nep-ppm New Economics Papers
on Project, Program and Portfolio Management
Issue of 2012‒09‒22
seven papers chosen by
Arvi Kuura
Parnu College - Tartu University

  1. How Much Are Resource Projects Worth? A Capital Market Perspective By Liang Li
  2. Modeling the impact of climate change in hydropower projects’ feasibility valuation By Suarez, Ronny
  3. International Risk Sharing with Market Segmentation By Eric Fesselmeyer; Leonard J. Mirman; Marc Santugini
  4. The Linkage between Outcome Differences in Cotton Production and Rural Roads Improvements - A Matching Approach By Christian K.M. Kingombe
  5. Theory and Practice in Business Intelligence By Muntean, Mihaela
  6. Bargaining in River Basin Committees: Rules Versus Discretion By Le Breton, Michel; Thomas, Alban; Zaporozhets, Vera
  7. Innovation at the Firm Level across Countries with Different Economic and Technological Capacity By Andreas Reinstaller; Fabian Unterlass

  1. By: Liang Li (Business School, University of Western Australia)
    Abstract: In many cases, a company’s capital investment decision is not a one-off “yes/no”, but occurs as a result of a sequence of decisions of a more preliminary nature. Major resource investment projects, for example, typically have to pass several “feasibility” tests before companies fully commit to them. Accordingly, there is an “investment pipeline” of projects. In this study, we examine the stock-market reaction to announcements of the progress of investment projects as they flow down the pipeline. Using a sample of Australian stocks in the resources sector, we find substantial positive abnormal returns when firms announce a change in the status of their planned projects. Interestingly, the magnitude of reaction varies substantially with the location of the project in the pipeline (such as the project being “committed”, “under construction” and “completed”). These results reveal the value-enhancing effects of the market being informed of projects in the later stages of the investment pipeline. Further analysis shows that larger stock-market reactions tend to be associated with bigger projects, smaller firms and those with lower free cash flow.
    Date: 2012
  2. By: Suarez, Ronny
    Abstract: In this paper a case study is presented to propose an alternative mechanism to include the impact of climate change into the hydropower projects’ feasibility valuation. We started from an independent engineer historical energy generation simulations; therefore, applying mixing unconditional disturbance and extreme value theory, a new path that satisfies a return level’ specification is created. The new path is used to analyze the effect of extreme events on the internal rate of return of the project. This mechanism could also be used to execute an educated guess as simple sensitivity test.
    Keywords: Extreme Value Theory; Generalized Pareto Distribution; Return Level; Mixing Unconditional Disturbances; Climate Change; Stress Testing
    JEL: C00 G00
    Date: 2012–09–12
  3. By: Eric Fesselmeyer; Leonard J. Mirman; Marc Santugini
    Abstract: We study the effect of market segmentation on international risk sharing. In our model, entrepreneurs consider undertaking risky projects in the real sector as well as selling part of their projects to investors. To capture the idea of market segmentation (i.e., agents from different countries have different opportunity costs of participating in the risky projects), the returns on the alternative risk-free investment are allowed to differ between the entrepreneurs and the investors. We first show that market segmentation establishes links between the risk-free and risky sectors as well as between the real and financial sectors. In particular, if there is market segmentation, then the amount of risk sharing depends on the risk-free rates and the expected return of the risky project. Moreover, the level of real investment also depends on the risk-free rates. Second, we show how different risk-free rates may encourage or discourage risk sharing, and even prevent risk sharing altogether.
    Keywords: International financial markets, market segmentation, risk sharing, risk project
    JEL: G15 O16
    Date: 2012
  4. By: Christian K.M. Kingombe (Graduate Institute of International Studies)
    Abstract: This paper tests the linkage between a binary treatment (rural road improvement project) and a continuous outcome (cotton productivity) in Zambia’s agro-based Eastern Province as measured by repeated cross-sections of farm-level data from the Zambian post-harvest survey (PHS). We use this PHS dataset, which covers the period from 1996/1997 to 2001/2002 across two phases, the pre-treatment phase (1996/1998) and the treatment phase when the Eastern Province Feeder Road Project (EPFRP) was being implemented (1998/2002). The identification strategy relies on the implementing of matching estimators for all three treatment parameters: Average Treatment Effect (ATE); Treatment on the Treated (TT) and Treatment on the Untreated (TUT), which is crucial in terms of policy relevance (Arcand, 2012). Matching ensures a sub-set of non-project areas that best represents the counterfactual and is done at the same geographic level of aggregation (van de Walle, 2009). Since treatment participation is not by random asignment we use the propensity score as a method to reduce the bias in the estimation of these treatment effects with observational PHS data sets in order to reduce the dimensionality of the matching problem. We find the ATT estimation results are not the same when