Iowa Family Farm Meat Directory, 2007

This directory is for all the meat producers in Iowa.

The Farm, the city, and the emergence of social security

We study the social, demographic and economic origins of social security. The data for the U.S. and for a cross section of countries suggest that urbanization and industrialization are associated with the rise of social insurance. We describe an OLG model in which demographics, technology, and social security are linked together in a political economy equilibrium. In the model economy, there are two locations (sectors), the farm (agricultural) and the city (industrial) and the decision to migrate from rural to urban locations is endogenous and linked to productivity differences between the two locations and survival probabilities. Farmers rely on land inheritance for their old age and do not support a pay-as-you-go social security system. With structural change, people migrate to the city, the land loses its importance and support for social security arises. We show that a calibrated version of this economy, where social security taxes are determined by majority voting, is consistent with the historical transformation in the United States.

Integrated Farm/Livestock Management Demonstration Program, 2002

Farm/Livestock Management Demonstration Program produced by Iowa Departmment of Agriculture and Land Stewardship

On-farm animal welfare assessment in dairy cattle: improved lameness detection

Estudi realitzat a partir d’una estada a la University of British Columbia, Canada, entre 2010 i 2012. Primerament es va desenvolupar una escala per mesurar coixeses (amb valors de l’1 al 5). Aquesta escala es va utilitzar per estudiar l’associació entre factors de risc a nivell de granja (disseny de le instal.lacions i maneig) i la prevalencia de coixeses a Nord America. Les dades es van recollir en un total de 40 granges al Nord Est dels E.E.U.U (NE) i 39 a California (CA) . Totes les vaques del group mes productiu es van categoritzar segons la severitat de les coixeses: sanes, coixes i severament coixes. La prevalencia de coixeses en general fou del 55 % a NE i del 31% a CA. La prevalencia de coixeses severes fou del 8% a NE i del 4% a Ca. A NE, les coixeses en general increntaren amb la presencia de serradura als llits i disminuiren en granjes grans, amb major quantitat de llit i acces a pastura. Les coixeses mes severes incrementaren amb la falta d’higiene als llit i amb la presencia de serradura als llits, i disminuiren amb la quantitat de llit proveit, l’us de sorra als llits i amb la mida de la granja. A CA, les coixeses en general incrementaren amb la falta d’higiene al llit, i disminuiren amb la mida de la granja, la presencia de terres de goma, l’increment d’espai als cubicles , l’espai a l’abeuredor i la desinfeccio de les peulles. Les coixeses severes incrementaren amb la falta d’higiene al llit i disminuixen amb la frequencia de neteja del corral. En conclusio, canvis en el maneig i el disseny de les instal.lacions poden ajudar a disminuir la prevalencia de coixeses, tot i que les estrategies a seguir variaran segons la regio.

Farm-Level Analysis of Risk Management Proposals, March 2000

This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.

U.S. Farm Policy and the Variability of Commodity Prices and Farm Revenues, February 2000

A dynamic, three-commodity rational-expectations storage model is used to compare the impact of the Federal Agricultural Improvement and Reform (FAIR) Act of 1996 with a freemarket policy and with the agricultural policies that preceded the FAIR Act. Results support the hypothesis that the changes made when FAIR was enacted did not lead to permanent significant increases in the volatility of farm prices or revenues. An important finding is that the main economic impacts of the Pre-FAIR scenario, relative to the free-market regime were to transfer income to farmers and to substitute government storage for private storage in a way that did little to support prices or to stabilize farm incomes.

Integrated Farm/Livestock Management Demonstration Program, 2004

Farm/Livestock Management Demonstration Program produced by Iowa Departmment of Agriculture and Land Stewardship

Integrated Farm/Livestock Management Demonstration Program, 2001

Farm/Livestock Management Demonstration Program produced by Iowa Departmment of Agriculture and Land Stewardship

Integrated Farm/Livestock Management Demonstration Program, 2003

Farm/Livestock Management Demonstration Program produced by Iowa Departmment of Agriculture and Land Stewardship

Get a GRIP: Should Area Revenue Coverage Be Offered through the Farm Bill or as a Crop Insurance Program? 2007

