From immersion to intention? Exploring advances in prosocial storytelling

Little empirical work has explored the psychological processes triggered by immersive technologies and how they might lead to more effective desirable prosocial outcomes. Thus, the current study explores two different modalities for presenting 360 videos—YouTube and head-mounted display (HMD)—as strategies for engaging audiences with cause-related stories. Across three stories, using these technologies led to the highest levels of presence, but there was no association between presence and increased attitudes towards the story content. Only narrative engagement impacted prosocial attitudes towards the video content. Data suggest that regardless of the technology used, telling engaging narratives that increase the viewer's self-efficacy is key to behavioral intentions—immersive technologies help viewers feel closer to the physical location of the narrative, but not the narrative itself.     

Equilibrium Search Models and the Transition From School To Work

This paper applies the Burdett–Mortensen (1998) equilibrium search model to study the school to work transitions of U.S. high school graduates. We consider the case of discrete firm heterogeneity and provide a computational method to obtain the MLE. Our results show that unemployed blacks receive fewer offers than whites and employed blacks are more likely to lose their jobs. Importantly, employed blacks and whites receive job offers at the same rate. Assigning the whites' search parameters to the blacks and re-solving reveals that 75 percent of the observed wage differential is explained by the job destruction rate differences.     

Horseshoe Regularisation for Machine Learning in Complex and Deep Models1

Since the advent of the horseshoe priors for regularisation, global–local shrinkage methods have proved to be a fertile ground for the development of Bayesian methodology in machine learning, specifically for high-dimensional regression and classification problems. They have achieved remarkable success in computation and enjoy strong theoretical support. Most of the existing literature has focused on the linear Gaussian case; for which systematic surveys are available. The purpose of the current article is to demonstrate that the horseshoe regularisation is useful far more broadly, by reviewing both methodological and computational developments in complex models that are more relevant to machine learning applications. Specifically, we focus on methodological challenges in horseshoe regularisation in non-linear and non-Gaussian models, multivariate models and deep neural networks. We also outline the recent computational developments in horseshoe shrinkage for complex models along with a list of available software implementations that allows one to venture out beyond the comfort zone of the canonical linear regression problems.     

Cross‐boundary working: Implications for HRM theory,methods, and practice

Major changes have taken place in work organisation, which originate predominantly from working across organisational boundaries. This paper argues for a more sophisticated approach to HRM that includes three types of cross‐boundary working, that is, intraorganisational, interorganisational, and transorganisational. Herein lies the contribution of our paper; we argue that we cannot assume a transition from one type of working to another because cross‐boundary forms of working coexist. We also need to understand the tensions of this simultaneity at the levels of the organisation/network, HRM systems, and the individual. We consider the impact of the simultaneous existence of these types of cross‐boundary working for the following: (a) theory, especially the development of HRM systems; (b) methods, including an activity‐based unit of analysis; and (c) practice, where we pay attention to the challenges of control, collaboration, and consistency.     

The Economics of Lockdown

In this paper, we suggest an approach to analysing policies relating to the COVID-19 pandemic. We discuss the formulation of policy and sketch how the approach can be applied to different specific challenges as policymakers try to make difficult choices for managing the pandemic and protecting the economy and society.     

Public transit and air pollution: Evidence from Canadian transit strikes

Little is known about the causal impacts of public transit on local air pollution. Exploiting variation in transit availability resulting from transit strikes in 18 Canadian cities between 1974 and 2011, this study identifies the short-run effect of public transit on air pollution. Our findings indicate that transit leads to a 3.5 part per billion increase in nitrogen oxides while having no statistically significant effect on carbon monoxide or PM_2.5. Estimates are robust to a series of specification tests and magnitudes are consistent with a calibrated simulation model. Overall, the results suggest that expanding the current configuration of public transit in North American cities is unlikely to yield improvements in local air quality.     

If You Build It Nearby and Keep the Price Low,Will They Come? Large-Scale Evidence on the Relative Roles of Access and Quality in Use of Healthcare in Low-and Middle-Income Countries

Health policy reform often emphasises improving access to healthcare. Recent studies highlight the role healthcare quality plays in determining which health providers individuals use and health outcomes. Yet, there is little standardised large-scale evidence on the importance of quality of care relative to access in determining healthcare use. This paper examines the relative roles of access and quality in whether individuals seek healthcare and how these vary with socioeconomic status in a sample of over 250,000 national household survey respondents from low- and middle-income countries. My results suggest that quality is as large a barrier as access. Among quality barriers, drug availability is as large a barrier as provider availability. Analyses of the barriers-socioeconomic status gradients indicate that the quality-SES gradient is much less steep than the access-SES gradient, highlighting that increasing incomes may not be sufficient to address quality barriers and that supply-side interventions may be necessary.     

Do Medium-scale Farms Improve Market Access Conditions for Zambian Smallholders?

This study is motivated by the need to understand how the rise of medium-scale farms in Africa is affecting small-scale farm households. Survey evidence over the past decade has shown a dramatic rise in the prevalence of ‘medium’ sized farms between 5 and 100 hectares, but smaller farms still constitute the vast majority of farms and rural households. Prior evidence highlights a co-evolution between the concentration of landholdings, surplus production volumes, and entry of larger traders into the market. Whether these changes tend to impact on smallholders negatively, crowding them out of markets, for example, or positively, potentially opening new marketing channels, is an empirical question. Using a multi-stage model for maize market participation in Zambia, we find that in areas where medium-scale farms are growing, even the smaller farms are becoming more likely to sell maize, more likely to sell to the private sector, more likely to sell to larger traders, and expected sales amongst sellers are higher. On balance, the growth of medium-scale farms and large-scale traders seems to have positive spillover effects on nearby smallholder marketing options.     

Manufacturing output and extreme temperature: Evidence from Canada

This paper analyzes the effects of extreme temperature on manufacturing output using a data set covering the universe of manufacturing establishments in Canada from 2004 to 2012. Extreme temperature can affect manufacturing activity directly through its impact on labour productivity and indirectly through a change in demand for products. Using a panel fixed effects method, our results suggest a non-linear relationship between outdoor extreme temperature and manufacturing output. Each day where outdoor mean temperatures are below $-18$ °C or above 24 °C reduces annual manufacturing output by 0.18% and 0.11%, respectively, relative to a day with mean temperature between 12 ° and 18 °C. In a typical year, extreme temperatures, as measured by the number of days below $-18$ °C or above 24 °C, reduce annual manufacturing output by 2.2%, with extreme hot temperatures contributing the most to this impact. Given the predicted change in climate for the mid- and end of century, we predict annual manufacturing output losses due to extreme temperature to range between 2.8% and 3.7% in mid-century and 3.7% and 7.2% in end of century.