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This study seeks to evaluate the impacts of land rental arrangements on crop insurance and grain marketing decisions.

The analysis is conducted in an Illinois corn‐soybean setting in which optimal marketing and crop insurance decisions are estimated for a risk‐averse producer under typical cash rent and share rent agreements using numerical simulation methods.

Results indicate that the availability of crop insurance impacts the intensity of use of put options under both cash and share rent arrangements. Similar to previous work in this area, revenue insurance is found to cause a substitution away from marketing using put options, while yield insurance is complementary to price risk management alternatives. However, while insurance and marketing play a role under both types of land tenure arrangements, shifting from a cash rent to a share rent agreement provides a relatively greater degree of risk reduction.

The results suggest that additional research is needed to explain trends in land rental contracts. Crop insurance and other federal programs may provide incentives to switch from share leases to cash rent arrangements. Changes to the design of these programs could facilitate risk management for producers more efficiently.

The unique contribution of this study is the comparison of insurance and marketing decisions under both cash rent and share rent agreements for crop land.

This study utilizes an expected utility framework to conceptualize the risk‐adjusted valuation of cash versus share leases for farmers and landowners. Farm‐level data then are used to empirically estimate the rental spread between these leases in Illinois, and to econometrically evaluate how these spreads are related to risks and other farm characteristics. The results indicate that non‐risk factors likely are the primary determinants of the magnitude and sign of the rental spread. In particular, high cash rent may be a bidding strategy to control additional leased acreage and thus expand farm size.

The majority of investment property is valued at a point after the original letting or agreed market rent (MR) at review. This briefing aims to look at the valuation of “over‐rented” property. That is the term used to describe a property where the current rent passing exceeds the current market rent.

This briefing looks at the valuation of over‐rented property by discounted cash flow and provides an example of setting up a flexible template by spreadsheet.

The spreadsheet template allows the valuer to value the over‐rented cash flow by modified or full DCF.

The flexibility of the template allows the user to change the length of the lease, the rent reviews and it calculates the term until the rent passing is exceeded by the estimated market rent.

The technique is not original but the spreadsheet template helps to explain the profile of the cash flows derived from over‐rented properties.

The aim of this paper is to use rent and price dynamics in the future cash flows in order to improve real estate portfolio valuation.

Monte Carlo simulation methods are employed for the measurement of complex cash generating assets such as real estate assets return distribution. Important simulation inputs, such as the physical real estate price volatility estimator, are provided by results on real estate indices for Paris, derived in an article by Baroni et al..

Based on a residential real estate portfolio example, simulated cash flows: provide more robust valuations than traditional DCF valuations; permit the user to estimate the portfolio's price distribution for any time horizon; and permit easy values‐at‐risk (VaR) computations.

The terminal value estimation is a core issue in real estate valuation. To estimate it, the proposed method is not based on an anticipated growth rate of cash flows but on the estimation of the trend and the volatility of real estate prices.

A tax based on land value is in many ways ideal, but many economists dismiss it by assuming it could not raise enough revenue. Standard sources of data omit much of the potential tax base, and undervalue what they do measure. The purpose of this paper is to present more comprehensive and accurate measures of land rents and values, and several modes of raising revenues from them besides the conventional property tax.

The paper identifies 16 elements of land's taxable capacity that received authorities either trivialize or omit. These 16 elements come in four groups.

In Group A, Elements 1‐4 correct for the downward bias in standard sources. In Group B, Elements 5‐10 broaden the concepts of land and rent beyond the conventional narrow perception, while Elements 11‐12 estimate rents to be gained by abating other kinds of taxes. In Group C, Elements 13‐14 explain how using the land tax, since it has no excess burden, uncaps feasible tax rates. In Group D, Elements 15‐16 define some moot possibilities that may warrant further exploration.

