second, better connectivity between employment locations and residences makes it easier to match workers to jobs in which they are most productive even if those jobs are far away from workers’ residences. This allows locations to become more "specialized" using their comparative advantage as residence or employment locations or as employment hubs for specific sectors.

Table 1 shows that the BRT investments have large effects on sectoral output. Phase 1 of the BRT increases output by 4.4-5 percent in all sectors, while Phase 2 increases output by 7.2-7.6 percent in all sectors. Overall, output gains are relatively similar in all sectors. Similarly, we find very little reallocation of workers across sectors. These findings imply that the BRT supports output growth homogeneously across sectors and does not prompt a significant reallocation of workers across sectors.

# **6.3 Distributional Effects of the BRT across Neighborhoods**

**Distribution of Employment.** We next discuss how each phase of the BRT roll-out affects the distribution of jobs and economic activity across neighborhoods.

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Table 1: Large Aggregate Effects of BRT on Sectoral Output

|Bysector|Phase 1 of BRT|Phase 2 of BRT|
|---|---|---|
|Manufacturing|4.37 %|7.60 %|
|Non-tradable services|4.35 %|7.24 %|
|Tradable services|4.96 %|7.61 %|

Under this assumption, Figure 10 shows how employment density would change under BRT Phase 1 and Phase 2. We see large distributional effects with employment density decreasing in some neighborhoods by up to 11 percent and increasing in others by up to 31 percent. BRT Phase 1 increases employment density in the northeastern and northwestern parts of the center where density was already relatively high before the BRT investments. At the same time, employment density would decrease in the southern and northern periphery where density is relatively low before the BRT investments. This finding suggests that BRT Phase 1 would make Amman more mono-centric and spatial inequality in the city would increase. BRT Phase 2 would additionally increase employment density in the south and would decrease it in the eastern and northern periphery. Additionally, figure 11 and figure 12 shows how employment density and wage change by sector under BRT Phase 1 and Phase 2. We can see that workers in manufacturer sector benefits the most from the BRT, who also live the farthest away from the city center before the BRT investment.

**Distribution of Population, Rent, and Welfare.** Figure 13 shows the effects of the BRT on population density, rents, and welfare. In Phase 1, welfare increases in all locations, with the largest gains in the north, northwest, and northeast, where welfare increases up to 16 percent. Welfare increases in locations that are directly connected to the BRT line due to shorter commuting times and productivity/wage increases; some locations that are not directly connected to the BRT line also benefit from reductions in long commuting distances and can further gain from spillovers such as lower rents. BRT Phase 1 increases population density and rents most in the north and center, while it decreases in the south and center-

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west.

Under BRT Phase 2, welfare again increases in all regions, with largest gains (up to 16 percent) in the south and northwest. BRT Phase 2 increases population density and rent most in the south and north-west, with increases up to 14 percent for population density and up to 18 percent for rent.

# **6.4 The Impact of Zoning Restrictions on Outcomes of the BRT**

Zoning restrictions can limit economic development and agglomeration forces in highlyproductive locations. Our analysis in Figure 14 shows that (holding population and employment constant) zoning restrictions may bind in several locations located mostly in the center west of Amman. Before the BRT investments, zoning restrictions bind in 9 neighborhoods for residential floor space and in one neighborhoods additionally for commercial floor space. With the opening of the BRT lines (Phases 1 and 2), our model predicts that the demand for commercial floor space would further increase, making zoning restrictions binding in a total of 13 neighborhoods among which commercial and residential restrictions would simultaneously bind in 10 or 11 neighborhoods (cf. Figure 14, (a) and (b) respectively).

The neighborhoods in northwestern Amman in which zoning restrictions are binding (highlighted in Figure 14), fall around a BRT interchange site in Sweileh. The neighborhoods are characterized by a mix of formal and informal mid-rise structures, with both main highways and more narrow winding streets, and medium levels of planning and modernization. The BRT terminal building itself, and the surrounding areas, are underused and underleveraged. The analysis suggests this neighborhood will receive considerable new demand as an employment and residential location in response to the BRT, and has considerable potential to create new economic opportunities, with strong potential as a site for urban regeneration, densification, and land value capture through intentional transit-oriented de14
velopment. However, realizing this potential may require a revision of zoning rules that prevent the neighborhood from adjusting to its new opportunities.