The successful expansion of the U.S. crop insurance program has not eliminated ad hoc disaster assistance. An alternative currently being explored by members of Congress and others in preparation of the 2007 farm bill is to simply remove the “ad hoc” part of disaster assistance programs by creating a standing program that would automatically funnel aid to hard-hit regions and crops. One form such a program could take can be found in the area yield and area revenue insurance programs currently offered by the U.S. crop insurance program. The Group Risk Plan (GRP) and Group Risk Income Protection (GRIP) programs automatically trigger payments when county yields or revenues, respectively, fall below a producer-elected coverage level. The per-acre taxpayer costs of offering GRIP in Indiana, Illinois, and Iowa for corn and soybeans through the crop insurance program are estimated. These results are used to determine the amount of area revenue coverage that could be offered to farmers as part of a standing farm bill disaster program. Approximately 55% of taxpayer support for GRIP flows to the crop insurance industry. A significant portion of this support comes in the form of net underwriting gains. The expected rate of return on money put at risk by private crop insurance companies under the current Standard Reinsurance Agreement is approximately 100%. Taking this industry support and adding in the taxpayer support for GRIP that flows to producers would fund a county target revenue program at the 93% coverage level.

An analysis of the accounting principles applied by the European Farm Accountancy Data Network

In spite of its relative importance in the economy of many countriesand its growing interrelationships with other sectors, agriculture has traditionally been excluded from accounting standards. Nevertheless, to support its Common Agricultural Policy, for years the European Commission has been making an effort to obtain standardized information on the financial performance and condition of farms. Through the Farm Accountancy Data Network (FADN), every year data are gathered from a rotating sample of 60.000 professional farms across all member states. FADN data collection is not structured as an accounting cycle but as an extensive questionnaire. This questionnaire refers to assets, liabilities, revenues and expenses, and seems to try to obtain a "true and fair view" of the financial performance and condition of the farms it surveys. However, the definitions used in the questionnaire and the way data is aggregated often appear flawed from an accounting perspective. The objective of this paper is to contrast the accounting principles implicit in the FADN questionnaire with generally accepted accounting principles, particularly those found in the IVth Directive of the European Union, on the one hand, and those recently proposed by the International Accounting Standards Committee’s Steering Committeeon Agriculture in its Draft Statement of Principles, on the other hand. There are two reasons why this is useful. First, it allows to make suggestions how the information provided by FADN could be more in accordance with the accepted accounting framework, and become a more valuable tool for policy makers, farmers, and other stakeholders. Second, it helps assessing the suitability of FADN to become the starting point for a European accounting standard on agriculture.

Accounting information and the prediction of farm viability

Until recently farm management made little use of accounting and agriculture has been largely excluded from the scope of accounting standards. This article examines the current use of accounting in agriculture and points theneed to establish accounting standards for agriculture. Empirical evidence shows that accounting can make a significant contribution to agricultural management and farm viability and could also be important for other agents involved in agricultural decision making. Existing literature on failureprediction models and farm viability prediction studies provide the starting point for our research, in which two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. The firstmodel considered only non-financial variables, while the other also considered financial ones. When accounting variables were added to the model, a significant reduction in deviance was observed.

New opportunities for farm accounting

There is a gap between the importance given to accounting and the low level of bookkeeping and accounting practice in the agricultural sector. Current general accounting rules do not adapt very well to the particularities of farming and are difficult and expensive to implement. The Farm Accountancy Data Network (FADN) and IASC's Proposed International Accounting Standard on Agriculture (PIASA) could be key elements to improve the use of accounting in European farms. The PIASA provides a strong conceptual framework but might need further instruments for its implementation in practice. FADN is an experienced network that has elaborated very detailed farm accounting procedures. Empirical data indicate that current FADN reports are already considered useful by farmers for different purposes. Some changes in the FADN procedures are suggested, while some aspects of FADN are worthwhile for the future IAS on agriculture.

Measuring and explaining farm inefficiency in a panel data set of mixed farms

This paper aims to estimate a translog stochastic frontier production function in the analysis of a panel of 150 mixed Catalan farms in the period 1989-1993, in order to attempt to measure and explain variation in technical inefficiency scores with a one-stage approach. The model uses gross value added as the output aggregate measure. Total employment, fixed capital, current assets, specific costs and overhead costs are introduced into the model as inputs. Stochasticfrontier estimates are compared with those obtained using a linear programming method using a two-stage approach. The specification of the translog stochastic frontier model appears as an appropriate representation of the data, technical change was rejected and the technical inefficiency effects were statistically significant. The mean technical efficiency in the period analyzed was estimated to be 64.0%. Farm inefficiency levels were found significantly at 5%level and positively correlated with the number of economic size units.

Department of Commerce, Farm Account FY2007

These Facts sheets have been developed to provide a multitude of information about executive branch agencies/departments on a single sheet of paper. The Facts provides general information, contact information, workforce data, leave & benefits information, and affirmative action data. This is the most recent update of information for the fiscal year 2007.