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1、Mobility and Development PeriodicalFall 20242024 Transport Global Practice International Bank for Reconstruction and Development/The World Bank 1818 H Street NW,Washington DC 20433 Internet:http:/www.worldbank.org/transportStandard DisclaimerThis work is a product of the staff of The International B

2、ank of Reconstruction and Development/World Bank.The findings,interpretations,and conclusions expressed in this work do not necessarily reflect the views of Executive Directors of the World Bank or the governments they represent.The World Bank does not guarantee the accuracy of the data included in

3、this work.The boundaries,colors,denominations,and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.This work is available under the Creative Commons

4、 Attribution 3.0 IGO license(CC BY 3.0 IGO)http:/creativecommons.org/licenses/by/3.0/igo.Under the Creative Commons Attribution license,you are free to copy,distribute,transmit,and adapt this work,including for commercial purposes,under the following conditions:AttributionPlease cite the work as fol

5、lows:World Bank,2024.Mobility and Development Periodical,License:Creative Commons Attribution CC by 3.0.TranslationsIf you create a translation of this work,please add the following disclaimer along with the attribution:This translation was not created by the Transport unit or the World Bank and sho

6、uld not be considered an official World Bank translation.Transport and the World Bank shall not be liable for any content or error in this translation.AdaptationsIf you create an adaptation of this work,please add the following disclaimer along with the attribution:This is an adaptation of an origin

7、al work by The World Bank.Views and opinions expressed in the adaptation are the sole responsibility of the author or authors of the adaptation and are not endorsed by The World Bank.Copyright StatementThe material in this publication is copyrighted.Copying and/or transmitting portions or all of thi

8、s work without permission may be a violation of applicable law.The International Bank for Reconstruction and Development/The World Bank encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly.Editor-in-Chief:Binyam Reja Series Editor:Jonatha

9、n Davidar Copy Editor:Susanna Lazarus,RR DonnellyTechnical Reviewer:Asif FaizBig Data Readiness for Urban Transport Planning in Latin American Cities Ellin Ivarsson,Aiga Stokenberga and Juan Ignacio Fulponi01Harmonization-The Key to Unlocking Drone Potential for All Catalina Ochoa,Edward Anderson,Gr

10、egor Engelmann and David Guerin02The Case for Metropolitan Transit Authorities,in Dhaka and Beyond Catalina Ochoa,Jesse Harber and Mokaddesul Hoque05A Tale of Three Cities:The Role of Public Transportation in Boosting Womens Economic Opportunities in MENA Muneeza Alam and Mira Morad06An Economic Cor

11、ridor Approach to Harness Lithium as a Transformational Opportunity for Argentinas Northwest Liljana Sekerinska and Aiga Stokenberg09A note from the Editor-in-Chief Binyam RejaForeword Nicolas Peltier-ThibergeOff the Books:Understanding and Mitigating the Fiscal Risks of the Transport Sector Matias

12、Herrera Dappe,Vivien Foster,Aldo Musacchio,Teresa Ter-Minassian and Burak Turkgulu03Transforming the Urban Mobility Landscape:Challenges and Opportunities Ajay Kumar and Sam Zimmerman04Impacts of improved road infrastructure on jobs in rural Armenia Nino Pkhikidze07Accelerating Electric Mobility Ado

13、ption in Pakistan Shyam Srinivasan,Fatima Noor Aftab,Pablo Claudio Armando Mollinedo,and Lincoln Flor0867Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionA note from the Editor-in-ChiefCities worldwide are investing in transport systems to add

14、ress urban challenges,but what will make the difference is effective urban mobility governance.Catalina Ochoa,Jesse Harber,and Mokaddesul Hoque discuss metropolitan transport agencies as a model for integrating planning,regulation,and enforcement.Using Dhaka as an example,their article highlights th

15、e limitations of the existing Dhaka Transport Coordination Authority(DTCA)and advocates for reforms to empower it.On the topic of innovation in transport sector,almost 10 years ago,Ajay Kumar and Sam Zimmerman observed that successful urban transport strategies reflect an understanding of the links

16、between factors across transport,land use,social,economy,and environment.As these observations remain valid,there have been new challenges and opportunities in transforming the urban mobility landscape globally.In their piece,they use examples from across Africa to give a fresh perspective on what m

17、akes it so difficult to achieve success and offers a guiding framework around which to plan and implement future interventions.We then join Muneeza Alam and Mira Morad for A Tale of Three Cities,in which they examine the challenges women face using public transport in Amman,Beirut,and Cairo,and its

18、impact on their economic opportunities.The article finds that a well-functioning public transport system is crucial for womens labor force participation but must be tailored to each citys unique context.Improving womens transport experiences can significantly enhance their economic participation and

19、 empowerment.Transportation infrastructure projects typically emphasize direct benefits like reduced travel times and lower costs.However,the broader impact on job creation and economic growth is often overlooked.Nino Pkhikidzes article examines research on how road infrastructure projects affect em

20、ployment,particularly for women,and contribute to structural economic transformation across sectors from agriculture to manufacturing and services.A case study of the upgrade of Armenias Lifeline Roads Network highlights these indirect benefits.From roads,the conversation shifts to modes of transpor

21、tation.The global shift to electric mobility,driven by environmental and economic goals,is reflected in Pakistans policies.Aiming to reduce emissions,decrease fuel imports,and boost economic growth,the government provides incentives for EV adoption,though the transition is still in its early stages.

22、Shyam Srinivasan,Pablo Mollinedo and Fatima Aftab examine the significance of EVs in Pakistan,challenges and opportunities,and strategies to accelerate the transition,offering valuable lessons for other lower-middle-income countries.We close this issue at Argentinas Northwestern provinces,which hold

23、 some of the worlds largest lithium reserves.In this article,Liljana Sekerinska and Aiga Stokenberga discuss the transport and infrastructure challenges that must be overcome to effectively utilize these lithium resources.It explores how addressing these issues can drive economic transformation in t

24、he region and benefit other key local industries.Additionally,they highlight opportunities for decarbonizing the lithium value chain in Argentina through a mode shift from road to rail.I express my heartfelt gratitude to all the contributors for their research in this issue.Your work will undoubtedl

25、y contribute to enhancing transportation and transitioning mobility systems towards a more sustainable and resilient future.We welcome suggestions for future topics.Please contact the editorial team at WBGTransportworldbank.org with your ideas.Welcome to the latest edition of Mobility and Developmen

26、t:Innovations,Policies,and Practices.This online periodical was launched by the World Banks Transport Global Practice to distribute policy-focused and practical publications impacting the global transport sector.The inaugural Fall 2021 issue examined solutions for enhancing low-carbon and resilient

27、mobility in a post-pandemic world.In the Spring 2022 issue,we allowed the submissions to guide the conversation within the broad framework of mobility and development.And so it is with this Summer 2024 Edition 2024 issue.From technology regulation to policy making and socio-economic impact to indust

28、ry benefits,we explore multiple aspects of mobility and how it influences development in the current context.These are timely topics that cover key trends in the sector,contributed by both World Bank staff and guest authors.We open the issue with Big Data.Ellin Ivarsson,Aiga Stokenberga,and Juan Ign

29、acio Fulponi delve into research that reviews the Big Data readiness in Latin American cities.The article aims to highlight cases where they already use it for investment and policy making.The analysis reveals that many Latin American cities have a sound basis for maximizing the use of Big Data in t

30、ransport planning,although locally tailored methodologies are not always readily available.Catalina Ochoa,Edward Anderson,Gregor Engelmann,and David Guerin take to the skies with their article on the growing need to harmonize drone regulations.The growing use of drones excites businesses and benefic

31、iaries,but raises concerns among regulatory agencies and the public about safety,privacy,and equitable access.Regulatory harmonization can address these issues,as streamlined regulations build trust,improve efficiency,and promote wider economic development through increased accessibility.Even as gov

32、ernments invest in infrastructure in the transport sector,there is always a risk factor.In their article,Matias Herrera Dappe,Vivien Foster,Aldo Musacchio,Teresa Ter-Minassian,and Burak Turkgulu assess fiscal risks in the transport sector across developing countries,identifying root causes and mitig

33、ation strategies.Based on“Off the Books:Understanding and Mitigating the Fiscal Risks of Infrastructure”(2023),it highlights the importance of good governance,varying fiscal risks,and sustainable investment.Key questions addressed include the significance of fiscal risks from public provision,state-

34、owned enterprises,and public-private partnerships,and mitigation strategies.Binyam Reja,Global Practice Manager for Transport,The World Bank89Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionIt is my pleasure to welcome you to the fourth editi

35、on of Mobility and Development:Innovations,Policies,and Practices.This online periodical continues to draw attention to the dynamic landscape of the global transport sector and its intersection with development.As governments and policymakers navigate the complexities of a rapidly evolving transport

36、 sector,the importance of sustainable and inclusive mobility cannot be overstated.From facilitating economic growth and social inclusion to mitigating climate change and improving public health,transportation plays a fundamental role in shaping the future of our planet.Nicolas Peltier-Thiberge,Globa

37、l Director for Transport,Transport,The World BankAt the World Bank,we recognize the transformative potential of innovative transport solutions and policies in driving progress and prosperity.Through Mobility and Development,we aim to foster dialogue,share knowledge,and showcase best practices that c

38、an inform and inspire action towards building more resilient,efficient,and equitable transport systems.In this edition,I am thrilled to see the numerous facets of the sector that have been explored.Be it regulatory issues,access to jobs,gender and socio-economic impact,or fiscal risk associated with

39、 innovation,each has been covered with nuance and detail.Every article offers valuable insights into the challenges and opportunities that lie ahead.The authors have displayed their deep expertise and dedication to their fields of practice.I am confident that the diverse perspectives and experiences

40、 shared in this edition will enrich our understanding of the complex dynamics at play in the world of mobility.By harnessing collective expertise,the global transport sector can work together to address key challenges and unlock new opportunities for sustainable development.I invite you to engage wi

41、th the content,share your insights and experiences,and join us in shaping the future of mobility and development.Together,let us leverage the transformations taking place in the transport sector to create a better future for people and the planet.1011Mobility and Development Periodical|Fall 2024 Edi

42、tionMobility and Development Periodical|Fall 2024 EditionAt a GlanceBig Data1 can empower city leaders as they work to improve policy and infrastructure decision-making to increase economic impact and foster development.Big Data application has a significant regional imbalance.Even though there are

43、tremendous opportunities,many developing countries havent unlocked the potential of Big Data that can reduce the“data poverty”around overall urban mobility.This article reviews the Big Data readiness in Latin American cities(LAC)and aims to highlight cases where they already use it for investment an

