In this study, I investigate the commuting behavior of workers in Germany. Using comprehensive geo-referenced administrative employee and firm data, I can calculate the exact commuting time and the distance between workers' residence and workplace locations. Based on a behavioral economic approach (Simonson and Tveresky in J Mark Res 29:281-295, 1992), I show that individual commuting decisions are influenced by wages and individual heterogeneity as well as depending on the context individuals observed in the past. In particular, my results show that previously observed commutes have an impact on subsequent commuting behavior: workers choose longer commuting times in the region they recently moved to when the average commute in the region they left was longer. The results indicate that while selectivity and sorting do not influence the effect of the context, the inclusion of individual fixed effects is crucial.

This paper focuses on creative industries and the role played by the existing spatial distribution and agglomeration economies of these activities in relation to their entry decisions. We rely on employment and firm-level data in the creative industries (provided by INSEE) and compare the location of new establishments in the creative and non-creative industries between 2009 and 2013 in French departments (NUTS 3 regions). We use count data models and spatial econometrics to show that location determinants are rather similar in creative and non-creative industries and that specialisation in creative industries positively influences the entry of all other industries. The French case provides new insights to understand the geographical patterns of creative industries.

Our objective is to investigate if hiring discrimination in France has a cyclical nature using an innovative set of repeated correspondence tests. The methodology covers one type of job only, that of administrative manager, in both the private and public sectors, and two discrimination criteria, ethnic origin and place of residence. The empirical analysis is based on five waves of tests starting in 2015, covering the periods before, during, and after the first lockdown, with 4749 applications sent for 1583 job openings in total. Our results indicate that hiring discrimination based on the dual criteria of origin and place of residence has decreased in France since the mid-2010s, within the context of an improved labor market, but that it increased sharply during the Covid health crisis, in recessionary conditions, suggesting that it generally follows a counter-cyclical behavior. Overall, the temporal patterns of discrimination, as measured by callback rates, mirror those of the unemployment rate.

Short-term rental platforms, led by Airbnb, have disrupted the tourism accommodation industry over the last decade. This disruption has encouraged policy-makers to intervene. However, little is known about how effective such interventions are. This paper empirically evaluates the impact Bordeaux's regulation has had on short-term rental (STR) activity through both a differences-in-differences and a triple-difference design. We find that regulation has had a reductive effect of over 322 rented days per month per district on average. This equates to 44% of mean reservation days and over 28 thousand less nights spent per month in STRs across the city. This effect is persistent in peripheral areas of the city, with an average effect of 35% of monthly reservation days. However, the city's attempts to limit activity stemming from targeted (commercial) listings yields mixed results as non-targeted (home-sharing) listings also seem to have modified their behavior. Additionally, analysis in the periphery paves the way for discussion about the effectiveness of one-size-fits-all STR policy design.

This research aims to investigate the role of employment protection in affecting the relationship between regional self-employment and unemployment during turbulent times. In doing so, data comprised of 230 regions, nested in 17 EU countries, for the 2008-2015 period were used. When accounting for individual effects, we find that an increase in regional unemployment would decrease regional self-employment, while the opposite was found true for employment protection. When accounting for the cross-level interaction between regional unemployment and national employment protection legislation, however, we find that the underlying increased labor market rigidity not only decreases regional self-employment, but it also magnifies the adverse effect of regional unemployment. Our key results thus indicate that high labor market rigidity hinders self-employment.

The economic literature has been silent on two key channels regarding how innovation affects labor supply: skilled-worker migration and "local production" of college graduates. Through these two channels, innovation influences wage divergence, skill levels, and productivity across urban areas. Using patents to proxy for regional innovation, we find that from 2005 to 2015, local college-graduate production plays a greater role in explaining US skill divergence across urban counties. Our findings suggest that local governments should focus on investing in greater local capacity for developing innovations and increasing their local higher-education capacity. Conversely, efforts to attract highly-educated workers from elsewhere should be relatively de-emphasized.

