Benefits of preventive dentistry in children: Cost factors and public policy

Dental caries in children is now recognized as a preventable disease. The use of fluoride and sealants has produced a major reduction in caries prevalence among school aged children in the United States and other countries. A portion of the child population who are educationally and socioeconomically disadvantaged are not fully receiving these benefits. Public policy, insurance and medicaid groups must be made aware of these preventative measures and strategies developed to implement them.     

Economics, sociobiology and behavioral psychology on preferences

Economists have become increasingly interested in hypotheses from sociobiology as a source of inspiration for filling gaps in the economic model of behavior. To avoid borrowing eclectically and arbitrarily from neighboring disciplines, this paper attempts to outline in a systematic way the similarities and differences between the approaches taken in economics and sociobiology. In doing so, special attention is given to an empirical theory of preferences that is lacking in economics. Here, inspiration from sociobiology would seem to be particularly useful. The considerations in the paper suggest that sociobiological arguments may indeed be helpful, albeit at a very elementary level only. A more comprehensive theory cannot ignore the influences of innate learning mechanisms in higher living beings. An elaborated theory of preferences in economics will have to acknowledge and incorporate insights from behavioral psychology.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

中德婚姻市场供需情况的比较研究

本文从概念、形成机制、度量方法、后果及其解决途径等方面探讨了婚姻挤压问题 ,考虑到婚姻挤压对婚姻寿命、初婚人数及其性别差异的影响而创立了婚姻寿命指数与初婚挤压指数两指标 ,提出了婚姻市场类型的划分标准。通过对中德两国婚姻市场的历史与现状的考察 ,揭示了中德两国婚姻挤压产生的原因、类型、差异和未来的变化趋势 ,并对如何化解中国未来婚姻市场的供求矛盾提出了对策与建议     

Fast and approximate exhaustive variable selection for generalised linear models with APES

We present APproximated Exhaustive Search (APES), which enables fast and approximated exhaustive variable selection in Generalised Linear Models (GLMs). While exhaustive variable selection remains as the gold standard in many model selection contexts, traditional exhaustive variable selection suffers from computational feasibility issues. More precisely, there is often a high cost associated with computing maximum likelihood estimates (MLE) for all subsets of GLMs. Efficient algorithms for exhaustive searches exist for linear models, most notably the leaps‐and‐bound algorithm and, more recently, the mixed integer optimisation (MIO) algorithm. The APES method learns from observational weights in a generalised linear regression super‐model and reformulates the GLM problem as a linear regression problem. In this way, APES can approximate a true exhaustive search in the original GLM space. Where exhaustive variable selection is not computationally feasible, we propose a best‐subset search, which also closely approximates a true exhaustive search. APES is made available in both as a standalone R package as well as part of the already existing mplot package.     

Income inequality and risk taking: the impact of social comparison information

Theory and Decision - In contrast to the assumptions of standard economic theory, recent experimental evidence shows that the income of peers has a systematic impact on observed degrees of risk...     

How to measure and proxy permanent income: evidence from Germany and the U.S.

Permanent income (PI) is an enduring concept in the social sciences and is highly relevant to the study of inequality. Nevertheless, there has been insufficient progress in measuring PI. We calculate a novel measure of PI with the German Socio-Economic Panel (SOEP) and U.S. Panel Study of Income Dynamics (PSID). Advancing beyond prior approaches, we define PI as the logged average of 20+ years of post-tax and post-transfer (“post-fisc”) real equivalized household income. We then assess how well various household- and individual-based measures of economic resources proxy PI. In both datasets, post-fisc household income is the best proxy. One random year of post-fisc household income explains about half of the variation in PI, and 2–5 years explain the vast majority of the variation. One year of post-fisc HH income even predicts PI better than 20+ years of individual labor market earnings or long-term net worth. By contrast, earnings, wealth, occupation, and class are weaker and less cross-nationally reliable proxies for PI. We also present strategies for proxying PI when HH post-fisc income data are unavailable, and show how post-fisc HH income proxies PI over the life cycle. In sum, we develop a novel approach to PI, systematically assess proxies for PI, and inform the measurement of economic resources more generally.