implementing various matching using ‘the logarithm of (cotton) yield’ compared to using ‘cotton productivity’ as variable. In the latter case the following matching methods all have negative difference between treated and controls: 1-to-1 propensity score matching; k-nearest neighbours matching; radius matching; and 'spline-smoothing'. However, the Kernel matching has positive difference between treated and controls for the ‘productivity’ variable: Finally, some of the local linear regression and the Mahalanobis matching specifications yields positive difference between treated and controls for the ‘logyield’ variable, but not for the ‘productivity’ variable and not for all specifications either. Through our robustness checks of the Matching Assumpion and Sensitivity of Estimates we find that the matching doesn’t reduce the starting unbalancing. The comparison of the simulated ATT and the baseline ATT tells us that the latter is robust. We conclude that the application of various non-parametric matching methods didn’t enable us to identify a robust linkage, most likely due to the PHS data source and the evaluation design. Future rigorous rural roads impact evaluation requires panel (with pre-intervention) data for project and appropriate non-project areas, which allows for an evaluation design that combines a double difference (DID) with controls for initial conditions either through propensity score matching, regression controls or an IV (van de Walle, 2009). Regression discontinuity designs would offer an alternative method for impact evaluation (ADB, 2011; see Arcand, 2012).
    Keywords: cAverage Treatment Effects; Average Treatment on the Treated; Matching Methods; Poor rural area development project; Impact evaluation of cotton productivity; Africa; Zambia (Eastern Province).
    JEL: C2 C83 D2 O12 O13 Q12 R3
    Date: 2012–08–07
  5. By: Muntean, Mihaela
    Abstract: The debate is developed based on the following considerations: 1 - Business Intelligence (BI) is unanimous considered the art of gaining business advantage from data; therefore BI systems and infrastructures must integrate disparate data sources into a single coherent framework for real-time reporting and detailed analysis within the extended enterprise; 2 - Business Intelligence can be described as a value proposition that helps organizations in their decision-making processes; 3 – the Business Intelligence Value Chain represents a „From DATA To PROFIT“ approach and is recommended to ground any performance management program. Different aspects, including theoretical considerations and practice examples, regarding location intelligence, mobile BI, cloud-based BI, social BI and collaborative Business Intelligence will be treated, pointing out some of the author’s contributions. Nowadays, organizations have adopted more prudent policies requiring a financial justification for nearly every IT initiative, including Business Intelligence system implementations. A business-driven methodology is recommended in any BI project management approach, project scoping and planning being vital for the project success. A business-driven approach of a BI project implementation starts with a feasibility study. The decision-making process for large projects is very complicated, and will not be subject of this paper. Having in mind a middle-sized BI project, a feasibility study based on the Monte Carlo simulation method will be conducted.
    Keywords: Business Intelligence (BI); BI value chain; BI project; Location Intelligence; Social BI; Mobile BI; Cloud BI; Collaborative BI
    JEL: M10 L86
    Date: 2012–08–05
  6. By: Le Breton, Michel; Thomas, Alban; Zaporozhets, Vera
    Abstract: In this paper, we introduce a game-theoretical non-cooperative model of bargaining to analyse project funding in the French river basin com- mittees. After sorting out some of the main theoretical predictions, we proceed with an empirical application to the subsidy policy of French Wa- ter Agencies. The theoretical model of bargaining is simulated for various risk preferences, and a reduced-form estimation of the distribution of sub- sidies is performed. We find some evidence in support of the predictions regarding the role of bargaining in decision-making for water management.
    JEL: D10 D64 D91 E21
    Date: 2012–07–18
  7. By: Andreas Reinstaller (WIFO); Fabian Unterlass (WIFO)
    Abstract: This paper presents an analysis of innovation behaviour at the firm level across countries with different levels of technological capabilities and economic development. Using data from the Community Innovation Survey for 20 European countries the paper shows that the impact of total innovation expenditures – including next to R&D also outlays for technology transfer, the market introduction of innovations or new designs – increases monotonically across countries with their level of technological capabilities. R&D investments instead have a significant impact on the generation of innovations only for firms located in countries with higher levels of technological capabilities. Firm specific competencies to suggest or contribute to innovation projects have a more significant effect on the innovation output the higher the level of economic development of the countries in which firms are located. Finally, the paper presents also evidence that R&D does not generally increase the absorptive capabilities of firms.
    Keywords: Innovation decision, Catching up, Technological capabilities, R&D
    Date: 2012–09–14

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