Twenty years ago the Swedish school system underwent serious change in that students were given the right to choose their school, though those living near each school had priority. Since then, there has been a new geographical debate concerning where students live and go to school and possible implications of this on student educational achievement and educational equality, as well as on students' daily lives. In studies of changes in the school system, travel distances to school have so far been less studied in the Swedish context. In this paper we will analyze the changes in distance to school for 15-year-olds, from 2000 to 2006, in order to identify who, and in which context, is traveling shorter/longer distances, and thus performing a school choice. We use register data from the database PLACE, Uppsala University. The focus is not on effects on achievement, nor school composition, but instead on the difference in ability/possibility of using school choice as measured by distance. A time-geography approach concerning variation in constraints between students is used. School choice may be a matter of preference for certain schools, but importantly, it might also be a matter of time and space restrictions for families with fewer resources: that is, with less spatial capital and a limited opportunity structure. Results show that travel to school distances have increased since the year 2000. Foreign-born students are traveling shorter distances, except for those with highly educated parents. Shorter distances are also travelled by students from families with social assistance and for visible minorities in areas where such minorities exist.
Sweden is today an immigrant country with more than 14% foreign born. An increasing share of the immigrants comes from non-European countries. This implies that Sweden has been transformed from an ethnically homogenous country into a country with a large visible minority. In this paper we survey the effect of this change on school segregation. Building on Schelling's model for residential segregation, we argue that establishment of a visible minority has triggered a process of school segregation that in some respects can be compared with the developments in the United States. In order to test the validity of a Schelling-type process in Swedish schools we compare segregation levels in regions with different shares of visible minority students.We use data from the PISA 2003 survey in combination with register data on the ethnic composition of student population in different parts of Sweden. We find that school segregation is higher in regions with a large visible-minority population.We also find that, controlling for student background, there are smaller differences in performance across schools in regions with low shares of minority students.
Urban small water bodies, such as ponds, are essential elements of human socio-economic landscapes. Ponds also provide important habitats for species that would otherwise not survive in the urban environment. Knowledge on the biodiversity of urban ponds and the relationship between their ecological value and factors linked to urbanization and socio-economic status is crucial for decisions on where and how to establish and manage ponds in cities to deliver maximum biodiversity benefits. Our study investigates if the pattern of urban-pond biodiversity can be related to different socio-economic factors, such as level of wealth, education or percentage of buildings of different types. Because of lack of previous studies investigating that, our study is of exploratory character and many different variables are used. We found that the biodiversity of aquatic insects was significantly negatively associated with urbanisation variables such as amount of buildings and number of residents living around ponds. This relationship did not differ depending on the spatial scale of our investigation. In contrast, we did not find a significant relationship with variables representing socio-economic status, such as education level and wealth of people. This latter result suggests that the socio-economic status of residents does not lead to any particular effect in terms of the management and function of ponds that would affect biodiversity. However, there is a need for a finer-scale investigation of the different potential mechanism in which residents in areas with differing socio-economic status could indirectly influence ponds.
Early empirical studies in labour and urban economics addressing the role of commuting (on, e.g., wages and locational choice) have typically been confined to the use of survey data. Researchers are, however, increasingly getting access to large register databases with detailed information on where individuals live and work. A variety of methods have thus emerged to exploit the geocoded characteristic of the data to calculate commuting measures that go beyond simple Euclidean metrics. These methods involve new techniques that make use of geographic information system (GIS) routing software or application programming interfaces provided by third-party developers. This article provides (i) a brief survey of the small but emerging literature that uses geocoded register data to calculate different commuting measures, (ii) an example on how register-based commuting measures can be constructed along with descriptive evidence on how different commuting measures compare for different socio-economic groups using rich Swedish register data, (iii) a discussion of the pros and cons of different methods and measures, and (iv) a discussion of the potential of using mobile phone data to further improve registerbased commuting measures.
During the first months of the COVID-19 outbreak, countries adopted different strategies in order to mitigate the effects of the pandemic, ranging from recommendations to limit individual movement to severe lockdown measures. Regarding higher education, university studies were shifted to digital solutions in most countries. The sudden move to online teaching affected stu-dents differently, depending on the overall mitigation strategies applied. Severe lockdown and closure measures caused a disruption of their academic and social interactions. In contrast, rec-ommendations to limit activities probably did not change students' life to a great extent. The heterogeneity of the policies adopted in three countries (Italy, Sweden and Turkey) gives us an opportunity to assess the effects of lockdown measures due to the COVID-19 pandemic on uni-versity students' performance. We employ a difference-in-differences approach by exploiting the fact that Italy and Turkey experienced national lockdowns, while Sweden never applied nation-wide mandatory restrictive policies. We use administrative data from universities in the three countries to estimate the probability to pass exams after the spread of COVID-19 pandemic (and the shift to distance education), with respect to the previous comparable period. We find that the pass rate decreased with the shift to online teaching. However, lockdown measures, especially if very restrictive as those applied in Italy, helped to compensate such negative effect. A possible explanation is that students took advantage of the huge increase in the time available for their studies, given the impossibility to carry out any activity outside the home.