The three closely related COVID-19 outcomes of incidence, intensive care (IC) admission and death, are commonly modelled separately leading to biased estimation of the parameters and relatively poor forecasts. This paper presents a joint spatiotemporal model of the three outcomes based on weekly data that is used for risk prediction and identification of hotspots. The paper applies a pure spatiotemporal model consisting of structured and unstructured spatial and temporal effects and their interaction capturing the effects of the unobserved covariates. The pure spatiotemporal model limits the data requirements to the three outcomes and the population at risk per spatiotemporal unit. The empirical study for the 21 Swedish regions for the period 1 January 2020-4 May 2021 confirms that the joint model predictions outperform the separate model predictions. The fifteen-week-ahead spatiotemporal forecasts (5 May-11 August 2021) show a significant decline in the relative risk of COVID-19 incidence, IC admission, death and number of hotspots.

This paper studies amenities and wage premiums in a service economy where individuals with different skills choose cities with different amenities and choose occupations to produce different services, namely the high-quality service or the low-quality service. Workers with higher skills have stronger preferences for amenity and choose the high-amenity city. Within each city, workers with higher skills choose to produce the high-quality service, and workers with lower skills choose to produce the other. Workers with higher skills are willing to sacrifice more wages to live in the high-amenity city. As a result, the price of the high-quality service, relative to the price of the low-quality service, is lower in the high-amenity city, because the wage equals the price times skill or productivity. The wage of a worker with a given skill in the high-quality service sector, relative to the wage of a worker in the low-quality service sector, or the wage premium, is thus lower in the high-amenity city. A quantitative analysis shows that the wage premium is about 3% lower when amenity is 10% higher. However, the average wage of high-quality service workers over that of low-quality service workers may be lower or higher in the high-amenity city due to skill concentration in the high-amenity city.

This paper revisits the debate around the link between population density and the severity of COVID-19 spread in the USA. We do so by conducting an empirical analysis based on graphical evidence, regression analysis and instrumental variable strategies borrowed from the agglomeration literature. Studying the period between the start of the epidemic and the beginning of the vaccination campaign at the end of 2020, we find that the cross-sectional relationship between density and COVID-19 deaths changed as the year evolved. Initially, denser counties experienced more COVID-19 deaths. Yet, by December, the relationship between COVID deaths and urban density was completely flat. This is consistent with evidence indicating density affected the timing of the outbreak-with denser locations more likely to have an early outbreak-yet had no influence on time-adjusted COVID-19 cases and deaths. Using data from Google, Facebook, the US Census and other sources, we investigate potential mechanisms behind these findings.

The digital entrepreneurship indicator (DEI), which combines individual and institutional data, is designed to chart the vitality of metropolitan areas in terms of digital entrepreneurship on a suburban scale. In this study, we apply it to the case of the Greater Paris Metropolitan area. Using geographically weighted regression, we explore the spatial heterogeneity of the effect of digital entrepreneurial ecosystems on the location quotient of information and communication technology firms with fewer than 10 employees. The results highlight a positive link between the DEI and the location quotient of small ICT firms. In particular, the aspects of both ATTitudes and CAPacities (i.e., urbanization economies, Human Development Index, density of incubators, accounting and financial services, and fiber optic coverage) appear to have a significant effect on a suburban scale.

Clusters facing a crisis could have devastating effects on the economic conditions of the regions. Therefore, it is important to study how resilience works in the lives of clusters. The purpose of the current study is to more quantitatively understand the life path of the growth and decline of industrial clusters by verifying actual patterns. Also, it is to explain why these patterns were formed by qualitatively analyzing the process of utilizing resilience. The main contribution to the field of the lifecycle of clusters would be proving the theoretical concepts with data of the entire official industrial clusters in South Korea for 2 decades. Although previous works have attempted to define life paths by classifying the groups, most of their cases only dealt with one or two cases, making it difficult to generalize to a theory that can explain all types of clusters. This research used South Korean data as representative data for classification by analyzing the 1375 industrial clusters for 20 years. The trend of their life paths was calculated using a classic time-series decomposition method, and dynamic time series warping was adopted to measure the similarity between the paths. The -medoids method from an unsupervised machine learning technique was adopted to classify the data. They were classified into three types: Malmo-type, Silicon Valley-type, and Detroit-type. The same classification method can be applied to other countries. Through this classification, the necessary or weak determinants of resilience in their clusters can be found. By making up for these shortcomings, continuous growth can be achieved.

We developed a spatial computable general equilibrium model of South Korea to assess the spatial spillover effects of the COVID-19 pandemic on South Korea's regional economic growth patterns. The model measures a wide range of economic losses, including human health costs at the city and county level, through an analysis of regional producers' profit maximization on the supply side and regional households' utility maximization on the demand side. The model's findings showed that if the level of spatial interaction decreases by 10% as a result of social distancing policies, the national gross domestic product drops by 0.815-0.864%. This loss in economic growth can be further decomposed into 0.729% loss in agglomeration effect, 0.080-0.130% loss in health effect associated with medical treatment and premature mortality, and 0.005% loss in labor effect. The results of the models and simulations shed light on not only the epidemiological effects of social distancing interventions, but also their resultant economic consequences. This ex-ante evaluation of social distancing measures' effects can serve as a guide for future policy decisions made at both the national and regional level, providing policymakers with the tools for tailored solutions that address both regional economic circumstances and the spatial distribution of COVID-19 cases.

Patriotism-as an ambivalent attitude towards the nation-has less exclusionary characteristics than nationalism and regional identification, because it does not require comparisons and hierarchies. What is less clear, however, is how to explain the positive evaluation of patriotism in the wider population. The article analyses the positive relationship of patriotism with nationalism and regional identification in 29 national and 421 regional contexts. The paper clearly shows that different factors explain the positive evaluation of patriotism and the mind-set of patriotism itself. While a nationalist attitude and regional identification at the individual level are strongly associated with a positive evaluation of patriotism and patriotism itself, institutionalised forms of regional autonomy are shown to be insignificant for the evaluation of patriotism and ambivalent for patriotism itself at the context level. The article concludes by discussing these results in the context of a Janus-faced nature of regional identification that can contribute to an inclusive society as much as to a nationalist-chauvinist attitude and which has so far been overlooked in regional science.

This paper presents a simulation exercise undertaken with a newly available regional general equilibrium model for the Spanish region of Andalusia. The exercise is intended to assess the structural adjustment processes and impacts on the Andalusian economy directly induced by the dramatic fall in tourism expenditure which occurred in the year 2020, due to the prevention measures implemented because of the COVID-19 pandemic. We also undertake a preliminary evaluation of the impact on some environmental indicators, such as greenhouse gases emissions and air pollutants. The key insight emerging from our analysis is that the COVID crumbling of tourism demand reduces the environmental pressure but also generates very relevant distributional consequences. We believe that these insights are not peculiar to Andalusia but could be extended to many other regions in the world, especially those similar in terms of magnitude of the shock, economic structure, and labor market. We illustrate the latter point by contrasting Andalusia with a set of South-East Asian countries.

We examine the trajectory of regional income dynamics in Colombia. Using data on all 33 Colombian departments from 2000 to 2016, we employ extensions of (spatial) Markov chains, space-time mobility measures, along with a fully weighted version of the distribution analysis approach. By considering these extensions, our analysis enables us to answer questions such as whether the role of spatial context influences the distributional dynamics of Colombian departments, or the magnitude of the moderating effect of department's population. The inclusion of additional measures such as the asymptotic half-life of convergence provides additional results, informing on how long it would take to reach the hypothetical long-run distribution of per capita income. Results, which are reported for both pre- and post-2008 trends, complement previous literature on regional economic convergence in a relevant South American context, showing stronger convergence patterns when controlling for the population living in each department. The patterns do not particularly intensify when controlling for spatial spillovers, since the role of spatial context was already playing a relevant role from the beginning of the period analyzed. Therefore, although the ergodic distributions show a conditional-convergence pattern, addressing the problems of spatial exclusion fully, persistent polarization among geographical departments and populations, along with the relevant core-periphery gaps, still requires the design and implementation of specific policies.

