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This paper exploits location choices of all generalist physicians graduated in Brazil between 2001 and 2013 to study policies aiming at increasing the supply of physicians in underserved areas. We set up and estimate a supply and demand model for physicians. We estimate physicians' locational preferences using a random coefficients discrete choice model. The demand has private establishments competing for physicians with private and public facilities around the country. Policy counterfactuals indicate that quotas in medical schools for students born in underserved areas and the opening of vacancies in medical schools in deprived areas are more cost-effective than financial incentives.

Abstract This article interprets emerging scholarship on rental housing platforms—particularly the most well-known and used short- and long-term rental housing platforms—and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators’ own financial and political interests. The question of which data—and people—are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations. Policy and practice recommendations As rental housing technologies upend traditional market processes in favor of platform oligopolies, policymakers must reorient these processes toward the public good. Long-term and short-term rental platforms offer different market benefits and drawbacks, but the latter in particular requires proactive regulation to mitigate harm. At a minimum, policymakers must require that short-term rental platforms provide the information necessary for cities to enforce current, let alone new, housing regulations. Practitioners should be cautious inferring market conditions from rental housing platform data, due to difficult-to-measure sampling biases.

We propose a regional inequality-based mechanism to explain the heterogeneity in the spread of Covid-19 and test it using data from India. We argue that an area characterized by core-periphery economic structure creates regional inequality in which the periphery remains dependent on the core for the supply of jobs, goods and services. Hence, areas arranged in core-periphery structure induce greater degree of mobility which in turn ends up at a higher infection rate than the more homogeneously developed areas at the time of pandemic. Using nightlights data to measure regional inequality in the degree of economic activity, we find evidence in support of our hypothesis. Further, we find that regions with higher nightlight inequality also experience higher spread of Covid-19 only when lockdown measures have been relaxed and movement of goods and services are near normal. Using mobility data, we provide direct evidence in support of our proposed mechanism; that the positive relationship between regional inequality and Covid-19 infection is driven by mobility. Our findings imply that policy responses to contain Covid-19 contagion needs to be heterogeneous across India where the priority areas can be chosen ex-ante based on inequality in economic activity.

• This study explores how regional-level interactions of livestock and crop sectors influence the capacity of a southern Africa sub-region to meet its future demand for livestock-derived foods. • It uses a spatial equilibrium modeling framework to simulate regional trade in poultry and maize products in Malawi, Mozambique, South Africa, and Zambia. • Model outputs on the demand, production, and trade of poultry products and maize are compared for a baseline and an alternative future scenario representing drought conditions. • The study’s abstraction of a regional approach to livestock and feed sector interactions in the selected region highlights the role of markets in addressing cross-boundary challenges related to food demand expansion and resource management. • Results imply that the study countries could benefit from addressing their growing demands for livestock-derived foods using a harmonized approach. Further, regional livestock markets may offer cushioning effects to the impacts of climate change in at least one of the countries. • However, improved quality data and an enhanced specification of the analytical model to better account for the nuances of livestock and feed trade in the region and for varied scenarios of future climate change will be needed, to extend the current study to practical policy application.

This paper exploits quasi-random variation in the share of Black students across cohorts within US schools to investigate whether childhood interracial contact impacts the residential choices of Whites when they are adults. We find that, 20 years after exposure, Whites who had more Black peers of the same gender in their grade go on to live in census tracts with more Black residents. Further investigation suggests that this result is unlikely to be driven by economic opportunities or social networks. Instead, the effect on residential choice appears to come from a change in preferences among Whites.

The creative industries have received much attention from economic geographers and others, both for their propensity to co-locate in urban settings and their potential to drive urban economic development. However, evidence on the latter is surprisingly sparse. In this paper we explore the long-term, causal impacts of the creative industries on surrounding urban economies. Adapting Moretti’s local multipliers framework, we build a new 20-year panel of UK cities, using fixed effects and a historic instrument to identify effects on non-creative firms and employment. We find that each creative job generates at least 1.9 non-tradable jobs between 1998 and 2018: this is associated with creative business services employees’ local spending, rather than visitors to urban amenities such as galleries and museums. We do not find the same effects for workplaces, and find no causal evidence for spillovers from creative activity to other tradable sectors, findings consistent with descriptive evidence on the increasing concentration of creative industries in a small number of cities. Given the small numbers of creative jobs in most cities, however, the overall effect size of the creative multiplier is small, and shapes only a small part of non-tradable urban employment change. Overall, our results suggest creative economy-led policies for cities can have positive – albeit partial – local economic impacts.