There continues to be cross-disciplinary interest in the patterns, extent, and changing contexts of segregation and spatial inequality more generally. The changes are clearly context dependent but at the same time there are broad generalizations that arise from the processes of residential sorting and selection. A major question in U.S. segregation research is how the growth of Asian and Hispanic populations is influencing patterns of segregation and diversity at the neighborhood level. In this article we use a variant of a nearest neighbor approach to map, graph, and evaluate patterns of race and ethnicity at varying scales. We show that using a multiscalar approach to segregation can provide a detailed and more complete picture of segregation. The research confirms work from other studies that segregation is decreasing between some groups and increasing between others, and the patterns, and processes can be described as dynamic diversity. In a series of maps of ethnic clusters and population homogeneity we show how metropolitan areas, represented in this case by Los Angeles, now display patterns of complex living arrangements with multiple groups inhabiting both local neighborhoods and wider community spheres.
Studies of segregation continue to explore analytic tools to engage with patterns of separation within cities. In recent work, scale has emerged as an important dimension of understanding segregation - simply put, separation is strongly affected by the scale which is used in the measurement process. Levels of segregation are also influenced by the time in which the analysis takes place. We outline an approach to separation which has four dimensions - (1) using bespoke neighborhoods - who do you meet at varying scales, (2) measuring the size of the change in separation over time, (3) estimating the rate of change in separation across space and time and (4) visualizing the change, mapping changing levels of contact. The themes are explored using data from the diverse, multi ethnic neighborhoods in Californian metropolitan areas. The result of a bespoke neighborhood approach to segregation provides a more complete demonstration of the pattern of ethnic segregation. We know that there are declining overall levels of segregation, but while levels are decreasing for Whites they are increasing for Hispanics and Asians but at different rates depending on local contexts. Viewing assimilation in a multi-scalar visual context expands our understanding of segregation and assimilation.
Sweden has adopted far less restrictive social distancing policies than most countries following the COVID-19 pandemic (1–7). This paper uses data on all mobile phone users, from one major Swedish mobile phone network, to examine the impact of the Coronavirus outbreak under the Swedish mild recommendations and restrictions regime on individual mobility and if changes in geographical mobility vary over different socio-economic strata. Having access to data for January-March in both 2019 and 2020 enables the estimation of causal effects of the COVID-19 outbreak by adopting a Difference-in-Differences research design. The paper reaches four main conclusions: (i) The daytime population in residential areas increased significantly (64 percent average increase); (ii) The daytime presence in industrial and commercial areas decreased significantly (33 percent average decrease); (iii) The distance individuals move from their homes during a day was substantially reduced (38 percent decrease in the maximum distance moved and 36 percent increase in share of individuals 2 who move less than one kilometer from home); (iv) Similar reductions in mobility were found for residents in areas with different socioeconomic and demographic characteristics. These results show that mild government policies can compel people to adopt social distancing behavior.
Theory states that residential segregation may have a strong impact on people's life opportunities. It is unclear, however, to what extent the residential environment is a good representation of overall exposure to different people and environments. Daily mobility could reduce the negative effects of segregation if people change environments and/or become more mixed. They could also enhance existing segregation patterns if daily mobility produces more segregated environments. This article uses mobile phone data to track daily mobility patterns with regard to residential segregation. We test the extent to which patterns differ between residents in immigrant-dense areas and those from areas with a greater proportion of natives. Results suggest, in line with previous research, that daily mobility patterns are strongly segregated. Phones originating from more immigrant-dense areas are more likely to (1) remain in the home area and (2) move towards other immigrant-dense areas. Hence, although mobility does mitigate segregation to some extent, most people are mainly exposed to people and neighbourhoods who live in similar segregated environments. These findings are especially interesting given the case study areas: two medium-sized Swedish regions with relatively low levels of segregation and inequality and short journey distances.