44、d policy making.The analysis reveals that many LAC have a sound basis for maximizing the use of Big Data in transport planning,although locally tailored methodologies are not always readily available.1 Larger,more complex datasets,especially from new data sources such as mobile telephony and GPS dev

45、ices1Big Data Readiness for Urban Transport Planning in Latin American CitiesEllin Ivarsson Aiga Stokenberga Juan Ignacio FulponiAbout the AuthorsAiga Stokenberga is a Senior Economist in the Latin America and the Caribbean Transport team.Her focus is on analytical work and investment and policy len

46、ding in the areas of urban mobility,regional corridors,and sustainable infrastructure planning.Aiga StokenbergaSenior Economist,Transport Global Practice,World BankEllin Ivarsson is a Transport Specialist in the Latin America and the Caribbean Transport team.Her wor includes the analysis and the app

47、lication of new technologies to solve transportation problems,along with investment lending in the areas of urban mobility,and rural transport.Ellin IvarssonTransport Specialist,World BankJuan Ignacio Fulponi is a Geospatial Data Scientist and Transportation Consultant with a strong background in tr

48、ansportation economics and urban planning,currently working with The World Bank.His areas of fouc include data science as applied to urban mobility analytics and operations.Juan Ignacio FulponiTransportation Consultant,World Bank 1213Mobility and Development Periodical|Fall 2024 EditionMobility and

49、Development Periodical|Fall 2024 EditionThe increasing importance of Big Data in transport policy developmentDue to technology adoption,rapid urbanization,and other factors,urban mobility has been changing at an ever-increasing pace.Countries have an increased need to create transport infrastructure

50、 that provides safer,greener,and more efficient transport.A key example is the impact of teleworking and e-shopping on travel demand that has reduced the number of work and shopping trips.Meanwhile,leisure and urban freight trips are modifying the temporal patterns of demand and transport mode choic

51、es.Today,e-commerce generates more traffic than it avoids.Previous analysis on Bogot and Buenos Aires shows that e-commerce is likely to have a net effect of increasing road traffic,because of an increased number of freight vehicle trips and limited substitution effect on the demand for private vehi

52、cle trips.2Since the transport sector requires large-scale investments,planners and modelers must have access to data and tools that forecast demand and inform key policy and investment decisions that will have an impact decades,or even centuries,into the future.These decisions include transport pol

53、icies(e.g.,introducing road pricing,setting public transport fares),prioritizing the implementation of new infrastructure,upgrading existing infrastructure,and introducing improved services(e.g.,new bus routes).Leveraging the power of Big Data in the developing world can bring important opportunitie

54、s for the transportation and mobility sector.3Traditionally,these decisions have been based on manual travel surveys(conducted on board or at roadside stops),household surveys,and censuses.These data inform the development of travel origin-destination(OD)matrices to predict travel behavior and solve

55、 traffic problems.These traditional methods are labor intensive and associated with high costs.As a result,sample sizes are smalltypically around 1-2 percent of the population in the case of household surveys.4 Therefore,they cannot be regularly updated,5 and the resulting datasets usually contain e

56、rrors in reporting and are prone to statistical errors.6 In the context of developing countries,using these traditional methods is problematic,as resources are even more limited.It is also difficult to pick up on rapidly evolving changes in mobility patterns.And so,transport planning,infrastructure,

57、and policy decisions are often based on information that is 10 to 15 years old.In the last decade,Big Data has increasingly been considered by transport sector decision-makers,among others,to improve policymaking,and more effectively contribute to economic growth and development.However,in the devel

58、oping world,so far,its use for decision-making 2 Stokenberga,Aiga;Fulponi,Juan Ignacio.2023.A Net Cure or Curse?:Tracking the Impact of E-Commerce on Urban Freight Transport Intensity in Bogot and Buenos Aires.Policy Research Working Papers;10485.World Bank,Washington,DC.http:/ Torre-Bastida,A.I.,J.

59、Del Ser,I.Lana,M.Ilardia,M.Nekane Bilbao,S.Campos-Crodobes.2018.Big Data for transportation and mobility:recent advances,trends and challenges.IET Intelligent Transport Systems,12(8),742-755.4 Catapult Transport Systems.2016.Utilising Mobile Network Data for Transport Modelling:Recommendations Paper

60、.London:Department for Transport.5 Iliashenko,O.,Iliasheno,V.,Lukyanchenko,E.2021.Big Data in Transport Modelling and Planning.Transportation Research Procedia.Vol.54,900-908.6 Milne,D.,&Watling,D.2019.Big Data and understanding change in the context of planning transport systems.Journal of Transpor

61、t Geography.has been less common,even though there are huge opportunities and potential.While many developing countries have been increasingly exploiting traditional transport planning data such as household travel surveys,it is less clear if their decision-makers are aware of other available method

62、ologies.Big Data in particular,in combination with traditional data sources,can leverage each type of data for its unique advantages.The proliferation of mobile devices and the widespread adoption of geolocation and sensing technologies open new opportunities to collect large samples of mobility dat

63、a continuously.It comes with a high degree of detail and spatial and temporal resolution.This is no surprise,as the number of smartphone mobile network subscriptions worldwide reached almost 6.6 billion in 2022,7 equivalent to around 85 percent of the 8-billion global population.Is LAC Big Data-read

64、y?This article investigates readily available Big Data sources for city planners in Latin America and the Caribbean and assesses their preparedness to utilize its potential.It explores their openness to using Big Data for strategic(long-term transport planning),tactical(service adjustments),and oper

65、ational(public transport performance)decisions.To assess Latin America and the Caribbeans readiness and current Big Data use in transportation,the article analyzes:mobile phone penetration and mobile network operators(MNOs);public transport network coverage by smart cards(digital ticketing);availabi

66、lity of updated household survey;and presence of e-commerce platforms.Mobile Phone DataHigh levels of mobile phone adoption rates ensure a better representation of the populations travel patterns.MNOs create data that contains timestamped locations for individuals,such as call detail records(CDRs),s

67、ignaling data,and mobile GPS data.This information can provide high-quality,granular information on mobility.CDR data helps to infer peoples daily travel patterns by extracting tower-to-tower transient OD(Origin-Destination)with their timestamps.It has an astonishing advantage in terms of increasing

68、 spatiotemporal survey coverage and reducing time and cost of survey implementation.Smart cards(Digital ticketing systems)Smart card automated fare collection systems produce large quantities of detailed data on onboard transactions.This data is key to understanding public transport use and behavior

69、s.Each time the card is used,a transaction is recorded,providing a snapshot of the cardholders boarding location and time.The dataset contains reliable information but has some limitations in terms of sociodemographic information unless the user registers the smart card.The most significant limitati

70、on is that the trip purpose and the exact trip origin and destination are unknown.7 Statista.2023.Number of smartphone mobile network subscriptions worldwide from 2016 to 2022,with forecasts from 2023 to 2028.1415Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodica

71、l|Fall 2024 EditionThere is more variability across the cities regarding the availability of complementary data such as public transport smart card data and household travel survey data.These are typically needed for calibrating,validating,and developing robust,mode-disaggregated OD matrices from CD

72、R data.Smart card data that covers the entire public transport system is available only in a selection of the assessed cities.This includes Mexico City,Sao Paulo,Rio de Janeiro,Caracas,Bogota,Buenos Aires,Asuncion,Montevideo,and San Jose(listed in order of population size)(Figure 1 C.).In most citie

73、s,smart card data is available but covers only part of the public transport system,such as the formally operated bus(e.g.,Bus Rapid Transit,or BRT)and metro services.Examples of such cities include Lima,in which the smart card system covers Metro Line 1 and the Metropolitano BRT system.Similarly,in

74、Medellin and Cali(in Colombia),smart card systems exist,but exclude urban and inter-urban transport services that are not part of the SITVA and MIO systems,respectively.On the other hand,in Santiago(Chile),the TBip!smart card covers all public transport,but is limited to the city and does not cover

75、travel in the broader metropolitan area,thus limiting the application of the collected data for developing CDR-based metropolitan-scale OD matrices.No smart card data is available in most of the smaller analyzed cities,such as Cordoba(Argentina),Arequipa(Peru),and most of the Central American and Ca

76、ribbean cities.Finally,in terms of household travel data,the analysis distinguishes between cities that have:Relatively recent(2017 or newer)data Older household travel surveys Only partial travel pattern indicators(for example,only perception-based surveys)Cities that do not have any data of this t

77、ype(Figure 1 D)As expected,the megacities(Sao Paulo,Mexico City,Buenos Aires,Ro de Janeiro,Bogot)fall in the first category.Among the cities with population of 5-10 million,relatively recent and complete household travel survey data is available for Monterrey,while Guadalajara only has a perception-

78、based survey available and Santiago has a household travel survey that by now is over a decade old.In the group of smaller cities,most do not have recent and comprehensive survey data,except Brasilia,Medellin,Cali,La Paz,Santo Domingo,Montevideo,and Asuncion.E-commerce platformsPrivate companies in

79、the e-commerce sector are generating a key source of information on freight transport flows.Household surveysAlthough the most important data source for a range of key demographic and socioeconomic statistics and mobility patterns,this information suffers from limited sample size and temporal covera

80、ge.Fusing it with Big Data sources such as CDR and smart card data allows planners to appropriately calibrate,validate,and create robust city-wide,multiday,and all-day OD matrices.This investigation focused on cities in Latin American and the Caribbean countries,ranging from megacities like So Paulo

81、,Lima,and Mexico City to smaller capitals in Central America and the Caribbean.The study prioritizes countries where data is readily available,assuming this reflects a higher potential for Big Data adoption.City-level evaluations are then aggregated to assess readiness at the national level.Potentia

82、l for Big Data use in LAC urban transport planningThe analysis finds that the Latin America and the Caribbean region is rather heterogeneous regarding Big Data readiness for transport sector applications,both at a country and individual city level.At the individual city level,many cities have the pr

83、erequisites to leverage Big Data for transport planning.However,there are gaps,especially in the availability of household travel surveys and the presence of e-commerce platforms that would allow the inference of urban freight flows.Overall,large cities have robust and recent datasets and technologi

84、cal solutions to better understand transport behavior,while medium-to-small cities show low ranking in some or all the four categories.Except for Havana(Cuba),there are several MNOs operating(Figure 1A)in the analyzed cities.This presents opportunities for data partnerships in order to leverage CDR

