Michael P. Cameron

Several studies have investigated the association between socio-economic factors and household solar photovoltaic energy adoption. However, the extent to which household income and education contribute to the adoption of clean energy and discourage the use of dirty energy sources remains relatively unexplored. Therefore, using nationally representative data from the Pakistan Social and Living Measurement Survey 2018-19, we first applied Tukey’s test to examine the income and education differences among the main lighting source adopters. We then applied multinomial logit regression to estimate the odds of choosing each main lighting source. Lastly, we run simulations to identify the role of income and education in the adoption of the main lighting source. The results suggest that income and education significantly differ among the adopters of dirty fuel, solar energy, and electricity from the grid. Income, education, number of rooms in the home, and male household head are all positively associated with the adoption of solar energy in comparison to dirty fuels. Our simulation analysis shows that, as income and education of the household increase, grid-sourced electricity remains the most preferred source of lighting. This suggests that shifting electricity production from fossil fuels to cleaner, sustainable, and renewable resources would reduce the adverse environmental, health, and economic impact. Moreover, our results suggest that solar photovoltaic energy may be more suitable for rural areas where the transmission cost of electricity is high. Our findings are crucial for developing targeted policies to meet the UN’s seventh Sustainable Development Goal, which focuses on ensuring affordable and clean energy in Pakistan and other developing countries.

Introduction: India has the second largest HIV epidemic in the world. Despite successes in epidemic control at the population level, a concentrated epidemic persists among gay and other men who have sex with men (MSM). However, India lags in implementation of biomedical prevention technologies, such as HIV pre-exposure prophylaxis (PrEP). In order to inform scale-up of new HIV prevention technologies, including those in the development pipeline, we assessed willingness to use oral PrEP, rectal microbicides, and HIV vaccines, and choices among product characteristics, among MSM in two major Indian cities. Methods: A cross-sectional survey was conducted with a discrete choice experiment (DCE), an established methodology for quantitively estimating end-user preferences in healthcare. Survey participants were randomly assigned to one of three questionnaire versions, each of which included a DCE for one prevention technology. Participants were recruited using chain-referral sampling by peer outreach workers, beginning with seeds in community-based organizations and public sex environments, in Chennai and Mumbai. DCE data were analyzed using random-parameters (mixed) logit (RPL) models. Results: Among participants (n = 600), median age was 25 years, with median monthly income of INR 9,000 (~US$125). Nearly one-third (32%) had completed a college degree and 82% were single/never married. A majority of participants (63%) reported condomless anal sex in the past month. The acceptability of all three products was universally high (≥90%). Across all three products, four attributes were significant predictors of acceptability—with efficacy consistently the most important attribute, and in decreasing order of preference, side-effects, dosing schedule, and venue. MSM varied in their preferences for product attributes in relation to their levels of education and income, and engagement in sex work and HIV risk behavior. Conclusion: This study provides empirical evidence to facilitate the integration of end users’ preferences throughout design, testing, and dissemination phases of HIV prevention technologies. The findings also suggest action points and targets for interventions for diverse subgroups to support the effectiveness of combination HIV prevention among MSM in India.

In this paper we focus on modelling and forecasting gross interregional migration in a way that can be embedded within multiregional population projections. We revisit, and apply, a family of spatial interaction models first formulated during the 1970s. The classic gravity model—in which migration is positively related to the populations of sending and receiving areas, but inversely related to various types of spatial friction associated with migrating between them—is a special case that is nested within this family of models. We investigate which member of the family of models gives the best fit when modelling five-year migration flows between the 66 Territorial Authorities (TAs) of Aotearoa New Zealand, using 2013 and 2018 census data. We find that predicting migration between two TAs can be improved by taking into account, firstly, an index of the ‘draw’ from all other TAs when modelling out-migration of any TA and, secondly, an index of the ‘competitiveness’ of a TA vis-à-vis all other TAs when modelling in-migration of any TA. We highlight the properties of the statistically-preferred model by simulating the impact on internal migration of an exogenous increase in Auckland’s population. In this model, such a population change affects not only migration flows from and to Auckland, but also migration between other TAs. The usefulness of this approach for population projections is assessed by forecasting the 2013–18 migration matrix by means of 2013 census data only. In this specific case, the model outperforms the classic gravity model in terms of forecasting gross migration, but not net migration.

Pets are an important part of many peoples’ lives, and provide mental, physical and emotional benefits. However, the costs of pet ownership have received little attention. We investigate the association between pet ownership and wage income using data from the 2018 General Social Survey. We hypothesise that pet ownership may negatively influence income by lowering labour mobility and positively influence income by garnering valuable psychosocial attributes. We analyse interactions between pet ownership and education, pet ownership and housing tenure, and pet ownership and race to further investigate the potential labour mobility channel. Overall, we find that pet ownership decreases wage income and that these negative effects are larger for groups where mobility effects are likely higher.

Media bias is an important and underexplored feature of the economics of information. In this article, the author outlines two models that can be used to illustrate media bias in a policy-oriented undergraduate economics or public policy course. The models rely on relatively simple and intuitive underlying assumptions and draw on related empirical research. They do not require extensive mathematical derivations, although the models can easily be extended for more mathematically-inclined students. The models are useful in linking economic theory and empirical research in a context that undergraduate students can relate to and in which they often have direct experience. The models also can be used to motivate a range of discussions on media and competition policy.

The structural ageing of the population is one of the key global trends of the 21st Century. In this paper, we outline four axioms that, along with easy interpretability, we believe should underpin a theoretically valid measure of structural ageing: (1) population size invariance; (2) strong dominance; (3) weak dominance; and (4) age sensitivity. We then present a class of structural ageing indices that satisfy the axioms and are easily interpretable, with root-mean-squared-age (RMSA) as our preferred measure within the class. Using historical and cross-national data from the World Population Prospects, state-level data from the US Census Bureau, and local-authority-level data from New Zealand, we demonstrate that our preferred measure is correlated with conventional measures of structural ageing. Nevertheless, in each case there are large disparities in ranking for some countries, states, or local authorities between the different measures. These ranking disparities could be highly consequential for the allocation of resources, particularly between states or local areas within countries. Our proposed class of measures may help to avoid these disparities due to their axiomatically-consistent nature. Finally, we present considerations for future extensions of this important work, including the development of equivalent measures based on prospective age.