Studies of neighbourhood effects typically investigate the instantaneous effect of point-in-time measures of neighbourhood poverty on individual outcomes. It has been suggested that it is not solely the current neighbourhood, but also the neighbourhood history of an individual that is important in determining an individual's outcomes. Using a population of parental home-leavers in Stockholm, Sweden, this study investigates the effects of two temporal dimensions of exposure to neighbourhood environments on personal income later in life: the parental neighbourhood at the time of leaving the home and the cumulative exposure to poverty neighbourhoods in the subsequent 17 years. Using unique longitudinal Swedish register data and bespoke individual neighbourhoods, we are the first to employ a hybrid model, which combines both random and fixed effects approaches in a study of neighbourhood effects. We find independent and non-trivial effects on income of the parental neighbourhood and cumulative exposure to poverty concentration neighbourhoods.
Nearly all segregation measures use some form of administrative unit (usually tracts in the United States) as the base for the calculation of segregation indices, and most of the commonly used measures are aspatial. The spatial measures that have been proposed are often not easily computed, although there have been significant advances in the past decade. We provide a measure that is individually based (either persons or very small administrative units) and a technique for constructing neighborhoods that does not require administrative units. We show that the spatial distribution of different population groups within an urban area can be efficiently analyzed with segregation measures that use population count-based definitions of neighborhood scale. We provide a variant of a k-nearest neighbor approach and a statistic spatial isolation and a methodology (EquiPop) to map, graph, and evaluate the likelihood of individuals meeting other similar race individuals or of meeting individuals of a different ethnicity. The usefulness of this approach is demonstrated in an application of the method to data for Los Angeles and three metropolitan areas in Sweden. This comparative approach is important as we wish to show how the technique can be used across different cultural contexts. The analysis shows how the scale (very small neighborhoods, larger communities, or cities) influences the segregation outcomes. Even if microscale segregation is strong, there may still be much more mixing at macroscales.
Several studies have analysed the relationships between individuals' commuting distances and individual characteristics, discrimination, societal structure and planning. Largely left unexplored, however, are the long-term relationships between changes in the economic cycle and the effects on individual commuting distances. Using regression analyses, this study focuses on the relationship between changes in GDP and commuters' response reflected in commuting distances. The empirical data consist of records of almost 12 million Swedish commuting events between 1990 and 2006. Results of the analyses indicate that changes in GDP growth rate have an impact on commuting distances, especially for younger workers, the recently unemployed and commuters in metropolitan areas.
In this paper we explore and compare various techniques for the calculation of distance decay parameters which are estimated using statistical methods with half-life decay parameters which are derived mathematically. Half-life models appear to be a valid alternative to traditional spatial interaction models, especially in the presence of spatially highly disaggregate data. Our results indicate that Half-life models are more accurate for the construction of decay parameters than are unconstrained spatial interaction models in 'medium' sized datasets but not as accurate as doubly-constrained models. However, using highly detailed and disaggregate datasets Half-life models may be viable alternatives to doubly-constrained spatial interaction models as the latter will be difficult to estimate when the number of origins and destinations increase. In addition, Half-life models rise in accuracy with increasing degrees of disaggregation due to reductions of systematic errors between observed individual level commuting distance and modelled distances between origins and destinations.
In sum, our findings are as follows. First, since unconstrained and doubly-constrained spatial interaction models become increasingly difficult to estimate and/or less accurate to use compared to Half-life models as the spatial disaggregation increases choice of decay parameter estimation model should be considered in relation to level of disaggregation. Secondly, Half-life models are not affected by the systematic errors observed in the statistically derived models. Finally, using Half-life models for the estimation of decay parameters is simple which may make it easy to employ among practitioners lacking skills or computer means for the estimation of more complex statistically derived models.
In most studies of economic resilience, much effort is attributed to the development of factors and measures representing economic and related resilience. In this context, a great deal of attention is devoted to the role of regions and to their abilities to withstand an economic shock. Usually, however, less attention is given to the size, distribution and interaction of the regions containing the underlying statistics used in the calculation of resilience factors. In this article, we argue that more attention should be devoted to choosing spatial units to increase the potential of resilience measures. In particular, we consider a smaller spatial unit, such as the municipality level, to better visualize resilience's variations. In addition, by complementing measures of resilience with a measure of accessibility, we try to depict the municipality's economic functioning. We have carried out experiments with reference to the system of the 290 municipalities in Sweden. Our municipality-level analyses reveal that (a) proxies of resilience and accessibility, in general, are positively and significantly correlated and that the municipalities estimated to be most resilient and accessible are also the major economic centers in Sweden, and (b) classifying the municipality position in ranks of proxies for resilience and accessibility is more useful for the classification of municipalities with differential resilience than classifying municipalities using proxies for resilience alone. For example, whereas high proxy values for resilience and high accessibility municipalities often are both job- and population-rich, municipalities with low resilience estimates and high accessibility indices can typically be depicted as suburban and commuting municipalities in metropolitan areas. While municipalities with estimates of poor resilience and poor accessibility can in general be used to categorize remote municipalities experiencing population loss, estimated low resilience and high accessibility are characteristics of municipalities increasing in population. This analysis combining estimates of resilience and accessibility can be considered a suitable tool for providing a more complete insight into the economic investigation and measurement of resilience.
