Customs compliance and the power of imagination

This paper studies the role of beliefs about own performance or appearance for compliance at the customs. In an experiment in which underreporting has a higher expected payoff than truthful reporting we find: a large share, about 15-20 percent of the subjects, is more compliant if they have reason to imagine that their performance influences their subjective audit probability. In contrast, we do not find evidence for individuals who believe that by their personal performance they can reduce the subjective probability for an audit. Our results suggest that the power of imagination, i.e. the role of second-order beliefs in the process of customs declarations is important and may potentially be used to improve customs and tax compliance. --Customs,tax compliance,audit probability,second-order beliefs

Customs Compliance and the Power of Imagination

This paper studies the role of beliefs about own performance or appearance for compliance at the customs. In an experiment in which underreporting has a higher expected payoff than truthful reporting we find: a large share, about 15-20 percent of the subjects, is more compliant if they have reason to imagine that their performance influences their subjective audit probability. In contrast, we do not find evidence for individuals who believe that by their personal performance they can reduce the subjective probability for an audit. Our results suggest that the power of imagination, i.e. the role of second-order beliefs in the process of customs declarations is important and may potentially be used to improve customs and tax compliance.customs, tax compliance, audit probability, second-order beliefs

Sweeps in time:Leveraging the joint distribution of branch lengths

Current methods of identifying positively selected regions in the genome are limited in two key ways: the underlying models cannot account for the timing of adaptive events and the comparison between models of selective sweeps and sequence data is generally made via simple summaries of genetic diversity. Here, we develop a tractable method of describing the effect of positive selection on the genealogical histories in the surrounding genome, explicitly modeling both the timing and context of an adaptive event. In addition, our framework allows us to go beyond analyzing polymorphism data via the site frequency spectrum or summaries thereof and instead leverage information contained in patterns of linked variants. Tests on both simulations and a human data example, as well as a comparison to SweepFinder2, show that even with very small sample sizes, our analytic framework has higher power to identify old selective sweeps and to correctly infer both the time and strength of selection. Finally, we derived the marginal distribution of genealogical branch lengths at a locus affected by selection acting at a linked site. This provides a much-needed link between our analytic understanding of the effects of sweeps on sequence variation and recent advances in simulation and heuristic inference procedures that allow researchers to examine the sequence of genealogical histories along the genome

Inferring population history from genealogies

This thesis investigates a range of genealogical approaches to making quantitative inferences about the spatial and demographic history of populations with application to two insect systems: A local radiation of high alpine ground beetles (Carabidae) in the genus Trechus and major refugial populations of the oak gall parasitoid Cecidostiba fungosa (Pteromalidae). i) Summary statistics, which make explicit use of genealogical information are developed. Using simulations their power to detect a history of population growth is shown to be higher than that of standard measures such as Tajima’s D for single and multilocus data. The improvement arises from the fact that in contrast to pairwise measures, the new statistics are minimally confounded with the topology. ii) A Bayesian method to reconstructing character states is used to infer the Pleistocene history of populations of high alpine Trechus sampled along a singlemountain range frommitochondrial and nuclear data. Despite evidence for some incomplete lineage sorting, a simple model of a series of extreme founder events out of two refugia during or before the last glacial maximum provides a good fit to the data. iii) A large set of exon-primed, intron-spanning (EPIC) loci is developed for Hymenoptera from EST and genomic data. Amplification success is screened on a range of Hymenopteran species associated with two insect-plant interactions: Oak galls and figs. iv) Borrowing model-based approaches developed to quantify species divergence, the new EPIC loci are used to investigate the relationships between three major European refugia in the oak gall parasitoid C. fungosa. These analyses reveal strong support for an eastern origin, effective ancestral population sizes comparable to insect model species and evidence for recent population divergence during the last interglacial. The results also suggest that there is significant information in minimal samples provided a large number of loci are available. v) Results for the probability of gene tree topologies are derived for a model of divergence with gene flow between three populations. I outline how the asymmetries in the frequency of gene tree topologies may be used to distinguish incomplete lineage sorting from migration and discuss the results in the context of next generation sequence data from D. melanogaster and humans and Neanderthals

The genome sequence of the northern brown argus, aricia artaxerxes (Fabricius, 1793)

We present a genome assembly from an individual Aricia artaxerxes (the northern brown argus; Arthropoda; Insecta; Lepidoptera; Lycaenidae). The genome sequence is 458 megabases in span. Most of the assembly (99.99%) is scaffolded into 23 chromosomal pseudomolecules, including the assembled Z sex chromosome. The mitochondrial genome has also been assembled and is 15.8 kilobases in length. Gene annotation of this assembly on Ensembl has identified 12,688 protein coding genes