Purpose The purpose of this paper is to analyze the time-allocation decisions of individuals who work from home (i.e. teleworkers), and compare them with their commuter counterparts. Design/methodology/approach Using data from the American Time Use Survey for the years 2003–2015, the authors analyze the time spent working, and the timing of work, of both commuters and teleworkers. Findings Results show that teleworkers devote 40 percent less time to market work activities than do commuters, and less than 60 percent of teleworkers work at “regular hours,” vs around 80 percent of their commuter counterparts. Using information from the Well-being Module for the years 2012 and 2013, the authors find that male teleworkers experience lower levels of negative feelings while working than do commuters. Originality/value This paper addresses the timing of work of workers working from home; and the instant well-being experienced, exploiting information at diary level.

In this paper, we analyze the commuting behavior of workers in the United States, with a focus on the differences between employees and the self-employed. Using the American Time Use Survey for the years 2003-2014, our empirical results show that employees spend 7.22 more minutes per day to commuting than their self-employed counterparts, which represents a difference of 17 percent of the average commuting time of employed workers. This is especially prevalent in non-metropolitan areas, and it also appears to depend on the size of the population of the area of residence. Our results suggest that there is a complex relationship between urban form and the commuting behavior of workers.

We analyze whether efficiency wages operate in urban labor markets, within the framework proposed by Ross and Zenou, in which shirking at work and leisure are assumed to be substitutes. We use unique data from the American Time Use Survey (ATUS) that allow us to analyze the relationships between leisure, shirking, commuting, employment, and earnings. We confirm that shirking and leisure are substitutes, and present an estimate of this relationship, representing the only empirical test of the relationship between a worker's time endowment and shirking at work. Our findings point to the existence of efficiency wages in labor markets.

Sustainable commuting (SC) usually refers to environmentally friendly travel modes, such as public transport (bus, tram, subway, light rail), walking, cycling, and carpooling. The double aim of the paper is to summarize relevant prior results in commuting from a social approach, and to provide new, international empirical evidence on carpooling as a specific mode of sustainable commuting. The literature shows that certain socio-demographic characteristics clearly affect the use of non-motorized alternatives, and compared to driving, well-being is greater for those using active travel or public transport. Additionally, this paper analyzes the behavior of carpooling for commuting, using ordinary least squares (OLS) models, which have been estimated from the Multinational Time Use Study (MTUS) for the following countries: Bulgaria, Canada, Spain, Finland, France, Hungary, Italy, South Korea, the United Kingdom, and the United States. Results indicate that carpooling for commuting is not habitual for workers, as less than 25% of the total time from/to work by car is done with others on board. With respect to the role of the socio-demographic characteristics of individuals, our evidence indicates that age, gender, education, being native, and household composition may have a cross-country, consistent relationship with carpooling participation. Given that socializing is the main reason for carpooling, in the current COVID-19 pandemic, carpooling may be decreasing and, consequently, initiatives have been launched to show that carpooling is a necessary way to avoid crowded modes of transport. Thus, the development of high-occupancy-vehicle (HOV) lanes by local authorities can increase carpooling, and draw attention to the economic and environmental benefits of carpooling for potential users.

In this paper, we propose an algorithmic approach based on resampling and bootstrap techniques to measure the importance of a variable, or a set of variables, in econometric models. This algorithmic approach allows us to check the real weight of a variable in a model, avoiding the biases of classical tests, and to select the more relevant variables, or models, in terms of predictability, by reducing dimensions. We apply this methodology to the Global Entrepreneurship Monitor data for the year 2014, to analyze the individual and national-level determinants of entrepreneurial activity, and compare results with a forward selection approach, also based on resampling predictability, and a standard forward stepwise selection process. We find that our proposed techniques offer more accurate results, which show that innovation and new technologies, peer effects, the socio-cultural environment, entrepreneurial education at University, R&D transfers, and the availability of government subsidies, are among the most important predictors of entrepreneurial behavior.