Rapid process of urbanization has been leading the direction of Latin American development over decades. However, the pattern of urbanization has been changing over the recent years, which can be seen as increasing rural-urban connections and growing importance of small towns and intermediate cities. This has also resulted in livelihood diversification in rural and peri-urban sites, which might include off-farm income generating activities and temporal labor migration. Over the last decades, an increasing flow of rural-to-urban migrants have transformed the urban as well as rural landscapes in Bolivia. The aim of this study is to identify national and transnational migration patterns in the Bolivian case study and to understand links between changing migration flows and population structure of urban space. Using a unique database containing records of thousands of migrations from rural areas to the major city of Cochabamba, we are able to analyze to what extent socio-economic backgrounds, earlier residence locations, ethnic belongings, and previous migration experiences determines type and location of residence areas chosen by migrants.
Rapid process of urbanization has been leading the direction of Latin American development over decades. However, the pattern of urbanization has been changing over the recent years, which can be seen as increasing rural-urban connections and growing importance of small towns and intermediate cities. This has also resulted in livelihood diversification in rural and peri-urban sites, which might include off-farm income generating activities and temporal labor migration. Over the last decades, an increasing flow of rural-to-urban immigrants have transformed the urban as well as rural landscapes in Bolivia. The aim of this study is to identify national and transnational migration patterns in the Bolivian case study and to understand links between changing migration flows and structure of urban space. Using a unique database containing records of thousands of migrations from rural areas to the major city of Cochabamba, we are able to analyze to what extent socio-economic backgrounds, earlier residence locations, ethnic belongings, and previous migration experiences determines type and location of residence areas chosen by migrants.
Does living in an area characterized by high concentrations of residents of the same country-of-origin deprive ethnic minority groups, or does potential access to an extended country-of-origin-specific network stimulate their integration? This paper takes a new approach to analysing the potential of country-of-origin-specific economic capital in neighbourhoods to increase employment opportunities. We add to the 'ethnic enclave' debate by measuring country-of-origin-specific economic capital as the rate of employed co-countrymen, while controlling for the presence of co-countrymen and general employment rates in the neighbourhood. Whereas many studies employ aggregated data to estimate the impact of neighbourhood, here we use individualized, scalable neighbourhoods. This allows for a flexible approach in studying the impact of country-of-origin-specific economic capital in neighbourhoods. We employ individual longitudinal Swedish registry data for 2000-2010 on working-age individuals of Iraqi, Iranian, Turkish, and Somalian backgrounds in Stockholm, Goteborg, and Malmo. We find that an increased share of employed co-countrymen positively influences individual employment prospects. We add to existing knowledge by showing that the impact of minority clustering on employment outcomes is conditional on the quality of local networks - i.e., country-of-origin-specific economic capital - and on the scale of measurement.
This paper offers a novel contribution to an evidence-based assessment of the attractiveness features (or perceived qualities) of cities or urban neighbourhoods, based on a quantitative evaluation of such areas by introducing and applying what is called 'city-love' analysis. To put this new concept in context, we offer first a concise overview of related and complementary notions (e.g. happiness, satisfaction, well-being, quality of life, contentment). Then we propose a new departure for attractiveness research pertaining to micro-based information on residents or users of cities by introducing the notion of a 'city-love production function'. This function expresses the ability of cities to enhance the love or appreciation for a city or its neighbourhoods through an appropriate combination of five specific 'city capital' constituents. We test the validity of this so-called 'Pentagon' approach to city love by means of the city-love production function using a multivariate econometric model based on extensive heterogeneous statistical data on municipalities in Sweden and complemented with cell phone data. Our results are confronted with empirical 'big data' on the appreciation of Swedish places - and their characteristics - taken from social media platforms. The study offers also interesting findings from an advanced spatial-econometric and multilevel modelling approach. Our estimations show that the concept of the city-love production function allows us to quantitatively uncover important determinants of citizens' love for their local environment.
