Remittances and subjective well-being: A static versus dynamic panel approach to happiness

Using all five waves of the National Income Dynamics Study (NIDS) panel dataset, we examine the effect of domestic remittances on the static and dynamic subjective well-being (SWB) of recipient individuals in South Africa, by using a random effects ordered probit model that accounts for individual heterogeneity. Moreover, we check the robustness of our static model results by making use of an instrumental variable for migrants’ remittances. Two major empirical findings emerge from this paper: firstly, domestic remittances are consistently found to have a positive and statistically significant impact on the happiness of recipient individuals. Moreover, this finding persists in both the static and dynamic panel models. Secondly, the coefficient on lagged SWB (derived from the dynamic model) is found to be positive and statistically significant, confirming that SWB today is significantly influenced by SWB in the past.

Pension Reform and Life-Course Distributions

In order to carry out micro-level analyses of economic behavior, and of the influence of public policy over time, such as examining the redistributive impact of the tax-benefit system over the life course, it is necessary to utilize a panel dataset with many years of data. In general, such datasets are not available, either because the analysis relates to the future, as in the case of pension projections, or because existing datasets do not cover sufficiently-long time horizons. Instead, therefore, dynamic microsimulation models are used to synthetically generate a hypothetical panel. In this chapter, we discuss some of the methodological issues related to the construction of a dynamic microsimulation model. Building upon the work in Chapter 8, we develop the concept of income-generation models to model changing income distributions over time. We also introduce the concept of alignment, which allows us to calibrate the aggregate results of income-generation models to external control totals. The chapter discusses methodological issues related to dynamic modelling, such as static versus dynamic ageing, behavioural versus statistical simulation, discrete versus continuous time, open versus closed models, steady state versus forecasted projections, cohort versus population models, and validation. Methodologically, we discuss the calibration method known as alignment. From a measurement issue point of view, we describe how to quantify inter-temporal redistribution, between and within life trajectories. We conclude by undertaking a simulation exercise, modelling the distribution of income over the lifetime, and developing and applying a dynamic microsimulation model using a Chile case study.

The specious interaction of time and numerosity perception

Magnitude information is essential to create a representation of the external environment and successfully interact with it. Duration and numerosity, for example, can shape our predictions and bias each other (i.e. the greater the number of people queuing, the longer we expect to wait). While these biases suggest the existence of a generalized magnitude system, asymmetric effects (i.e. numerosity affecting duration but not vice versa) challenged this idea. Here, we propose that such asymmetric integration depends on the stimuli used and the neural processing dynamics they entail. Across multiple behavioural experiments employing different stimulus presentation displays (static versus dynamic) and experimental manipulations known to bias numerosity and duration perceptions (i.e. connectedness and multisensory integration), we show that the integration between numerosity and time can be symmetrical if the stimuli entail a similar neural time-course and numerosity unfolds over time. Overall, these findings support the idea of a generalized magnitude system, but also highlight the role of early sensory processing in magnitude representation and integration.

Effectiveness of Green Warning Lights with Different Flashing Patterns for Winter Maintenance Operations

Snow removal activities are performed by roadway agencies to enhance winter mobility and safety. Slower travel speeds during these operations, combined with low visibility and reduced pavement friction, mean that safety and collision avoidance remain a persistent concern. Many studies have implemented signing and lighting technologies to improve the visibility of snowplows. Although a few studies have evaluated the use of different colors on snowplows, there is no rigorous study that evaluates the potential impacts of using green warning lights for winter maintenance operations. This study, therefore, investigates the impacts of various warning light configurations on the visibility of snowplows, with the focus on green lights. To this end, 37 warning light configurations are designed using various color combinations (green and amber), and flashing patterns (single and quad) on the back (LED), the top (beacon), or both, of snowplows. These configurations are evaluated to identify the most effective configurations. Three sets of experiments are designed and implemented: static, dynamic, and weather to evaluate the visibility effectiveness in different contexts: day versus night, clear versus snowy weather, and static versus dynamic scenarios. Human subjects are employed to conduct the experiments and the test results are evaluated using statistical analyses. The conspicuity during the day time and glare during the night time are statistically different among various configurations. In addition, adding green lights with a single flash pattern to amber warning lights improves the conspicuity, while keeping the glare at an acceptable level relative to configurations using only amber.