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Register a new userHow happy are my neighbours? Modelling spatial spillover effects of well-being
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This article uses data of subjective Life Satisfaction aggregated to the community level in Canada and examines the spatial interdependencies and spatial spillovers of community happiness. A theoretical model of utility is presented. Using spatial econometric techniques, we find that the utility of community, proxied by subjective measures of life satisfaction, is affected both by the utility of neighbouring communities as well as by the latters average household income and unemployment rate. Shared cultural traits and institutions may justify such spillovers. The results are robust to the different binary contiguity spatial weights matrices used and to the various econometric models. Clusters of both high-high and low-low in Life Satisfaction communities are also found based on the Morans I test
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This paper aims to enhance our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multi-level models. To date, there have been numerous quantitative research studies of the happiness of individuals, based on single-level regression models, where typically a happiness index is related to a set of explanatory variables. There are also several single-level studies comparing aggregate happiness levels between countries. Nevertheless, there have been very few studies that attempt to simultaneously take into account variations in happiness and well-being at several different levels, such as individual, household, and area. Here, multilevel models are used with data from the British Household Panel Survey to assess the nature and extent of variations in happiness and well-being to determine the relative importance of the area (district, region), household and individual characteristics on these outcomes. Moreover, having taken into account the characteristics at these different levels in the multilevel models, the paper shows how it is possible to identify any areas that are associated with especially positive or negative feelings of happiness and well-being.
Travellers in autonomous vehicles (AVs) need not to walk to the destination any more after parking like those in conventional human-driven vehicles (HVs). Instead, they can drop off directly at the destination and AVs can cruise for parking autonomously. It is a revolutionary change that such parking autonomy of AVs may increase the potential parking span substantially and affect the spatial parking equilibrium. Given this, from urban planners perspective, it is of great necessity to reconsider the planning of parking supply along the city. To this end, this paper is the first to examine the spatial parking equilibrium considering the mix of AVs and HVs with parking cruising effect. It is found that the equilibrium solution of travellers parking location choices can be biased due to the ignorance of cruising effects. On top of that, the optimal parking span of AVs at given parking supply should be no less than that at equilibrium. Besides, the optimal parking planning to minimize the total parking cost is also explored in a bi-level parking planning design problem (PPDP). While the optimal differentiated pricing allows the system to achieve optimal parking distribution, this study suggests that it is beneficial to encourage AVs to cruise further to park by reserving less than enough parking areas for AVs.
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We examine how the institutional context affects the relationship between gender and opportunity entrepreneurship. To do this, we develop a multi-level model that connects feminist theory at the micro-level to institutional theory at the macro-level. It is hypothesized that the gender gap in opportunity entrepreneurship is more pronounced in low-quality institutional contexts and less pronounced in high-quality institutional contexts. Using data from the Global Entrepreneurship Monitor (GEM) and regulation data from the economic freedom of the world index (EFW), we test our predictions and find evidence in support of our model. Our findings suggest that, while there is a gender gap in entrepreneurship, these disparities are reduced as the quality of the institutional context improves.
Difference-in-differences estimation is a widely used method of program evaluation. When treatment is implemented in different places at different times, researchers often use two-way fixed effects to control for location-specific and period-specific shocks. Such estimates can be severely biased when treatment effects change over time within treated units. I review the sources of this bias and propose several simple diagnostics for assessing its likely severity. I illustrate these tools through a case study of free primary education in Sub-Saharan Africa.
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