This study examines the COVID-19 vulnerability and subsequent market dynamics in the volatile hospitality market worldwide, by focusing in particular on individual Airbnb bookings-data for six world-cities in various continents over the period January 2020-August 2021. This research was done by: (i) looking into factual survival rates of Airbnb accommodations in the period concerned; (ii) examining place-based impacts of intracity location on the economic performance of Airbnb facilities; (iii) estimating the price responses to the pandemic by means of a hedonic price model. In our statistical analyses based on large volumes of time- and space-varying data, multilevel logistic regression models are used to trace 'corona survivability footprints' and to estimate a hedonic price-elasticity-of-demand model. The results reveal hardships for the Airbnb market as a whole as well as a high volatility in prices in most cities. Our study highlights the vulnerability and 'corona echoeffects' on Airbnb markets for specific accommodation segments in several large cities in the world. It adds to the tourism literature by testing the geographic distributional impacts of the corona pandemic on customers' choices regarding type and intra-urban location of Airbnb accommodations.
In 2009, Sweden experienced a wave of urban unrest concentrated in areas with large foreign-born populations. This episode was seen by many as reflecting a trend towards increased ethnically based residential segregation, in line with scholarly literatures that correlate inequality and rising segregation with increases in unrest or rebellion. In this paper, we analyze the empirical connection between ethnic residential segregation and episodes of urban unrest in Sweden. Unrest is measured by the number of car burnings reported to police between 2002 and 2009. We find a positive and statistically significant link between residential segregation and car burnings at the scale of municipalities and metropolitan districts. Unrest/rebellion is also correlated with high proportion of young adults and social welfare assistance.
This study uses Cox proportional hazard models to examine the likelihood of transition to first employment among specific groups of African migrants compared to the general population and other immigrants, respectively, in Sweden. Our findings demonstrate that the likelihood of employment upon arrival is strictly linked to country of origin after taking socio-demographic characteristics into account. When compared with the general population, lower employment likelihood was found among immigrant men and women from most African countries, especially from Somalia. In general, African men experienced better employment chances when compared with women. A gender gap on transition to first employment was found among immigrants from Tunisia, Algeria and Egypt indicating that it is particularly difficult for women from these countries to find employment.
This paper provides a comprehensive overview of intergenerational income mobility in Sweden. Intergenerational income mobility is considered in both relative and absolute terms, and the analysis is carried out at the individual and municipality level. We use multilevel models to explore the correlation between upward mobility and social, economic and demographic characteristics of cities. We account for a wider set of local characteristics, such as the spatial distribution of income inequality within city and housing affordability that have not been considered by previous studies analysing social mobility in the United States or other European countries. The analyses are carried out on three subpopulations: off-spring who live in a different municipality than their parents (spatial mobile population); offspring who live in the municipality where they grew up (spatial immobile population); off-spring belonging to visible minority groups. Our results show substantial differences across municipalities, meaning that the particular combination of municipality attributes contributes to shaping the chance of status attainment among young generations. Highly mobile municipalities have more significant human capital, more residential segregation by income, more local levels of income inequality, and greater accessibility to jobs. The results indicate that dependence on parents' support and network for upward mobility is of less importance, and that spatial mobility (regardless of background) especially to larger urban areas is associated with upward mobility for the children.
In this study, we set out to understand how the changes in daily mobility of people during the first wave of the COVID-19 pandemic in spring 2020 influenced daytime spatial segregation. Rather than focusing on spatial separation, we approached this task from the perspective of daytime socio-spatial diversity – the degree to which people from socially different neighbourhoods share urban space during the day. By applying mobile phone data from Greater Stockholm, Sweden, the study examines weekly changes in 1) daytime social diversity across different types of neighbourhoods, and 2) population groups' exposure to diversity in their main daytime activity locations. Our findings show a decline in daytime diversity in neighbourhoods when the pandemic broke out in mid-March 2020. The decrease in diversity was marked in urban centres, and significantly different in neighbourhoods with different socio-economic and ethnic compositions. Moreover, the decrease in people's exposure to diversity in their daytime activity locations was even more profound and long-lasting. In particular, isolation from diversity increased more among residents of high-income majority neighbourhoods than of low-income minority neighbourhoods. We conclude that while some COVID-19-induced changes might have been temporary, the increased flexibility in where people work and live might ultimately reinforce both residential and daytime segregation.
Business owners play an important role in driving regional economic growth, and policy-makers seek to attract and retain such entrepreneurs by most means available. This paper analyses migration patterns, the factors that influence the propensity to move and assesses the relationship between firm performance and individual migration both before and after the move. The results show that (1) known explaining variables of migration propensity also hold for business owners; (2) owners with more substantial firms in terms of turnover and employees are more geographically anchored; and (3) a simultaneous move of residence and firm has an unclear impact on firm performance.
