Valuing Lost Home Production for Dual-Earner Couples

Economists’ principal tool for studying household behavioral responses to changes in tax and other government policies, and the magnitude and determinants of private saving, is the life—cycle model. The purpose of this paper is to attempt to incorporate into that model one of the most conspicuous changes in the U.S. economy in the last 50 years, the rise in labor market participation for married women. The increased presence of married women in the labor force has obvious benefits: women now earn much more income than they did in the past. On the other hand, working women presumably spend less time doing housework and other types of home production, and the forgone value of time at home reduces the net benefit of their work in the market. Conventional accounts do not provide measurements of the costs of lost home production, but we attempt to use comparisons of household net worth at retirement to deduce valuations indirectly. This paper modifies a standard life—cycle model to include women’s labor supply decisions, estimates key parameters of the new specification, and attempts to assess the significance of rising female labor market participation for aggregate national saving in the U.S. Using panel data from the Health and Retirement Study, we find that the difference between measured labor market earnings for married women and earnings net of the value of lost home production seems moderately small – about 30 percent – and that the corresponding long—run effect on the overall rate of private saving is minor.

The impacts and benefits of using CASE tools in the system development life cycle

The basic idea underlying computer-aided software engineering (CASE) technology is to increase a systems developer\u27s productivity by providing a set of well-integrated, labor-saving tools that transform computer-based information systems (CBIS) development into an automated process. Two major issues of interest are addressed by this article. The first issue includes subjects related to the corporate data processing environment when adopting CASE technology for developing CBIS applications. The second issue includes subjects related to examining the impacts and benefits of using CASE technology as an automated development CBIS application tool within the system development life cycle

Development of an Innovative Mango's Wrapper Tool

This paper presenting a new design and development of an innovative and user-friendly tool by using mechanism of compression spring to wrap mango fruits in an efficient and systematic manner. The tool is capable to solve the problem faced by mango farmers or entrepreneurs during traditionally wrapping process. Previously, the wrapping process is handled manually by using paper wrapper and rope while ladder is sometimes used for tall trees. 30 mango fruits are picked for size sampling. The diameter for the mature mango fruits is within the range of 5.8cm to 7.9cm. The suitable casing size is determined to be 10cm in which 3.1 cm is the tolerance. The tool is designed by using SolidWork 2016. Later, tool fabrication process is carried out including cutting and joining the parts such as steel compression spring, paddle , cable and PVC pipe . The analysis is focused on the compression spring and the maximum force of 45.117N is applied on the pedal to pull the jaws while releasing the rubber band. Meanwhile, the tool is highly efficient and the time for the tool to wrap one mango fruit is 65 seconds compared to 190 seconds by way of traditional method. Significant saving in term of labor workforce is as much as 67% and the ratio of manpower requirements is reduced to 3: 1. Among the factors contributing to the saving are the used of 210cm long pole which eliminate the need of use a ladder. Lastly the tool is lightweight, convenience to use with minimum maintenance

Machinist vs. Mismanagement at Eastern Airlines

IAM 100 leaders interviewed by Paul J. Baicich

Exploring GPS Data for Operational Analysis of Farm Machinery.

Global Positioning System (GPS) has made a great evolution in different aspects of modern agriculturalsectors. Today, a growing number of crop producers are using GPS and other modern electronic and computer equipments to practice Site Specific Management (SSM) and precision agriculture. This technology has the potentialin agricultural mechanization by providing farmers with a sophisticated tool to measure yield on much smaller scales as well as precisely determination and automatic storing of variables such as field time, working area,machine travel distance and speed, fuel consumption and yield information. This study focuses on how to interpretand process raw GPS data for operational analysis of farm machinery. Exact determinations of field activities usingGPS data along with accurate measurements and records of yield provide an integrated tool to calculate field efficiency and field machine index which in turn increases machine productivity and labor saving. The results canalso provide graphical tools for visualizing machine operator’s performance as well as making decision on field and machine size and selection

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing : an empirical study

With the penetration of smart grid into factories, energy-efficient production scheduling has emerged as a promising method for industrial demand response. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and labor-aware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instances, which encompass the cases where energy cost is minor, moderate, and major compared to the joint energy and labor cost. The results have proven that the ignorance of labor in existing energy-efficient production scheduling studies increases the joint energy and labor cost, although the energy cost can be minimized. To achieve effective production cost reduction, energy and labor awareness are recommended to be jointly considered in production scheduling. (C) 2017 Elsevier Ltd. All rights reserved

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning