Hot and cold seasons in Texas housing markets

Hattapoglu, Mustafa; Hoxha, Indrit

doi:10.1108/ijhma-02-2020-0017

Cited by 6 publications

(10 citation statements)

References 26 publications

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“…Both estimated parameters for RM are positive and surpass the 5-percent significance criterion. That differs from what has been documented in other studies (Chong, 2020) and may reflect the prevalence of alternate channels of influence in the Las Cruces housing market (Hattapoglu & Indrit, 2021). The sum of the real rent, RENT, parameter estimates in Table 10 is positive as anticipated.…”

Section: Econometric Methodology and Empirical Resultscontrasting

confidence: 64%

Additional Evidence Regarding Las Cruces Housing Price Dynamics

Fullerton

2022

5009

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To examine housing price dynamics for Las Cruces, New Mexico, a theoretical model is developed that takes into account the supply and demand sides. The employed ARDL estimation methodology allows for more realistic modeling of market dynamics than prior studies of this residential real estate market, the second largest in New Mexico. A slightly larger sample size is also utilized. The results obtained corroborate evidence reported in several previous housing studies. Some unexpected outcomes also indicate that consistently reliable interlinkages between housing prices and explanatory variables may be elusive. Among the latter, an inverse relationship between apartment rents and single-family housing prices is most surprising but may be a consequence of the large university and college student population in Las Cruces. As post-secondary enrollments increase, so too do faculty numbers, allowing both housing prices and apartment rents to increase simultaneously. That implies that apartments and single-unit houses may be complements rather than substitutes in college towns like Las Cruces. Additional research using data for other small- and medium-sized urban economies would be helpful.

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Section: Econometric Methodology and Empirical Resultscontrasting

confidence: 64%

Additional Evidence Regarding Las Cruces Housing Price Dynamics

Fullerton

2022

5009

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“…Also, the matching quality is significantly higher for both buyers and sellers in a hot season that results in a higher surplus to be shared between them. Hattapoglu and Hoxha (2021) provide evidence for hot and cold seasons using MSA-level data in state of Texas. They find that there is a significant impact of listing prices, unemployment rates, 30-year mortgage rates, consumer sentiment and oil price changes on the liquidity of the housing markets and decisions of sellers to adjust the prices down.…”

Section: Literature Reviewmentioning

confidence: 99%

“…12. Hoxha and Yilmaz (2020) and Hattapoglu and Hoxha (2021) show that majority of MSAs in Pennsylvania and Texas experience significant differences between the hot and cold seasons in house prices.…”

Section: Notesmentioning

confidence: 99%

Short-run effects of hurricanes on the housing markets: evidence from Florida

Dogan

Hattapoglu

Hoxha

2022

IJHMA

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Purpose Many studies have shown that the intensity and the number of hurricanes are likely to increase. This paper aims to look at the immediate effects of hurricanes on the time on the market, share of houses sold and percentage of houses with price cuts in the housing market using the metropolitan statistical area-level data in Florida. Design/methodology/approach Using a difference-in-difference method, the authors estimate the impact that a hurricane has on the housing markets. Findings The authors find that a hurricane has a positive and significant effect on the time on the market. A hurricane leads to a delay of the sale of a typical house in Florida by five days. The authors test for within-year seasonality and show that these effects change with seasonality of the housing market. Markets with seasonal housing prices tend to be affected more by hurricanes than those where housing prices are not seasonal. The authors also show that effects of a hurricane are transient and fade away in a few months. The results remain significant as the hurricane intensity changes. Originality/value This is the first study to look at the short-term effects of the hurricanes and how their effects vary based on seasonality of the markets.

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“…More specifically, the sale-to-list ratio holds significance for several reasons [9][10][11][12][13]. Firstly, it serves as a pivotal gauge of housing market health, reflecting the percentage of listing prices realized in sales.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Insights: Exploring Key Factors Influencing Sale-to-List Ratio—Insights from SVM Classification and Recursive Feature Selection in the US Real Estate Market

Sobieraj,

Metelski

2024

Buildings

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The US real estate market is a complex ecosystem influenced by multiple factors, making it critical for stakeholders to understand its dynamics. This study uses Zillow Econ (monthly) data from January 2018 to October 2023 across 100 major regions gathered through Metropolitan Statistical Area (MSA) and advanced machine learning techniques, including radial kernel Support Vector Machines (SVMs), used to predict the sale-to-list ratio, a key metric that indicates the market health and competitiveness of the US real estate. Recursive Feature Elimination (RFE) is used to identify influential variables that provide insight into market dynamics. Results show that SVM achieves approximately 85% accuracy, with temporal indicators such as Days to Pending and Days to Close, pricing dynamics such as Listing Price Cut and Share of Listings with Price Cut, and rental market conditions captured by the Zillow Observed Rent Index (ZORI) emerging as critical factors influencing the sale-to-list ratio. The comparison between SVM alphas and RFE highlights the importance of time, price, and rental market indicators in understanding market trends. This study underscores the interplay between these variables and provides actionable insights for stakeholders. By contextualizing the findings within the existing literature, this study emphasizes the importance of considering multiple factors in housing market analysis. Recommendations include using pricing dynamics and rental market conditions to inform pricing strategies and negotiation tactics. This study adds to the body of knowledge in real estate research and provides a foundation for informed decision-making in the ever-evolving real estate landscape.

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Hot and cold seasons in Texas housing markets

Cited by 6 publications

References 26 publications

Additional Evidence Regarding Las Cruces Housing Price Dynamics

Additional Evidence Regarding Las Cruces Housing Price Dynamics

Short-run effects of hurricanes on the housing markets: evidence from Florida

Machine Learning Insights: Exploring Key Factors Influencing Sale-to-List Ratio—Insights from SVM Classification and Recursive Feature Selection in the US Real Estate Market

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