85、data for mobility analysis.At the same time,the presence of multiple MNOs in places like Venezuela,Panama,Honduras,and Puerto Rico also means that each individual operator will represent a smaller overall market share.This needs to be considered and appropriately adjusted for when analyzing the data

86、.Similarly,all the considered cities except Port-au-Prince(Haiti)and Havana(Cuba)have several operational e-commerce platforms present.The likes of Rappi8 and Mercado Libre9 provide general e-commerce services as do more specific platforms such as those for food delivery(Figure 1 B.).However,accessi

87、ng data from these platforms for urban freight transport analysis and planning depends on the presence of specific data-sharing agreements between the platform operators and public sector authorities.8 Rappi is a technology company that builds a marketplace where local commerce in Latin America can

88、thrive.It focuses on food,grocery,and pharmacy delivery.9 Mercado Libre hosts the largest online commerce and payments ecosystem in Latin America.1617Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionFigure 1:Big Data and complementary data in

89、LAC citiesA.Number of MTOsB.Operational e-commerce platformsAvailableAvailable for part of the systemNot availableAvailablePartial indicators/OldNot availableC.Availability of public transport smart card dataD.Availability of household travel surveysSource:World Bank.At the aggregate level,the count

90、ries that have better readiness to use Big Data in transport sector analysis and decision-making are Brazil,Colombia,Mxico,Paraguay,and Dominican Republic(Table 1).These countries have high levels of smartphone adoption,MNOs with high market shares,smartcard data,recent household surveys,and multipl

91、e e-commerce platforms.Overall,the great majority of countries have at least one city that has implemented digital ticketing systems and smart cards that can provide information on public transportation usage.On the other hand,countries such as Cuba,Guatemala,Haiti,Venezuela,Honduras,and Nicaragua s

92、uffer“Big Data poverty”,particularly in areas such as availability of smart card data and recent household surveys.It therefore depends on the urban transport planning authorities to develop an initial strategy to allow for transport sector planning innovations driven by Big Data.Countries such as A

93、rgentina,Brazil,Chile,Colombia,and Mexico,show high levels of smartphone adoption with a few MNOs that each count with a large market share(usually above 25 percent).Selecting one of the top MNOs would provide a reliable dataset that represents a large percentage of the population.Countries such as

94、El Salvador have a low smart adoption rate and multiple MNOs,reducing the quality of the raw data that could be obtained from CDRs.Table 1.Transport data readiness for LAC citiesBig Data readinessCountrySmartphone adoptionMNOsSmart card dataHousehold surveysE-commerce platformsHighBrazil86.0%3Availa

95、ble RecentMultipleColombia67.0%4AvailableRecentMultipleMexico67.0%4AvailableRecentMultipleParaguay58.0%4AvailableRecentMultipleDominican Rep.69.7%3AvailableRecentMultipleMediumArgentina73.0%3Partially availablePartial/oldMultipleChile70.0%4Partially availablePartial/oldMultipleCosta Rica65.0%3Availa

96、blePartial/oldMultipleEcuador65.0%3AvailablePartial/oldMultipleEl Salvador54.5%5AvailableNone publishedMultiplePanama71.5%4AvailableNone publishedMultiplePuerto Rico69.5%3AvailableNone publishedMultipleUruguay67.5%3AvailablePartial/oldMultiple1819Mobility and Development Periodical|Fall 2024 Edition

97、Mobility and Development Periodical|Fall 2024 EditionBig Data readinessCountrySmartphone adoptionMNOsSmart card dataHousehold surveysE-commerce platformsLowBolivia50.0%3AvailablePartial/oldLimitedCuba56.0%1No smart card useNone publishedNoneGuatemala65.0%2Mostly availableNone publishedMultipleHaiti5

98、1.0%2No smart card useNone publishedNoneHonduras61.0%3No smart card useNone publishedMultipleNicaragua55.5%2No smart card useNone publishedMultiplePeru62.0%4Partially availableRecentMultipleVenezuela71.5%3AvailableNone publishedMultipleSource:World Bank.Leveraging Big Data in LAC for urban transport

99、 analysis The private sector holds the key to unlocking valuable data for transport planning.This is because they control most Big Data sources relevant to transportation,including geolocation data from mobility services,trip planners,MaaS apps,and electronic transactions.Heres whats changed:Uber Mo

100、vement,an initiative to share data on travel times and speeds,aiming to contribute to a more sustainable mobility Waze for Cities,that measures congestion levels Cuebiq,that collects positioning data based on the aggregation of data from different mobile applications,consolidating this data into a s

101、ingle integrated dataset Veraset,that aggregates the information collected from mobile apps providing pre-processed population movement datasets Google Maps,that provides information on multimodal transport options,travel times,and other indicators through different APIs Establishing mobility data-s

102、haring agreements between the private sector and city authorities can create an ideal data ecosystem to enable robust decision-making that can benefit the society.In recent years,many such initiatives have emerged in the Latin America and the Caribbean region.For example,Bogot has developed three da

103、ta sharing initiatives.These include the“content cross-licensing agreement”between the District Mobility Secretariat(SDM)and Waze;the obligation imposed on micro-mobility service operators to share data with the city;and the creation of a district data analytics agency called gata.Buenos Aires has s

104、igned a cross-licensing agreement between the Ministry of Urban Development and Transportation of the Government of the City of Buenos Aires(GCABA)and Google Inc.Several South American countries are leveraging Big Data for transportation planning and investment.These include Brazil,Mexico,Colombia,A

105、rgentina,Chile,Bolivia,Paraguay,Peru,and Uruguay.Notably,cities like Bogot,Medelln,and Buenos Aires have pioneered the development of fully segmented OD matrices using CDRs.By employing advanced algorithms,these matrices account for various travel modes and trip purposes.Matrices disaggregating by m

106、ode,hour of the day,and trip purpose were successfully developed by Bogots Mobility Secretariat,Aburra Valley Metropolitan Area,and Buenos Airess Transport and Public Works Secretariat with World Bank technical assistance.In the case of Buenos Aires,gender-disaggregated OD matrices were also produce

107、d.Following the same methodology,CDR based matrices are currently being developed to inform the planning of mobility in the Asuncion Metropolitan Area in Paraguay.Leveraging the CDR-based matrices in Latin America and the Caribbean cities allowed transport planners to gain insights on aspects of mob

108、ility that were otherwise difficult to analyze,such as the rapid developments unfolding during the COVID-19 pandemic.With World Bank assistance,CDR-based matrices were created for the pre-pandemic,“deep pandemic”and so-called“new normal”periods(2019,2020,and 2021).This allowed the local authorities

109、to track the impact of the pandemic in Bogot and Buenos Aires and provided them with policy-relevant insights.Specifically,the information allowed themto explain how the pandemic had changed mobility patterns and which of those changes persisted.10 It also allowed a better understanding of whether t

110、he pandemic accelerated a shift to e-commerce,and,if so,how it affected the intensity of urban freight transport.11 The CDR data,combined with a large-scale interception survey,has also provided relevant information to analyze the role of gender in mobility patterns in Buenos Aires,suggesting that w

111、omen travel shorter distances,engage in more complex trips with multiple stops and purposes,and travel more in off-peak times,among others.Despite the absence of some of the CDR data-friendly conditions,the Lima and Callao Urban Transport Authority(ATU)in Peru has been leading the development of ope

112、n and updatable tools that leverage Big Data.This is to allow for more accurate diagnosis and planning of urban and mobility issues in the context of limited official mobility data such as household travel 10 Stokenberga,A.,Ivarsson,E.,Fulponi,J.I.(2023).The COVID-19 Mark on Urban Mobility:A Tale of

113、 Two Cities Journey to Recovery.Policy Research Working Papers;10484.World Bank,Washington,D.C.https:/openknowledge.worldbank.org/handle/10986/3992611 Stokenberga,A.,Ivarsson,E.,Fulponi,J.I.(2023).A Net Cure or Curse?:Tracking the Impact of E-Commerce on Urban Freight Transport Intensity in Bogot an

114、d Buenos Aires.Policy Research Working Papers;10485.World Bank,Washington,D.C.https:/openknowledge.worldbank.org/handle/10986/399242021Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 Editionsurveys.Geolocated information from mobile devices,both agg

115、regated(with pre-built indicators such as from Mapbox and Waze)and disaggregated(spatial GPS location points over time from Veraset),helped the authorities understand mobility patterns in a more comprehensive and consistent way.General Transit Feed Specification(GTFS)data collected using a smartphon

116、e application allowed ATU to also study informal transport routes.Accurate information on this is otherwise extremely difficult to obtain.The GTFS data was also used to compare the characteristics of formal and informal routes,including fares by distance and the type of vehicle used for the journey.

117、Across numerous cities in Mexico,Big Data from smartphone applications is currently being used to retroactively evaluate the demand projections that informed federal public transport planning and financing over the past 15 years.Moving forward with mobility planning,enhanced by Big DataA methodologi

118、cal guide for cities to leverage the use of Big Data is given in the decision tree in Figure 2.It provides a structured way to create robust OD matrices for transport planning based on the city characteristics and data availability.Figure 2.Decision-tree for using Mobile Network Data(MND)for transpo

119、rt planningCombined method(Traditional methods+mobile phone general mobility patterns)YesSmall(few thousand inhabitants)Medium/largeWhat is the size of my city?Is public transport supply/demand and/or transport mode survey information available?Is there cellphone information available?Is supply/dema

120、nd data collection an option?Is there cellphone information available?Proposed methodology(mobile phone+modal supply/demand)Simplified proposed methodology(obtain only full mobility(no mode)with mobile phone)Traditional methods(e.g.,Household and Mobility surveys)YesYesYesNoNoNoNoSource:World Bank.F

121、irst,authorities should define whether it is cost-effective and convenient to use CDR data for mobility analysis depending on the size of the city.The cost-benefit of applying these techniques in small cities(a few thousand inhabitants)may not be as advantageous as in medium to large cities.In small

122、 cities,the mobile technology may not have the capacity to provide much mobility related information,since there are not enough antennas.The spatial granularity of the insights gained is low.Thus,in these cases,it is recommended to use traditional methods such as travel and household surveys.Second,

123、it is important to define whether there is an MNO available to process the data.Therefore,the following conditions should be met:(i)One of the countrys main mobile telephone operators is interested in using the data for mobility studies.(ii)The mobile telephone operator has the technological capacit

124、y to extract the data with sufficient quality for subsequent use.(iii)The operator or a technological ally of the operator has a reliable analytical solution to obtain mobility indicators with the required quality and timeframe.If mobile phone data is unavailable(or not of sufficient quality),tradit