This paper shows how previous estimates of rent and land values have been narrowly limited to a fraction of the whole, thus giving a false impression that the tax capacity is low. The paper adds 14 elements to the traditional narrow “single tax” base, plus two moot elements advanced for future consideration. Any one of these 16 elements indicates a much higher land tax base than economists commonly recognize today. Taken together they are overwhelming, and cast an entirely new light on this subject.

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 study is to determine the Turkish housing price and rent dynamics among seven big cities with a unique monthly data set over 2003–2019. The secondary purpose is to examine bubble dynamics within the price convergence framework through alternative tests.

The paper conducts two autoregressive distributed lag (ARDL) cointegration estimates for housing prices and rents and applies conditional error correction model to investigate the long-run drivers of the Turkish housing market. The authors compare ARDL cointegration in-sample forecasts and discounted cash flow (DCF) estimates with actual prices to determine the timing, magnitude and collapse period(s) of bubbles within the price convergence framework. In particular, the generalized sup augmented Dickey–Fuller (GSADF) approach time stamps multiple explosive price behaviors.

The ARDL results confirm the theory of investment value by addressing mortgage rates, the price-to-rent ratio and rents as the fundamental factors of house prices. The price-to-rent ratio offers a comparison mechanism among houses deciding to buy a new house in which rents increase monthly real estate investment returns, and mortgage rates act as the discount rate. One key finding is that these dynamics have a greater impact on house prices than mortgage rates. Furthermore, the ARDL, DCF and GSADF findings exhibit temporal overvaluations rather than bubble signals, implying that housing price appreciations, including explosive behaviors, are consistent with fundamental advances.

This paper is considered to be innovative in determining housing market dynamics through two different ARDL estimates for the Turkish housing price index and rents in real terms as dependent variables. The authors compare the boom and collapse periods of the real housing price index and its fundamentals via the GSADF test. A final key feature of this research is its extensive data set, with 11 different regressors between 2003 and 2019.

When valuing “no market” properties using the cost approach, one of the fundamental problems is the reflection of “age‐related” depreciation in the appraisal process. The uncritical use of straight‐line depreciation produces illogical results and a new methodology “discounted assets rent” (DAR) is introduced to overcome these difficulties: site values based on existing use should not be depreciated per se in the process. A new software program (DAR) has incorporated these facilities as a “user‐friendly” valuation tool.

The operating activities section of the statement of cash flows presents a long-standing teaching challenge for accounting educators. The direct method is easy to understand yet difficult to prepare; the indirect method is harder to understand but easier to prepare. Many instructors address the two methods separately, requiring students to learn two different ways for preparing the operating section of a statement of cash flows. Because of this focus on the mechanics of preparation, the result is often an emphasis on how to prepare the cash flow statement rather than on the essential information the statement provides. In this paper, the authors note that both direct and indirect methods begin at the same point, that is, the income statement, and end at the same point, that is, cash flow from operations. Then, the authors describe one process by which the income statement and the balance sheet can be analyzed to provide the information required to present operating cash flow using either the direct or the indirect method. Using this approach allows students to apply one intuitive process for computing cash flow from operations rather than memorizing two different sets of rules for direct and indirect methods.

The purpose of this paper is to investigate the relationship between dairy farmland prices and farmland rental incomes in New Zealand from 1982 to 2009.

Using the net cash income received under a 50/50 share‐milking agreement to proxy the net cash rent, the paper attempts to explore the prices and rental incomes relationship using the present value model and then apply them in a pool regression model to show how farmers formulate their price bids.

Results show that over the long‐term dairy farmland price growth tends to be in line with rental growth. However, there is substantially higher growth in land prices in relation to the rental growth since 2002. Moreover, the risk premium placed by farmland owners on future rental cash flows since 2002 appears substantially below the historical average. The research further shows that farmers nowadays place more emphasis on the current season's payout than historical incomes in their price bids.

As a consequence the recent high land prices will be extremely sensitive to a permanent change to the low interest rate environment and future growth of dairy income. A policy recommendation is also highlighted.

The results of this paper indicates that the rapid price appreciation for New Zealand dairy farmland since 2000s might give rise to bubbles.