Marriage fields - the geographical areas where people meet to partner - traditionally tend to be relatively small and local. Increasing international travel and the use of the internet have broadened the geographical opportunity structure of potential partners.This increases the chances of meeting a partner from abroad, possibly resulting in a rise in international marriage migration. This paper uses unique longitudinal population data for the whole of Sweden to explore the globalisation of Swedish marriage fields. The results show an increase of ‘marriage migrants’ in Sweden between 1990 and 2004,although absolute numbers remain relatively low. The paper yields two new insights notpreviously recorded in the literature. First, we found a substantial proportion of allmarriage migrants in Sweden to be males, while most existing literature on marriage migration focuses almost exclusively on females. Second, the pattern of geographical origins of marriage migrants is highly gendered, with male and female marriage migrants in Sweden originating from different regions in the world. This suggests that different mechanisms underlie male and female marriage migration.
The partition of the Mobile Phone Network (MPN) service area into the cell towers' Voronoi polygons (VP) may serve as a coordinate system for representing the location of the mobile phone devices, as demonstrated by numerous papers that exploit mobile phone data for studying human spatial mobility. In these studies, the user is assumed to be located inside the VP of the connected antenna. We investigate the credibility of this view by comparing volunteers' empirical data of two kinds: (1) VP of the connected 3G and 4G cell towers and (2) GPS tracks of these users at the time of connection. In more than 60% of connections, the user's mobile device was found outside the VP of the connected cell tower. We demonstrate that the area of a possible device's location is many times larger than the area of the cell tower's VP. To comprise 90% of the possible locations of the device connected to a specific cell tower, one has to consider the tower's VP together with the two adjacent rings of VPs. An additional, third, ring of the adjacent VPs is necessary to comprise 95% of the possible locations of the device connected to the cell tower.
The revealed location uncertainty is in the nature of the MPN structure and service and entails essential overlap between the cell towers' service areas. We discuss the far-reaching consequences of this uncertainty for estimating locational privacy and urban mobility - population flows and individual trajectories. Our results undermine today's dominant opinion that an adversary, who obtains access to the database of the Call Detail Records maintained by the MPN operator, can identify a mobile device without knowing its number based on a very short sequence of time-stamped field observations of the user's connection.
Syftet med rapporten är att diskutera och analysera förekomsten av förtidspension och aktivitetsersättning bland unga och unga vuxna i Sverige.1 Utvecklingen i Sverige speglas utifrån ett internationellt perspektiv. En övergripande fråga i rapporten är om de senaste årens ökning av antalet unga med aktivitetsersättning kan relateras till socioekonomiska bakgrundsfaktorer och förhållanden på arbetsmarknaden.
Hedonic house price models are frequently used to improve our understanding of local housing markets. In recent years, rich registers containing details about home-qualities and neighbourhood characteristics have successfully been coupled with spatial qualities such as job-accessibility or distances to transport. Additional data sources provided by Open data communities, NGOs, data created by governmental agencies on regional national and international level has the potential of being very useful for analysing housing prices. However, the recent methodological advances in GIS and spatial analysis have not been extensively applied. We expand the hedonic price modelling toolbox with geo-coded free data on environmental amenities. We specifically include local measures describing the view-shed, and more varied specifications of access or dominance of green and blue amenities, in addition to urban public-type service and sport facilities. The GIS-derived data is used to study how the variables should be specified and to study their ability to improve even well specified hedonic price models. To our knowledge, this paper is the first to combine all the listed environmental properties in a hedonic model, and at the same time controlling for a large number of other important local neighbourhood characteristics.
The COVID-19 pandemic has profoundly affected the spatial mobility of a major part of the population in many countries. For most people, this was an extremely disruptive shock, resulting in loss of income, social contact and quality of life. However, forced to reduce human physical interaction, most businesses, individuals and households developed new action lines and routines, and were gradually learning to adapt to the new reality. Some of these changes might result in long-term changes in opportunity structures and in spatial preferences for working, employment or residential location choice, and for mobility behavior. In this paper we aim to extend the time-geographic approach to analyzing people’s spatial activities, by focusing on health-related geographical mobility patterns during the pandemic in Sweden. Starting from a micro-approach at individual level and then looking at an aggregate urban scale, we examine the space-time geography during the coronavirus pandemic, using Hägerstrand’s time-geography model. We utilize a massive but (location-wise) fuzzy dataset to analyze aggregate spatiotemporal impacts of the COVID-19 pandemic using a contemporary time-geographical approach. First, we address micro-level behavior in time-space to understand the mechanisms of change and to illustrate that a temporal drastic change in human mobility seems to be plausible. Then we analyze the changes in individuals’ mobility by analyzing their activity spaces in aggregate using mobile phone network data records. Clearly, it is too early for predicting long-term spatial changes, but a clear heterogeneity in spatial behavior can already be detected. It seems plausible that the corona pandemic may have long-lasting effects on employment centers, city roles and spatial mobility patterns.
Mobile phone data – with file sizes scaling into terabytes – easily overwhelm the computational capacity available to some researchers. Moreover, for ethical reasons, data access is often granted only to particular subsets, restricting analyses to cover single days, weeks, or geographical areas. Consequently, it is frequently impossible to set a particular analysis or event in its context and know how typical it is, compared to other days, weeks or months. This is important for academic referees questioning research on mobile phone data and for the analysts in deciding how to sample, how much data to process, and which events are anomalous. All these issues require an understanding of variability in Big Data to answer the question of how average is average? This paper provides a method, using a large mobile phone dataset, to answer these basic but necessary questions. We show that file size is a robust proxy for the activity level of phone users by profiling the temporal variability of the data at an hourly, daily and monthly level. We then apply time-series analysis to isolate temporal periodicity. Finally, we discuss confidence limits to anomalous events in the data. We recommend an analytical approach to mobile phone data selection which suggests that ideally data should be sampled across days, across working weeks, and across the year, to obtain a representative average. However, where this is impossible, the temporal variability is such that specific weekdays’ data can provide a fair picture of other days in their general structure.
To what extent an individual is successful in a variety of outcomes is the result of multiple factors such as (but not limited to) parental background, level of education, discrimination and business cycles. Factors like these also indicate that the success in life can be attributable to factors that both take individual-level merits into account but also to structural factors such as discrimination and contextual effects. Over the last decades, a growing interest in decomposing and categorising factors that affect the life chances of individuals has led to the formation of inequality of opportunity as a research field. This paper builds upon this growing literature, which amounts to quantify the contribution of factors that lie beyond the control of individuals to the total inequality observed in different spheres of life. Using rich Swedish longitudinal register data, we are able to follow individuals over time and their educational attainment during upbringing and later labour market outcomes. In difference from other inequality of opportunity studies, we make use of an egocentric neighbourhood approach to integrate the socio-economic composition of the parental neighbourhood in an inequality model and illustrate its contribution to the total inequality in both outcomes quantitatively. Using multilevel regression analyses, we show that the parental neighbourhood is highly influential in educational attainment and remains so for market outcomes even years after exposure.
Destination attractiveness research has become an important research domain in leisure and tourism economics. But the mobility behaviour of visitors in relation to local public transport access in tourist places is not yet well understood. The present paper seeks to fill this research gap by studying the attractiveness profile of 25 major tourist destination places in the world by means of a 'big data' analysis of the drivers of visitors' mobility behaviour and the use of public transport in these tourist places. We introduce the principle of 'the path of least resistance' to explain and model the spatial behaviour of visitors in these 25 global destination cities. We combine a spatial hedonic price model with geoscience techniques to better understand the place-based drivers of mobility patterns of tourists. In our empirical analysis, we use an extensive and rich database combining millions of Airbnb listings originating from the Airbnb platform, and complemented with TripAdvisor platform data and OpenStreetMap data. We first estimate the effect of the quality of the Airbnb listings, the surrounding tourist amenities, and the distance to specific urban amenities on the listed Airbnb prices. In a second step of the multilevel modelling procedure, we estimate the differential impact of accessibility to public transport on the quoted Airbnb prices of the tourist accommodations. The findings confirm the validity of our conceptual framework on 'the path of least resistance' for the spatial behaviour of tourists in destination places.
After a heated debate, the Norwegian parliament voted for the introduction of Cash-for-Care (CFC) in 1997, a programme designed to give parents more opportunities to plan childcare. The pro-CFC faction claimed that the reform would give parents more time with their children, whereas CFC opponents pointed to the increased risks of creating gender traps and discouraging women from returning to work. Earlier studies have suggested that the socio-economic dimensions are important for understanding the use of CFC. However, the role of geography in the implementation of CFC has not been studied, though it is well-known that the residential context is important to understand how parents choose to organize childcare. Our study is designed to examine the use of CFC in order to determine how much can be attributed to socio-economic factors and how much can be attributed to geography. We focus on mothers who gave birth to their first child in 2009 and follow their life course through 2011. We use a unique and comprehensive longitudinal data set with annual economic, demographic, and geographical information that includes all mothers residing in Norway during the study period. We find that the use of CFC is strongly correlated with several socio-economic variables and that there are also strong geographical factors, local and regional, affecting the choice to use CFC.
