skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


This content will become publicly available on March 6, 2026

Title: Buying and Selling: Exploring Residential Landlords’ Acquisition and Disposition Decisions
We examine rental landlords’ decisions to buy and sell investment properties. We use the results of a new survey of owners of rental properties in nine major US cities, focusing on a subset of rental investors who own properties themselves, where we ask questions about their demographic and economic backgrounds, rental portfolios, and business management practices, and questions about their interest in acquiring new investments and plans to sell properties currently in their portfolio. We use these data to specify a series of regressions examining the factors that shape owners’ decisions to grow or shrink their businesses. First, we examine whether financial factors affect acquisition and disposition decisions. In this category, we include a variety of measures, including rents, external shocks, the owner’s reliance on rental income, debt, and portfolio characteristics. Second, we examine the impact of the owner’s personal characteristics—including age, gender, race, and ownership length—on investment behavior. Finally, we examine the influence of operating experience on future investment decisions, including interactions, vacancies, evictions, property investment, and business impacts from COVID-19 and other external events. Our analysis contributes to a growing body of research on the businesses of small landlords and their impact on the housing system.  more » « less
Award ID(s):
2139816 2050264
PAR ID:
10645259
Author(s) / Creator(s):
; ;
Publisher / Repository:
Taylor & Francis online
Date Published:
Journal Name:
Journal of Real Estate Practice and Education
Volume:
27
Issue:
1
ISSN:
1521-4842
Subject(s) / Keyword(s):
Rental housing Residential rental property owners
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Despite the central role that landlords, or residential rental property owners (RRPOs), play in housing, important areas of RRPO decision making are not well understood. Because of the importance of RRPOs in the housing system, gaps in our knowledge leave planners at a disadvantage when creating policies to improve housing stability for tenants. This article is a comprehensive, interdisciplinary literature review of RRPO characteristics and behavior framed around three decision points: career lifecycle, portfolio maintenance and development, and property operations. This review ends with suggestions for an RRPO-focused research agenda that supports urban resiliency and housing stability for renters. 
    more » « less
  2. Abstract Businesses are the driving force behind economic systems and are the lifeblood of the community. A business shares striking similarity to a living organism, including birth, infancy, rising, prosperity, and falling. The success of a business is not only important to the owners, but is also critical to the regional/domestic economic system, or even the global economy. Recent years have witnessed many new emerging businesses with tremendous success, such as Google, Apple, Facebook etc., yet millions of businesses also fail or fade out within a rather short period of time. Finding patterns/factors connected to the business rise and fall remains a long lasting question puzzling many economists, entrepreneurs, and government officials. Recent advancement in artificial intelligence, especially machine learning, has lend researchers powers to use data to model and predict business success. However, due to data driven nature of all machine learning methods, existing approaches are rather domain-driven and ad-hoc in their design and validations. In this paper, we propose a systematic review of modeling and prediction of business success. We first outline a triangle framework to showcase three parities connected to the business: Investment-Business-Market (IBM). After that, we align features into three main categories, each of which is focused on modeling a business from a particular perspective, such as sales, management, innovation etc., and further summarize different types of machine learning and deep learning methods for business modeling and prediction. The survey provides a comprehensive review of computational approaches for business performance modeling and prediction. 
    more » « less
  3. Small businesses have suffered disproportionately from the COVID-19 pandemic. We use near-real-time weekly data from the Small Business Pulse Survey (April 26, 2020 - June 17, 2021) to examine the constantly changing impact of COVID-19 on small businesses across the United States. A set of multilevel models for change are adopted to model the trajectories of the various kinds of impact as perceived by business owners (subjective) and those recorded for business operations (objective), providing insights into regional resilience from a small business perspective. The findings reveal spatially uneven and varied trajectories in both the subjectively and the objectively assessed impact of COVID-19 across the U.S., and the different responses to the pandemic shock can be explained by evolving health situations and public policies, as well as by the economic structure and degree of socioeconomic vulnerability in different areas. This study contributes to scholarship on small businesses and regional resilience, as well as identifying policies and practices that build economic resilience and regional development under conditions of global pandemic disruption. 
    more » « less
  4. Abstract Using the exclusion of business development companies (BDCs) from stock indexes, this paper studies the effectiveness of market discipline in the direct lending space. Amid share sell-offs by institutional investors, a drop in BDCs’ valuations limits their ability to raise new equity capital. Following this funding shock, BDCs do not adjust their capital structure. At the same time, they are reducing the risk exposure of their portfolios. We document a greater reduction in risk for BDCs subject to stronger market discipline from their debtholders. BDCs pass through the capital shock to their portfolio firms by reducing their investment intensity. 
    more » « less
  5. This paper introduces an extensible framework to predict small-business closures to inform urban planners, lenders, and business owners as to factors to improve business resilience. This paper couples machine learning with two point of interest (POI) datasets and infrastructure data and uses New York State’s COVID-19 PAUSE as a stressor for investigating small-business resiliency. The study included 2537 food-related, non-chain, retail businesses across select New York City zip codes, of which 17.7% closed permanently. Macro-, meso-, and micro-levels of features included the neighborhood profile, street dynamics, and venue-specific, location-related characteristics. A Gaussian Mixture Neural Network model achieved 74.1% precision, 92.5% recall, and an 82.3% F1-score without use of financial data. High-end restaurants located further than average from public transit were most at risk for closure, while non-restaurant, food businesses in commercially diverse areas having higher-than-average social media ratings were least at risk. This paper introduces a model for timely prediction of pandemic-induced, food-related, small-business closures without reliance on private or protected financial data, and provides insights into urban design to promote small, food business survivability. 
    more » « less