125、ional methodologies based on surveys or smartphone application data may be more appropriate.Third,it is important to have secondary data that can be“fused”with CDR data to estimate trip purposes,modes,and other details.This data includes:(i)Land use and point of interest data.(ii)Transportation netw

126、ork and transportation service supply data.(iii)Census or sociodemographic statistics.(iv)Transport demand data such as household survey-based OD matrices.The availability of one or more of these data sources will help process and improve the accuracy of the trip matrices generated from mobile phone

127、 data.12 If this information is not available,it will be necessary to carry out additional field work by mode of transport.If this option is not possible,mobile phone data can still be used to gain insights on overall mobility.When incorporated into the citys transport models,it can help to improve

128、the estimates of modal assignment.Finally,CDRs are nonpublic data and contain personal information that is complex and costly to process.In many cases,cities do not have direct access to raw data from mobile telephony.They also may not have the analytical and computational capabilities needed to car

129、ry out this type of analysis.This is why it is generally recommended to purchase OD matrices produced by specialized companies unless there is robust in-house technical capacity and resources available.Alternatively,it is possible to establish data sharing agreements with the MNOs and process it int

130、ernally or by a third party.12 Willumsen,L.(2021).Use of Big Data in Transport Modelling.Retrieved from International Transport Forum Discussion Papers,No.2021/05,OECD Publishing,Paris:https:/www.itf-oecd.org/sites/default/files/docs/big-data-transport-modelling.pdf2223Mobility and Development Perio

131、dical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionThe role of the local and national governmentsGovernments in Latin America and the Caribbean cities still have some way to go to effectively use Big Data in public policies.Public administrators can use currently available t

132、raditional data and Big Data more extensively to create public value.This is provided they know how to analyze and use it in public investment and policy planning.Data-sharing partnerships between the public and private sectors can bridge the previously mentioned data gaps and open opportunities for

133、 governments to address transportation challenges with data-driven decisions.Latin America and the Caribbean cities must create or,in some cases,expand data partnerships to build reliable and robust data sources for transport planning.Private companies can share their data for a compensation,either

134、financially or through other types of remuneration(privileged access to data from public sources that allow them to improve their service).In addition,companies can gain enhanced visibility and corporate reputation.On the other hand,transport authorities can collect information of better quality and

135、/or at a lower cost than information obtained through traditional approaches.This will improve the efficiency of decision-making processes related to mobility planning and management.Better information also benefits other public and private stakeholders who make up the urban mobility ecosystem by en

136、abling them to improve their services and optimize their operations.ConclusionBig Data can help decision makers design and implement transportation policies that help cities move toward a more efficient,inclusive,sustainable,and resilient mobility system.Local and regional authorities must monitor,u

137、nderstand,and anticipate these disruptive opportunities.While Big Data sources bring important advantages,they also have limitations in terms of data quality,biases depending on the source,and future applicability due to data privacy considerations.These sources can benefit hugely from traditional m

138、ethods to calibrate and validate the information.Governments need to build a robust data ecosystem that integrates these multiple data sources to ensure that it can adequately support their policy priorities.The national governments have an important role to play in ensuring that medium and small ci

139、ties are not left behind in the data revolution.Governments must support cities in creating technical knowledge,securing sustainable funding,and sharing lessons from cities that have embraced these new technologies,so they can shape the evolution of technology and data.2425Mobility and Development P

140、eriodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionReferencesAkar,G.Bicycling Choice and Gender Case Study:The Ohio State University.International Journal of Sustainable Transportation 7(5),2013.https:/doi.org/10.1080/15568318.2012.673694Alam,M.;Kurshitashvili,N.;Domingu

141、ez Gonzalez,K.,Gonzales Carvajal K.,Baruah B.Is a mile for one a mile for all?Mobility and Transport Connectivity Series.Transport Global Practice World Bank,Washington D.C.,2022.Bachir,D.;Khodabandelou,G.;Gauthier,V.;El Yacoubi,M.;Puchinger,J.Inferring dynamic origin-destination flows by transport

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144、es;V.Raffo;S.Guerrero;I.Portabales.What does she move?A study of womens mobility in Latin American cities.World Bank,Washington D.C.,2020.Duchene,C.Gender and Transport.International Transport Forum,Discussion Paper 11,2011.https:/www.itf-oecd.org/sites/default/files/docs/dp201111.pdfGarrard,J.;Rose

145、,G.;Kai Lo,S.Promoting transportation cycling for women:The role of bicycle infrastructure.Preventative Medicine,46(1),55-59,2008.Gonzlez-Snchez,G.;Olmo-Snchez,M.I.;Maeso-Gonzlez,E.Challenges and Strategies for Post-COVID-19 Gender Equity and Sustainable Mobility.Sustainability 13,2510,2021.https:/d

146、oi.org/10.3390/su13052510Government of Buenos Aires,Boom de la bici:se multiplicaron los viajes y las mujeres ciclistas que circulan por las nuevas ciclovas de Corrientes y Crdoba,2021.https:/buenosaires.gob.ar/ecobici/noticias/boom-de-la-bici-se-multiplicaron-los-viajes-y-las-mujeres-ciclistas-que-

147、circulan International Labor Organization.World Employment and Social Outlook:Trends for women.International Labor Office,Geneva,2017.Meja-Dorantes,L.;Montero,L.;Barcel,J.Mobility Trends before and after the Pandemic Outbreak:Analyzing the Metropolitan Area of Barcelona through the Lens of Equality

148、and Sustainability.Sustainability.13,7908,2021.https:/doi.org/10.3390/su13147908Perez,G.Polticas de movilidad y consideraciones de gnero en Amrica Latina,serie Comercio Internacional,N 152(LC/TS.2019/108).Comisin Econmica para Amrica Latin y el Caribe(CEPAL),Santiago,2019.Snchez de Madariaga,I.From

149、Women in Transport to Gender in Transport:Challenging Conceptual Frameworks for Improved Policymaking.Journal of International Affairs 67(1):4365,2013.Stokenberga,A.;Ivarsson,E.;Fulponi,J.I.The COVID-19 Mark on Urban Mobility:A Tale of Two Cities Journey to Recovery.Policy Research Working Papers 10

150、484,World Bank,2023.2627Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 Edition2Harmonization-The Key to Unlocking Drone Potential for AllCatalina Ochoa Edward Anderson Gregor Engelmann David GuerinAbout the AuthorsDavid has been working as a short-

151、term consultant with the World Bank since 2017.In his role,he offers advice on safety,operations,regulations,and airspace interactions for projects related to drones.Additionally,he volunteers his time to support drone initiatives focused on humanitarian aid and conservation Sustainable Development

152、Goals(SDGs).Prior to this,David worked for thirty years as an air traffic controller and specialized in aviation and risk management.Catalina is a Senior Urban Transport Specialist at the World Bank and co-founder of the African Drone Forum.Her work focuses on transforming urban mobility and integra

153、ting disruptive technologies into the transport sector.Prior to joining the Bank,she worked in the transport tech sector as a Product Manager,Strategy Manager,and General Manager.She holds masters degrees in urban and regional planning,transport engineering,and business administration.Catalina Ochoa

154、Senior Urban Transport Specialist,World BankDavid GuerinConsultant,World BankEdward Anderson is a Senior Disaster Risk Management Specialist at the World Bank and leads the global program on Digital Earth Partnership,leveraging opportunities in frontier Earth Observation technologies for climate and

155、 disaster risk management.He holds masters degrees in both Aerospace Engineering and International Economics.Edward AndersonSenior Disaster Risk Management Specialist,World BankGregor Engelmann is a Drone Ecosystem and Operationalization Consultant,collaborating with Digital Development,Transport,an

156、d Health,Nutrition,and Population units.He works across Africa,East Asia Pacific,and FCV contexts,focusing on drone feasibility assessments,deployment planning,and regulatory and national strategy development.Gregor EngelmannDrone Ecosystem and Operationalization Consultant,World Bank2829Mobility an

157、d Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionAt a GlanceThe growing use of drones is a source of both excitement and apprehension.The excitement is among businesses and beneficiaries across sectors who are anticipating,or already realizing,substantia

158、l benefits from drones.The apprehension is seen in regulatory agencies and the public,with concerns ranging from safety,privacy,and management of airspace,to sustainability,ethics,and equitable access.However,we cannot realize all the benefits of drones due to the differences in(or lack of)regulatio

159、ns and requirements governing drone operations across countries.Regulatory harmonization presents an opportunity to address these apprehensions while opening cross-border operations,leading to potentially higher return on investment.By enlarging target markets and addressing uncertainties,these inve

160、stments become scalable.They reach a size that is attractive for financiers,inevitably addressing Sustainable Development Goals.By streamlining,clarifying,and enforcing regulations,harmonized and well-designed frameworks can build trust,improve operational efficiency and capacity,and open doors to w

161、ider economic development through increased accessibility.Connection,access,flexibility:Why drones matterUncrewed Aircraft Systems(UAS),often called drones,give countries the opportunity to leapfrog infrastructure gaps and challenging terrain to improve accessibility and address national development

162、 priorities.They accelerate digitization efforts to support agriculture,help plan construction and monitor assets,support urban land administration,and strengthen the resilience of supply chains for health,logistics,and e-commerce(see Box 1).Compared to conventional modalities,the flexibility of dro

163、nes makes them an appropriate tool for connecting underserviced or remote communities.They are a crucial downstream enabler of economic growth,poverty reduction,and shared prosperity globally,and particularly in Africa(Stokenberga,Ochoa,2021).Improved access“can reduce transaction costs in agricultu

164、re and rural development more broadly by improving access to inputs and product markets,facilitating access to education and health services,and expressing the commitment to serving women and the most vulnerable groups”(World Bank,2020).Drones in World Bank-supported projects:Global reach and divers

165、e applicationsThe World Bank supports drone activities through procurement and technical assistance across more than 80 projects in multiple sectors.AgricultureCombat food security by monitoring pests(Chad,Ghana,Sierra Leone)and livestock movement(Mongolia);measure the seasonal availability of water

166、(Cambodia);mapping watersheds(India);and non-data applications like phytosanitary treatments(Morocco)and pest control spraying(Ethiopia,India)Environment&Natural ResourcesAid in managing forests and protected areas(Argentina,Cambodia,Chad,Lao Peoples Democratic Republic,Senegal,Tajikistan),coastal z