For many years the HDI or human development index has been a global de-facto standard to describe the potential for well-being and development of individuals in countries around the world. The index is built around three central elements: health, knowledge and standard of living and serves the purpose of moving the attention from national economics to the potential of the individual in each country. Despite its individual-centred orientation, the index is almost always constructed and compared on national levels. In this study, the index is disaggregated to municipality levels to study the local patterns. Using small scale data for all residents in Sweden, we can construct individual-centred HDI-calculations that are used to depict variations on local, to regional levels. Here the HDI aggregated to municipality level and the engineering resilience index (RCI) are compared. Observed patterns are strongly correlated with commonly used resilience indexes and the newly constructed HDI index has the benefit of being transferable and comparable on any level from nation to neighbourhood.
HDI is a frequently used quantitative index of human potential and welfare, developed as a comprehensive measure for the cross-sectional and temporal comparison of socioeconomic performance. The HDI is a standardised quantitative estimation of welfare comprising indicators of health, knowledge and standard of living, enabling assessment over countries, regions or time periods, in case of limited data access. The index highlights critical conditions for equity and socioeconomic development outside the group of stakeholders and researchers. The HDI provides a learning potential that may be harnessed to enhance insights into the magnitude of human potential at super-local levels. In this paper we design, implement and test the validity of a super-local variant of HDI in the context of pedagogical performance of young pupils. We compare whether HDI is a good predictor for school grades among all ninth-grade students in Sweden during the year 2014. Our results show that a super-local HDI index is performing equal to or better than the one related to standard measures of human potential, while the index can be generated on individual levels using k-nearest neighbour approaches during the index creation process.
The extent to which socioeconomic (dis) advantage is transmitted between generations is receiving increasing attention from academics and policymakers. However, few studies have investigated whether there is a spatial dimension to this intergenerational transmission of (dis) advantage. Drawing on the concept of neighbourhood biographies, this study contends that there are links between the places individuals live with their parents and their subsequent neighbourhood experiences as independent adults. Using individual-level register data tracking the whole Stockholm population from 1990 to 2008, and bespoke neighbourhoods, this study is the first to use sequencing techniques to construct individual neighbourhood histories. Through visualisation methods and ordered logit models, we demonstrate that the socioeconomic composition of the neighbourhood children lived in before they left the parental home is strongly related to the status of the neighbourhood they live in 5, 12 and 18 years later. Children living with their parents in high poverty concentration neighbourhoods are very likely to end up in similar neighbourhoods much later in life. The parental neighbourhood is also important in predicting the cumulative exposure to poverty concentration neighbourhoods over a long period of early adulthood. Ethnic minorities were found to have the longest cumulative exposure to poverty concentration neighbourhoods. These findings imply that for some groups, disadvantage is both inherited and highly persistent.
During the last two decades, an increasing number of studies on the geographies of gay and lesbian couples have been carried out, stressing the urban significance, tolerance, and amenities. In this study, it is argued that former studies have only mapped a fraction of the gay and lesbian population, that is, the couples, and present a new method for retrieving information from the Internet to map gay and lesbian singles and couples. The findings indicate that there is a significant difference between gay and lesbian singles and couples and that the urban significance is much stronger for singles than for couples. In the conclusion, it is suggested that a life course perspective could explain this where gay and lesbian singles tend to concentrate in cities, but when they have found a partner and decide to move together, the city is less important. Finally, a recommendation reconsidering partnership data is made as it can be problematical to generalise such data for a gay and lesbian population.
We study the impact of job proximity on individual employment and earnings. The analysis exploits a Swedish refugee dispersal policy to get exogenous variation in individual locations. Using very detailed data on the exact location of all residences and workplaces in Sweden, we find that having been placed in a location with poor job access in 1990–91 adversely affected employment in 1999. Doubling the number of jobs in the initial location in 1990–91 is associ-ated with 2.9 percentage points higher employment probability in 1999. The analysis suggests that residential sorting leads to underestimation of the impact of job access.
We study the impact of job proximity on individual employment and earnings. The analysis exploits a Swedish refugee dispersal policy to obtain exogenous variation in individual locations. Using very detailed data on the exact location of all residences and workplaces in Sweden, we find that having been placed in a location with poor job access in 1990–1991 adversely affected employment in 1999. Doubling the number of jobs in the initial location in 1990–1991 is associated with 2.9 percentage points higher employment probability in 1999. Considering that the 1999 employment rate was 43% among the refugees, this is a considerable effect. The analysis suggests that residential sorting leads to underestimation of the impact of job access.