This paper proposes a new methodological framework to identify economic clusters over space and time. We employ a unique open source dataset of geolocated and archived business webpages and interrogate them using Natural Language Processing to build bottom-up classi- fications of economic activities. We validate our method on an iconic UK tech cluster – Shoreditch, East London. We benchmark our results against existing case studies and admin- istrative data, replicating the main features of the cluster and providing fresh insights. As well as overcoming limitations in conventional industrial classification, our method addresses some of the spatial and temporal limitations of the clustering literature.

Despite clear limitations, poverty research in the rich world overwhelmingly relies on income-based measures. Households may have significant savings and assets that they can draw on to boost their living standards, but may also have debts that depress the living standard they can actually achieve with their disposable income. Using data from the Eurosystem Household Finance and Consumption Survey (HFCS) this paper offers a picture of poverty in 17 EU countries that takes into account assets and debt, using various approaches. While earlier studies have found that poverty rates tend to be lower when wealth is accounted for, this study highlights the situation of those who become or remain poor even when savings and assets are included. It focusses both on within country patterns of joint income-wealth poverty as on cross-country differences. It is shown that the elderly are generally less prone to being poor once assets are accounted for. However, for renter households with a young, female, low educated, unemployed or inactive and single head, the risk of being poor when assets and debt are accounted for remains high and in some cases even increases. That is generally the case because they have few assets, rather than because of high debts. The substantial variation in poverty rates observed across countries can to some extent be accounted for by socio-demographic factors but a lot of variation still remains unaccounted for. (Stone Center on Socio-Economic Inequality Working Paper)

We study housing supply in markets where informal housing is common. Using a combination of census and satellite data, we estimate housing supply for more than 90 metropolitan areas in Brazil. We find that widespread informal housing increases the housing supply elasticity, partially offsetting the downward pressure of geographical constraints. Our empirical approach is guided by a monocentric city model that includes informal housing. Our identification strategy relies on the use of two novel instruments, combining demographic data and public land ownership. We use the supply elasticity estimates to forecast the response of future housing prices to natural population growth.

International audience; The phenomenon of global value chains (GVCs) indicates a division of labour type production structure in which tasks and business functions are distributed among several companies, globally, or regionally (Grossman and Rossi-Hansberg 2008). The critical features of GVCs are therefore the international dimension of the production process and the "contractualisation" of buyer and seller relationships, often across international borders (Antras 2016). As a result, these international production networks are highly complex regarding geography, technology, and the different types of firms involved (from large retailers and highly large-scale mechanised manufacturers to small home-based production). Sometimes it may be impossible even to identify all the countries that are involved or the extent of their involvement (Gereffi and Fernandez-Stark 2016). However, the recent development of OECD-WTO's Trade-in Value Added (TiVA) data represents a fundamental step forward in understanding GVC trade. Grossman & Rossi-Hansberg (2008, 2012) rightly point out that the different tasks, rather than sectors, define the specialisation of countries in the value chains.

We calculate measures of economic complexity for US metropolitan areas for the years 2007-2015 based on industry employment data. We show that the concept of economic complexity translates well from the cross-country to the regional setting, and is able to incorporate local as well as traded industries. The largest cities and the Northeast of the US have the highest average complexity, while traded industries are more complex than local-serving ones on average, but with some exceptions. On average, regions with higher complexity have a higher income per capita, but those regions also were more affected by the financial crisis. Finally, economic complexity is a significant predictor of within-decreases in income per capita and population. Our findings highlight the importance of subnational regions, and particularly metropolitan areas, as units of economic geography., 80 pages, 13 figures

Local minimum wage laws are becoming common across U.S. cities, and their effects may be different from the effects of state or national minimum wage policies. This paper studies the effect of changes in the minimum wage on spatial equilibriums in local labor markets. Using residence and workplace data for the United States, I analyze how commuting, residence, and employment locations change across city and state borders if the minimum wage changes on one side of the border. I find that areas in which the minimum wage increases receive fewer low-wage commuters. A 10 percent increase in the minimum wage reduces the inflow of low-wage commuters by about 2.5 percent. Rises in the minimum wage are also associated with employment relocation across borders toward areas that did not witness an increase in the minimum wage. I formulate a spatial equilibrium gravity model to explain the distribution of workers between low- and high-minimum wage areas. I calculate counterfactual equilibriums with a higher minimum wage for U.S. counties with cities considering an increase, highlighting the role of commuting and migration responses. About two-fifths of the counties considering increases would receive fewer low-wage commuters. Employment relocation away from high-minimum wage areas drives the commuting losses.

