Real option valuation of public sector R&D investments with a down-and-out barrier option

This paper presents a real options approach for valuing public-sector research and development projects, using a down-and-out barrier option. Specifically, it considers the potential savings to the tax payer for investing in technology to be purchased by a national government. The valuation is performed with stretched trinomial lattices. Government-driven demand for this technology is equated with the underlying asset, and valuation measured in terms of potential government savings. Two variables, volatility of demand for the technology and unit cost, are treated as uncertain. A Monte Carlo simulation is performed to understand the effects of these variables on the valuation. Other variables are estimated, and a parametric analysis is performed to understand the effects of these variables. To illustrate how this approach could be used, the development of a new sensor, to be used in large networks that track greenhouse gas fluxes, is considered as an example.     

Exact linear rank tests for two‐sample equivalence problems with continuous data

The present paper introduces a methodology for the semiparametric or non‐parametric two‐sample equivalence problem when the effects are specified by statistical functionals. The mean relative risk functional of two populations is given by the average of the time‐dependent risk. This functional is a meaningful non‐parametric quantity, which is invariant under strictly monotone transformations of the data. In the case of proportional hazard models, the functional determines just the proportional hazard risk factor. It is shown that an equivalence test of the type of the two‐sample Savage rank test is appropriate for this functional. Under proportional hazards, this test can be carried out as an exact level α test. It also works quite well under other semiparametric models. Similar results are presented for a Wilcoxon rank‐sum test for equivalence based on the Mann–Whitney functional given by the relative treatment effect.     

Der Lehrstuhl für Allgemeine Betriebswirtschaftslehre — insbesondere Rechnungswesen und Controlling — der Helmut-Schmidt-Universität,Universität der Bundeswehr Hamburg

Ohne Zusammenfassung     

Nearly exact sample size calculation for powerful non‐randomized tests for differences between binomial proportions

In the case of two independent samples, it turns out that among the procedures taken in consideration, BOSCHLOO'S technique of raising the nominal level in the standard conditional test as far as admissible performs best in terms of power against almost all alternatives. The computational burden entailed in exact sample size calculation is comparatively modest for both the uniformly most powerful unbiased randomized and the conservative non‐randomized version of the exact Fisher‐type test. Computing these values yields a pair of bounds enclosing the exact sample size required for the Boschloo test, and it seems reasonable to replace the exact value with the middle of the corresponding interval. Comparisons between these mid‐N estimates and the fully exact sample sizes lead to the conclusion that the extra computational effort required for obtaining the latter is mostly dispensable. This holds also true in the case of paired binary data (McNemar setting). In the latter, the level‐corrected score test turns out to be almost as powerful as the randomized uniformly most powerful unbiased test and should be preferred to the McNemar–Boschloo test. The mid‐N rule provides a fairly tight upper bound to the exact sample size for the score test for paired proportions.     

Utility maximization under a shortfall risk constraint

The article analyzes optimal portfolio choice of utility maximizing agents in a general continuous-time financial market model under a joint budget and downside risk constraint. The risk constraint is given in terms of a class of convex risk measures. We do not impose any specific assumptions on the price processes of the underlying assets. We analyze under which circumstances the risk constraint is binding. We provide a closed-form solution to the optimization problem in a general semimartingale framework. For a complete market, the wealth maximization problem is equivalent to a dynamic portfolio optimization problem.     

Sustainable humanitarian supply chain management – exploring new theory

Disaster response operations aim at helping as many victims as possible in the shortest time, with limited consideration of the socio-economic context. During the disaster rehabilitation phase, the perspective needs to broaden and comprehensively take into account the local environment. We propose a framework of sustainable humanitarian supply chain management (SCM) that facilitates such comprehensive performance. We conceptualise the framework by combining literature from the fields of sustainable and humanitarian SCM. We test the framework through an analytic induction process by means of multiple case studies of four relief organisations. Our framework suggests that supply chain design needs to be aligned not only to relief organisations’ enablers, but also to the population's long-term requirements as well as any socio-economic and governmental contingency factors. A good fit between these dimensions leads to sustainable performance. The framework provides an instrument for relief organisations to achieve sustainable performance in the disaster rehabilitation phase.     

Increasing the price variation in a repeated cross section

Insufficient price variation seriously hampers many applications of consumer demand models. This paper examines the empirical performance of a potential remedy for this problem that was suggested by [Lewbel, A., 1989. Identification and estimation of equivalence scales under weak separability. Review of Economic Studies 56, 311–316], the construction of individual specific price indices for bundles of goods. These individual specific price indices allow for a population with heterogeneity in preferences for goods within a given bundle of goods. We confine ourselves to heterogeneous Cobb Douglas within bundle preferences, while between bundles, we allow for several parametric and even general nonparametric specifications. In a variety of settings, we show that such prices produce superior empirical results than the ones obtained through the traditional practice of using aggregate price indices. Our empirical analysis is based on the British Family Expenditure Survey data, and uses several categories of food. Both in parametric as well as nonparametric models, we obtain higher precision of estimates for parameters or functions, as well as economically more plausible results.