RESUMO
Increasingly, rural households in developing countries are shopping for food online, and the COVID-19 pandemic has accelerated this trend. In parallel, dietary guidelines worldwide recommend eating a balanced and healthy diet. With this in mind, this study explores whether online food shopping boosts dietary diversity-defined as the number of distinct food groups consumed-among rural households in China. Because people choose to shop for food online, it is important to account for the self-selection bias inherent in online food shopping. Accordingly, we estimate the treatment effects of online food shopping on dietary diversity using the endogenous switching model with a count outcome variable. The results indicate that online food shopping increases dietary diversity by 7.34%. We also find that education, asset ownership, and knowing the government's dietary guidelines are the main factors driving rural households' decisions to shop for food online.
RESUMO
During the COVID-19 pandemic lockdown, the number of people shopping online has increased worldwide, and New Zealand is no exception. To date, little is known about the online shopping behaviours of New Zealanders in a pandemic environment. This paper provides the first attempt by exploring the factors affecting online shopping frequency in New Zealand, a country widely regarded as a paragon of excellence for containing the COVID-19 pandemic. A Poisson regression model is utilized to analyze data collected through an online survey between July and November 2020. The empirical results show that people's online shopping frequency is positively affected by payment convenience, competitive pricing, living in the city, and the number of children. The perceived effectiveness of the government's action in combating COVID-19, having poor past online shopping experiences, and being married reduce online shopping frequency.
RESUMO
Tourism research is replete with applications of univariate time-series decomposition techniques: multivariate frameworks have been largely ignored. In this paper, we employ a common-feature-based, multivariate trend-cycle decomposition approach to examine common trends and common cycles amongst the demand for New Zealand tourism originating in Australia, China, the US, the UK, as well as other tourism-importing countries considered as one group: Others. Upon isolating trends and cycles in tourism demand from these countries, we find evidence of strong long-term comovement: they share one common trend. We also find evidence of short-term comovement, albeit to a lesser extent: four common cycles emerge; the cyclical patterns in tourism demand from Australia, China, the US, and Others are strongly correlated.