Pedestrian accessibility is an important factor in urban transport and land use policy and critical for creating healthy, sustainable cities. Developing and evaluating indicators measuring inequalities in pedestrian accessibility can help planners and policymakers benchmark and monitor the progress of city planning interventions. However, measuring and assessing indicators of urban design and transport features at high resolution worldwide to enable city comparisons is challenging due to limited availability of official, high quality, and comparable spatial data, as well as spatial analysis tools offering customizable frameworks for indicator construction and analysis. To address these challenges, this study develops an open source software framework to construct pedestrian accessibility indicators for cities using open and consistent data. It presents a generalized method to consistently measure pedestrian accessibility at high resolution and spatially aggregated scale, to allow for both within- and between-city analyses. The open source and open data methods developed in this study can be extended to other cities worldwide to support local planning and policymaking. The software is made publicly available for reuse in an open repository.

Complex agriculture projects directly affect the welfare of over half the world’s population, are a key Sustainable Development Goal (SDG), and account for the single most extensive human activity across 40% of the world’s surface. Furthermore, they are highly susceptible to environmental, social, and economic pressures such as climate change, cyclical pandemics, market disruptions, and diminishing arable land. These issues are also becoming increasingly vital in dint of the fact that population growth is placing increasing pressure on sustainable priorities. However, a recent scientometric review indicates a significant paucity in the extant literature on agriculture projects, with a pressing need for further research to examine sustainable project management practices from an institutional perspective. This research, therefore, aims to respond to this gap in the literature by drawing on Institutional Theory through a multi-case study of Agriculture Co-operative Institutions (ACIs). These are often viewed as valuable vehicles to deliver agricultural projects which can benefit communities, especially in emerging markets. Initial findings from two rounds of fieldwork as well as an extensive literature review suggest that ACIs as value-based organisations embedded within institutional contexts help stimulate elements of agility in project management processes, to deliver sustainable outcomes for their members and external stakeholders. Agile ACI project managers can also stimulate innovative outcomes across broader sustainable agriculture projects. It is the aim of this research also to undertake a larger cross-country comparison with international research cases. Therefore, this study will aim to not only contribute to critical project management discourse and knowledge but also to uncover agile project management practices for future pressing policy development and implementation to help foster greater sustainable agriculture project processes. Cite this Paper: Dong, H., Dacre, N., & Bailey, A. (2021). Sustainable Agile Project Management in Complex Agriculture Projects: An Institutional Theory Perspective. Advanced Project Management, 21(3).

This paper aims to analyze the impact of irrigation on crop diversification. Crop diversification index has been employed to study the nature and extent of crop diversification in the study area. Descriptive statistics is used to explain the average CDI and irrigation. We found a mixed correlation between the factors and also observed a fluctuate impact on the crop diversification in the study area.

The measurement of poverty is essential for the development of effective poverty policy. Unfortunately, approaches using poverty rates to assess the causes and consequences of poverty do not fully capture the components of change in the poverty population. This is because changes in the conventional poverty rate can occur due to processes of natural increase, migration, or transitions in and out of poverty. This paper presents an accounting framework for changes in poverty within and between places. The framework, termed the poverty balancing equation, generates a series of summary statistics which can be used in place of the conventional poverty rate in future research. The approach is then demonstrated using the 2014 panel of the Survey of Income and Program Participation to generate state-level estimates of the poverty components of change for three states in the American South between January and December of 2013. Results show that even when poverty rates remain constant, there is significant dynamism within poor and non-poor populations. By applying this approach, either completely or in-part, researchers can provide more specific and actionable evidence for poverty alleviation policy.

Culture has played a pivotal role in human evolution. Yet, the ability of social scientists to study culture is limited by the currently available measurement instruments. Scholars of culture must regularly choose between scalable but sparse survey-based methods or restricted but rich ethnographic methods. Here, we demonstrate that massive online social networks can advance the study of human culture by providing quantitative, scalable and high-resolution measurement of behaviourally revealed cultural values and preferences. We employ data across nearly 60 000 topic dimensions drawn from two billion Facebook users across 225 countries and territories. We first validate that cultural distances calculated from this measurement instrument correspond to traditional survey-based and objective measures of cross-national cultural differences. We then demonstrate that this expanded measure enables rich insight into the cultural landscape globally at previously impossible resolution. We analyse the importance of national borders in shaping culture and compare subnational divisiveness with gender divisiveness across countries. Our measure enables detailed investigation into the geopolitical stability of countries, social cleavages within small- and large-scale human groups, the integration of migrant populations and the disaffection of certain population groups from the political process, among myriad other potential future applications. Á.C. acknowledges funding from the European Union’s Horizon 2020 innovation action program under grant agreement no. 101019206 (TESTABLE project); and the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M (‘Fostering Young Doctors' Research’, UE-MEASURE-CM-UC3M). R.C. acknowledges funding from H2020 EU Project PIMCITY (grant no. 871370) and the Taptap Digital-UC3M Chair in Advanced AI and Data Science applied to Advertising and Marketing. Á.C., R.C, K.D, I.O.-O. and Ö.Ö. acknowledge funding from ECO2013-42710-P, MDM 2014-0431 and Fundacion BBVA. I.M. acknowledges funding from the Spanish Ministry of education with the FPU programme (FPU15/03518).

