Hedonic regression for digital cameras in Germany

Standard measures of consumer price inflation are based on a bundle of representative goods. It is well known that this approach might overstate inflation for new products and products with fast increasing quality. For this reason, hedonic adjustment methods have been proposed and introduced in official statistics for some products like personal computers. In this contribution, we consider the application of a hedonic regression to digital cameras, which have been introduced in the product bundle of the German consumer price index in 2003 – so far without hedonic quality adjustment. We present first results on hedonic price measurement for digital cameras in Germany for the time period 1999 to 2004. The results are based on data sampled from public interest journals and advertisements. --Hedonic regression,hedonic price index,quality adjustment

Stochastic tunneling and metastable states during the somatic evolution of cancer

Tumors initiate when a population of proliferating cells accumulates a certain number and type of genetic and/or epigenetic alterations. The population dynamics of such sequential acquisition of (epi)genetic alterations has been the topic of much investigation. The phenomenon of stochastic tunneling, where an intermediate mutant in a sequence does not reach fixation in a population before generating a double mutant, has been studied using a variety of computational and mathematical methods. However, the field still lacks a comprehensive analytical description since theoretical predictions of fixation times are only available for cases in which the second mutant is advantageous. Here, we study stochastic tunneling in a Moran model. Analyzing the deterministic dynamics of large populations we systematically identify the parameter regimes captured by existing approaches. Our analysis also reveals fitness landscapes and mutation rates for which finite populations are found in long-lived metastable states. These are landscapes in which the final mutant is not the most advantageous in the sequence, and resulting metastable states are a consequence of a mutation-selection balance. The escape from these states is driven by intrinsic noise, and their location affects the probability of tunneling. Existing methods no longer apply. In these regimes it is the escape from the metastable states that is the key bottleneck; fixation is no longer limited by the emergence of a successful mutant lineage. We used the so-called Wentzel-Kramers-Brillouin method to compute fixation times in these parameter regimes, successfully validated by stochastic simulations. Our work fills a gap left by previous approaches and provides a more comprehensive description of the acquisition of multiple mutations in populations of somatic cells.Comment: 33 pages, 7 figure

International price discovery in the presence of microstructure noise

This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares

Tell-tale tails: A data driven approach to estimate unique market information shares

The trading of securities on multiple markets raises the question of each market's share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions. Thereby we resolve the main drawback of the widely used Hasbrouck (1995) methodology which merely delivers upper and lower bounds of a market's information share. When these bounds diverge, as is the case in many applications, informational leadership becomes blurred. We show how fat tails and tail dependence of price changes, which emerge as a result of differences in market design and liquidity, can be exploited to estimate unique information shares. The empirical application of the new methodology emphasizes the leading role of the credit derivatives market compared to the corporate bond market in pricing credit risk during the pre-crisis period. --price discovery,information share,fat tails,tail dependence,liquidity,credit risk

International price discovery in the presence of market microstructure effects

This paper addresses and resolves the problems caused by microstructure effects when measuring the relative importance of home and U.S. market in the price discovery process of internationally cross listed stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, this entails a potential bias of estimated information shares induced by microstructure effects. We propose a modified approach that relies on distributional assumptions and yields unique and unbiased information shares. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been severely underestimated to date. Moreover, we find that rather than stock specific factors, market design determines information shares. --international cross-listings,market microstructure effects,price discovery

Context-dependency and complexity of plant-herbivore interactions in fragmented forests

For centuries, humans extensively used and profoundly altered ecosystems at a global scale, which is assumed to have serious implications for ecosystem functioning and human-well being. Amongst others, it has been suggested that deforestation and the associated process of forest fragmentation have severe and multi- faceted consequences entailing an overall loss in biodiversity, the disruption of trophic interactions and impaired functioning of forest ecosystems. Eventually, consequences of forest fragmentation may threaten ecosystem stability and ecosystem services of forests. Insect herbivores are known to play a key role in all plant-based ecosystems, i.e. they affect growth, fitness and reproduction of plant individu als and thus, have been suggested to influence plant species persistence as well as the structure and composition of plant communities. Hence, changes in insect herbivore communities due to forest fragmentation, particularly increased insect herbiv ore abundances, may cause an overall increase in the susceptibility of plants to insect herbivory with severe consequences for forest ecosystems. So far, there is no consensus regarding the implications of forest fragmentation for plant-herbivore interactions. Findings of previous studies indicate inconsistent responses of insect herbivores to forest fragmenta ion and the ultimate degree of insect herbivory in fragmented forest landscapes varies correspondingly. With this thesis, I aimed to unravel the discrepancy in the above findings by addressing the context-dependency and the complex nature of antagonistic plant-herbivore interactions, which may both cause spatial variability. To address the context-dependency of plant-herbivore interactions, I conducted two field studies in a subtropical forest landscape in southern KwaZulu-Natal (South Africa). The first field study aimed at disentangling potential interactive effects of forest fragmenta tion on the landscape scale and local tree diversity on plant-herbivore interactions and the associated process of insect herbivory. With the second field study, I examined the trophic control of herbivorous insects through insectivorous birds along a gradient of increasing forest fragmentation including ultimate consequences for the degree of insect herbivory. Finally, to address the complexity of plant-herbivore interactions, I performed a comprehensive meta-analysis on plant responses to insect herbivory and thus, feedback effects on insect herbivores as well as the potential of plants to mediate the outcome of plant-herbivore interactions. Overall, findings obtained in the three studies support the assumption that both context-dependency and the complexity of plant-herbivore interactions may contribute to the discrepancy in findings of empirical studies on plant-herbivore interactions in fragmented forests. In more detail, underlying mechanisms of the effect of forest fragmentation include complex interactive effects of co-occurring environmen tal drivers as well as multitrophic cascades which mediate the properties of plant-herbivore interactions in fragmented forests. Hence, without considering the environmental context of plant-animal interac tions, attempts to unravel the impact of human-driven landscape modifications such as forest fragmentation are prone to lead to biased conclusions. Similarly, plant responses to herbivory have the potential to mediate the outcome plant-herbivore interactions through compensatory growth and induced defence. More specifically, full compensatory growth may blur differences in the feeding pressure of in sect herbivores on plants and thus, studies on plant- herbivore interactions that solely monitor the de gree of herbivory may easily overlook differences in insect herbivore abundances. Moreover, herbivo ry-induced production of defence compounds may create feedback effects and thus, alter the compo-sition of insect herbivore communities with potential consequences for the degree of insect herbivo ry. Hence, plants have to be considered as active counterparts of insect herbivores and thus, have to be incorporated in considerations on effects of human-driven landscape modifications on plant-herbivore interactions. Findings of the two field studies further show that forest fragmentation has a major impact on forest ecosystems and that the consequences are multi- faceted. In addition to shifts in the community composition and species loss, my results demonstrate that forest fragmentation further interferes with trophic interactions involving multiple trophic levels. In more detail, increasing forest fragmentation altered the community composition of insect herbivores and thereby, diminished the significance of patterns in local tree diversity for insect herbivores. Further, increasing forest fragmentation triggered a trophic cascade beginning with the loss of insectivorous birds, disrupting the trophic control of insect herbivores and ultimately, resulting in increased levels of insect herbivory, which may have serious implications for plant communities. The latter finding additionally reveals that species with similar ecological functions are not necessarily redundant. In contrast, I argue that it is highly likely that species loss is tightly linked to a loss in the ecological function of species. Moreover, I conclude that we have to consider that disturbance-resistant species may not necessarily compensate for the loss of species and maintain the ecological function. Altogether, I could show that forest fragmentation poses a serious threat to forest communities and trophic interactions and thereby, puts ecosystem functioning and services of forests at high risk. In terms of conservation management, I argue that it is essential to reduce forest fragmentation to a minimum and maintain a network of continuous forests that are well-connected with smaller forest remnants at the landscape scale. This in turn, will benefit species persistence, species migration and recolonization as well as trophic interactions and thereby, ensure species and ecosystem functioning. Likewise, considering the patterns in the findings derived from the meta-analysis may offer man agement implications, e.g. for grassland and forest ecosystems. For instance, alleviated herbivory allows plants to fully recover from herbivory (or artificial defoliation), but may simultaneously maintain plant diversity of grasslands. Additionally, despite short-term benefits for plant growth, high nutrient availability and thus, fertilization or increased nitrogen deposition may not necessarily mitigate effects of herbivory. To conclude, holistic research approaches that view species and their trophic interactions from different angles as well as consistent advances in ecological research tools (e.g. interactive effects, communitiy-level and landscape scale approaches, multitrophic network approaches, meta-analyses in ecology) may contribute to a more comprehensive understanding of the dynamics that structure communities and trophic networks. Both a more holistic view as well as methodological progress in turn, will help to develop effective management implications in order to sustainably maintain functioning and stability of forest ecosystems as well as the services they provide in a human-modified world

