Influence of the Premium Subsidy on Farmers’ Crop Insurance Coverage Decisions, April 2005

The Agricultural Risk Protection Act greatly increased the expected marginal net benefit of farmers buying high-coverage crop insurance policies by coupling premium subsidies to coverage level. This policy change, combined with cross-sectional variations in expected marginal net benefits of high-coverage policies, is used to estimate the role that premium subsidies play in farmers’ crop insurance decisions. We use county data for corn, soybeans, and wheat to estimate regression equations that are then used to obtain insight into two policy scenarios. We first estimate that eventual adoption of actuarially fair incremental premiums, combined with current coupled subsidies, would increase farmers’ purchase of high-coverage policies by almost 400 percent from 1998 levels across the three crops and two plans of insurance included in the analysis. We then estimate that a return to decoupled subsidies would decrease farmers’ high-coverage purchase decisions by an average of 36 percent.

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.

Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Academic Building Revenue Bond Funds for the year ended June 30, 2009

Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Academic Building Revenue Bond Funds for the year ended June 30, 2009

Audit report of the accompanying Schedule of Debt Service and Coverage for Iowa State University of Science and Technology as of February 10, 2012 for the Athletic Facilities Revenue Bond Funds

Audit report of the accompanying Schedule of Debt Service and Coverage for Iowa State University of Science and Technology as of February 10, 2012 for the Athletic Facilities Revenue Bond Funds

Report to the Governor and General Assembly on Voluntary Employer-Sponsored Health Care Coverage Demonstration Project-Non-licensed Direct Care Workers, December 2008

Iowa faces a growing crisis in providing an adequate number of direct care workers for its again population. Direct care workers caring for the aging and disabled population are among those in our work force with the lowest wages and lack of access to health insurance. A survey of direct care workers conducted by the Iowa Caregivers Association in June of 2066 indicated that benefits ranked second only to wages in the reasons for job-hoping. A study of the direct care workforce in Vermont healthy insurance, ranked second only to wages, as important to attracting and keeping direct care workers.

Audit report of the Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Dormitory Revenue Refunding Bonds for the year ended June 30, 2012

Audit report of the Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Dormitory Revenue Refunding Bonds for the year ended June 30, 2012

Audit report of Debt Service and Coverage for Iowa State University of Science and Technology as of June 30, 2014

Audit report of Debt Service and Coverage for Iowa State University of Science and Technology as of June 30, 2014

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

Guide to Medicare prescription drug coverage, 2013

A guide for seniors on medicare and prescription drug plans