Reducing road fatalities is a key policy goal in several countries and there is a vast literature on what factors affect road safety performance. Nonetheless, there is limited evidence on whether highway concessions and Public Private Partnerships (PPP) can bring road safety benefits, despite the growing number of countries adopting this type of policy to finance and manage road infrastructure. In this paper, we use a difference-in-differences approach to examine the causal effect of highway concessions on road safety outcomes using daily data from Brazilian Federal highways over 11 years between 2007-2017. We exploit the transition from public to private management in some but not all Brazilian states to provide both within- and between-states comparison. We find that concessions promote a small but significant reduction in the number and fatality of road crashes as well as and the number of people and vehicles involved in crashes. Between 2007-2017, procured roads had on average 16 fewer deaths then publicly managed highways for every 1000 crashes each year. These road safety benefits only become statistically significant a few years after a concession implementation, but they are marginally larger for every additional year of concession. Finally, our results suggest that including safety-based incentives in concession contracts can substantially improve road safety performance. The findings of the paper have important implications for the social and economic evaluation of road concessions and for road infrastructure policy more broadly.

The Internet, like railways and roads in the past, is paving innovation and alters the way in which citizens, consumers, businesses, and governments function and interact with each other. This digital revolution is empowering societies. It opens new, effective, and scalable services for governments and the private sector. It provides us with a more adaptive, data-driven approach to decision making in many aspects of our life. The digitalisation is particularly relevant for developing countries, as they can seize the opportunity for leapfrogging in order to become part of the global digitalised economy. With the example of Eastern Europe and Central Asia, this work illustrates how openly available online data can be used to identify, monitor, and visualise trends in digital economic development. Our interactive online dashboard allows researchers, policy-makers, and the public to explore four aspects of digital development: E-services, online labour markets, online knowledge creation and access to online knowledge.

Agglomeration economies and clustering effects are a key driver of urban growth. They can also be a source of vulnerability when cities and regions specialize in export-intensive industries. Foreign competition and technological change can threaten the survival of exporters, and shocks to these industries can have long-run effects on the communities which rely on them. In this paper, I study the impact of a rapid and large-scale trade shock: The quartz crisis, which devastated the globally dominant Swiss watch industry in the 1970s. I document the geographic agglomeration pattern of the industry and the impact of the crisis on exports, employment, and wages. Using a differences-in-differences strategy, I show that this trade shock led to a large and rapid loss of population in affected areas, and a long-run change in growth patterns. I explore the mechanisms behind this population change, including the role of manufacturing employment and immigration. I discuss the implications of these results for theories of urban growth, and contrast them with recent work on the China shock in Europe and the United States.

Previous research on educational aspirations and educational decision-making has mostly focused on high-income countries and thus on a relatively homogeneous socio-economic context. However, educational decision-making may be sensitive to contextual factors such as economic deprivation, a dysfunctional welfare state or poor access to credit markets – characteristics shared by most low- and middle-income countries. To better understand how economically disadvantaged individuals in developing countries make their educational choices, we conducted a survey based on a random sample with high school students in the rural department Morazan in El Salvador, a lower middle-income country in Latin America. Our results show that regardless of the social background, almost all students aspire to pursue tertiary education, probably due to the high tertiary degree premium in earnings and the high social benefits. However, the lack of possibilities to finance their studies generally prevents the realisation of these aspirations for lower social background students. While in high-income countries, cost factors are not very important in the decision-making process, the burden of costs explains around 45 percent of the social background effect in El Salvador. Other factors such as academic confidence, expected future economic benefits, parental status maintenance wish, individual risk aversion and time discounting preferences play only a minor role.