167、ones(Guinea-Bissau,Vietnam),fisheries(Liberia,Tonga),and monitoring wildlife(Burkina Faso,Chad)Health,Nutrition&PopulationStrengthen diagnostic networks and improve the emergency preparedness and resilience of fragile medical goods supply chains(Chad,India,Malawi,Maldives,Peru,Timor-Leste,Zambia)Tra

168、nsportSupport mapping and data collection efforts to assist with the planning,design,and monitoring of infrastructure development programs(Congo,Serbia,PNG);and provision of technical assistance on regulation and airspace management(Grenada,Haiti,Saint Lucia,Malawi,Tanzania)Urban,Disaster Risk,Resil

169、ience&LandAssist with integrated planning and land tenure management(Indonesia,Liberia,Philippines,Tanzania);disaster risk reduction(Bhutan,Mali,Mozambique,Nepal,Saint Lucia,Sri Lanka);and project monitoring(Bangladesh,Pakistan,Sierra Leone,Tanzania)Digital DevelopmentHelp build digital infrastructu

170、re(Benin,Congo,Nepal,Sierra Leone)and support climate resilience(Maldives)The Convention on International Civil Aviation(Chicago Convention)established core principles underpinning international air transport and created the International Civil Aviation Organization(ICAO)as a specialized agency of t

171、he United Nations.The role of ICAO is to help“States achieve the highest degree of uniformity in civil aviation regulations,standards,procedures,and organization”(ICAO,n.d.).Aviation has evolved significantly since the ratification of the Chicago Convention on April 4,1947,with the Annexes to the co

172、nvention now comprising more than 12,000 internationally agreed standards and recommended practices(SARPs).Each SARP defines necessary or recommended technical standards and requirements to“ensure the safety,regularity or 3031Mobility and Development Periodical|Fall 2024 EditionMobility and Developm

173、ent Periodical|Fall 2024 Editionefficiency of international air navigation”(ICAO,2007).These apply to larger uncrewed and remotely piloted aircraft(RPAs)in international,ICAO-classified airspace and at controlled aerodromes.However,aside from minor efforts such as the ICAO Model UAS Regulations and

174、associated advisory circulars(ICAO,2020),which have seen limited adoption,ICAO governance does not extend to smaller drones,uncrewed aircraft carrying persons,and those operating with high levels of automation or outside controlled airspace.The impetus for harmonization of drone regulationsIn the ab

175、sence of ICAO SARPs covering smaller UAS,regulatory development for drones has occurred in relative isolation with limited guidance.This has resulted in a largely disharmonized patchwork of regulatory approaches and frameworks across the globe with some aligning with the FAA,CASA,EASA or other frame

176、works.Presently,drone regulations across many countries are nonexistent,overly complex,prescriptive or restrictive,or function per exception.Of the 193 UN members,106 are known to have UAS regulations,48 have no regulations,rules,or guidance,while no information is available for about 23 countries(G

177、DRD,2024;Figure 1).Europe remains the only region with a harmonized regulatory UAS framework adopted by all of its Member States and several nonmembers.Figure 1.Status of regulatory frameworks for small UASSource:GDRD(2024).The resulting lack of harmonization hampers the nascent drone industry.Opera

178、tors must follow differing technical requirements,rules,and processes,providing a significant barrier to realizing value where it is needed.The“absence of clear and fit-for-purpose regulations or rules,timelines for permits,or long-term contracts to offset potential capital and pre-launch costs”(ADF

179、,2024-a)also contribute to uncertainty among operators.Research in Europe has further shown that lack of harmonization will lead to safety deterioration caused by drones operating without any clear and common regulatory or legal framework(ADF,2024-b).“African countries are faced with the challenge o

180、f providing oversight of these rapidly evolving technologies in a way that supports the benefit they can provide,while mitigating the risks they can pose.To meet their responsibilities,Civil Aviation Authorities are being asked to move beyond legacy regulatory approaches and develop new paradigms fo

181、r drone regulation.While safety must always come first,the new opportunities created by advanced drone operations to save lives,improve well-being,and reduce risk in areas such as inspections and security operations must also be considered”(EAC-CASSOA,2020).Regulatory harmonization can lead to more

182、cohesive and interoperable frameworks that ensure safety and reduce administrative overhead for involved stakeholders while enabling innovation across industries and sectors.Both harmonization and global interoperability are paramount to enabling the provision of seamless services.Effective safety g

183、overnance depends on“a coherent,interoperable approach requiring collaboration within and across aviation industry segments,more sharing of best practices and data,more working together on safety issues,and closer integration of safety management and business management”(ACARE,2017).These opportunit

184、ies extend to technical development,operating procedures,and common infrastructures such as shared UAS Traffic Management(UTM),platform registration and pilot licensing systems.Such streamlined,transparent,and enforceable processes stemming from harmonized and fit-for-purpose regulatory frameworks p

185、rovide several tangible benefits,including:Increased trust:Transparent and enforceable approval processes can help increase accountability and trust among involved stakeholders(Pisa,et al.,2020).Clarity and transparency help operators with planning,while the added accountability can help inspire tru

186、st from local communities and the general public.The resulting credibility can further encourage market growth and development by attracting investments.Improved operational efficiency:Regulators find risk evaluation and approval of drone operations demanding even in the most advanced countries.In l

187、ower-income countries,they face resource challenges and technical capacity constraints.Harmonized processes supported by knowledge exchange and collaboration can foster mutual capacity building.Assessments and evaluations can be streamlined and administrative overhead reduced.Timely approval of oper

188、ations will benefit drone operators and help unlock use cases.Enhanced operating capacity:Training and education among operators are quintessential enablers of safe and efficient aviation(ICAO,2016-b).Requirements for drone pilots and operators are not standardized as in conventional aviation.Harmon

189、ization would allow training organizations to design standard curriculums,courses,and ongoing training could be common across regions.3233Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 Edition Cross-border movement:Many operators will look beyond n

190、ational opportunities to operate in multiple countries.Mutual recognition of registration,certification,and approvals will unlock international use cases.It will also facilitate the cross-border movement of trained personnel,addressing two critical challenges:finding talent with the right experience

191、 and connecting that talent with opportunities(ADF,2024-a).Although there are clear and tangible benefits to harmonization,the question of prioritization and what guidance to follow remains.What are the main elements and options policy makers should prioritize?Where should regulatorspotentially unfa

192、miliar with the unique implications of dronesturn for guidance?And which existing regulatory frameworks should they align with?The goal and design of regulationsAny proposed regulatory framework for UAS should prioritize safety,while establishing transparent and efficient processes that do not compr

193、omise safety,security,or country-specific needs and requirements.Considering the inherent complexities of(international)aviation,most regulatory frameworks include a combination of“hard”regulations and“soft”advisory documents that allow them to be responsive to innovation.The regulatory framework fo

194、r drone legislation Drone legislation tends to be governed by a two-tiered hard law and soft law legal system.Hard Law consists of binding rules and regulations that have the force of law.They are established through formal legislative processes and normally include:Basic Regulation or Primary Civil

195、 Aviation Act:This act,passed by parliament,sets up the Civil Aviation Authority(CAA)and outlines its core functions and powers.It also grants the CAA the authority to create additional regulations.Civil Aviation Regulations:These are specific rules issued by the CAA under the authority of the prima

196、ry act.They cover areas like airspace use,safety standards,and aircraft maintenance requirements.Soft Law contains non-binding instruments that provide guidance and recommendations.They can influence behavior but cannot be directly enforced through courts.They usually consist of:Advisory Documents:T

197、hese documents offer practical guidance on complying with hard law regulations.They may explain the reasoning behind specific rules,provide best practice examples,or outline steps for achieving compliance.Guidance Text:Similar to advisory documents,these materials offer best practices and recommenda

198、tions.They can take various forms,including public education materials,manuals,or drone rule explanations.Waivers:These are permissions granted by the CAA to deviate from specific hard law requirements.Waivers are issued after a review process to ensure the proposed operation maintains safety while

199、accommodating technological advancements or specific situations.In essence,hard law establishes the core principles and minimum requirements,while soft law provides additional details,best practices,and flexibility in applying the hard law.Regulatory frameworks for UAS need to account for the unique

200、 capabilities that make them so valuable.For instance,most UAS do not require runways or extensive infrastructure.But they require additional considerations that fall outside the purview of conventional aviation:Most users are relatively new to aviation and unfamiliar with airmanship,airspace rules,

201、and other conventions and tenets of conventional aviation.Rapid technological development makes conventional type certification prohibitively expensive,raising ground risk concerns.The use of camera equipment for data collection and low-level operations raises concerns regarding privacy,data protect

202、ion,and noise pollution(EASA,2019).The disposal of LiPo batteries in electric propulsion drones throughout the project lifecycle raises environmental protection concerns.Threats from the unlawful use of drones(WEF,2018).“The civil aviation authority is responsible for,inter alia,ensuring aviation sa

203、fety and protecting the public from aviation hazards.Operators of aircraft,whether manned or unmanned,are likewise responsible for operating safely.The rapid rise of UAS raises new challenges that were not considered in historic aviation regulatory frameworks.Before devising any regulatory framework

204、 for UAS operations,the regulator should understand and assess the UAS situation in his or her State”(ICAO,2016-b).Each member state owns the UAS regulatory process.As there are no ICAO SARPs to adopt,they have the prerogative to develop their own rules and regulations,adopt best practices,and align

205、 with tried and tested regulatory frameworks depending on their capability,need,and demand.While regulations and their stipulations vary widely,nearly all frameworks address several elements,including the following:Categorizations:Provide structure to the overall regulatory approach.Most advanced re

206、gulations today are categorized by operational risk with different stipulations and requirements for low,medium,and high flight complexity operations(risk-based)based on different operational aspects(Table 1).Registration:Requirements for operators,pilots,and their equipment to determine who owns an

207、d can legally operate what within a country and ease the enforcement of regulations.Licensing and certification:Requirements as minimum levels of assurance for pilots quality and training to ensure safety for higher complexity categories of UAS operations.Operational restrictions:To ensure operation

208、s take place within relatively safe parameters from maximum altitudes and minimum distances to airports and restricted airspace for air traffic management to mitigate ground risk.Reporting:Mechanisms and requirements for incidents and accidents for investigative purposes.3435Mobility and Development

209、 Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionTable 1.Sample categorization of UAS flight complexities based on common operational parameters under the EASA frameworkOpen(Low Risk)Specific(Increased risk)Certified(High risk)Allowed Operations 25kg and 25kg and 120

210、m AGLControlled airspace and U-SpaceVisual Line of SightBVLOSNo flights over assemblies of peopleAbove people(VLOS)or away from people(BVLOS)Over assemblies of peopleNo dangerous goodsTransport of dangerous goods in a crash proof containerTransport of people or dangerous goodsRequirementsWithout aut

