Assessing Project Risk

Finding the appropriate discount rate, or cost of capital, for evaluating investment projects requires an accurate estimate of project risk. This can be challenging because project risk cannot be estimated directly using the CAPM, but must instead be inferred from a set of traded securities, typically the equity betas of comparable firms in the same industry. These equity betas are then unlevered to undo the effect of comparable companies' financial leverage and obtain estimates of “asset” betas, which are then used to estimate project risk. The authors show that asset betas estimated in this way are likely to overestimate project risk. The equity returns of companies are risky not only because of their existing projects but also because of their growth opportunities. Such growth opportunities often include embedded “real options,” such as the option to delay, expand, or abandon a project. Because such real options are similar to leveraged positions in the underlying project, a company's growth opportunities are typically riskier than its existing projects. Therefore, to properly assess project risk, analysts must also unlever the asset betas derived from comparable company stock returns for the leverage contributed by their growth options. The authors derive a simple method for unlevering asset betas for growth options leverage in order to properly assess project risk. They then show that standard methods for assessing project risk significantly overestimate project costs of capital—by as much as 2–3% in industries such as healthcare, pharmaceuticals, communications, medical equipment, and entertainment. Their method should also be applied to stock return volatility to derive project volatility, an important input for determining the value of a firm's growth opportunities and the appropriate time for investing in these opportunities.     

Modernity/art and Marketing/aesthetics—a Note on the Social Aesthetics of Georg Simmel

This paper interrogates and contrasts representations of work and Utopia in two examples of popular culture. The examples are a sample of contemporary popular management books and a sample of work-related themes in the popular music of Bruce Springsteen. In comparing the two the paper examines how they both use utopian representations as a key element of their claims, yet do so in markedly different ways. It is argued that Springsteen uses a “voice from within” to explore the ambiguities and paradoxes that emerge from the gap between real experience and utopian desire. Conversely, popular management books tend to speak from a “voice from above” that actively suppress ambiguity and ignore power in order to reproduce the dominant ethos of contemporary capitalism. Thus while popular management provides uncritical support for its imaginary Utopia, Springsteen provides a compelling critique of the promises of economic freedom through capitalism—promises which management writers are so often complicit in (re)producing.     

An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes

Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) aims at finding the start times and execution modes for the activities of a project that optimize a given objective function while verifying a set of precedence and resource constraints. In this paper, we focus on this problem and develop a hybrid Genetic Algorithm (MM-HGA) to solve it. Its main contributions are the mode assignment procedure, the fitness function and the use of a very efficient improving method. Its performance is demonstrated by extensive computational results obtained on a set of standard instances and against the best currently available algorithms.     

Identifying barriers to the application of standardized performance indicators in local government

Abstract

Local governments in many countries are implementing administrative reforms within the framework of New Public Management (NPM) in order to improve the quality and productivity of public services. The use of performance indicators and benchmarking facilitates evaluation of efficiency regarding the provision of such services and favours the acquisition of better practices. The problems that may arise in the introduction of performance indicators in local government mainly concern the consensual design and standardization of indicators for various entities, the method to be used for calculations and the selection of analytical criteria to be applied to the values obtained. In this article, we identify obstacles that may be encountered in achieving a standardized definition of performance indicators within local government and, on the basis of learning from the practical experience of several large city councils in Spain, formulate strategies to resolve these problems, taking note of the viability and real efficacy of the solutions adopted.     

Asymptotics for panel quantile regression models with individual effects

This paper studies panel quantile regression models with individual fixed effects. We formally establish sufficient conditions for consistency and asymptotic normality of the quantile regression estimator when the number of individuals, n$n$, and the number of time periods, T$T$, jointly go to infinity. The estimator is shown to be consistent under similar conditions to those found in the nonlinear panel data literature. Nevertheless, due to the non-smoothness of the objective function, we had to impose a more restrictive condition on T$T$ to prove asymptotic normality than that usually found in the literature. The finite sample performance of the estimator is evaluated by Monte Carlo simulations.     

A conditionally heteroskedastic independent factor model with an application to financial stock returns

We propose a new conditionally heteroskedastic factor model, the GICA-GARCH model, which combines independent component analysis (ICA) and multivariate GARCH (MGARCH) models. This model assumes that the data are generated by a set of underlying independent components (ICs) that capture the co-movements among the observations, which are assumed to be conditionally heteroskedastic. The GICA-GARCH model separates the estimation of the ICs from their fitting with a univariate ARMA-GARCH model. Here, we will use two ICA approaches to find the ICs: the first estimates the components, maximizing their non-Gaussianity, while the second exploits the temporal structure of the data. After estimating and identifying the common ICs, we fit a univariate GARCH model to each of them in order to estimate their univariate conditional variances. The GICA-GARCH model then provides a new framework for modelling the multivariate conditional heteroskedasticity in which we can explain and forecast the conditional covariances of the observations by modelling the univariate conditional variances of a few common ICs. We report some simulation experiments to show the ability of ICA to discover leading factors in a multivariate vector of financial data. Finally, we present an empirical application to the Madrid stock market, where we evaluate the forecasting performances of the GICA-GARCH and two additional factor GARCH models: the orthogonal GARCH and the conditionally uncorrelated components GARCH.     

Uncovering the US term premium: An alternative route

The estimates of the US term premium crucially depend upon the ex-ante decision on whether the short-term rate is either an I(0) or an I(1) process. In this paper we estimate a fractionally integrated (I(d)) model which simultaneously determines both the order of integration of the short-term rate and the associated term premium. We show that the term premium experienced a sharp increase from essentially zero in mid-2007 to almost 3% in 2009. We also show that unemployment and term premium dynamics exhibit a very significant positive co-movement.     

Strategic planning in public R&D organizations for agribusiness: Brazil and the United States of America

There is increasing evidence that public organizations dedicated exclusively to research and development (R&D) in agribusiness need systematic management tools to incorporate the uncertainties and complexities of technological and nontechnological factors of external environments in its long-term strategic plans. The major issues are: “What will be the agribusiness science and technology (S&T) needs be in the future?” “How to prepare in order to meet these needs?” Both Empresa Brasileira de Pesquisa Agropecuária (Brazilian Agricultural Research Corporation, Embrapa), attached to the Brazilian Ministry of Agriculture and the Agricultural Research Service (ARS) of the US Department of Agriculture (USDA) have developed a comprehensive strategic and operational planning process in order to answer these key questions in the 1990s. The main objective of this article is to present a comparative and preliminary analysis of concepts, methodologies, and processes utilized, and some results obtained by these public organizations.