The neighborhoods with binding zoning restrictions to the South-East of Sweileh in Figure 14 are currently wealthy, planned, predominantly residential, neighborhoods near central Amman. These neighborhoods also host some substantial commercial centers, such as shopping malls, international hotels, the new Central Business District, and Sport City. The analysis suggests that many of these neighborhoods are mainly zoned for low-density residential development: Residential zones A and B, requiring lot sizes of at least 750-1,000 square meters, only four floors above street level, and maximum lot coverage of 39-45 percent. There is expected to be demand for densification, and for more productive and commercial activities, in these neighborhoods due to the BRT, above the levels allowed by current zoning regulations. Low-density residential zoning may prevent this productive evolution of the neighborhood, dampening the more transformative job- and wealth- creating benefits that the BRT may bring. The city may consider allowing for additional stories, lower setbacks, and more mixed-use zoning in these neighborhoods, to allow a more productive adaptation to these new opportunities.

Development of these neighborhoods could create opportunities for lower-income residents in other areas of Amman, such as the East and South, if zoning restrictions are addressed and transit-oriented development encouraged. After Phase 1 of the BRT, the discussed centerwest neighborhoods are at approximately 30 to 45 minutes commuting distance from lowerincome communities of East Amman, and 45 to 60 minutes from informal settlements further South around Wahdat refugee camp. These latter southern informal settlements are expected to benefit from further commuting time reductions under Phase 2 of the BRT, to which they are proximate. Accessibility in eastern low-income neighborhoods could be supported by ’last mile’ connectivity improvements: currently, walking to taxi or minibus stands, waiting for taxis, and taxi rides to reach the BRT station comprise 20 to 30 minutes of the 30 to 40 minute commute time estimated.

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One of the highlighted neighborhoods in Figure 14 , Amir Al Hassan, located East of Amman, largely consists of a Palestinian refugee camp with unique planning, zoning, and social characteristics analysis of which is beyond the scope of this paper.

The above results on the bindingness of zoning could be subject to measurement errors due to the imperfect capture of housing volumes from the satellite data and due to the difficulty of matching all land-use plots and building types to the legal GAM Zoning Restrictions. In addition, restrictions would become more binding over time, to the extent the Amman population and economy continues to grow, raising aggregate demand for floor space.

It is therefore useful to complement these results with a measure of how close the supply and demand for floor space is to the legal limit under the zoning restriction. We show this in Figure 14, which plots the ratio between current floor space demand and the limit under existing zoning restrictions, after BRT Phase II. A ratio larger than 1 implies that zoning restrictions are binding in the neighborhood, while a low number implies that the building stock is far from the legal limits. Figure 15 shows that floor space demand is much lower than the zoning restrictions in most neighborhoods with ratios below 50 percent in many locations. However, the demand for floor space in the most constrained locations in the center-west far exceeds the legal limits with demand being up to 40 percent higher than the legal limit.

# **7 Conclusions**

This paper studied the long-run welfare and productivity effects of recently completed and ongoing expansion of the Greater Amman Municipality’s BRT system. It constructed a rich, quantitative spatial model that captured many aspects of the economic geography of Amman, including households’ residential locations, firms’ and workers employment decisions, building supply and regulation, and sectors’ spatial distribution and productivity.

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We find that the BRT expansion should support large increases in output for all sectors. Compared to the baseline, it is expected to raise output in manufacturing, tradable services, and non-tradable services by 4.4 to 5 percent in "Phase 1", and 7.2 to 7.6 percent in "Phase 2". Workers in manufacturing benefit the most from the BRT’s expansion, reflecting that they lived farthest from the city center at baseline.

Both phases of the BRT improve welfare in all of Amman’s 152 neighborhoods. Phase 1 tends to promote greater mono-centricity of the city, with the greatest welfare and density increases in already-dense neighborhoods in the north-west and north-east. Phase 2 encourages more poly-centricity, with additional densification of the (initially less dense) south.

Anticipating these incremental changes in employment, population, and/or building density across the city can help city planners to plan appropriate complementary policies to the BRT. This may include, for example, spatially targeting new services (such as education and health facilities, or water and sanitation) to accommodate incoming populations or firms; reviewing and adjusting land use plans to accommodate densification in areas made more productive or attractive by the BRT; land value capture targeting locations benefiting from the BRT; and complementary transport services for targeted areas currently expected to benefit less from the BRT, among other policies.

Among these considerations, we analyze the interaction of zoning restrictions with the BRT. This analysis suggests that current land use zoning limits would restrict the private sector’s response to the BRT, by restricting new construction in some locations with large excess demand for real estate resulting from the BRT. The desirability of amending zoning regulations in these areas will depend on further considerations, such as any risks associated with densification of those locations.

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- Redding, Stephen J, Daniel Sturm, and Stephan Heblich. 2018. “The Making of the Modern Metropolis: Evidence from London.” .

- Tsivanidis, Nick. 2019. “Evaluating the impact of urban transit infrastructure: Evidence from bogotaâs transmilenio.”

- Zárate, Román D. 2022. “Spatial Misallocation, Informality, and Transit Improvements: Evidence from Mexico City.”

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