In the digital economy, innovation processes increasingly rely on highly specialised know-how and open-source software shared on digital platforms on collaborative programming. The information that feeds into the content on these platforms is provided voluntarily by a vast crowd of knowledgeable users from all over the world. In contributing to the platforms, users invest their time and share knowledge with strangers to add to the rising body of digital knowledge.This requires an open mindset and trust. In this study, we argue that such a mindset is not just an individual asset, but determined by the local communities the users are embedded in. We, therefore, hypothesise that places with higher levels of trust should contribute more to StackOverflow, the world’s largest question-and-answer platform for programming questions. In relating the city-level contributions of 266 OECD metropolitan areas to infrastructure, economic, and trust measures, we find this hypothesis confirmed. In contrast, click rates to the platform are solely driven by infrastructure and economic variables, but not by trust. These findings highlight the importance of societal values in the 21st century knowledge economy: if policy-makers want to develop a lively local digital economy, it is not enough to provide fast Internet access and business opportunities. Instead, it is equally important to establish a trust-building environment that fosters sharing of innovative ideas, collaborations, and knowledge spillovers.

We outline a grid-based approach to provide further evidence against the misconception that the results of spatial econometric models are sensitive to the exact specification of the exogenously set weighting matrix (otherwise known as the 'biggest myth in spatial econometrics'). Our application estimates three large sets of specifications using an original dataset which contains information on the Prime Central London housing market. We show that while posterior model probabilities may indicate a strong preference for an extremely small number of models, and while the spatial autocorrelation parameter varies substantially, median direct effects remain stable across the entire permissible spatial weighting matrix space. We argue that spatial econometric models should be estimated across this entire space, as opposed to the current convention of merely estimating a cursory number of points for robustness.

International audience; The exposure of rural communities to illegal waste dumping practices associated with the lack of or poor waste collection schemes prior to the closure of rural dumpsites under EU regulations and the role of collection efficiency afterward in reducing this critical environmental threat constitutes a key issue in rural Romania. The present study reveals huge amounts of household uncollected waste released into the natural environment outside the official statistics of rural dumpsites. Despite the expansion of waste collection coverage towards rural areas since 2010, the problem of illegal dumping practice is difficult to solve. The improvement of collection efficiency, better law enforcement, and surveillance of environmental authorities coupled with educational and environmental awareness are necessary steps to combat this bad practice. A circular economy paradigm must be enacted in rural regions through separate collection schemes and to improve cost-efficient alternatives, such as home composting, and traditional and creative reuse practices, particularly in less developed regions

It was measured and evaluated the economic impact and job creation on from the expenses and investments of the University of Contestado in Canoinhas municipality using a Keynesian spending multiplier model of whose coefficient was estimated at 2.84. The total economic impact motivated by the university in the local economy was about 252.8 million reais, or 6.47% of the city’s GDP.

How does expansion in the high-tech sector influence the broader economy of a region? We demonstrate that an infusion of venture capital in a region appears associated with: (i) a decline in entrepreneurship, employment, and average incomes in other industries in the tradable sector; (ii) an increase in entrepreneurship and employment in the non-tradable sector; and (iii) an increase in income inequality in the non-tradable sector. An expansion in the high-tech sector therefore appears to lead to a less diverse tradable sector and to increasing inequality in the region.

The production of materials is an important source of greenhouse gas emissions. In order to reduce emissions, policies aim to enhance material efficiency and the circular economy but our understanding of the dynamics of material-related greenhouse gas emissions is limited. Here, I quantify the greenhouse gas emissions from material production and the carbon footprint of materials in industries that are the first users of materials, and in final consumption, using in a multiregional input-output model of the global economy and the hypothetical extraction method. From 1995 to 2015, greenhouse gas emissions from just material production increased by 120%, with 11 billion tons CO2-equivalent emitted in 2015. As a proportion of global emissions, material production rose from 15 to 23%. China accounted for 75% of the growth. In terms of the first use of materials, two fifths of the carbon footprint of materials is attributed to construction, and two fifths to the manufacturing of machinery, vehicles, and other durable products. Overall, the replacement of existing or formation of new capital stocks now accounts for 60% of material-related emissions. Policies that address the rapidly growing capital stocks in emerging economies therefore offer the best prospect for emission reductions from material efficiency.

Trust explains the functioning of markets, institutions or society as a whole. It is a key element in almost every commercial transaction over time and might be one of the main explanations of economic success and development. In Europe, the determinants of (generalized) trust have been investigated in the past. Most scholars have focused on aggregate (national) levels of trust. However, it can be assumed that driving forces, which foster or diminish trust, act at a sub-national level. Regional clusters remain undetected. With the use of the European Social Survey 6 and modern spatial diagnostics, this work examines the individual and regional determinants of trust in 88 European NUTS1 regions in 26 countries. There are two main findings. First, wealth, linguistic fragmentation, and religious ideologies shape trust on a regional level, education, income, and membership in associations foster trust on an individual level. Secondly, the study unravels regional dispersions in different types of "trust regimes" in Europe. Regional clusters of generalized trust are confirmed by spatial diagnostics. The "regionality" of trust could be of importance for future targeted policy making.

