Dickey-fuller tests with trend

The Dickey-Fuller [rcirc]_τ and [pcirc]_τ tests are based on a regression of a variable on its lagged value, an intercept, and a trend term. The distributions of both statistics depend on the coefficient of the trend, and the usual Dickey-Fuller tabulations assume that this coefficient equals zero. This paper provides tabulations for the case that the coefficient of the trend is non-zero.     

Digital platforms and the changing freelance workforce in the Russian Federation: A ten-year perspective

This article traces the development of the online labour market in the Russian Federation and across the wider post-Soviet space. The authors draw on the unique data of four waves of an online survey for 2009, 2011, 2014 and 2019 on the leading Russian-speaking general-purpose platform for creative and knowledge-based work. The results shed light on key trends, such as spatial decentralization, occupational diversification, feminization, maturing, rising educational attainment and educational mismatch, the consolidation of freelance careers, platformization and legalization. The article discusses these findings and their potential policy implications for the future development of online platform work in the Russian Federation.     

Bayesian Development of a Dose‐Response Model for Aspergillus fumigatus and Invasive Aspergillosis

Invasive aspergillosis (IA) is a major cause of mortality in immunocompromized hosts, most often consecutive to the inhalation of spores of Aspergillus. However, the relationship between Aspergillus concentration in the air and probability of IA is not quantitatively known. In this study, this relationship was examined in a murine model of IA. Immunosuppressed Balb/c mice were exposed for 60 minutes at day 0 to an aerosol of A. fumigatus spores (Af293 strain). At day 10, IA was assessed in mice by quantitative culture of the lungs and galactomannan dosage. Fifteen separate nebulizations with varying spore concentrations were performed. Rates of IA ranged from 0% to 100% according to spore concentrations. The dose‐response relationship between probability of infection and spore exposure was approximated using the exponential model and the more flexible beta‐Poisson model. Prior distributions of the parameters of the models were proposed then updated with data in a Bayesian framework. Both models yielded close median dose‐responses of the posterior distributions for the main parameter of the model, but with different dispersions, either when the exposure dose was the concentration in the nebulized suspension or was the estimated quantity of spores inhaled by a mouse during the experiment. The median quantity of inhaled spores that infected 50% of mice was estimated at 1.8 × 10⁴ and 3.2 × 10⁴ viable spores in the exponential and beta‐Poisson models, respectively. This study provides dose‐response parameters for quantitative assessment of the relationship between airborne exposure to the reference A. fumigatus strain and probability of IA in immunocompromized hosts.     

Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification

Imbalances in covariates between treatment groups are frequent in observational studies and can lead to biased comparisons. Various adjustment methods can be employed to correct these biases in the context of multi-level treatments (> 2). Analytical challenges, such as positivity violations and incorrect model specification due to unknown functional relationships between covariates and treatment or outcome, may affect their ability to yield unbiased results. Such challenges were expected in a comparison of fire-suppression interventions for preventing fire growth. We identified the overlap weights, augmented overlap weights, bias-corrected matching and targeted maximum likelihood as methods with the best potential to address those challenges. A simple variance estimator for the overlap weight estimators that can naturally be combined with machine learning is proposed. In a simulation study, we investigated the performance of these methods as well as those of simpler alternatives. Adjustment methods that included an outcome modeling component performed better than those that focused on the treatment mechanism in our simulations. Additionally, machine learning implementation was observed to efficiently compensate for the unknown model specification for the former methods, but not the latter. Based on these results, we compared the effectiveness of fire-suppression interventions using the augmented overlap weight estimator.     