211、hority involvement Authorization based on operational risk assessment or scenarioAuthorizationFamiliarity with the user manual and basic remote pilot competencyRemote Pilot licenseLicensed crew&certified UAS(similar to manned aviation)Source:EASA(2024,Apr).Global trends for harmonization:EASA and IC

212、AO The European Unions UAS regulatory approach is the most notable and successful example of regional harmonization.While the ICAO Model UAS Regulations,published in 2020,have not been widely adopted,future amendments with additional guidance on Beyond Visual Line of Sight(BVLOS),insurance,and other

213、 aspects may see increased uptake.Both follow a risk-based categorization approach that considers the expected operational complexity to govern requirements and operational limitations.Unlike the ICAO(2020)regulations,the European Union Aviation Safety Agency(EASA,2024,Apr)framework provides a more

214、nuanced categorization approach and provisions for BVLOS.It also follows the Joint Authorities for Rulemaking in Unmanned Systems(JARUS)recommended requirements by using the Specific Operations Risk Assessment(SORA)to evaluate the air and ground risk of proposed UAS operations.EASA also provides a h

215、igh-level regulatory framework for UTM,called U-Space in Europe,to address airspace integration and air traffic management.Ongoing efforts focus on electronic conspicuity,certified operations,standard scenarios that address flight in urban environments,environmental protection regulations which incl

216、ude noise specifications,future needs to support Urban Air Mobility,and relevant aerodrome or vertiport design.The EASA framework:This is the only regionally harmonized UAS framework globally adopted by the 27 EASA member states and several states outside the EU.The European RPAS Steering Committee

217、established in 2012 developed an initial integration roadmap followed by a risk-based concept of operations for drones.The European Air Traffic Management(ATM)Master Plan Drone roadmap issued by the Single European Sky ATM Research(SESAR)program culminated in a European Commission(EC)mandate for EAS

218、A to develop a common EU regulation in 2015.In 2019,the EC adopted the outcomes in the form of Delegated and Implementing Acts,Regulations(EU)2019/945 and(EU)2019/947).They moved to mandate registration and required member states to fully convert national authorizations,certificates,and declarations

219、 to the new system and adopt the regulations by 2021.Following a highly consultative multiyear rulemaking process has ensured that the resulting regulations deliver the full and intended benefits of mitigating risks with minimum drawbacks(EASA,2022).The ICAO Model UAS Regulations:These regulations o

220、ffer guidance text for a basic regulatory framework for drones,with a focus on harmonization that can be adopted in part or entirely.Despite its release in 2020 and broad promotion,uptake remains limited.Rwanda has adopted much of it and added Annexes on BVLOS and Security.Nepal has adopted lowest r

221、isk sections into soft law and has chosen to follow a separate operational categorization approach.Although the framework covers noncertified drones operating in the lower airspace,it neither fully addresses higher-complexity BVLOS operations nor guides ground risk management.The Advanced Air Mobili

222、ty Study group(AAM-SG),founded in 2023,has a working group with a mandate to produce a global summary of UAS regulations as a potential basis for revised model regulations.Unfortunately,the AAM-SG has yet to release a timeline for this effort.Additional considerations of drone operationsDespite best

223、 intentions,acute demand,and a well-defined governance framework,the inherent complexity of aviation operations can pose significant challenges to UAS operations being sustainable and functioning at scale.Although policy makers may address harmonization of UAS regulations,others require changes to a

224、ncillary regulatory frameworks(see Table 2).These may govern customs procedures,telecommunications,and more.In contrast,others require investments beyond mere regulatory changes.These have the potential for broader community improvements,including investments in more reliable power grids or widening

225、 network connectivity to rural and remote communities.3637Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionTable 2.Regulatory challenges and opportunitiesAreaChallengeOpportunitiesTransparency&community engagementA lack of transparency or poor

226、 community and stakeholder engagement can exacerbate drone technology concerns.This leads to a lack of trust,buy-in,and service uptake.Insufficient two-way communication channels may lead to resistance,delays,or cancellation of UAS operations.Limited technological literacy of community members is a

227、particular challenge in rural and remote communities.Regulatory bodies may develop policies and guidelines establishing principles and best practices for stakeholder engagement,incident reporting,and broader information sharing.Educational information that informs the public about regulations,techno

228、logies,and policies must be made broadly available.Further opportunities to enhance transparency and trust include demonstrating the use and benefits of technologies;providing mechanisms for incident reporting and investigating;and publishing findings and lessons learned.Community input to regulator

229、y matters and infrastructure design can ensure policies and regulations address their concerns.CapacityCapacity,resources,and specialist expertise to develop regulations and evaluate safety and risk work for UAS are seldom available.The disharmonized nature of technical and training requirements als

230、o leads to a need for more qualified remote pilots and support staff.Compared to conventional aviation,the specialist nature of UAS operations will require additional resources and bring an upsurge in costs.Scaling UAS operations from individual flight requests will only exacerbate resource constrai

231、nts further and likely lead to lengthy delays in obtaining operational approval.The mutual recognition of training certificates and qualifications,development of interoperable registries,and standardizing requirements and processes can help harmonize requirements and reduce burdens on regulators and

232、 operations.Regulations may further address the cross-border movement of service providers to make it easier for foreign operators to register drones and commence UAS operations.Trained pilots too can find employment and address local capacity constraints.Establishing internationally accredited orga

233、nizations to train pilots and operators can further help reduce capacity bottlenecks.Regulations can also support the development of local innovation capacity by enabling test and training regions and the legal flying of prototypes.AreaChallengeOpportunitiesClimate and weatherClimate and weather may

234、 significantly impact the safety and reliability of UAS operations.Small UAS,in particular,are more susceptible to hazardous meteorological conditions.Operating at night,in poor weather or visibility,or outside flight parameters increases flight complexity and risk,potentially leading to harm or dam

235、age.Operation-centric and risk-based regulations and approval processes can foster an array of use cases across environmental and meteorological conditions.A flexible operational risk assessment methodology is the basis for such regulations and processes.Regulations commonly restrict or prohibit fli

236、ghts under certain conditions,i.e.,flying in low visibility or at night.Bans should be based on solid safety and security data with an ideology to safely enable beneficial operations.TechnologyTechnological maturity and the absence of universal agreements on acceptable airworthiness standards may li

237、mit the scale of UAS operations and overall safety.UAS platforms may face environmental resilience,range,reliability,or safety limitations.Improvements in alternative propulsion performance(battery,hydrogen-powered)are required to increase range,payload,and environmental sustainability.Software syst

238、ems and avionics and the absence of UTM systems may limit the scaling-up of multi-drone operations and the use of fleets.The absence of airworthiness standards,technical requirements,and testing opportunities affects manufacturers likelihood of establishing long-term safety track records.Considering

239、 the rapidly evolving technological capabilities of UAS platforms,risk or performance-based regulations may facilitate operational approvals without proven track records of efficiency and reliability.Mandating Detect and Avoid capabilities,arrestor systems(such as parachutes)and UTM provide opportun

240、ities to increase the safety of operations.Regulations may stimulate further development of these and other technologies,such as electronic conspicuity and identification,counter-drone systems,flight software capable of supporting multi-drone operations,and high levels of automation.3839Mobility and

241、 Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionAreaChallengeOpportunitiesInfrastructure&operationsChallenges to setting up and scaling UAS operations include unreliable power supply;insufficient land to install droneports;and lack of accurate,recent map

242、ping data to assess population density,infrastructure and hazards.Requirements for ground infrastructure range from a small,cleared area to a fully certified landing site or aerodrome with suitable approach and departure zones.Connectivity to support drone operations in remote settings may be sporad

243、ic or missing.Similarly,UTM service provision integral to scaling UAS operations relies on interfacing or integrating with existing Air Traffic Management(ATM)systems(ADF,2024-b).Addressing infrastructure and operations bottlenecks extends to ancillary sectors,from telecommunications to electricity

244、and land management.In addition to regulatory change and harmonization,investments in backhaul,power grids,and other infrastructure may be necessary.This will lead to improved quality of living in impacted areas beyond enabling UAS operations.Although potentially complex to implement,UTM service pro

245、vision represents a crucial enabler to long-term UAS operations at scale.LogisticsThe transport of UAS platforms,components,batteries,or ancillary equipment may be affected by export or transport restrictions,high importation taxes,mandatory inspections and declarations.These challenges often lead t

246、o further delays and expenses or outright cancellations of operations.A stable supply of replacement components,batteries,and equipment will be necessary to avoid costly service interruptions once a program is ongoing.Clear import and exportation rules and mutual recognition of authorizations and ce

247、rtifications across different countries can reduce operator uncertainties and support better planning.Manufacturers must comply with different technical requirements imposed in different,often adjacent countries,leaving the market fragmented and pushing up the cost for each UAS operation.Further tec

248、hnological developments may address issues with battery transportation as differing technologies are subject to varying dangerous goods classifications.AreaChallengeOpportunitiesSafetyUAS operations require considerations over ground risk,damage to infrastructure or people,and the risk to other airs

249、pace users.As the flight complexity increases,so does the associated risk.Many mapping and surveillance operations pose little risk and require little training as long as safety-related procedures are adhered to.Higher-risk cargo operations require trained remote pilots and risk assessments and miti

250、gations commensurate with the operations.Categorizing drone flights based on complexity opens up more opportunities.Risk assessment becomes clear and transparent,which allows the identification of low-risk scenarios where individual flight authorization becomes unnecessary,streamlining the process f

251、or everyone.However,without suitable international standards,moving toward full airspace integration and certification(see Table 1)is prohibitively expensive.Privacy&data protectionUnderdeveloped and disparate data protection laws and policies may hamper the socially beneficial development of UAS-en

252、abled services.There are many differences in structure and approaches to implementation globally,as many countries still need to have rulesets covering privacy and data protection(ADRH,2019).Some countries may limit the use of certain sensors to specific operational scenarios or impose privacy-by-de

253、sign requirements for camera or sensor equipment or platforms themselves,posing potential challenges for operators working across regions.Responsible digitization can be supported by comprehensive,transparent,uniform data protection;privacy regulations centered around a responsible-use mentality;and

254、 preventing the misuse of personal information alongside privacy-by-design standards.UAS regulations can address personal data protection concerns and complement a broader overarching regulatory framework on data protection.These can include requirements to conduct data protection risk assessments,l

