The Smile behind the Sales Counter: Soviet Shop Assistants on the Road to Full Communism

The article explores the role of sales assistants in Soviet retail trade in the 1960s, who were overwhelmingly female. It investigates the causes of and remedies for what was widely perceived to be rude and grudging service. Soviet customers and officials felt entitled to a positive consumer experience, and managers and trade union officials agonized over the ways to promote and incentivize “service with a smile.” In addition to the poor performance of Soviet manufacturing, which produced goods that were difficult to sell, other factors included poor training and minimal education, low prestige, and low pay. The article also highlights the continuities in retail sales culture from the 1920s to the 1960s, but emphasizes the increasing role assigned to “emotional labor” as important and necessary work by sales workers

Are there asymmetries in the effects of training on the conditional male wage distribution?

Recent studies have used quantile regression (QR) techniques to estimate the impact of education on the location, scale and shape of the conditional wage distribution. In our paper we investigate the degree to which work-related training – another important form of human capital – affects the location, scale and shape of the conditional wage distribution. Using the first six waves of the European Community Household Panel, we utilise both ordinary least squares and QR techniques to estimate associations between work-related training and wages for private sector men in ten European Union countries. Our results show that, for the majority of countries, there is a fairly uniform association between training and hourly wages across the conditional wage distribution. However, there are considerable differences across countries in mean associations between training and wages

Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data

Considerable effort has been exercised in estimating mean returns to education while carefully considering biases arising from unmeasured ability and measurement error. Recent work has investigated whether there are variations from the “mean” return to education across the population with mixed results. We use an instrumental variables estimator for quantile regression on a sample of twins to estimate an entire family of returns to education at different quantiles of the conditional distribution of wages while addressing simultaneity and measurement error biases. We test whether there is individual heterogeneity in returns to education and find that: more able individuals obtain more schooling and that higher ability individuals (those further to the right in the conditional distribution of wages) have higher returns to schooling consistent with a non-trivial interaction between schooling and unobserved abilities in the generation of earnings. The estimated returns are never lower than 9 percent and can be as high as 13 percent at the top of the conditional distribution of wages but they vary significantly only along the lower to middle quantiles. Our findings may have meaningful implications for the design of educational policies

Changes in extreme sea-levels in the Baltic Sea

In a climate change context, changes in extreme sea-levels rather than changes in the mean are of particular interest from the coastal protection point of view. In this work, extreme sea-levels in the Baltic Sea are investigated based on daily tide gauge records for the period 1916–2005 using the annual block maxima approach. Extreme events are analysed based on the generalised extreme value distribution considering both stationary and time-varying models. The likelihood ratio test is applied to select between stationary and non-stationary models for the maxima and return values are estimated from the final model. As an independent and complementary approach, quantile regression is applied for comparison with the results from the extreme value approach. The rates of change in the uppermost quantiles are in general consistent and most pronounced for the northernmost stations

Global distribution and bioclimatic characterization of alpine biomes

Although there is a general consensus on the distribution and ecological features of terrestrial biomes, the allocation of alpine ecosystems in the global biogeographic system is still unclear. Here, we delineate a global map of alpine areas above the treeline by modelling regional treeline elevation at 30 m resolution, using global forest cover data and quantile regression. We then used global datasets to 1) assess the climatic characteristics of alpine ecosystems using principal component analysis, 2) define bioclimatic groups by an optimized cluster analysis and 3) evaluate patterns of primary productivity based on the normalized difference vegetation index. As defined here, alpine biomes cover 3.56 Mkm(2) or 2.64% of land outside Antarctica. Despite temperature differences across latitude, these ecosystems converge below a sharp threshold of 5.9 degrees C and towards the colder end of the global climatic space. Below that temperature threshold, alpine ecosystems are influenced by a latitudinal gradient of mean annual temperature and they are climatically differentiated by seasonality and continentality. This gradient delineates a climatic envelope of global alpine biomes around temperate, boreal and tundra biomes as defined in Whittaker's scheme. Although alpine biomes are similarly dominated by poorly vegetated areas, world ecoregions show strong differences in the productivity of their alpine belt irrespectively of major climate zones. These results suggest that vegetation structure and function of alpine ecosystems are driven by regional and local contingencies in addition to macroclimatic factors

Traditional Eastern European diet and mortality: prospective evidence from the HAPIEE study

PURPOSE: Cardiovascular disease (CVD) and cancer mortality rates in Eastern Europe are among the highest in the world. Although diet is an important risk factor, traditional eating habits in this region have not yet been explored. This analysis assessed the relationship between traditional dietary pattern and mortality from all-causes, CVD and cancer in Eastern European cohorts. METHODS: Data from the Health, Alcohol and Psychosocial factors in Eastern Europe prospective cohort were used, including participants from Russia, Poland and the Czech Republic. Based on food frequency questionnaire data, we constructed an Eastern European diet score (EEDS) from nine food groups which can be considered as traditional in this region. The relationship between categorical (low, moderate, high) and continuous (range 0-18) EEDS and mortality was estimated with Cox-regression. RESULTS: From 18,852 eligible participants, 2234 died during follow-up. In multivariable adjusted models, participants with high adherence to the traditional Eastern European diet had significantly higher risk of all-cause (HR 1.23; 95% CI 1.08-1.42) and CVD (1.34; 1.08-1.66) deaths compared to those with low adherence. The association with cancer mortality was only significant in Poland (high vs. low EEDS: 1.41; 1.00-1.98). From the specific EEDS components, high consumption of lard was significantly positively related to all three mortality outcomes, while preserved fruit and vegetable consumption showed consistent inverse associations. CONCLUSION: Our results suggest that traditional eating habits may contribute to the poor health status, particularly the high CVD mortality rates, of populations in Eastern Europe. Adequate public health nutritional interventions in this region are essential

Value at Risk models with long memory features and their economic performance

We study alternative dynamics for Value at Risk (VaR) that incorporate a slow moving component and information on recent aggregate returns in established quantile (auto) regression models. These models are compared on their economic performance, and also on metrics of first-order importance such as violation ratios. By better economic performance, we mean that changes in the VaR forecasts should have a lower variance to reduce transaction costs and should lead to lower exceedance sizes without raising the average level of the VaR. We find that, in combination with a targeted estimation strategy, our proposed models lead to improved performance in both statistical and economic terms