Modeling Resource-Based Growth for Development Policy Analysis
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This dissertation focuses on the design and implementation of simulation models for development policy analysis, to support a broader understanding of the development process and the identification of effective development strategies. Development is a complex transformation process. Some countries undergo this process rapidly and successfully, while others fail to do so. Research in this field indicates that policies that are inefficiently designed and implemented can affect the ability of a country to succeed. We argue that policy-makers require appropriate quantitative models to understand the development process in their country and to support the design of effective policies, and we propose a comprehensive analytical framework for the analysis of development issues. The studies presented in this dissertation illustrate how we develop, test, and implement a resource-based approach to development policy analysis. The resource-based approach, originally developed and broadly applied in the field of firms’ strategic management, has so far known little application to the development field. We adopt a quantitative and dynamic resource-based approach, in line with current research in strategic management, and we further develop it and apply it to the analysis of development policies. We practically implement our approach through the development of System Dynamics (SD) models that we apply to policy analysis. The use of the SD method enables us to properly represent the elements of complexity that characterize the development process. We emphasize in particular how, by focusing on resources’ dynamics, our approach allows for the recognition of the key development mechanisms, to identify the relevant constraints, and to design effective policies. A key aspect of computer models for development policy analysis is the way they represent the process of growth underlying development. This first chapter initially describes the context and purpose of the work carried out as part of this dissertation. Section two discusses some limits to the applicability of current growth research – theory and empirical work alike – to development policy analysis. Subsequently, in section three we report the results of a survey recently conducted among government officials from 12 sub-Saharan countries. The survey indicates that growth theory is not consistently applied in practical medium and long term planning exercises in most of the surveyed countries, also due to some limits of the modeling methods used. In sections four and five we argue that a dynamic, resource-based approach can complement current growth research, and can provide a broader perspective on development policy analysis; and that the SD method is well suited for the implementation of such an approach. In section six, we provide an overview of our studies on the application of the resource-based approach and the SD method to various development issues. Finally, the last section of the chapter summarizes our findings and points to the need for further research in this area. The results of the analyses presented in this dissertation point to the value of the resourcebased approach as a framework for development policy analysis. In each study, the causes of development failure or unintended policy outcomes are identified in the characteristics of the mechanisms of resources’ accumulation. A variety of alternative scenarios are analyzed, and, based on their results, policy recommendations are provided. Such recommendations, although derived in different contexts, have some similarities: they generally tend to stress the importance, for effective policy design, of characterizing development beyond the purely economic perspective; and of considering its strong links with the social and human dimensions. Also, our results stress the value for development policy analysis of considering the inherent difficulties, including time lags, involved in the cumulative processes that bring about development. Most of the studies collected in this thesis have been carried out for – and often in collaboration with – policy-makers, international organizations, and field’s experts from developing countries. This not only allowed us to design our models around the needs and questions of the development stake-holders, but also gave us the opportunity to observe how – beyond the mere appreciation of the analytical results produced – the process of applying our approach contributed to stimulating the development debate. Designing effective policies is a learning process, in which the learning that occurs during the process is as important as the analytical outcomes themselves. Our last study investigates ways to enhance such learning, and we believe this to be a fertile area for further research.
Paper I: Pedercini, M., 2009, A resource-based approach to development policy analysis: a cross-country analysis. DraftPaper II: Pedercini, M., 2009, Resource-based development policy analysis in Mali: alternative growth prospects. Full text not available in BORA.Paper III: Socio-Economic Planning Sciences 44(2), Pedercini, M.; Barney, G. O., Dynamic analysis of Millennium Development Goals (MDG) interventions: the Ghana case study. Published as: Dynamic analysis of interventions designed to achieve millennium development goals (MDG): The case of Ghana, pp. 89-99. Copyright 2009 Elsevier Ltd. Reproduced with permission. Accepted version. The published article is available at: http://dx.doi.org/10.1016/j.seps.2009.08.002Paper IV: Pedercini, M.; Qureshi, M. A., 2009, A resource-based approach to modelling and simulation of income distribution: the case of Pakistan. Full text not available in BORA.Paper V: Pedercini, M., 2009, Migration and development: a resource-based approach. DraftPaper VI: Kopainsky, B.; Pedercini, M.; Alessi, S.; Davidsen, P., 2009, A blend of planning and learning: simplifying a simulation model of national development. Full text not available in BORA.
PublisherThe University of Bergen