255、imiting flights over private property,or requirements to obtain consent.Source:World Bank.4041Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionA roadmap toward regulatory change and harmonization Although UAS regulatory development is conventi

256、onally an isolated process,regulatory harmonization is inherently collaborative and is led by a countrys CAA,usually in accord with the government ministry for aviation.In many cases,it would prove valuable to invite observers from ICAO and its relevant regional offices,regional civil aviation organ

257、izations such as AFCAF,PASO,or LACAC,or organizations such as the World Bank Group,UNICEF,or World Food Programme that have previously supported rulemaking efforts.Successful harmonization efforts tend to follow a multistep approach(Lindstrm-Gommers,Theresa,2019;Heinrich,Mey,2019).Step 1:Establishin

258、g different steering group levels,as regulatory harmonization is an inherently collaborative process.National-level steering groups should coordinate any harmonization process to ensure national alignment and representation of national priorities,needs,and requirements,and region-wide steering group

259、s should coordinate efforts and represent affected stakeholders.Step 2:Building consensus to determine the most suited regulatory style,conditions,limitations,exemptions,operational classification,ancillary regulations,and dissemination approach.Step 3:Develop draft guidelines that are fit for purpo

260、se and reflect the regional environment and resource settings.Although East Africa must design its own future harmonized regulations,there are ample opportunities to learn from progressive regulators such as Europe.Step 4:Consultation and discussion with all stakeholders involved in regulatory polic

261、ymaking and those required to comply with new standards and regulations are crucial.This will ensure regulations are fit for purpose and encourage investment in the market.Opinions can assist in refining draft proposals and developing guidance material associated with the rules.Step 5:Adoption and i

262、mplementation of harmonized regulations represent the final step.They could follow a phased adoption approach similar to ICAOs(2016-a)Aviation System Block Upgrades(ASBU)concept in the Global Air Navigation Plan(GANP).Regulators should focus on creating regulations for key use cases first.This will

263、generate enough operations and interest in UTM systems to pave the way for broader adoption.Regulations should also consider removing barriers to private investment,which is essential to create a critical mass of operations.Conclusion The adaptability and capabilities of small drones render them a v

264、aluable instrument for strengthening digitization initiatives and enhancing the efficiency and resilience of supply chains.Realizing the full potential of these benefits in an effective,secure,and scalable manner necessitates the implementation of innovative policy and regulatory adjustments.This mu

265、st foster cross-sectoral and cross-governmental collaboration.However,the challenges of coordination and collaboration loom large,particularly in a domain where clear leadership often remains elusive.The tendency to isolate(regulatory)operations is also a major hurdle.When capacity building and impl

266、ementation occur independently with limited communication or overlap,rulemaking efforts may duplicate or receive inconsistent advice,resulting in diminished outcomes and inefficient use of limited resources.There is a significant opportunity to engage in harmonization efforts through relevant specia

267、lized agencies such as regional aviation authorities,development partners such as the World Bank,or a suitable collaborative platform such as JARUS.Ultimately,the objective should be to improve coordination at national and regional levels to safely unlock the lower skies and effectively translate it

268、s potential into reality.4243Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionReferencesACARE(Advisory Council for Aviation Research and Innovation in Europe).2017.Strategic Research&Innovation Agenda.2017 Update(Volume 1).Brussels:ACARE.ADRH(

269、Africa Digital Rights Hub).2019.Data Protection Code of Practice for Digital Identity Schemes in Africa.Accra:ADRH.ADF(African Drone Forum).2024-a.Playbook for Enabling Civilian Drone Operations.Washington D.C.:World Bank.2024-b.Review of Drone Regulations.Washington D.C.:World Bank unpublished.EAC-

270、CASSOA(East African Community Civil Aviation Safety and Security Oversight Agency).2020.Emerging safety&security issues:common approach to operationalize drones in Africa(Agenda Item 5).EAC OSG(Office of the Secretary General)(2020)Request letter.Letter sent to the World Bank Group.EASA(European Avi

271、ation Safety Agency).2019.Acceptable Means of Compliance(AMC)and Guidance Material(GM)to Commission Implementing Regulation(EU)2019/947(Issue 1).Annex I to ED Decision 2019/021/R.Cologne:EASA.2022.Management Board Decision Management Board Decision N01-2022 of 2 May 2022;RMT-0230.Cologne:EASA.2024,A

272、pr.Easy Access Rules for Unmanned Aircraft Systems(Regulations(EU)2019/947 and 2019/945).Cologne:EASA.GDRD(Global Drone Regulations Database).2024.Global Drone Regulations Database.https:/droneregulations.info/Heinrich,O.,Mey,J.H.(2019).EU Harmonization Moves ForwardWhats Changed?What Are the Implic

273、ations?https:/ Civil Aviation Organization).2007.Assembly Resolution in Force(as of 28 September 2007)Doc 9902.Montreal:ICAO.2016-a.The Aviation System Block Upgrades:The Framework for Global Harmonization.Montreal:ICAO.2016-b.The ICAO UAS Toolkit.Helpful tools to assist States in realizing effectiv

274、e UAS operational guidance and safe domestic operations.ICAO:Montreal.2020.ICAO Model UAS Regulations.Montreal:ICAO https:/www.icao.int/safety/UA/Pages/ICAO-Model-UAS-Regulations.aspx.n.d.The History of ICAO and the Chicago Convention.https:/www.icao.int/about-icao/history/pages/default.aspxLindstrm

275、-Gommers,L.,Theresa,M.2019.International Conference on Harmonization:Recent Reforms as a Driver of Global Regulatory Harmonization and Innovation in Medical Products.Clinical Pharmacology&Therapeutics,105(4).Stokenberga,A.,Ochoa,C.(2021).Unlocking the lower skies:The Costs and Benefits of Deploying

276、Drones across Use Cases in East Africa.Washington:World Bank.WEF(World Economic Forum).2018.Advanced Drone Ops toolkit:Accelerating the Drone Revolution.Geneva:WEF.World Bank.2020.Country Partnership Framework:For the Republic of Rwanda FY 21-FY26(Report No.148876-RW).Washington,D.C.:World Bank Grou

277、p.4445Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 Edition3Off the Books:Understanding and Mitigating the Fiscal Risks of the Transport SectorMatas Herrera Dappe Vivien Foster Aldo Musacchio Teresa Ter-Minassian Burak TurkguluAbout the AuthorsAld

278、o Musacchio is Director of the Master of Business Administration(MBA)program at Brandeis University,as well as a Professor of Management and Economics at the Brandeis International Business School and a faculty research associate at the National Bureau of Economic Research.Previously,he was an assoc

279、iate professor and Marvin Bower Fellow at the Harvard Business School.He holds a PhD in the economic history of Latin America from Stanford University.Together with Sergio G.Lazzarini,he has written Reinventing State Capitalism:Leviathan in Business,Brazil and Beyond(Harvard University Press,2014).A

280、ldo MusacchioDirector,MBA Program,Brandeis UniversityMatas Herrera Dappe is a Senior Economist and the Global Lead on Transport Economics and Policy at the World Bank,where he leads policy research programs on infrastructure with a focus on transport.He has published extensively on a wide range of t

281、opics including transport economics,economic development,trade,public-private partnerships,state-owned enterprises,and fiscal policy.Matas Herrera DappeSenior Economist and Global Lead on Transport Economics and Policy,World BankVivien Foster is a Principal Research Fellow at the Centre for Environm

282、ental Policy at Imperial College London and International Partnerships Director for Climate Compatible Growth,as well as a Senior Research Associate at ODI,the UKs premier development think tank.She holds a PhD in economics from University College London.Previously she was chief economist for the In

283、frastructure Vice-Presidency of the World Bank.Over the past 20 years,she has advised the governments of more than 30 developing countries on a wide range of infrastructure policy challenges.Vivien FosterPrincipal Research Fellow,Centre for Environmental Policy,Imperial College London4647Mobility an

284、d Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionAt a GlanceThis article,based on Off the Books:Understanding and Mitigating the Fiscal Risks of Infrastructure(2023),presents a systematic assessment of the magnitude and prevalence of fiscal risks from tr

285、ansport and their root causes,across a range of developing countries.Drawing on important new sources of evidence,it shows just how much is at stake in the good governance of the transport sector,how fiscal risks vary across contexts,and how they can be mitigated to create sustainable fiscal space f

286、or transport investments.The article answers these key questions:What are the fiscal risks from the transport sector and why are they important?How important are the fiscal risks from direct public provision of transport?How important are the fiscal risks from state-owned enterprises and public-priv

287、ate partnerships in the transport sector?And how can the fiscal risks of the transport sector be mitigated?What are the fiscal risks from the transport sector and why are they important?Developing countries face both significant infrastructure needs and increasing pressure on the funds available for

288、 infrastructure.Estimates put the annual transport infrastructure investment needed in the developing world to deliver on the Sustainable Development Goals and the Paris Climate Agreement at 1.3 to 3.3 percent of GDP through 2030(Rozenberg and Fay 2019).The triple challenge of heavy debt burdens,the

289、 global tightening of financial conditions,and declining economic growth rates in developing countries puts pressure on their transport sector budgets.Under these conditions,it is imperative that these countries create a sustainable fiscal space for infrastructure.Numerous governance challenges unde

290、rmine the efficiency of spending on infrastructure and absorb scarce fiscal space.Whether governments spend directly on budget,spend at arms length through state-owned enterprises(SOEs),or delegate spending via public-private partnerships(PPPs),the risk of fiscal surprises is high.Because of these r

291、isks,infrastructure service delivery may end up costing significantly more than initially expected.If policy makers are to make reforms that have the greatest impact,they must understand the potential fiscal risks of different provision modalities,how the magnitude and frequency of those risks varie

292、s across modalities,what their root causes are,and how they can be mitigated.Fiscal risks from transport infrastructure manifest themselves in different ways,depending on how infrastructure is provided(Figure 1).Figure 1.Fiscal risks associated with the provision of transport infrastructure and thei

293、r sourcesCommon sourcesof riskModality-specific sources of riskFiscal risksDirect public provisionFlaws in public investment managementCost overrun riskAsset impairment riskSOE guarantees/insurance schemesCashflow riskBailout riskDirect liabilitiesGuaranteesRenegotiation riskEarly termination riskFl

294、aws in fiscaland corporate governanceState-owned enterprisesFlaws in PPP governancePublic-private partnershipsInfrastructure specific factorsEconomic factorsNatural disastersSource:Herrera Dappe and others,2023.Burak TurkguluBurak Turkgulu is an extended-term consultant working as a data specialist