The economic plight and consequent social and political attitudes of ‘left behind’ communities have become subjects of intense focus across a world impacted by inequality, social unrest, and political populism. We examine whether particular types of local long-term economic decline affect how residents in different places view the world; here in former mining communities of the UK which remain economically peripheral, and are home to community narratives that emphasise the shared economic, political and cultural heritages that are often fundamental to those places' very existence. We use data from the UK Household Longitudinal Study to contrast political views and social attitudes in communities that were (in 1981) economically dependent on coal mining with other communities that are similarly economically peripheral in contexts and challenges, but without a shared history of economic decline. We find that residents of former coalmining communities are highly politically disengaged, with low levels of trust and political efficacy, and low involvement in the political process. Moreover, our analysis shows an increase in political engagement over the EU referendum campaign period, which directly addressed some of the grievances felt by these communities. We conclude that community narratives of economic peripherality are strongly inter-linked with trust in government and political engagement.

As the rental housing market moves online, the internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings’ representativeness could impact different communities’ access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners’ and researchers’ ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the USA and finds that they spatially concentrate and overrepresent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities’ online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real time, it does not evenly represent all market segments. The internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms like Craigslist construct new institutions with the power to shape spatial economies, human interactions, and planners’ ability to monitor and respond to urban challenges.

This paper analyses the impact of Information and Communication Technology (ICT) on policymaking on an Indonesian Village level. In this study, I use data from different waves of the Indonesian Village Potential Statistics (Potensi Desa) to determine whether mobile phone signal strength affects village policies and civic engagement activities. The results indicate that villages with a strong signal are statistically more likely to possess the proper infrastructure and economic programs. Furthermore, mobile phones increase civic engagement, which is consistent with previous studies related to collective action or mass mobilisation. Using the plausibly exogenous variation of lightning strike intensity as the instrumental variable, this study suggests that higher mobile phone signal strength is positively associated with the policies implemented by the village head. This study also demonstrates that ICT has a stronger effect in rural areas. One possible explanation is that mobile phones improve the relative ability for rural people to interact with their leaders. Another potential answer is the fact that there are significant differences between rural village and urban village governments, which could also affect policymaking.

While the Syrian war is entering its seventh year, the situation is getting worse day after day. It has drifted from civil war to a global conflict, with many challenges and obstacles. An interview and discussion about the rebuilding plans in Syria, also relevant data were extracted from eligible research. The Syrian economy and social life faced a considerable fall. The interviewee suggested that the Marshall Plan would be the proposed plan for the reconstruction of Syria.

Urban researchers have long debated the extent to which urban employment is monocentric, polycentric, or diffuse. In this paper I use high-resolution data based on unemployment insurance records to show that employment in US metropolitan areas is not centralized but is spatially concentrated. Unlike residents, who form a continuous surface covering most parts of each MSA, jobs have a bimodal spatial distribution, with most blocks containing no jobs whatsoever and a small number having extremely high employment densities. Across the 100 largest MSAs about 75% of jobs are located on the 10% of built land in Census blocks with at least twice as many jobs as people. Further, most of these jobs are in clustered business districts of more than 5 contiguous employment blocks. These relative proportions are extremely consistent across MSAs, even though cities vary greatly in the physical density at which they are constructed. Motivated by these empirical regularities, I introduce an algorithm to identify contiguous business districts and classify them into four major types. Based solely on the relative densities of employment and population, this algorithm is both simpler to implement and more flexible than current approaches, requiring no metro-specific tuning parameters and no assumptions about urban form. As one output, it provides an inductive, data-driven method of identifying city centers for the purposes of urban economic analysis.