Regional science has, in its great history since the 1950s, made a decisive contribution to a better scientific understanding of spatial development issues and dynamics and to a more effective implementation of knowledge-based regional policy in many countries of the world, in both developed and developing nations on our planet. This special issue of the annals of regional science, titled "Spotlight on the Region", celebrates the scholarly importance and impact of the late Roger Stough on regional science. The issue is comprised of fourteen self-standing on regional and urban development and highlights the critical importance of regional and urban dimensions in sustainable development. They confirm once more the seminal significance of the contributions of one of the great giants in regional science, Roger Stough.

This paper presents a simultaneous equation, knowledge and perception-based averting behavior model of health risk caused by air pollution, with application to the Jinchuan mining area, China. Three types of averting behavior are distinguished: (a) purchases of purifying equipment, plants, or masks; (b) purchases of preventive or curing medication or food; and (c) adjustment of daily outdoor activities. Two types of perceived health risk are distinguished: (a) risk due to the intensity of exposure and (b) risk caused by the hazardousness of pollutants. The estimations show that an increase in perceived air pollution of two or more days a week leads to a restriction of outdoor activities of approximately 90 min per person per week. Another result is that the average annual household expenditure on air filters, foods, or medicines is 206.25 CNY (US$ 31.73) to prevent the hazardousness of air pollution. The total willingness to pay for air quality improvement is 2.95% of annual net household income. Because air quality improving investments can only be implemented in the medium or long run, daily disclosure of air quality is an adequate short-run policy handle to assist residents to take the right kind and level of risk-reducing actions.

In this paper, we present results of a land-use forecasting model that we calibrated with vast geo-referenced data of a major metropolitan area. Each land parcel includes information concerning regulations indicating permitted land-uses as well as the certain characteristics of existing buildings. Data concerning all real estate transactions include information about the assets and the price of the exchanges. Based on these data we estimated the spatial dynamics of land values in the metropolitan area over time and identified locations experiencing development pressures. This analysis allows us to forecast plausible futures of the urban spatial configuration. Taking the approach one step further, we propose simulations motivated by the natural experiment of COVID 19. We assumed that part of the behavioral changes observed during the pandemic will endure. The resulting simulations provide forecasts of the future spatial structure of the metropolitan area. Comparing the actual and the forecasted scenarios we interpret the spatial dynamics of the city as they would be if a business-as-usual-pre-Covid-19 scenario is realized, and possible trend changes if the impact of the pandemic is long lasting.

In this paper, the relocation decisions of manufacturing plants across the NUTS-3 regions of the German economy are investigated. A relocation decision concerns whether a plant (an incumbent) moves its location from one region to another over a given time period or whether it remains in the same region. This decision is distinct from a location decision (of a start-up). To analyze the relocations of plants, the rich information of the official German regional statistics as well as the official German firm statistics that are maintained by the German Federal Statistical Office and the Statistical Offices of the Federal States is exploited for the first time. Both pull and push factors that influence relocation decisions are investigated. The results reveal that, in particular, regional road infrastructure and accessibility of regions as well as the quality of the available labor force positively affect the decision to relocate a plant in the German economy. A reduction of 10% in travel time by road to reach the three nearest agglomeration centers leads to an increase in relocation probability of about 9.5% on average. Policy implications involve the need for improvement of accessibility and infrastructure as well as incentives to support human capital in order to attract businesses to move to a region.