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1 – 10 of over 1000Irina Farquhar and Alan Sorkin
This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative…
Abstract
This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.
Raouf Boucekkine, David de la Croix and Omar Licandro
Vintage capital growth models have been at the heart of growth theory in the 1960s. This research line collapsed in the late 1960s with the so-called embodiment controversy and…
Abstract
Vintage capital growth models have been at the heart of growth theory in the 1960s. This research line collapsed in the late 1960s with the so-called embodiment controversy and the technical sophisitication of the vintage models. This chapter analyzes the astonishing revival of this literature in the 1990s. In particular, it outlines three methodological breakthroughs explaining this resurgence: a growth accounting revolution, taking advantage of the availability of new time series; an optimal control revolution, allowing to safely study vintage capital optimal growth models; and a vintage human capital revolution, along with the rise of economic demography, accounting for the vintage structure of human capital similarly to physical capital age structuring. The related literature is surveyed.
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The purpose of this chapter is to outline new methodological developments in business valuation, with particular attention to how those developments are being used in litigation…
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The purpose of this chapter is to outline new methodological developments in business valuation, with particular attention to how those developments are being used in litigation involving lost profits and the value of operating businesses. In addition to methodological developments, the chapter also includes a discussion of recent legal developments, particularly selected cases that affect the use and standards for business valuation techniques within litigation settings. Finally, the chapter includes a mathematical appendix.
Victor Aguirregabiria and Arvind Magesan
We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to…
Abstract
We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.
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CHRISTOPHE DEISSENBERG, GUSTAV FEICHTINGER, WILLI SEMMLER and FRANZ WIRL
This chapter presents selected multiobjective methods for multiperiod portfolio optimization problem. Portfolio models are formulated as multicriteria mixed integer programs…
Abstract
This chapter presents selected multiobjective methods for multiperiod portfolio optimization problem. Portfolio models are formulated as multicriteria mixed integer programs. Reference point method together with weighting approach is proposed. The portfolio selection problem considered is based on a multiperiod model of investment, in which the investor buys and sells securities in successive investment periods. The problem objective is to allocate the wealth on different securities to optimize the portfolio expected return, the probability that the return is not less than a required level. Multiobjective methods were used to find tradeoffs between risk, return, and the number of securities in the portfolio. In computational experiments the data set of daily quotations from the Warsaw Stock Exchange were used.
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