Located in the state of North Carolina, Mecklenburg county is among the ten fastest growing counties in the Unites States (Carmen et al., 2010). As of 2010 census data the population of the county is 919,628, with an estimated population of 1,034,070 in 2015. The city of Charlotte, that covers the most area of Mecklenburg county, is the largest city in NC with close to 700,000 residents, and the seventeenth largest city in the US. Mecklenburg county is part of the NC-SC Metropolitan Statistical Area (MSA) of Charlotte, Concord, Gastonia.546 square miles (1,410 km2) of Mecklenburg county is land and 22 square miles (57 km2) is water (US Census Bureau). Adjacent counties include: Iredell county, Cabarrus county, Union county, Gaston county, Catawba county, Lincoln county, Lancaster county (SC), and York county (SC).Charlotte is home of a large banking industry and several Fortune 500 companies (Carmen et al., 2010). The banking industry makes Charlotte the second largest financial center in the US after New York and has one of the highest median wages in the region (Kozar, 2010). Another large industry in Charlotte is finance, insurance, and real estate, and the headquarters of several national corporations located in Charlotte (Bacot, 2008). Five Fortune 500 Companies that have their headquarters in Mecklenburg County are: Bank of America, Nucor, Sonic Automotive, Duke Energy, and Family Dollar (Dollar Tree) (Fortune, 2016). Education is another large economic sector in North Carolina due to having the largest public school system and a regional state university in this area (Bacot, 2008); these schools include: UNC Charlotte, Davidson College, Queens University, Johnson & Wales University, Wake Forest University (School of Business) Charlotte Center, Johnson C. Smith University, Southern Evangelical Seminary, Central Piedmont Community College, and Belmont Abbey College. Other large employers in Mecklenburg county are Charlotte Mecklenburg Hospital, Charlotte-Mecklenburg Board of Education, Wells Fargo Bank (A Corp), Bank of America, and US Air Inc (NC Department of Commerce, 2015, 4th quarter).Charlotte-Douglas International Airport is the main airport in the region that is the 5th busiest airport in the nation in 2015, and the 6th busiest in the world (Portillo, 2016). This airport is the hub for US Airways and American Airlines that have been merged in 2013, to become the second busiest hub for the combined carrier (Portillo, 2015). Charlotte, like other parts of the US, has been affected by the economic recession that started in 2007. Many job losses and unemployment expanded in all sectors of the economy. The banking industry that was the largest industry in the region was specifically affected by the recession, leaving the region with high unemployment (NC Department of Commerce, 2015, 4th quarter). However, one of the strongest assets of Charlotte economy is its diversity of employment, that even at the time of distress, would sustain its economy (Kozar, 2010).

As part of a New Deal initiative to minimize home foreclosure, federal government officials and local real estate professionals graded each neighborhood in America’s largest cities on its perceived credit risk. Using recently digitized maps that precisely show neighborhoods marked with red ink (highest risk) or yellow ink (slightly lower risk), I document that surveyors disproportionately assigned the most restrictive credit rating to neighborhoods with black residents. Nearly 90 percent of African Americans in 1940 lived in a census tract marked for credit redlining. Comparing credit-restricted "redlined" census tracts to adjacent "yellow-lined" tracts, I estimate the long-run effects of redlining on housing and neighborhood outcomes. Between 1940 and 1970, redlining was associated with large differential declines in housing supply and population density; homeownership rates and racial composition did not change differentially from their 1940 baseline though. Once discriminatory lending was outlawed during the mid-1970s, there was moderate convergence in homeownership rates and racial composition. However, housing supply and population density remain persistently lower in formerly credit-restricted census tracts relative to their credit-favored neighbors. Although African-American neighborhoods were much more likely to be redlined, I show the effects do not vary by a neighborhood’s initial share of African American residents. Results also hold when restricting the sample to neighborhoods without any black residents in 1940. Taken together, these findings suggest redlining impacted neighborhood housing supply and population independent of pre-war patterns of racial segregation.

Our aim is to estimate how local amenities, for example availability of schools or restaurants, and in general the level of happiness of a neighbourhood, affect the housing market. We consider the city of Phoenix, AZ, for which we hold housing transaction data. Our observation unit is the census tract. After having located schools, restaurants and Tweets in order to gain the average mood of the neighbourhood, we add a set of controls to our empirical estimation. We find a strong positive correlation of transaction prices with the average income of a district, as well as a negative correlation with the rate of violent crime.

Integrating land use, travel demand, and traffic models represents a gold standard for regional planning, but is rarely achieved in a meaningful way, especially at the scale of disaggregate data. In this report, we present a new pipeline architecture for integrated modeling of urban land use, travel demand, and traffic assignment. Our land use model, UrbanSim, is an open-source microsimulation platform used by metropolitan planning organizations worldwide for modeling the growth and development of cities over long (~30 year) time horizons. UrbanSim is particularly powerful as a scenario analysis tool, enabling planners to compare and contrast the impacts of different policy decisions on long term land use forecasts in a statistically rigorous way. Our travel demand model, ActivitySim, is an agent-based modeling platform that produces synthetic origin--destination travel demand data. Finally, we use a static user equilibrium traffic assignment model based on the Frank-Wolfe algorithm to assign vehicles to specific network paths to make trips between origins and destinations. This traffic assignment model runs in a high-performance computing environment. The resulting congested travel time data can then be fed back into UrbanSim and ActivitySim for the next model run. This technical report introduces this research area, describes this project's achievements so far in developing this integrated pipeline, and presents an upcoming research agenda.

