Return Migration as an Asset Maximization Strategy in Retirement

Mexican immigrants make up an increasing proportion of the US population 65 and older. Estimating outcomes for this population is complicated by return migration. Due to data limitations, theoretical frameworks and empirical evidence fail to provide clear indication of the economic selection mechanism of return migration, especially at older ages making it difficult to estimate economic determinants of return. Here two waves of data from the US based Health and Retirement Study and the Mexican Health and Aging Study are combined to create a novel dataset that enables a comparison of assets at older ages for those who stay in the US, those who return before age 50 and those who return at 50 and older. Unadjusted results show no difference in total net wealth at older ages between the three groups, with higher business assets among returnees and higher concentration of wealth in home equity among stayers. With evidence of higher inequality among stayers, lower median wealth in Mexico, and asset advantages operating through citizenship, older age return can be interpreted as a means to acquire a higher standard of living in retirement for non-citizen immigrants. Comparing assets between 2000 and 2012 reveal the vulnerability of stayers during the US housing crisis. These findings are novel because they point to return migration as a retirement strategy and expose a source of vulnerability among those Mexican immigrants who remain in the US into older ages.

Multi-trait selection index and cluster analyses in Angus cattle

In breeding programmes, the genetic selection process is based on the prediction of animal breeding values, and its results may vary according to the employed selection method. The current study developed an economic selection index for animals of the Angus breed; performed cluster analyses using the breeding values in order to evaluate the genetic profile of the animals candidates to selection, and compared the obtained results between the economic selection index and the cluster analyses. The evaluated traits included weaning weight, 18-month weight, scrotal circumference, fat thickness and ribeye area. Economic values were obtained using bioeconomic modelling, simulating a complete cycle production system of beef cattle breeds in Brazil, and the selection objective were the weaning rate and slaughter weight. The chosen selection index was composed of all of the traits used as selection criteria for the simulated production system. During the cluster analyses, the population was divided into two to four groups, in which the groupings containing potential animals were assessed. The animals of the grouping which was used for comparison with the selection index were identified, and most of the bulls that were included in the index were among the best in the analysed group. These results suggest that the cluster analyses can be used as a tool for the selection of animals to be used as parents for future generations.

Current challenges for trait economic values in animal breeding

Modern selection approaches are expected to bring about the cumulative and permanent improvement of animal performance and profitability of animal production. Breeding values of traits along with trait economic values (EVs) are utilised for economic selection purposes with many species all over the world. Currently, some challenges related to trait EVs in animal breeding should be considered. First, the selection response based on the higher accuracy of genomic selection may be reduced due to improper weighting of the trait breeding values of selection candidates. A comprehensive approach applied in bioeconomic models allows suitable trait EV calculations. Further challenges comprise the new breeding objectives associated with climate change, environmental mitigation and animal adaptability. The estimation of EVs for traits influencing greenhouse gas (GHG) emissions has been mostly based on including the value of CO₂ emission equivalent in the trait EVs, on calculating EVs for feed efficiency traits and on methane yield as a direct trait of GHG emission. Genetic improvement of production, functional, feed efficiency and methane traits through the application of multi-trait selection indices was found to be crucial for mitigation of emissions and farm profitability. Defining the non-market values of traits connected with climate protection could be a useful solution for including these traits in an economic breeding objective. While GHG emissions mostly change the costs per unit of production, animal adaptability in its complexity influences animal performance. Clear definitions of disease, fertility, mortality and other breeding objective traits allow the proper calculation of trait EVs, and an accurate estimation of trait genetic parameters could lead to sufficient economic selection response. This complex approach could be beneficial for more effective utilisation of inputs and overall economic and environmental sustainability of animal production.

90 Effectiveness of an Educational Program on Beef Bull Selection that Incorporates Classroom Instruction and a Mock Auction

An educational program was developed to assist beef producers with making informed bull purchasing decisions. There are two core pieces to this decision: targeting the bull’s genetics to the producer’s management and resources, and paying a price that maximizes the return on investment. This was a two-part educational program; the first session was classroom instruction with topics related to proper bull selection. At the conclusion of this session producers were assigned one of five management scenarios and received a sale catalogue with 60 bulls. Videos of all bulls were made available, along with all production information, including adjusted measurements, EPD and indices. The producers were tasked with returning the next week to attend the mock auction and purchase the best valued bull for their assigned scenario. At the conclusion of the auction, each scenario was discussed and the individual that purchased the best value bull in each scenario was recognized. Value was determined as the price paid for the bull compared to a price determined through an “economic selection index” equation. Beef producers (n = 322) participated in the program over 9 locations; in locations with less attendance, a reduced sale catalogue was used. Of the post-program survey respondents (n = 155), 71% were commercial beef producers, 27% were seedstock producers and 5% were Extension agents (n = 10, were cross classified). When asked how much time they spent reviewing the materials before the mock sale 8% said they made their decision at the sale, 16% spent 30 minutes or less, 58% spent 30 minutes to 2 hours and 18% spent over 2 hours preparing. When asked if the program would help with their next bull purchase, 88% said it would probably or definitely help. The conclusion was that this was a valuable educational program.

Planung automatischer Identifikationstechnologien/Planning of automatic identification technologies – Methodology for the technological and economic selection of Auto-ID technologies

Technologien zur automatischen Identifikation (Auto-ID) von Objekten dienen im industriellen Kontext zunehmend als Basis für neuartige Services. Sie sind essenzieller Bestandteil von Nachverfolgungsfunktionen, etwa für Produktionsfortschrittskontrollen und Materialflussoptimierungen. Sie identifizieren und lokalisieren Werkstücke, Produkte und/oder Betriebsmittel. Mit Anwendung und Akzeptanz in den Unternehmen steigt auch die Anzahl an Technologien und Anbietern im Markt. Um den Planungsprozess zum Einsatz dieser Technologien zu strukturieren und Planern einen Leitfaden zur Verfügung zu stellen, wurde ein Verfahren zur Auswahl geeigneter Technologien entwickelt.   Technologies for automatic identification (Auto-ID) of objects are increasingly used in industry as a basis for new services. They are essential for tracking functions – for example for production progress monitoring and material flow optimization. They are used for identifying and locating workpieces, products and/or resources. The number of technologies and suppliers in the market increases with application and acceptance in the companies. To structure the planning process for the use of these technologies and provide a guideline for planners, a procedure was developed for selecting suitable technologies.

Economic Importance of Genetic Improvements in Milk Production, Reproduction, and Productive Life

Florida dairy producers have access to genetic evaluations for many dairy traits that are economically important. These traits are combined in economic selection indexes to rank bulls and cows for total profitability. The first economic selection index, introduced in 1971 by the USDA-Animal Improvement Programs Laboratory (USDA-AIPL) in Beltsville, MD, included only milk and fat yield. But other traits, such as the ability to get pregnant in time or to avoid culling, determine a cow's profitability as well. This document is AN158, one of a series of the Animal Science Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Original publication date November, 2005.