Probabilistic Modeling of the Fate of Listeria Monocytogenes in Diced Bacon During the Manufacturing Process

To assess the impact of the manufacturing process on the fate of Listeria monocytogenes, we built a generic probabilistic model intended to simulate the successive steps in the process. Contamination evolution was modeled in the appropriate units (breasts, dice, and then packaging units through the successive steps in the process). To calibrate the model, parameter values were estimated from industrial data, from the literature, and based on expert opinion. By means of simulations, the model was explored using a baseline calibration and alternative scenarios, in order to assess the impact of changes in the process and of accidental events. The results are reported as contamination distributions and as the probability that the product will be acceptable with regards to the European regulatory safety criterion. Our results are consistent with data provided by industrial partners and highlight that tumbling is a key step for the distribution of the contamination at the end of the process. Process chain models could provide an important added value for risk assessment models that basically consider only the outputs of the process in their risk mitigation strategies. Moreover, a model calibrated to correspond to a specific plant could be used to optimize surveillance.     

Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process

In this paper we study a hybrid system with both manufacturing and remanufacturing. The inventory control strategy we use in the manufacturing loop is an automatic pipeline, inventory and order based production control system (APIOBPCS). In the remanufacturing loop we employ a Kanban policy to represent a typical pull system. The methodology adopted uses control theory and simulation. The aim of the research is to analyse the dynamic (as distinct from the static) performance of the specified hybrid system. Dynamics have implications on total costs in terms of inventory holding, capacity utilisation and customer service failures. We analyse the parameter settings to find preferred “nominal”, “fast” and “slow” values in terms of system dynamics performance criteria such as rise time, settling time and overshoot. Based on these parameter settings, we investigate the robustness of the system to changes in return yield and the manufacturing/remanufacturing lead time. Our results clearly show that the system is robust with respect to the system dynamics performance and the remanufacturing process can help to improve system dynamics performance. Thus, the perceived benefits of remanufacturing of products, both environmentally and economically, as quoted in the literature are found not to be detrimental to system dynamics performance when a Kanban policy is used to control the remanufacturing process.     

Inference of a hidden spatial tessellation from multivariate data: application to the delineation of homogeneous regions in an agricultural field

Summary.  In a precision farming context, differentiated management decisions regarding fertilization, application of lime and other cultivation activities may require the subdivision of the field into homogeneous regions with respect to the soil variables of main agronomic significance. The paper develops an approach that is aimed at delineating homogeneous regions on the basis of measurements of a categorical and quantitative nature, namely soil type and resistivity measurements at different soil layers. We propose a Bayesian multivariate spatial model and embed it in a Markov chain Monte Carlo inference scheme. Implementation is discussed using real data from a 15-ha field. Although applied to soil data, this model could be relevant in areas of spatial modelling as diverse as epidemiology, ecology or meteorology.     

Quality of life in rural areas: processes of divergence and convergence

In Germany, processes can be observed that have long been out of keeping with the principle of equality of opportunity. Unemployment is concentrated in the structurally weak peripheral areas, in Eastern Germany in particular; emigration of young and better-educated people to the West is not diminishing, but contrary to expectation is again on the increase; aging processes have set in already, and when it comes to the provision of infrastructure, e.g. in the field of professional training, some regions are already suffering from considerable problems. These difficulties are frequently interpreted as differences between East and West and are explained away as problems resulting from reunification, such as the deindustrialization and restructuring of the economy and the enormous decline in the birth rate in Eastern Germany. Although these problems cannot just be attributed to social transformation and the birth rate crisis alone, being subject to more general processes of intensified globalization and the aging of society, the increasing regional disparities are rarely considered in the overall context of regional development patterns throughout Germany. Moreover, the difficulty of even obtaining data for purposes of comparison generally means that an international yardstick is lacking when regional developments are analyzed. The present study investigates regional disparities over a period of time in the light of subjective and objective indicators of the quality of life for individuals. To this end, we make use of data from the Wohlfahrtssurvey [Welfare Survey] from 1978 to 2001, among other sources. On the basis of the Euromodule that has been established at the WZB, we compare current regional patterns in Germany with those in other European countries. This approach makes it possible to provide information on the scale of regional disparities in various different countries, and to identify privileged and handicapped regions with reference to standards of living and the sense of wellbeing. The study’s findings show that, in the past 25 years, welfare in Western Germany has evened out at a higher level, but currently a trend towards increasing economic disparity is discernible. In comparison with other European countries, on the other hand, the differences (regional differences) within Germany are comparatively slight.