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This study examines the heterogeneous correlations between rural farmers' land renting behavior and their grain production when they experienced a significant price decline.

We used well-timed panel data obtained from a two-round survey held in 2013 and 2017 among 621 households in the North China Plain. The empirical analyses were conducted by using the pooled ordinary least squares (OLS) and fixed effects models.

Rural tenants were having heterogeneous responses in land renting behavior and agricultural production when there was a price decline. A group of optimistic tenants (as professional farmers) were more likely to enlarge the farm scale for grain production through land rental markets but decrease variable investment levels (and subsequently decreased productivity) to cope with price decline. In contrast, nonprofessional farmers (the other rural tenants) were rather pessimistic about market performance, and they significantly decreased their grain production area to cope the price decline, but there was no decrease in grain productivity through reducing variable inputs.

This study contributes to the extant literature on the relationship between farmers' land renting-in behavior and agricultural production. By dividing the tenants into professional and nonprofessional farmers, we argue that there is a significant heterogeneous correlation between rural tenants' land renting behavior and grain production when farmers experience a price decline.

San Francisco started regulating short-term vacation rentals on rooms/apartments/houses located within city limits in September 2019. The objectives of this conceptual-scenario and regression study are to calculate the present value of the net earnings for a short-term residential rental property located in San Francisco pre-regulation and post-regulation, and consider a financial reason motivating households to list properties as short-term rentals.

A present value approach is used to estimate the value of rental space to tourists prior to the passage of San Francisco's short-term rental regulations compared to post-rental rules. Table 2 shows pre- and post-income scenarios. Price increases of +20, +40 and +60 percent over the initial base rate failed to restore host earnings to pre-registration levels. The present value model calculates the net revenue less net cost associated with listing a property. The regression model uses the number of listings as the dependent variable, and housing prices divided by weekly wages as independent variables.

The short-term rental regulations significantly reduce the profitability associated with short-term tourist stays offered by hosts and listed by online platforms. A host earns pre-regulation income when average daily rents increase by approximately 71.5 percent. It will likely limit income earned by hosts and Airbnb and other shared housing website platforms due to the reduced number of rental days allowed for shared housing caused by ordinances and host enrollment restrictions. The regression model results suggest that homeowners were listing properties for rent to help cover higher priced property purchases.

Airbnb, VRBO, Booking.com, and HomeAway are all private companies; this means that financial information is not publicly available. HomeAway, VRBO, and Booking.com are companies owned by Expedia. FlipKey is owned by TripAdvisor. Due to limited public information regarding income statements and property listing trends, regression analysis and descriptive statistics cannot be generated using audited financial statements.

Rent control restriction frequently sets the maximum price below the market-clearing price, which results in limited supply but increase in demand for housing. The San Francisco regulations outlaw second-home rentals and seriously limit the availability of other rentals to tourists. FlipKey and HomeAway tend to rent second homes, which San Francisco now bars from being rented for short-term.

The San Francisco restrictions were enacted with the goal of increasing the supply of rental housing available to permanent residents by restricting short-term rentals. This may have limited short-term benefits to permanent residents, but in the long term lowers income associated with single-family housing which will encourage housing arrangements that would avoid leasing restrictions and lower the number of new houses built. Other cities also have a history of rent controls, and are experiencing housing shortages and at the same time attracting large numbers of tourists. These cities may be motivated to enact similar rental restrictions as those approved in San Francisco.

These short-term rental restrictions just started being implemented and enforced. A court decision upheld them. There were media reports outlining the restrictions, but enforcement has just started, so no research papers have been written about San Francisco. Prior research studies have not used net present value analysis to calculate the loss to the host by enacted ordinances restricting tourists’ length of stay and have neither tried to explain why homeowners are listing properties for short-term rentals.

The purpose of this paper is to examine the relationship between house price affordability (HPA) and rental price affordability (RPA) in New Zealand. The cointegration of HPA and RPA is of particular focus given rising house prices and rising rents.

The study examines the lead-lad correlation between HPA and RPA. The method uses a generalised least square technique and the development of an ordinary least squares model.

The study shows that there is an existence of cointegration and unidirectional statistical causality effects between HPA and RPA across 11 regions in New Zealand. Furthermore, Auckland, Wellington and Canterbury are the three regions in which the results detect the most extreme effects amongst HPA and RPA compared to other places in the country. Extended empirical work shows interesting results that there are lead-lag effects of HPA and RPA on each other and on mortgage rates at the national scale. These effects are consistent for both methods but are changed at individual lead-lag variables and amongst different regions.

The study empirically provides useful insight for both academia and practitioners. Particularly in examining the long-run effects, cointegration and forecasting of the volatile interactions between HPA and RPA.

The majority of economic crises impact the wealth of people which in turn affect their financial capacity to purchase residential properties. However, the home financing method may also have an impact on the behaviour of house prices. This chapter intends to test argued resilience of Islamic finance to situations of financial crisis by using an Islamic home financing product called Enhanced Musharakah Mutanaqisah (EMM) which was proposed by Asadov and Ibrahim (2018) as an example and compare its performance to conventional mortgage. Two different models of home financing, conventional and EMM based ones are developed with the former reflecting basic features of conventional mortgage and the latter using rental rates and house price indices for product pricing. Both models are compared using aggregate data for the US housing market for the past 30 years in order to demonstrate the resilience of the EMM model. The findings of the study show that EMM is more flexible in terms of reflecting real situations in both the housing market and aggregate economy as compared to the conventional model. Its pricing is more accommodating particularly during times of economic downturns, and it can potentially provide the solution to numerous mortgage defaults arising from such conditions. Despite the proposed models being tested using data only from the United States, the analysis can be generalized for other countries as well. The implementation of the EMM model, as an example of Shariah-based Islamic financial product, is expected to bring fairness and justice in the relationship between financial institutions and its clients. To the best of our knowledge, this is the first attempt of simulating a Musharakah Mutanaqisah based home financing using both actual rental rates and house prices for product pricing.

The purpose of this paper is to empirically test for submarket existence based on an understanding of the residential rental housing market in Ghana.

Based on extant literature and market observations, the authors provide key concepts and an overview of the residential rental market dynamics in Ghana. Reseachers appreciate that submarkets may exist in the Ghanaian rental market but have ignored the empirical testing for submarket existence due to data asymmetries. Based on real estate experts and stakeholder consultations, a priori delineation of submarkets are constructed based on spatial, structural and a nested approach. Submarket existence is tested using the Kruskal–Wallis H test and Hedonic modelling techniques.

By using fieldwork data from Accra rental market, the analysis provides credence to the conceptualisation of submarkets and how to empirically test for same. It is argued that researchers should use alternative methods to compare results to make far-reaching conclusions.

Examining the hypothesis that differential rental values exists for submarkets has implications for policy decisions to target submarket constructs differently to improve market maturity.

The research provides stakeholder investors in the rental space an understanding of market dynamics for profit maximisation, and end-users to maximise utility in deciding where to live – and as such households could benefit from making informed investment decisions on housing.

This research is one of the first attempts to empirically identify and test for submarkets existence in Ghana’s residential rental housing market.

Short-term rental option enabled via accommodation sharing platforms is an attractive alternative to conventional long-term rental. The purpose of this study is to compare rental strategies (short-term vs long-term) and explore the main determinants for strategy selection.

Using logistic regression, this study predicts the rental strategy with the highest rate of return for a given property in the City of Philadelphia. The modeling result is then compared with the applied machine learning methods, including random forest, k-nearest neighbor, support vector machine, naïve Bayes and neural networks. The best model is finally selected based on different performance metrics that determine the prediction strength of underlying models.

By analyzing 2,163 properties, the results show that properties with more bedrooms, closer to the historic attractions, in neighborhoods with lower minority rates and higher nightlife vibe are more likely to have a higher return if they are rented out through short-term rental contract. Additionally, the property location is found out to have a significant impact on the selection of the rental strategy, which emphasizes the widely known term of “location, location, location” in the real estate market.

The findings of this study contribute to the literature by determining the neighborhood and property characteristics that make a property more suitable for the short-term rental vs the long-term one. This contribution is extremely important as it facilitates differentiating the short-term rentals from the long-term rentals and would help better understanding the supply-side in the sharing economy-based accommodation market.

This paper aims to show that the accuracy of real estate portfolio valuations and of real estate risk management can be improved through the simultaneous use of Monte Carlo simulations and options theory.

The authors' method considers the options embedded in Continental European lease contracts drawn up with tenants who may move before the end of the contract. The authors combine Monte Carlo simulations for both market prices and rental values with an optional model that takes into account a rational tenant's behaviour. They analyze how the options significantly affect the owner's income.

The authors' main findings are that simulated cash flows which take account of such options are more reliable that those usually computed by the traditional method of discounted cash flow.

Some limitations are inherent to the authors' model: these include the assumption of the rationality of tenant's decisions and the difficulty of calibrating the model given the lack of data in many markets.

The main contribution of the paper is both by accounting for market risk (Monte Carlo simulations for the prices and market rental values) and for accounting for the idiosyncratic risk (the leasing risk).

The purpose of this paper is to provide technically robust indicators of housing market performance from the records held by the Ghana Land Valuation Board, through the construction of the first ever residential price and rent indices for the aggregate and disaggregate markets.

The approach involved time series produced from hedonic models using 3,250 transaction‐based data, running from 1992 to 2007, and documents on movements in capital and rental values in Accra and Tema, the dominant commercial conurbations in the country.

The paper makes a major contribution to knowledge and understanding of housing market dynamics in Ghana. The results suggest that the derived price and rent indices look, at first sight, reasonably plausible with cyclical trends showing weak and strong patches.

The paper focuses on the development of formal housing markets through a detailed case study of Ghana, and provides findings and models of a wider application in other emerging economies.

The office market in São Paulo has been in recession since the year 2000. This situation came up due to two main factors: [i] the very aggressive attitude of developers during the period that comprises the year 1999 until 2000. At that time there was a very strong perception among investors that a new expansion era for new office buildings in São Paulo was about to begin and, moreover the Brazilian economy had started its recovery; [ii] The intense retraction of the Brazilian economy along with the political transition in 2002, which was mainly caused by the deterioration of the expectations in relation to the economic policies that would be performed by the new government.The recovery of the economic activity in the office building market firstly depends on the macroeconomic growth in Brazil and within the São Paulo metropolitan area. On the other hand, the expansion of the activity in the office buildings sector relies not only on the developers’ expectations of how and when the current vacant units will be rented, but also on the potential risk‐return composition of new buildings to be developed in the next years. This paper describes the economic scenario in which investment decisions to build new office buildings for rent in our local market are made and we also simulated both the necessary period of time for investments in the São Paulo office market to recover attractiveness and the time interval for the increase in the occupation rate absorb the actual vacant spaces. These simulations have taken place based on projections for the Brazilian GNP increase and they showed that for an annual increment of 4.5%, in 3 years could be reached both, attractiveness for new investment and occupation of vacant areas. For a 2.0% annual growth, the absorption of vacant spaces will take 4 years from now and new investment would be attractive only in 2012. Besides, we discuss the market prices fluctuations on the inflexion point where the transition from one phase of the real estate cycle (recession‐non attractiveness) to another (recovery‐attractiveness) occurs.

This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.