Hedging effectiveness of total returns swaps: application to the Japanese market

The development of the real estate swap market offers many opportunities for investors to adjust the exposure of their portfolios to real estate. A number of OTC transactions have been observed in markets around the world. In this paper we examine the Japanese commercial real estate market from the point of view of an investor holding a portfolio of properties seeking to reduce the portfolio exposure to the real estate market by swapping an index of real estate for LIBOR. This paper explores the practicalities of hedging portfolios comprising small numbers of individual properties against an appropriate index. We use the returns from 74 properties owned by Japanese Real Estate Investment Trusts over the period up to September 2007. The paper also discusses and applies the appropriate stochastic processes required to model real estate returns in this application and presents alternative ways of reporting hedging effectiveness. We find that the development of the derivative does provide the capacity for hedging market risk but that the effectiveness of the hedge varies considerably over time. We explore the factors that cause this variability.

Organic certification, export market access and the impacts of policy: Bayesian estimation of avocado smallholder “times-to-organic certification” in Michoacán Mexico

This study analyzes organic adoption decisions using a rich set of time-to-organic durations collected from avocado small-holders in Michoacán Mexico. We derive robust, intrasample predictions about the profiles of entry and exit within the conventional-versus-organic complex and we explore the sensitivity of these predictions to choice of functional form. The dynamic nature of the sample allows us to make retrospective predictions and we establish, precisely, the profile of organic entry had the respondents been availed optimal amounts of adoption-restraining resources. A fundamental problem in the dynamic adoption literature, hitherto unrecognized, is discussed and consequent extensions are suggested.

Demand, supply and willingness-to-pay for extension services in an emerging-market setting

Although it may be wholly inappropriate to generalize, the most important resource available to a subsistence household is the total amount of time that its members have available to spend in productive enterprises. In this context, services that minimize the time that it takes to perform productive activities are valuable to the household. Consequently the household is willing to relinquish quantities of other resources in exchange for quantities of the time-saving service. These simple observations motivate a search for the values that subsistence households place on time-saving services. This search is especially important when it is realized that extension services promote productivity, enhance the surplus-generating potential of the household and can, as a consequence, promote immersion into markets that are currently constrained by thinness and instability. In this capacity, extension visitation has the potential to overcome one of the principal impediments to economic development, namely lack of density of market participation. In this article, we consider this issue in the context of a rich data set on milk-market participation by small-holder dairy producers in the Ethiopian highlands.

Tobit estiamtion with unknown point of censoring with an application to milk market participation in the Ethiopian highlands

Data augmentation is a powerful technique for estimating models with latent or missing data, but applications in agricultural economics have thus far been few. This paper showcases the technique in an application to data on milk market participation in the Ethiopian highlands. There, a key impediment to economic development is an apparently low rate of market participation. Consequently, economic interest centers on the “locations” of nonparticipants in relation to the market and their “reservation values” across covariates. These quantities are of policy interest because they provide measures of the additional inputs necessary in order for nonparticipants to enter the market. One quantity of primary interest is the minimum amount of surplus milk (the “minimum efficient scale of operations”) that the household must acquire before market participation becomes feasible. We estimate this quantity through routine application of data augmentation and Gibbs sampling applied to a random-censored Tobit regression. Incorporating random censoring affects markedly the marketable-surplus requirements of the household, but only slightly the covariates requirements estimates and, generally, leads to more plausible policy estimates than the estimates obtained from the zero-censored formulation

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Commercial real estate and equity market bubbles: are they contagious to REITs?

This paper uses a regime-switching approach to determine whether prices in the US stock, direct real estate and indirect real estate markets are driven by the presence of speculative bubbles. The results show significant evidence of the existence of periodically partially collapsing speculative bubbles in all three markets. A multivariate bubble model is then developed and implemented to evaluate whether the stock and real estate bubbles spill over into REITs. The underlying stock market bubble is found to be a stronger influence on the securitised real estate market bubble than that of the property market. Furthermore, the findings suggest a transmission of speculative bubbles from the direct real estate to the stock market, although this link is not present for the returns themselves.