Bimodal activation of different neuron classes with the spectrally red-shifted channelrhodopsin chimera C1V1 in Caenorhabditis elegans

The C. elegans nervous system is particularly well suited for optogenetic analyses of circuit function: Essentially all connections have been mapped, and light can be directed at the neuron of interest in the freely moving, transparent animals, while behavior is observed. Thus, different nodes of a neuronal network can be probed for their role in controlling a particular behavior, using different optogenetic tools for photo-activation or –inhibition, which respond to different colors of light. As neurons may act in concert or in opposing ways to affect a behavior, one would further like to excite these neurons concomitantly, yet independent of each other. In addition to the blue-light activated Channelrhodopsin-2 (ChR2), spectrally red-shifted ChR variants have been explored recently. Here, we establish the green-light activated ChR chimera C1V1 (from Chlamydomonas and Volvox ChR1′s) for use in C. elegans. We surveyed a number of red-shifted ChRs, and found that C1V1-ET/ET (E122T; E162T) works most reliable in C. elegans, with 540–580 nm excitation, which leaves ChR2 silent. However, as C1V1-ET/ET is very light sensitive, it still becomes activated when ChR2 is stimulated, even at 400 nm. Thus, we generated a highly efficient blue ChR2, the H134R; T159C double mutant (ChR2-HR/TC). Both proteins can be used in the same animal, in different neurons, to independently control each cell type with light, enabling a further level of complexity in circuit analyses

Hedonic regression for digital cameras in Germany

Standard measures of consumer price inflation are based on a bundle of representative goods. It is well known that this approach might overstate inflation for new products and products with fast increasing quality. For this reason, hedonic adjustment methods have been proposed and introduced in official statistics for some products like personal computers. In this contribution, we consider the application of a hedonic regression to digital cameras, which have been introduced in the product bundle of the German consumer price index in 2003 - so far without hedonic quality adjustment. We present first results on hedonic price measurement for digital cameras in Germany for the time period 1999 to 2004. The results are based on data sampled from public interest journals and advertisements

Gap Filling in the Plant Kingdom---Trait Prediction Using Hierarchical Probabilistic Matrix Factorization

Plant traits are a key to understanding and predicting the adaptation of ecosystems to environmental changes, which motivates the TRY project aiming at constructing a global database for plant traits and becoming a standard resource for the ecological community. Despite its unprecedented coverage, a large percentage of missing data substantially constrains joint trait analysis. Meanwhile, the trait data is characterized by the hierarchical phylogenetic structure of the plant kingdom. While factorization based matrix completion techniques have been widely used to address the missing data problem, traditional matrix factorization methods are unable to leverage the phylogenetic structure. We propose hierarchical probabilistic matrix factorization (HPMF), which effectively uses hierarchical phylogenetic information for trait prediction. We demonstrate HPMF's high accuracy, effectiveness of incorporating hierarchical structure and ability to capture trait correlation through experiments.Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012