International audience; The paper aims to examine the changes in the rural waste management sector at regional scale since the Romania adhesion to the EU in 2007. Traditional waste management based on the mixed waste collection and waste disposal often on improper sites prevailed in municipal waste management options of transitional economies across the globe. The lack of formal waste collection services in rural areas has encouraged the open dumping or backyard burning. The paper analyses the improvements and challenges of local authorities in order to fulfill the new EU requirements in this sector supported by data analysis at local administrative unit levels and field observations. Geographical analysis is compulsory in order to reveal the local disparities. The paper performs an assessment of waste collection issues across 78 rural municipalities within Neamt County. This sector is emerging in rural areas of Eastern Europe, but is far from an efficient municipal waste management system based on the waste hierarchy concept.

Urban displacement – when a household is forced to relocate due to conditions affecting its home or surroundings – is frequently caused by rising housing costs, particularly in wealthy, prosperous cities. However, its dynamics are complex and often difficult to understand. This paper presents an agent-based model (ABM) of urban settlement, agglomeration, displacement, and sprawl. New human settlements form around a natural amenity that draws initial, poor settlers to subsist on the resource. As the settlement grows, subsequent settlers of varying income, skills, and interests are heterogeneously drawn to either 1) the natural amenity or 2) the emerging human agglomeration. As the agglomeration grows and densifies, land values increase, and the initial poor settlers may be displaced away from the natural amenity on which they relied. Through path dependence, high-income residents remain clustered around this natural amenity for which they have no direct use or interest. The agent-based model presented here explores the dynamics of this process. In particular, it reveals how urban displacement and gentrification can be sensitive to income inequality, density, and varied preferences for different types of spatial amenities.

Traditional U.S. rental housing data sources such as the American Community Survey and the American Housing Survey report on the transacted market—what existing renters pay each month. They do not explicitly tell us about the spot market—that is, the asking rents that current homeseekers must pay to acquire housing—though they are routinely used as a proxy. This study compares governmental data to millions of contemporaneous rental listings and finds that asking rents diverge substantially from these most recent estimates. Conventional housing data understate current market conditions and affordability challenges, especially in cities with tight and expensive rental markets.

The management of construction waste it is at an early stage in urban areas and lacking in rural areas where this fraction is frequently uncontrolled disposed on public lands. Despite the fact some items of construction waste are considered inert for the environment (soil, concrete) it also contains hazardous items (paint additives, cans, and containers) or recyclables (plastics, metals, wood). Potential recovery of this waste stream is high if it is properly managed. The paper estimates the potential amounts of waste resulted from residential constructions across rural municipalities of Neamț County between 2002 and 2010. These statistical values are calculated at commune level (rural territorial administrative unit) in order to outline the disparities between various geographical areas using thematic cartography. This approach is correlated with demographic features in order to reflect such spatial patterns. The map of population density within built-up areas reveals where the construction sector is emerging at the county scale. Field observations highlight the existence of illegal disposal practices of construction waste in the proximity of settlements or water bodies. This waste stream should receive proper attention in following years in order to achieve recycling and recovery targets imposed by EU regulations.

Harnessing technology startups for African development is a policy approach that simply cannot wait. Startups bring data, dynamism and daring to the development table, and have an important role to play in economic development today. Although nonprofit and government initiatives are also significant, social science evidence will enable such organizations to benefit from technology startups for new economic changes to be fast and inclusive.

Although the recent housing crash put the U.S. economy into a tailspin, we know very little about how the massive increase and decrease of house prices influenced property tax collections. Using local level housing data from Zillow matched to property tax data from 1998 to 2012, two questions are examined. First, the elasticity of property tax revenue with respect to house values is estimated. Second, the timing of this elasticity is determined. The analysis is able to rule out that local policy makers capture the entire increase of house value in property tax revenues but unable to rule out that increases in house values are completely offset by changes in effective property tax rates. Decreases in house values have an elasticity of between 0.3 and 0.4 and take three years for changes in house values to impact property tax revenues. While property tax collections declined, local policy makers adjusted effective millage rates such that revenues did not decline as much as home values.