981 resultados para cash rental


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The kind of rental arrangements for cropland vary widely in each locality and from one geographic area to another. What is desirable for one particular landlord/tenant relationship is not acceptable for others. The purpose of this publication is to help tenants and landlords develop fair cash-rent arrangements and assist them in making sound decisions based on a fair evaluation of resources. The first section addresses whether a fixed cash-rent lease arrangement should be used. Part II discusses how to develop a fair fixed cash rental rate, while Part III provides information on setting rent for other cropland, pasture, and buildings. Part IV outlines the advantages and disadvantages of flexible cash-leasing arrangements. Part V discusses the importance of developing a written lease agreement. A sample lease form also is included.

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This study was to evaluate the profitability of land use for production of sugar cane in the São Paulo North Region, under risk conditions, from two views: the owner operator and the cash rental operator. The owner operators have higher levels of profitability comparing to cash rental owners, but with higher levels of risk. The land owners aversive to risk fits better to rent system, since the minimum return is greater than the profitability of owners operators. Moreover, if the producer is willing to production risk, the income may reach approximately 3 times that one obtained by the tenants.

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Many farm or ranch families that are attempting to bring a son or daughter back into their business experience a strain on the cash flow. Recent changes to Nebraska's Beginning Farmer Tax Credit Program provide an attractive incentive that can be very beneficial to those families. Regulation changes made in 2008 now allow parents to rent agricultural assets to their own children.

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Real estate depreciation continues to be a critical issue for investors and the appraisal profession in the UK in the 1990s. Depreciation-sensitive cash flow models have been developed, but there is a real need to develop further empirical methodologies to determine rental depreciation rates for input into these models. Although building quality has been found to be an important explanatory variable in depreciation it is very difficult to incorporate it into such models or to analyse it retrospectively. It is essential to examine previous depreciation research from real estate and economics in the USA and UK to understand the issues in constructing a valid and pragmatic way of calculating rental depreciation. Distinguishing between 'depreciation' and 'obsolescence' is important, and the pattern of depreciation in any study can be influenced by such factors as the type (longitudinal or crosssectional) and timing of the study, and the market state. Longitudinal studies can analyse change more directly than cross-sectional studies. Any methodology for calculating rental depreciation rate should be formulated in the context of such issues as 'censored sample bias', 'lemons' and 'filtering', which have been highlighted in key US literature from the field of economic depreciation. Property depreciation studies in the UK have tended to overlook this literature, however. Although data limitations and constraints reduce the ability of empirical property depreciation work in the UK to consider these issues fully, 'averaging' techniques and ordinary least squares (OLS) regression can both provide a consistent way of calculating rental depreciation rates within a 'cohort' framework.

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The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.

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This report focuses on risk-assessment practices in the private rental market, with particular consideration of their impact on low-income renters. It is based on the fieldwork undertaken in the second stage of the research process that followed completion of the Positioning Paper. The key research question this study addressed was: What are the various factors included in ‘risk-assessments’ by real estate agents in allocating ‘affordable’ tenancies? How are these risks quantified and managed? What are the key outcomes of their decision-making? The study builds on previous research demonstrating that a relatively large proportion of low-cost private rental accommodation is occupied by moderate- to high-income households (Wulff and Yates 2001; Seelig 2001; Yates et al. 2004). This is occurring in an environment where the private rental sector is now the de facto main provider of rental housing for lower-income households across Australia (Seelig et al. 2005) and where a number of factors are implicated in patterns of ‘income–rent mismatching’. These include ongoing shifts in public housing assistance; issues concerning eligibility for rent assistance; ‘supply’ factors, such as loss of low-cost rental stock through upgrading and/or transfer to owner-occupied housing; patterns of supply and demand driven largely by middle- to high-income owner-investors and renters; and patterns of housing need among low-income households for whom affordable housing is not appropriate. In formulating a way of approaching the analysis of ‘risk-assessment’ in rental housing management, this study has applied three sociological perspectives on risk: Beck’s (1992) formulation of risk society as entailing processes of ‘individualisation’; a socio-cultural perspective which emphasises the situated nature of perceptions of risk; and a perspective which has drawn attention to different modes of institutional governance of subjects, as ‘carriers of specific indicators of risk’. The private rental market was viewed as a social institution, and the research strategy was informed by ‘institutional ethnography’ as a method of enquiry. The study was based on interviews with property managers, real estate industry representatives, tenant advocates and community housing providers. The primary focus of inquiry was on ‘the moment of allocation’. Six local areas across metropolitan and regional Queensland, New South Wales, and South Australia were selected as case study localities. In terms of the main findings, it is evident that access to private rental housing is not just a matter of ‘supply and demand’. It is also about assessment of risk among applicants. Risk – perceived or actual – is thus a critical factor in deciding who gets housed, and how. Risk and its assessment matter in the context of housing provision and in the development of policy responses. The outcomes from this study also highlight a number of salient points: 1.There are two principal forms of risk associated with property management: financial risk and risk of litigation. 2. Certain tenant characteristics and/or circumstances – ability to pay and ability to care for the rented property – are the main factors focused on in assessing risk among applicants for rental housing. Signals of either ‘(in)ability to pay’ and/or ‘(in)ability to care for the property’ are almost always interpreted as markers of high levels of risk. 3. The processing of tenancy applications entails a complex and variable mix of formal and informal strategies of risk-assessment and allocation where sorting (out), ranking, discriminating and handing over characterise the process. 4. In the eyes of property managers, ‘suitable’ tenants can be conceptualised as those who are resourceful, reputable, competent, strategic and presentable. 5. Property managers clearly articulated concern about risks entailed in a number of characteristics or situations. Being on a low income was the principal and overarching factor which agents considered. Others included: - unemployment - ‘big’ families; sole parent families - domestic violence - marital breakdown - shift from home ownership to private rental - Aboriginality and specific ethnicities - physical incapacity - aspects of ‘presentation’. The financial vulnerability of applicants in these groups can be invoked, alongside expressed concerns about compromised capacities to manage income and/or ‘care for’ the property, as legitimate grounds for rejection or a lower ranking. 6. At the level of face-to-face interaction between the property manager and applicants, more intuitive assessments of risk based upon past experience or ‘gut feelings’ come into play. These judgements are interwoven with more systematic procedures of tenant selection. The findings suggest that considerable ‘risk’ is associated with low-income status, either directly or insofar as it is associated with other forms of perceived risk, and that such risks are likely to impede access to the professionally managed private rental market. Detailed analysis suggests that opportunities for access to housing by low-income householders also arise where, for example: - the ‘local experience’ of an agency and/or property manager works in favour of particular applicants - applicants can demonstrate available social support and financial guarantors - an applicant’s preference or need for longer-term rental is seen to provide a level of financial security for the landlord - applicants are prepared to agree to specific, more stringent conditions for inspection of properties and review of contracts - the particular circumstances and motivations of landlords lead them to consider a wider range of applicants - In particular circumstances, property managers are prepared to give special consideration to applicants who appear worthy, albeit ‘risky’. The strategic actions of demonstrating and documenting on the part of vulnerable (low-income) tenant applicants can improve their chances of being perceived as resourceful, capable and ‘savvy’. Such actions are significant because they help to persuade property managers not only that the applicant may have sufficient resources (personal and material) but that they accept that the onus is on themselves to show they are reputable, and that they have valued ‘competencies’ and understand ‘how the system works’. The parameters of the market do shape the processes of risk-assessment and, ultimately, the strategic relation of power between property manager and the tenant applicant. Low vacancy rates and limited supply of lower-cost rental stock, in all areas, mean that there are many more tenant applicants than available properties, creating a highly competitive environment for applicants. The fundamental problem of supply is an aspect of the market that severely limits the chances of access to appropriate and affordable housing for low-income rental housing applicants. There is recognition of the impact of this problem of supply. The study indicates three main directions for future focus in policy and program development: providing appropriate supports to tenants to access and sustain private rental housing, addressing issues of discrimination and privacy arising in the processes of selecting suitable tenants, and addressing problems of supply.

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Accessibility to housing for low to moderate income groups in Australia has been experiencing a severe decline since 2001. On the supply side, the public sector has been reducing its commitment to the direct provision of public housing. Despite high demand for affordable housing, there has been limited supply generated by non-government housing providers. One possible solution to promote an increase in affordable housing supply, like other infrastructure, is through the development of multi-stakeholder partnerships and private financing. This research aims to identify current issues underlying decision-making criteria for building multi-stakeholder partnerships to deliver affordable housing projects. It also investigates strategies for minimising risk and ensuring the financial outcomes of these partnership arrangements. A mix of qualitative in-depth interviews and quantitative surveys has been used as the main method to explore stakeholder experiences regarding their involvement in partnership arrangements in the affordable housing sector in Queensland. Two sets of interviews were conducted following an exploratory pilot study: one set in 2003-2004 and the other in 2007-2008. There were nineteen respondents representing government, private and not-for-profit organisations in the first stage interviews and surveys. The second stage interviews were focussed on twenty-two housing providers in South East Queensland. Initial analyses have been conducted using thematic and statistical analyses. This study extends the use of existing decision making tools and combines the use of a Soft System Framework to analyse the ideal state questionnaires using qualitative thematic analysis. Soft System Methodology (SSM) has been used to analyse this unstructured complex problem by using systematic thinking to develop a conceptual model and carrying it to the real world situations to solve the problem. This research found that the diversity of stakeholder capability and their level of risk acceptance will allow partnerships to develop the best synergies and a degree of collaboration which achieves the required financial return within acceptable risk parameters. However, some of the negativity attached to future commitment to such partnerships has been found to be the anticipation of a worse outcome than that expected from independent action. Many interviewees agree that housing providers' fear of financial risk and community rejection has been central to dampening their enthusiasm for entering such investment projects. The creation of a mixed-use development structure will mitigate both risk and return as the commercial income will subsidise the affordable housing development and will normalise concentration of marginalised low-income people who live in a prime location with an award winning design. In addition, tenant support schemes and rent-to-buy incentive programs will encourage them to secure their tenancies and significantly reduce the risk of rent arrears and property damage. There is also a breakthrough investment vehicle offered by the social developer which sells the non-physical but financial product to individual and institutional investors to mitigate further financial risk. Finally, this study recommends modification of the current value-for-money framework in favour of broader partnership arrangements which are more closely aligned with risk minimisation strategies.

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Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

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The provision of shelter is a basic need and in Australia there has been a history of home ownership. However recent economic growth and rising construction costs, particularly over the past decade, has placed home ownership out of reach for some. In response to increased affordability pressures, the Australian Federal Government established the National Rental Affordability Scheme (NRAS) in 2008. The aim of establishing the NRAS initiative is to stimulate the supply of new affordable rental dwellings, targeting 50,000 new properties by June 2012, through the provision of a National Rental Incentive for each “approved” dwelling. To be approved the dwelling must be newly constructed and subsequently rented to eligible low and moderate income households at rentals no greater than 80 percent of market rates. There is a further requirement that the accommodation be provided as part of the scheme for no less than 10 years. The requirement to provide new residential accommodation at below market rentals for no less than 10 years has an impact on value and as such the valuation methodologies employed. To give guidance to valuers this paper investigates the scheme, the impact on value and expectations for the future.

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The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.