Affordable Housing Policies: An Overview

As urban housing markets throughout the United States increasingly exhibit challenges of affordability, federal, state, and local governments have placed renewed emphasis on housing, specifically mixed-income housing, which integrates affordable housing incentives into multifamily development projects. With such incentives, one must wonder what comprises a successful affordable housing policy and how affordable housing can be successfully implemented into a community. This article attempts to answer these questions by detailing the history of affordable housing policies, exploring some of the current affordable housing policies and programs, comparing affordable housing programs from different regions, and discussing some successful affordable housing programs and lessons that can be learned from them.

Impact of Rapid Transit on the Residential Market in Hudson County, New Jersey

The New York Metropolitan region is one of the most populous urban agglomerations in the world, and the single largest in North America.[1] It is also one of the most prominent economic centers, with New York City at the epicenter of its growth. With the entire region growing rapidly over the last decade, it is essential to analyze the socio-economic changes in order to understand the impact it has on commercial real estate. With its focus on housing rentals, this study aims to highlight housing costs as a function of rapid transit over time.

Lennar Technology: The Connected Consumer Has Arrived in Multifamily

As multifamily homebuilders progress into the 21st century, they have looked to integrate electronics and technology to simplify and enhance their businesses. The use of programs like Yardi and MRI for both property management and accounting have become the standard. Like Moore’s Law – the observation that the number of transistors in a dense integrated circuit will double approximately every two years – the use of technology in multifamily properties must equal both the pace and demand of present and future tenants.

Managing Rentals with Usage-Based Loss

Motivated by new and innovative rental business models, this paper develops a novel discrete-time model of a rental operation with random loss of inventory due to customer use. The inventory level is chosen before the start of a finite rental season, and customers not immediately served are lost. Our analysis framework uses stochastic comparisons of sample paths to derive structural results that hold under good generality for demands, rental durations, and rental unit lifetimes. Considering different \recirculation" rules | i.e., which rental unit to choose to meet each demand | we prove the concavity of the expected profit function and identify the optimal recirculation rule. A numerical study clarifies when considering rental unit loss and recirculation rules matters most for the inventory decision: Accounting for rental unit loss can increase the expected profit by 7% for a single season and becomes even more important as the time horizon lengthens. We also observe that the optimal inventory level in response to increasing loss probability is non-monotonic. Finally, we show that choosing the optimal recirculation rule over another simple policy allows more rental units to be profitably added, and the profit-maximizing service level increases by up to 6 percentage points.