Empirical models, rules, and optimization

This paper considers supply decisions by firms in a dynamic setting with adjustment costs and compares the behavior of an optimal control model to that of a rule-based system which relaxes the assumption that agents are explicit optimizers. In our approach, the economic agent uses believably simple rules in coping with complex situations. We estimate rules using an artificially generated sample obtained by running repeated simulations of a dynamic optimal control model of a firm's hiring/firing decisions. We show that (i) agents using heuristics can behave as if they were seeking rationally to maximize their dynamic returns; (ii) the approach requires fewer behavioral assumptions relative to dynamic optimization and the assumptions made are based on economically intuitive theoretical results linking rule adoption to uncertainty; (iii) the approach delineates the domain of applicability of maximization hypotheses and describes the behavior of agents in situations of economic disequilibrium. The approach adopted uses concepts from fuzzy control theory. An agent, instead of optimizing, follows Fuzzy Associative Memory (FAM) rules which, given input and output data, can be estimated and used to approximate any non-linear dynamic process. Empirical results indicate that the fuzzy rule-based system performs extremely well in approximating optimal dynamic behavior in situations with limited noise.Decision-making. ,econometric models ,TMD ,

Updating and estimating a Social Accounting Matrix using cross entropy methods

The problem in estimating a social accounting matrix (SAM) for a recent year is to find an efficient and cost-effective way to incorporate and reconcile information from a variety of sources, including data from prior years. Based on information theory, the paper presents a flexible “cross entropy” (CE) approach to estimating a consistent SAM starting from inconsistent data estimated with error, a common experience in many countries. The method represents an efficient information processing rule—using only and all information available. It allows incorporating errors in variables, inequality constraints, and prior knowledge about any part of the SAM. An example is presented applying the CE approach to data from Mozambique, using a Monte Carlo approach to compare the CE approach to the standard RAS method and to evaluate the gains in precision from utilizing additional information.Social accounting Mathematical models. ,Mozambique. ,Economics Models. ,Entropy (Information theory) ,

Food security and trade negotiations in the World Trade Organization

An important issue in WTO trade negotiations is whether further liberalization of trade and agricultural policies may help or hinder food security in WTO member countries, especially the developing countries. The WTO recognizes various classifications of countries: developed, developing, least developed (LDC) and net food importing developing (NFIDC). How well do these categories capture issues of food security? This paper employs various methods of cluster analysis (including an approach based on fuzzy sets) and data for 167 countries to identify groups of countries categorized according to five measures of food security: food production per capita, the ratio of total exports to food imports, calories per capita, protein per capita, and the share of the non-agricultural population share. The analysis identifies 12 distinct clusters characterized by similarities and differences across the various measures. The analysis suggests that the LDC category consists of largely food insecure countries, but that there also are food insecure countries that are not LDCs. NFIDCs is less precise as an indicator of food vulnerability, with more than a third of those countries not falling under any of the food insecure groups. Also, the general category of “developing countries” is very heterogeneous and is not very useful if the focus is on issues of food security. Finally, our typology shows that all developed countries are included in food secure categories.Food production. ,Food security. ,Trade liberalization. ,World Trade Organization. ,Trade policy. ,

Preoperative Education Regarding the Enhanced Recovery After Surgery (ERAS) Guideline for Colorectal Surgical Patients: A Quality Improvement Project

BACKGROUND: Advancements in colorectal surgeries can be attributed to the adoption of the Enhanced Recovery After Surgery (ERAS) clinical guideline, which is a system of perioperative interventions bundled together cohesively to enhance a patient’s surgical experience, especially their post-operative recovery. One of the first interventions that initiates the ERAS process is the delivery of patient education before surgery. However, there are currently no standardizations on the kind of content or method of delivery for this education. PURPOSE: This Quality Improvement (QI) project determined the effects of a private, in-person, educational program discussing in detail the ERAS guideline adopted by their treating facility and the patient’s active role in the recovery process. An enhanced quality of recovery for these colorectal surgical patients was evaluated by measures of an early return to normal activities of daily living (ADLs), symptom incidence, levels of anxiety, and patient satisfaction when compared to patients who receive usual care. METHODS: A multivariate, repeated measures design was used, which followed the Plan, Do, Study, and Act (PDSA) model. The sample consisted of ten participants who were scheduled for colorectal surgery at a community medical center. Participants were given code numbers where odd numbered participants received the educational intervention and even numbered participants represented the usual care, control group. After informed consent, a Demographic and Clinical Data form was completed for each participant. The Quality of Recovery- 40 (QoR-40) questionnaire was administered to the intervention and usual care groups at two time points: upon hospital discharge and one week following hospital discharge. Descriptive analysis was used to identify trends in the Demographic and Clinical Data forms, while changes in the scores on the QoR-40 questionnaires was measured by independent and paired t-tests. RESULTS: A two-tailed paired t-test analyzed the difference in mean scores of the intervention group on Discharge Day and One-week Post-Discharge, revealing statistical significance with a t-score (5) = 3.9198 and p-value = 0.0173. Another two-tailed paired t-test analyzed the difference in mean scores of the control group on Discharge Day and One-week Post-Discharge, revealing statistical significance by a t-score (5) = 2.9994 and a p-value = 0.004. However, completing a one-tailed independent t-test on Discharge Day scores between the intervention and control group revealed no statistical significance as demonstrated by t-score (5) = 0.6551, and a p-value = 0.5308 (p\u3e0.05). Another one-tailed independent t-test on One-week Post-Discharge scores between the intervention and control group revealed no statistical significance as demonstrated by a t-score (5) = 1.2421, and a p-value = 0.2494. DISCUSSION: The results of this QI project indicate that for elective colorectal surgical patients, education regarding the ERAS guideline is not required to enhance their surgical recovery, measured by an early return to ADLs, decreases postoperative symptoms, decreased levels of anxiety, and overall increased patient satisfaction. Further research is needed to study the effects of different preoperative educational material to determine what content is most influential on patients’ surgical recovery

Impediments to municipal water recycling in Australia

Local authorities in Australia face two great challenges when managing municipal waters: Meeting future demands for clean water; and Preserving and enhancing the health of waterways. Municipal water recycling provides a means to achieve these objectives by providing an alternative source of water as well as reducing sewage effluent discharges. This paper identifies the key factors impeding the rate of growth of water recycling in Australia. Such knowledge will be crucial to our effective allocation of efforts and resources required for a rapid and sustainable change in the way we manage our water. While Australia currently recycles around 11 per cent of effluents from sewage treatment plants, there is substantial scope for increase