111 research outputs found
Modeling the choices of individual decision-makers by combining efficient choice experiment designs with extra preference information
We show how to combine statistically efficient ways to design discrete choice experiments based on random utility theory with new ways of collecting additional information that can be used to expand the amount of available choice information for modeling the choices of individual decision makers. Here we limit ourselves to problems involving generic choice options and linear and additive indirect utility functions, but the approach potentially can be extended to include choice problems with non-additive utility functions and non-generic/labeled options/attributes. The paper provides several simulated examples, a small empirical example to demonstrate proof of concept, and a larger empirical example based on many experimental conditions and large samples that demonstrates that the individual models capture virtually all the variance in aggregate first choices traditionally modeled in discrete choice experiments
On Covid-19: new implications of job task requirements and spouse's occupational sorting
The Covid-19 pandemic has disrupted working life in many ways, the negative consequences of which may be distributed unevenly under lockdown regulations. In this paper, we construct a new set of pandemic-related indices from the Occupational Information Network (O*NET) using factor analysis. The indices capture two key dimensions of job task requirements: (i) the extent to which jobs can be adaptable to work from home; and (ii) the degree of infection risk at workplace. The interaction of these two dimensions help identify which groups of workers are more vulnerable to income losses, and which groups of occupations pose more risk to public health. This information is crucial for both designing appropriate supporting programs and finding a strategy to reopen the economy while controlling the spread of the virus. In our application, we map the indices to the labor force survey of a developing country, Thailand, to analyze these new labor market risks. We document differences in job characteristics across income groups, at both individual and household levels. First, low income individuals tend to work in occupations that require less physical interaction (lower risk of infection) but are less adaptable to work from home (higher risk of income/job loss) than high income people. Second, the positive occupational sorting among low-income couples amplifies these differences at the household level. Consequently, low-income families tend to face a disproportionately larger risk of income/job loss from lockdown measures. In addition, the different exposure to infection and income risks between income groups can play an important role in shaping up the timing and optimal strategies to unlock the economy
Agroecology and Health: Lessons from Indigenous Populations.
Purpose of reviewThe article aims to systematize and disseminate the main contributions of indigenous ancestral wisdom in the agroecological production of food, especially in Latin America. For this purpose, it is necessary to ask whether such knowledge can be accepted by academia research groups and international forums as a valid alternative that could contribute to overcome the world's nutritional problems.Recent findingsAlthough no new findings are being made, the validity of ancestral knowledge and agroecology is recognized by scientific research, and by international forums organized by agencies of the United Nations. These recommend that governments should implement them in their policies of development, and in the allocation of funds to support these initiatives. Agroecology and ancestral knowledge are being adopted by a growing number of organizations, indigenous peoples and social groups in various parts of the world, as development alternatives that respond to local needs and worldviews. Its productive potential is progressively being recognized at an international level as a model that contributes to improve the condition of people regarding nutritional food
Molecular cloning and analysis of functional envelope genes from human immunodeficiency virus type 1 sequence subtypes A through G
Metabolic synergies in the biotransformation of organic and metallic toxic compounds by a saprotrophic soil fungus
The saprotrophic fungus Penicillium griseofulvum was chosen as model organism to study responses to a mixture of hexachlorocyclohexane (HCH) isomers (α-HCH, β-HCH, γ-HCH, δ-HCH) and of potentially toxic metals (vanadium, lead) in solid and liquid media. The P. griseofulvum FBL 500 strain was isolated from polluted soil containing high concentrations of HCH isomers and potentially toxic elements (Pb, V). Experiments were performed in order to analyse the tolerance/resistance of this fungus to xenobiotics, and to shed further light on fungal potential in inorganic and organic biotransformations. The aim was to examine the ecological and bioremedial potential of this fungus verifying the presence of mechanisms that allow it to transform HCH isomers and metals under different, extreme, test conditions. To our knowledge, this work is the first to provide evidence on the biotransformation of HCH mixtures, in combination with toxic metals, by a saprotrophic non-white-rot fungus and on the metabolic synergies involved
Spatial distribution and long-term persistence of Wolbachia-infected Aedes aegypti in the Mentari Court, Malaysia
Dengue is endemic in Malaysia, and vector control strategies are vital to reduce dengue transmission. The Wolbachia strain wAlbB carried by both sexes of Ae. aegypti was released in Mentari Court, a high-rise residential site, in October 2017 and stopped after 20 weeks. Wolbachia frequencies are still being monitored at multiple traps across this site, providing an opportunity to examine the spatiotemporal distribution of Wolbachia and mosquito density with respect to year, residential block, and floor, using spatial interpolation in ArcGIS, GLMs, and contingency analyses. In just 12 weeks, Wolbachia-infected mosquitoes were established right across the Mentari Court site with an overall infection frequency of >90%. To date, the Wolbachia frequency of Ae. aegypti has remained high in all areas across the site despite releases finishing four years ago. Nevertheless, the Wolbachia invaded more rapidly in some residential blocks than others, and also showed a relatively higher frequency on the eighth floor. The Ae. aegypti index tended to differ somewhat between residential blocks, whilst the Ae. albopictus index was relatively higher at the top and bottom floors of buildings. In Mentari Court, only a short release period was required to infiltrate Wolbachia completely and stably into the natural population. The results inform future releases in comparable sites in a dengue control programme
Phylodynamics of HIV-1 from a Phase III AIDS Vaccine Trial in Bangkok, Thailand
In 2003, a phase III placebo-controlled trial (VAX003) was completed in Bangkok, Thailand. Of the 2,546 individuals enrolled in the trial based on high risk for infection through injection drug use (IDU), we obtained clinical samples and HIV-1 sequence data (envelope glycoprotein gene gp120) from 215 individuals who became infected during the trial. Here, we used these data in combination with other publicly available gp120 sequences to perform a molecular surveillance and phylodynamic analysis of HIV-1 in Thailand.Phylogenetic and population genetic estimators were used to assess HIV-1 gp120 diversity as a function of vaccination treatment, viral load (VL) and CD4(+) counts, to identify transmission clusters and to investigate the timescale and demographics of HIV-1 in Thailand. Three HIV-1 subtypes were identified: CRF01_AE (85% of the infections), subtype B (13%) and CRF15_AE (2%). The Bangkok IDU cohort showed more gp120 diversity than other Asian IDU cohorts and similar diversity to that observed in sexually infected individuals. Moreover, significant differences (P<0.02) in genetic diversity were observed in CRF01_AE IDU with different VL and CD4(+) counts. No phylogenetic structure was detected regarding any of the epidemiological and clinical factors tested, although high proportions (35% to 50%) of early infections fell into clusters, which suggests that transmission chains associated with acute infection play a key role on HIV-1 spread among IDU. CRF01_AE was estimated to have emerged in Thailand in 1984.5 (1983-1986), 3-6 years before the first recognition of symptomatic patients (1989). The relative genetic diversity of the HIV-1 population has remained high despite decreasing prevalence rates since the mid 1990s.Our study and recent epidemiological reports indicate that HIV-1 is still a major threat in Thailand and suggest that HIV awareness and prevention needs to be strengthened to avoid AIDS resurgence
How to model consumer heterogeneity? Lessons from three case studies on SP and RP data
The structure of consumer taste heterogeneity in discrete choice demand models is important, as it drives the structure of own and cross-price elasticities of demand, and the pattern of competition between products. Here we compare performance of three leading discrete choice models, using three datasets with very different properties. The models are the mixed logit with normal heterogeneity (N-MIXL), the generalized multinomial logit (G-MNL) and the mixture-of-normals logit (MM-MNL). Which model is preferred depends on the context: G-MNL does an excellent job of capturing the sort of departures from normality that are prevalent in stated preference (SP) data. But MM-MNL can capture more general departures from normality that are prevalent in revealed preference (RP) data. The finding that the structure of consumer taste heterogeneity is very different in SP vs. RP data suggests that caution should be applied before using SP to answer questions about the distribution of taste heterogeneity in actual markets. In an application to RP data on demand for frozen pizza, we obtain the interesting result that when a variety of a brand raises its price, most of the lost market share goes to other brands (rather than alternative varieties of the same brand). This suggests modeling heterogeneity in tastes for varieties is quite important for understanding brand switching
Comparing alternative models of heterogeneity in consumer choice behavior
When modeling demand for differentiated products, it is vital to adequately capture consumer taste heterogeneity, But there is no clearly preferred approach. Here, we compare the performance of six alternative models. Currently, the most popular are mixed logit (MIXL), particularly the version with normal mixing (N-MIXL), and latent class (LC), which assumes discrete consumer types. Recently, several alternative models have been developed. The 'generalized multinomial logit' (G-MNL) extends N-MIXL by allowing for heterogeneity in the logit scale coefficient. Scale heterogeneity logit (S-MNL) is a special case of G-MNL with scale heterogeneity only. The 'mixed-mixed' logit (MM-MNL) assumes a discrete mixture-of-normals heterogeneity distribution. Finally, one can modify N-MIXL by imposing theoretical sign constraints on vertical attributes. We call this 'T-MIXL'. We find that none of these models dominates the others, but G-MNL, MM-MNL and T-MIXL typically outperform the popular N-MIXL and LC models. © 2012 John Wiley & Sons, Ltd
How to model consumer heterogeneity? Lessons from three case studies on SP and RP data
The structure of consumer taste heterogeneity in discrete choice demand models is important, as it drives the structure of own and cross-price elasticities of demand, and the pattern of competition between products. Here we compare performance of three leading discrete choice models, using three datasets with very different properties. The models are the mixed logit with normal heterogeneity (N-MIXL), the generalized multinomial logit (G-MNL) and the mixture-of-normals logit (MM-MNL). Which model is preferred depends on the context: G-MNL does an excellent job of capturing the sort of departures from normality that are prevalent in stated preference (SP) data. But MM-MNL can capture more general departures from normality that are prevalent in revealed preference (RP) data. The finding that the structure of consumer taste heterogeneity is very different in SP vs. RP data suggests that caution should be applied before using SP to answer questions about the distribution of taste heterogeneity in actual markets. In an application to RP data on demand for frozen pizza, we obtain the interesting result that when a variety of a brand raises its price, most of the lost market share goes to other brands (rather than alternative varieties of the same brand). This suggests modeling heterogeneity in tastes for varieties is quite important for understanding brand switching
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