295、in the Subnational Business Ready team of the Development Economics Vice Presidencys Global Indicators Group.Previously,as a consultant in the Infrastructure Vice Presidency at the World Bank,he contributed to various empirical research projects in infrastructure economics and finance,including the

296、creation of the World Bank Infrastructure SOEs Database.His other work focuses on institutional economics,human capital valuation,growth and development,and political and economic history of Trkiye.He holds an MA in economics from the University of Maryland,College Park.Data Specialist,Subnational B

297、usiness Ready Team,Global Indicators Group,World BankTeresa Ter-Minassian is an international economic consultant and the former director of the Fiscal Affairs Department of the International Monetary Fund(IMF).At the IMF,she led missions to several countries,including Greece,Italy,and Spain,and pro

298、gram negotiations with Argentina,Brazil,and Portugal.She currently works on fiscal issues,particularly in Latin America.She has published more than 40 papers and books on fiscal issues,especially on macro-fiscal and intergovernmental fiscal relations.She holds a law degree from the University of Rom

299、e and an MA in economics from Harvard University.Teresa Ter-MinassianSenior Economic Consultant and former Director,Fiscal Affairs Department,International Monetary Fund 4849Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionDirect public provis

300、ion of transport infrastructure can lead to fiscal surprises through unanticipated spending caused by cost overruns or the need to repair deteriorated assets because of neglect or natural disasters,including extreme weather events.Transport SOEs can create substantial risks for public finances.These

301、 risks arise from explicit guarantees and public insurance schemes as well as cashflow and bailout risk.Cashflow risk stems from the volatility of the SOEs net income,which requires fiscal transfers to cover occasional and modest losses associated with exogenous shocks and inefficiencies related to

302、soft budget constraints.Bailout risk refers to the risk associated with having to recapitalize an SOE,help it avoid default or bankruptcy,or cancel a large SOEs liabilities because it has insufficient capital buffers to deal with large,unexpected shocks and the continuous write-off of losses.PPPs en

303、tail fiscal commitments of a different nature,which can lead to fiscal surprises.Liabilities such as upfront capital subsidies and availability payments arise even if the PPP proceeds according to plan.These direct liabilities can lead to fiscal surprises if they are kept off the balance sheet and o

304、ff the budget.PPPs also create contingent liabilities.Explicit contingent liabilities arise from contractual guarantees provided by the government to ensure the commercial feasibility and bankability of PPPs(for example,minimum revenue or demand guarantees,foreign exchange rate guarantees,and debt g

305、uarantees).Implicit contingent liabilities result from the risks of contract renegotiation and early termination.PPP contracts cannot account for all contingencies.As a result,the government and the concessionaires usually renegotiate PPP contracts over their lifetimes.Renegotiations usually lead to

306、 unexpected fiscal costs,such as larger government contributions,lower payments to the government,and longer contracts.When renegotiations fail,PPPs are terminated early.The transport sector tends to rely more heavily on budget spending than on SOEs and PPPs.For the 15 countries for which investment

307、 figures for all three modalities in the transport sector were available for 2009-18,the average direct public provision represented 82 percent,SOEs 11 percent,and PPPs 7 percent of total capital spending(Figure 2,Panel a).The contribution of transport SOEs rises to 28 percent of spending once capit

308、al and operating expenditures are considered(Figure 2,Panel b).Figure 2.Average share of capital and total spending in the transport sector,by modality,200918Percent of capital expenditurea.Capital expenditureb.Total expenditureShare of total expenditure1009080706050403020100200920102011201220132014

309、201520162017201810090807060504030201002009201020112012201320142015201620172018Direct provision State-owned enterprises Public-private partnershipsSource:Original figure for this publication based on data from the BOOST,World Bank Infrastructure SOEs,and PPI databases.Note:Capital expenditures in PPP

310、s were distributed over a five-year period beginning in the investment year indicated in the PPI Database.Expenditures through direct public provision are for the general government.Countries include Albania,Argentina,Bhutan,Bulgaria,Burundi,Ethiopia,Georgia,Indonesia,Kenya,Kosovo,Peru,Romania,the S

311、olomon Islands,South Africa,and Ukraine.PPP=Public-Private Partnership.5051Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionHow important are the fiscal risks from direct public provision of transport?On-budget public investment on transport h

312、as been low and mostly declining in recent years.According to the World Banks BOOST Database,average on-budget spending fell from 1.4 percent of GDP in 2012 to about 1.0 percent of GDP in 2019 and 2020(Figure 3).Lower-middle-income countries tend to devote slightly larger budgetary shares to public

313、investment in transport than upper-middle-income countries.The overall decline in public spending on transport contrasts with relatively stable trends for aggregate public expenditure over the same period,indicating a lower priority for transport.Figure 3.Government budgetary capital expenditure on

314、transport in low-and middle-income countries as percent of GDP,201020Percent of GDP201000.51.01.52.02.52011201220132014201520162017201820192020TotalUpper-middle incomeLower-middle incomeLower incomeSource:Herrera Dappe and others 2023.Note:Countries include Afghanistan,Albania,Angola,Armenia,Banglad

315、esh,Belarus,Benin,Bhutan,Bulgaria,Burkina Faso,Burundi,Cameroon,Cape Verde,Costa Rica,the Dominican Republic,Ecuador,El Salvador,Equatorial Guinea,Ethiopia,Fiji,Gabon,The Gambia,Georgia,Guatemala,Guinea,Guinea Bissau,Haiti,Indonesia,Jamaica,Jordan,Kenya,Kiribati,Kosovo,the Kyrgyz Republic,Lebanon,Le

316、sotho,Liberia,Macedonia,Malawi,Mali,Mauritania,Mauritius,Mexico,Moldova,Mongolia,Mozambique,Namibia,Niger,Papua New Guinea,Paraguay,Peru,Senegal,Sierra Leone,the Solomon Islands,South Africa,St.Lucia,Tajikistan,Tanzania,Togo,Tunisia,Uganda,and Ukraine.The near-term,and most direct,fiscal risk of dir

317、ect public provision is that the infrastructure project may cost the government more to deliver than anticipated during the construction phase.Under-execution of the capital budget may signify delays in project implementation,which usually translate into cost overruns.Under-execution of infrastructu

318、re investment budgets is a widespread problem.Foster,Rana,and Gorgulu(2022)found that more than 80 percent of the 65 developing countries they studied failed to fully spend their budgets in 2010-18.The average budget execution rate for public investments in roads across countries was 69 percent(63 p

319、ercent in low-income countries).Inefficiency in spending is another reason why infrastructure projects may end up costing more than originally projected.Using data envelopment analysis on a sample of 18 developing countries,Foster,Rana,and Gorgulu(2022)found a very slight increase in average product

320、ivity in the road sector between 2006 and 2018.However,10 of the 18 countries saw a decrease in the productivity of their road spending.In some countries,the change may have been driven by more stringent social and environmental requirements.However,more than half of the countries analyzed experienc

321、ed an increase in the inefficiency of road expenditure,delivered fewer kilometers of roads than countries with similar technology and level of spending,and even fewer kilometers of roads in 2018 than in 2006.The medium-term risk is that even after the initial investment phase of the project has been

322、 completed,the infrastructure might continue to make unplanned calls on the governments capital budget to sustain its capacity to deliver the intended stream of services.The extent of capital biasthat is,the preference for capital spending over maintenance spendingindicates the prevalence of this me

323、dium-term risk.Road spending is strongly skewed toward capital expenditure.In all but 4 of the 46 countries for which data is available,capital spending exceeded maintenance spending in 2006-18(Figure 4).Countries spent on average about seven times as much on investment as on maintenance.Countries w

324、ith road funds tended to spend more on maintenance than countries without road funds,but most still dedicated more resources to investment than maintenance.The findings suggest that asset impairment risk is high for most countries,leaving them susceptible to a build-neglect-rehabilitate cycle,which

325、costs governments more,and calls on fiscal resources at unexpected times when critical infrastructure fails.Figure 4.Capital bias in public expenditure on roads in selected countries,200618Maintenance expenditure as percent of GDPEthiopiaMozambiqueSierra LeoneTanzaniaLesothoNamibiaTogoKosovoEl Salva

326、dorTunisiaBhutan012345012345Capital expenditure as percent of GDPRoad fundsNo road fundsMoldovaGabonTajikistanBurkina FasoSource:Foster,Rana,and Gorgulu 2022.Note:Data points represent total spending divided by total GDP in 200618.5253Mobility and Development Periodical|Fall 2024 EditionMobility and

327、 Development Periodical|Fall 2024 EditionHow important are the fiscal risks from transport SOEs?On average,airline,airport,railway,and road SOEs performed poorly in the 19 countries covered by the World Bank Infrastructure SOEs Database in 200918,providing mostly negative rates of return on average

328、assets.The average return for airline and airport,railway,and road SOEs were 3.7 percent,3.5 percent,and 1.4 percent,respectively.These returns drop to 12.1 percent,16.1 percent,and 12.0 percent,respectively,once operations subsidies from the government are stripped out of the accounts,indicating th

329、at these SOEs require government support to operate1(Figure 5).Transport SOEs also frequently incur losses after adjusting for operations subsidies.In a given year,66-86 percent of railway and road SOEs and 33-57 percent of airline and airport SOEs lost money after netting out subsidies.Figure 5.Ret

330、urn on average assets of state-owned enterprises,with and without adjustment for operations subsidies,by sectorAirlines and airportsRailwaysRoads2.00.0-2.0-4.0-6.0-8.0-10.0-12.0-14.0-16.0Return on average assetsAdjusted return on average assetsSource:Herrera Dappe and others,2023.Note:Figures are av

331、erages over 200918.1 These returns compare poorly with the positive returns of power SOEs in the same countries(1.9 percent when operations subsidies are considered and 0.9 percent when they are removed)(See Herrera Dappe and others 2023).The underperformance of transport SOEs can be partly linked t

332、o their cost structure.Employment costs represented a very large share of revenues,averaging 188 percent for railway SOEs,90 percent for airline and airport SOEs,and 62 percent for road SOEs(Figure 6).Maintenance was the major cost item for road SOEs,accounting for 139 percent of revenues.Figure 6.E

333、mployment and maintenance costs of state-owned enterprises as a percentage of revenues,by sector.Percent of revenuesAirlines and airportsRailwaysRoads200050100150Employment costsMaintenance costs9018862720139Source:Herrera Dappe and others 2023.Note:Figures are averages over 200918.5455Mobility and Development Periodical|Fall 2024 EditionMobility and Development Periodical|Fall 2024 EditionThese h