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Cycling is cheaper, healthier and, in urban environments, often faster than other modes of transport . Nevertheless, many individuals do not cycle even for short distances . This publication aims to explain why commuters differ in their decisions as to whether or not to cycle. Results indicate that the individual (day-to-day) choice to commute by bicycle is affected by personal attitudes towards cycling to work, social norms, the work situation, weather conditions and trip characteristics. In addition, the book provides evidence that different groups of bicycle commuters exist: non-cyclists, part-time cyclists and full-time cyclists. The mode choice of individuals within these groups depends partly on a number of different factors. Non-cyclists seem not to cycle because they consider it impractical, either due to the distance involved, their need to transport goods, the need for a car during office hours or a negative subjective norm. The decision to cycle among part-time or full-time cyclists is also affected by these factors, but additional factors can be identified. Finally, the day-to-day choice to cycle is based on work characteristics, weather conditions and trip characteristics. Part-time cyclists who cycle only occasionally are encouraged by pleasant weather conditions, while frequent cyclists are found to be discouraged by more practical barriers, such as where they need to work on a particular day.

ABSTRACT  This paper argues that search theory is a useful addition to the way economists and geographers have approached the study of commuting behavior. This is illustrated by showing that introduction of a spatial element into the standard model of job search leads to the prediction of critical isochrones. Moreover, in the context of an urban economy with decentralized employment, the spatial search model predicts excess commuting. Search theory also suggests that regression toward the mean may play a confusing role in data describing the development of commutes over time, such as has been used in recent empirical work. Finally, the paper develops a simple spatial equilibrium search model in which employers set their wages optimally and searchers determine their reservation wages optimally in mutually consistent ways. The spatial element is crucial for the existence of such an equilibrium in which reservation wages of all searchers and wages set by all employers are identical.

The article presents the scale of such a phenomenon as commuting according to the data of the All-Russian Population Census 2020 and Labor Force Sample Survey by Rosstat. The authors examined and systematized the consequences of commuting, which can be represented at three levels: at the level of territory, employer and employee, which can have both negative and positive impacts. For the recipient territory, commuting migrants become a source of labor resources and tax revenue that can be assessed positively. Increase in the burden on the transport infrastructure, the environment, and inaccuracies in assessing the demographic potential can be considered as conditionally negative. At the level of the employer, commuting solves stuffing problems; commuting migrants do not have a special status, so the employer may bear the risks of violating labor discipline, which are regulated in a general manner. With regard to the level of worker, assessment of the consequences depends on the life context, which determines the balance of advantages and costs of such an employment strategy, namely: wage size, position and status, duration of movement and distance to work, family circumstances, necessary or voluntary character of trips. In the final part of the article, the authors present a methodology for assessing the economic consequences of long-distance commuting for Russian regions.

We examine the effects of differences in income tax rates on commuting times within multi-state MSAs. Our theoretical model introduces a border into a model of an urban area and shows that differences in average tax rates distort commute times and interstate commutes. Empirically examining multi-state MSAs allows us to exploit tax policy discontinuities while holding fixed other characteristics. We identify large effects on commuting times for affluent households and homeowners in MSAs in which taxes are based on the state of residence. We discuss how the model and empirical design can be used to study other policy differences.

Abstract
People care about crime, with the spatial distribution of both actual and perceived crime affecting the local amenities from living in different areas and residential decisions. The literature finds that crime tends to happen close to the offender's residence, but does not clearly establish whether this is because the location of likely offenders and crime opportunities are close to each other, whether more local crimes are likely to be solved or whether there is a high commuting cost for criminals. We use a rich administrative dataset from one of the biggest UK police forces to disentangle these hypotheses, proposing a procedure for controlling for the selection bias induced by the fact that an offender's location is only known when they are caught. We find that the cost of distance is very high, especially for crimes without any financial gain. For property crimes, we find a similar cost of distance to commuting for legal work. We also investigate how local socio-economic characteristics affect both the number of criminals and the number of crimes.