Korean National Health and Nutrition Examination Survey: High-Quality Healthcare Big Data

As indicated in the farmdoc daily article on January 14, 2015, many crop producers are in the process of making the farm program participation decision for the five years beginning with the 2014 crop. Price expectations for this five-year period play a central role in the decision. Several farmdoc daily articles (e.g., October 14, 2014; December 18, 2014; January 27, 2015) illustrate the sensitivity of expected program payments to alternative price projections for 2014/15. Long-term price projections for some crops are available from several sources, including the USDA's 10-year baseline projections, the Congressional Budget Office (CBO) 10-year baseline projections, and 10-year projections provided by The Food and Agricultural Policy Research Institute (FAPRI) at the University of Missouri. While USDA, CBO, and FAPRI baseline price projections may not be considered forecasts in the strictest sense because they are developed for policy analysis, they are generally referenced as sources for forming price expectations by producers enrolling in the farm program. Given the importance of the program participation decision, the accuracy of these long-term projections is of obvious relevance. The January 14 article examined the historical accuracy of two sources of long-term forecasts for corn: i) the USDA's 10-year baseline projections; and ii) the corn futures market. Here we examine the accuracy of these two sources of forecasts for soybean and wheat prices and repeat the examination for corn in order to provide a comprehensive analysis in one location.

Long-Term Corn, Soybeans, and Wheat Price Forecasts and the Farm Bill Program Choice

Differences in expected payments between Agricultural Risk Coverage – County Coverage (ARC-CO) and Price Loss Coverage (PLC) will be an important factor when making the program choice decisions offered under the 2014 Farm Bill. (See Step 4 on Farm Bill Toolbox for other factors – type of risk covered and availability of SCO --that influence the ARC-CO and PC decision). Realization of Market Year Average (MYA) prices and county yields from 2014 through 2018 will affect differences in payments. Much of the focus will be on price levels. General rules of thumb are:

Expected Payments from ARC-CO and PLC

A Study on the Utilization of the Satisfaction Survey and its Influential Factors for the Government Performance Management: Focused on Civil Servants' Recognition

This is a research-in-progress of developing a coffee eco-market with online bidding for different coffee stakeholders in selected provinces in the Philippines. The objective of this paper is to compare three different forecasting models using a five-year coffee production data. The three models explore and assess exponential smoothing, moving average, and regression. Different components such as seasonal, trend and irregular components are present in the data. Thus, the original data is adjusted by removing the seasonal component, trend component, and irregular component. For the computation of the forecasted values, the MS Excel data analysis tool is used. The standards used to measure the accuracy of each three model for comparison are the MAE, the MSE, and the MAPE. Among the three model, the moving average model rank first with a 9% error accuracy percentage, the next is the exponential smoothing with 12% error accuracy percentage, then the last is the regression with 14% error accuracy percentage.

Assessment of Predictive Models for Coffee Production in the Philippines

This article provides payment indicators for ARC-CO and PLC based on the January 12, 2015 WASDE (World Agricultural Supply and Demand Estimates) mid-price estimate and NASS’s (National Agricultural Statistical Service) crop production annual reports for corn, soybeans, and wheat. The term, payment indicator, is used because the estimates use state yield not the county yield used by ARC-CO or farm payment yield used by PLC. Thus, the indicators are not estimates of payments an individual FSA farm will receive. Nevertheless, they should help frame perspectives and questions regarding crop program choices. Previous estimates exist for the U.S. and are available at the farmdoc daily articles of August 13, September 18, October 14, and December 18, 2014.

Indicated ARC-CO and PLC Payment for 2014 Crop Year Corn, Soybeans, and Wheat by State: January 2014

Heo, Seong-Yoon; Kim, Sang-Hyo; Zulauf, Carl R. et al..2016.Satisfaction with food policies for consumer,Reports,[St. Paul]AgEcon Search,20

Satisfaction with Food Policies for Consumer: A Case Study of South Korea

This study aims to identify the regions and people with low food access (LFA) for Korea at the national level and to examine disparities in food consumption, dietary behavior, and health outcome for those regions and people. Based on the distance to the nearest grocery store from residence, the regions and people with LFA are identified through geographical information system (GIS) analysis. To examine disparities between the regions and people with LFA and without LFA, a consumer survey is conducted and data from National Health and Nutrition Examination Survey and Community Health Survey are analyzed. This study found that there exists a serious access to food issue in Korea, especially for the aged. Moreover, there also exist significant disparities between the regions and people with and without LFA in the distance and one-way travel time to the grocery store that is mainly visited, frequency of offline/online grocery shopping, availability of various foods, dietary habits such as eating regularly, eating nutritionally balanced foods, and eating sufficient fruit/vegetable/whole grains, the acquisition and utilization of food-related information, and health outcomes. This study suggests that, to resolve such a serious food access problem, assistance policies, such as mobile grocery stores and lunch-box delivery, need to be activated in countries similar to Korea since this problem could potentially deteriorate the national medical finances as well as the regional and individual disparities.

https://www.mdpi.com/1660-4601/17/21/7936/pdf

Identifying Food Deserts and People with Low Food Access, and Disparities in Dietary Habits and Health in Korea.

Return and Risk Performance of Basis Strategy: A Case Study of Illinois Corn and Soybeans, 1975-2012 Crop Years

Given the interest in the ability to forecast returns to storage and the inconclusiveness of the performance of the basis strategy, especially for unhedged storage; this study examines whether other variables enhance the forecast of storage returns. Specifically, the rate of harvest progress and the ratio of a demand for storage space relative to the supply of storage space are examined. The later variable has not been investigated by previous studies of the basis strategy. Using data for Illinois corn and soybeans over the 1988 through 2012 crop years and a fixed effect seemingly unrelated regression estimation, both variables are found to be significant in explaining observed returns to unhedged storage but not to hedged storage. Given the regression results, storage strategies based on harvest progress and ratio of demand to supply for storage space are constructed. These strategies do not improve the basis strategy’s return and risk for hedged storage. In contrast, these strategies improve the return and risk performance of unhedged storage relative to routine unhedged storage. Moreover, net return for the alternative strategies for unhedged storage is higher than net return for the basis strategy for hedged storage but the latter has a lower risk than the former. This finding is the classic return-risk tradeoff and provides an explanation for the common observation that storage is often unhedged, especially by farmers.

http://www.farmdoc.illinois.edu/nccc134/conf_2015/pdf/Kim_Zulauf_Roberts_NCCC_134_2015.pdf

Sanghyo Kim

Papers

Indicated ARC-CO and PLC Payment for 2014 Crop Year Corn, Soybeans, and Wheat by State: January 2014

Satisfaction with Food Policies for Consumer: A Case Study of South Korea

Identifying Food Deserts and People with Low Food Access, and Disparities in Dietary Habits and Health in Korea.

Return and Risk Performance of Basis Strategy: A Case Study of Illinois Corn and Soybeans, 1975-2012 Crop Years

Forecasting Returns to Storage: The Role of Factors other than the Basis Strategy