Economics as an Experimental Science: Using Field Experiments to Test Models of Economic Behavior

Economics is limited by the fact that it is not an experimental science: our ability to experimentally test models of economic behavior is constrained by logistics and ethics. However, this view has been reshaped by the credibility revolution of the last two decades and the recent growth of randomized trials in developing countries, which have shown that many economic models can indeed be tested experimentally. Critics of this movement claim that experimental and quasi-experimental results do not generalize, and that such studies focus on convenient rather than important topics. It is possible to overcome this critique by running so-called "mechanism experiments" that are designed to test economic models. Economic theory can also help uncover the drivers of specific results, shedding light on whether they will generalize to other settings and why. This approach can address topics that are not directly amenable to experimentation, by running experiments that capture the same theoretical object in another context. This dissertation applies this approach to three first-order questions in development economics. The first chapter reassesses the standard economic model of risk compensation, which assumes that increases in risk cause people to become more careful. I show that risk-seeking, or fatalistic, behavior, can also be rational. I then use a randomized experiment to show that some southern Malawians respond fatalistically to HIV risks. The second chapter, written with Lasse Brune, examines how random variations in income timing affect expenditure and savings in southern Malawi. We show that lump-sum payments lead to increased savings, but, contrary to existing theoretical work and empirical evidence from developed countries, we find no evidence that exposure to tempting goods affects this result. The third chapter, written with Rebecca Thornton, studies a literacy program in Northern Uganda. When implemented at full cost, the program strongly improves learning. A reduced-cost version of the program also improves learning, but only for the most basic reading and writing skills – and actually harms the development of advanced writing skills. Our results cast doubt on typical cost-effectiveness calculations: the cheaper version is more cost-effective for basic skills, but the opposite is true for overall learning.PhDEconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/113639/1/jtkerwin_1.pd

Missing safer sex strategies in HIV Prevention: A call for further research

Despite the efforts of educators, public health officials, and HIV/AIDS prevention experts, condom promotion has failed to stop the HIV epidemic in most of sub- Saharan Africa and most researchers and policy makers have focused on risk reductions for interventions for penetrative sex. We consider another HIV prevention option: female-to-male oral sex (fellatio). Extensive medical evidence indicates that fellatio is roughly as protective against HIV transmission as vaginal sex with a condom, and much safer than unprotected sex, but it is rarely emphasized in HIV prevention curricula. Moreover, available data on the practice of oral sex in Africa suggests that the practice is very rare compared to the practice in the United States. This paper reviews some of the existing evidence on the efficacy and prevalence of oral sex, discusses the potential of this safer sex strategy for mitigating the spread of HIV in Africa, and stresses the need for further research

The Defense Metabolite, Allyl Glucosinolate, Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway

14 páginas, 8 figuras y 3 tablas.Glucosinolates (GSLs) play an important role in plants as direct mediators of biotic and abiotic stress responses. Recent work is beginning to show that the GSLs can also inducing complex defense and growth networks. However, the physiological significance of these GSL-induced responses and the molecular mechanisms by which GSLs are sensed and/or modulate these responses are not understood. To identify these potential mechanisms within the plant and how they may relate to the endogenous GSLs, we tested the regulatory effect of exogenous allyl GSL application on growth and defense metabolism across sample of Arabidopsis thaliana accessions. We found that application of exogenous allyl GSL had the ability to initiate changes in plant biomass and accumulation of defense metabolites that genetically varied across accessions. This growth effect was related to the allyl GSL side-chain structure. Utilizing this natural variation and mutants in genes within the GSL pathway we could show that the link between allyl GSL and altered growth responses are dependent upon the function of known genes controlling the aliphatic GSL pathway.This work was funded by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Programme (PIOF-GA-2010-275286), the NSF DBI grant 820580 to DK, the NSF MCB grant 1330337 to DK, the USDA National Institute of Food and Agriculture, Hatch project number CA-D-PLS-7033-H to DK and by the Danish National Research Foundation (DNRF99) grant to DK and MB.Peer reviewe

Natural genetic variation in <i>Arabidopsis thaliana</i> defense metabolism genes modulates field fitness

Natural populations persist in complex environments, where biotic stressors, such as pathogen and insect communities, fluctuate temporally and spatially. These shifting biotic pressures generate heterogeneous selective forces that can maintain standing natural variation within a species. To directly test if genes containing causal variation for the Arabidopsis thaliana defensive compounds, glucosinolates (GSL) control field fitness and are therefore subject to natural selection, we conducted a multi-year field trial using lines that vary in only specific causal genes. Interestingly, we found that variation in these naturally polymorphic GSL genes affected fitness in each of our environments but the pattern fluctuated such that highly fit genotypes in one trial displayed lower fitness in another and that no GSL genotype or genotypes consistently out-performed the others. This was true both across locations and within the same location across years. These results indicate that environmental heterogeneity may contribute to the maintenance of GSL variation observed within Arabidopsis thaliana. DOI: http://dx.doi.org/10.7554/eLife.05604.00

Deterministic Lateral Displacement:Challenges and Perspectives

The advent of microfluidics in the 1990s promised a revolution in multiple industries from healthcare to chemical processing. Deterministic lateral displacement (DLD) is a continuous-flow microfluidic particle separation method discovered in 2004 that has been applied successfully and widely to the separation of blood cells, yeast, spores, bacteria, viruses, DNA, droplets, and more. Deterministic lateral displacement is conceptually simple and can deliver consistent performance over a wide range of flow rates and particle concentrations. Despite wide use and in-depth study, DLD has not yet been fully elucidated or optimized, with different approaches to the same problem yielding varying results. We endeavor here to provide up-to-date expert opinion on the state-of-art and current fundamental, practical, and commercial challenges with DLD as well as describe experimental and modeling opportunities. Because these challenges and opportunities arise from constraints on hydrodynamics, fabrication, and operation at the micro- and nanoscale, we expect this Perspective to serve as a guide for the broader micro- and nanofluidic community to identify and to address open questions in the field

Serum Metabolomics Reveals Higher Levels of Polyunsaturated Fatty Acids in Lepromatous Leprosy: Potential Markers for Susceptibility and Pathogenesis

Leprosy is an infectious disease caused by the obligate intracellular bacterium Mycobacterium leprae. M. leprae infects the skin and nerves, leading to disfigurement and nerve damage, with the severity of the disease varying widely. We believe there are multiple factors (genetic, bacterial, nutritional and environmental), which may explain the differences in clinical manifestations of the disease. We studied the metabolites in the serum of infected patients to search for specific molecules that may contribute to variations in the severity of disease seen in leprosy. We found that there were variations in levels of certain lipids in the patients with different bacterial loads. In particular, we found that three polyunsaturated fatty acids (PUFAs) involved in the inhibition of inflammation were more abundant in the serum of patients with higher bacterial loads. However, we do not know whether these PUFAs originated from the host or the bacteria. The variations in the metabolite profile that we observed provide a foundation for future research into the explanations of how leprosy causes disease

Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions