Arizona State and Local Government Documents Collection

In order to carry out the intent of Federal Fair Housing legislation, the United States Department of Housing and Urban Development, Fair Housing and Equal Opportunity division, requires that Community Development Block Grant entitlement jurisdictions comply with regulations to affirmatively further fair housing. This mandate is carried out by the CDBG jurisdictions, in part, by completing an Analysis of Impediments to Fair Housing Choice in their jurisdictions. The State of Arizona is a CDBG Entitlement Jurisdiction and has authorized the Arizona Department of Housing to conduct this analysis. HUD grantees are required to do the following:

-- Complete or update an “Analysis of Impediments to Fair Housing Choice” (AI) pursuant to HUD’s Fair Housing Planning Guidebook every three to five years in coordination with the Consolidated Planning Process.
-- Use their comprehensive AI study as the basis to formulate a “Fair Housing Plan” with measurable “actions to be taken to overcome the effects of any impediments” and take those appropriate actions.
-- Maintain records, including their AI study and records to support actions taken and to be taken in regard to implementing the Fair Housing Plan.

This AI is a supporting document to the State of Arizona Consolidated Plan and should be reviewed and evaluated within the context of that plan.

The agency is dedicated to allocating funds in a responsible manner to assist as many Arizona homeowners as possible and through ongoing adjustments to the program we remain optimistic that new avenues will be successful in reducing foreclosures and stabilizing our neighborhoods. Reports highlight the outstanding efforts of the Arizona Department of Housing, Arizona Housing Finance Authority, and the Arizona Home Foreclosure Funding corporation. We are confident that through the tireless efforts of the agency and our dedicated partners we will push through this recession and emerge stronger and better prepared for whatever challenges the future holds.

“Commodity promotion” consists of many activities, each designed to contribute to a consumer’s product knowledge or influence tastes. However, both knowledge and tastes are unobservable, or latent, variables influencing demand. This paper specifies a dynamic structural model of fresh fruit demand that treats promotion and other socioeconomic variables as "causal" variables influencing these latent variables. Estimating this state-space model using a Kalman filter approach provides estimates of both the system parameters and a latent variable series. The results show that these latent effects contribute positively to apple and other fruit consumption, while reducing banana consumption.

Proposals for reform of the federal multiple-peril crop insurance program for specialty crops seek to change fees for catastrophic insurance from a nominal fifty-dollar per contract registration fee to an actuarially sound premium. Growers argue that this would cause a significant reduction in participation rates, thus impeding the program’s goals of eventually obviating the need for ad hoc disaster payments and worsening the actuarial soundness of the program. The key policy issue is, therefore, empirical one - whether the demand for specialty crop insurance is elastic or inelastic. Previous studies of this issue using either grower or county-level field crop data typically treat the participation problem as either a discrete insure / don’t insure decision or aggregate these decisions to a continuous participation rate problem. However, a grower’s problem is more realistically cast as one of simultaneously making a coverage level / insurance participation decision. Because the issue at hand considers a significant price increase for only one coverage level (50%), differentiating between these decisions is necessary both from an analytical and econometric standpoint. To model this decision, the paper develops a two-stage estimation procedure based on Lee’s multinomial logit-OLS selection framework. This method is applied to a county-level panel data set consisting of eleven years of the eleven largest grape-growing counties in California. Results show that growers choose among coverage levels based upon expected net premiums and the variance of these returns, as well as the first two moments of expected market returns. At the participation-level, the mean and variance of indemnities are also important, as are several variables measuring the extent of self-insurance, such as farm size, enterprise diversity, or farm income. The results also show that the elasticity of 50% coverage insurance is elastic, suggesting that premium increases may indeed worsen the actuarial soundness of the program. These increases will also cause a significant adjustment of growers among coverage levels.