Highway to Economic Growth? Competition in Public Works Tenders in the Democratic Republic of Congo

The Democratic Republic of Congo (DRC) is one of the poorest countries in the world. The construction sector will play an essential part to bring the country on the path of economic growth, and competition within the sector is crucial to achieve this goal. In this paper, we analyse the effect of competition in public works tenders in the DRC, using a unique and newly assembled database on public works contracts. We find that the number of participating bidders significantly reduces contract prices, confirming our prior hypothesis that competitive pressure can enhance the overall performance of the sector. Further, we account for the possibility of heteregenous tender participants, finding that the competition effect can vary with the degree of bidders' heterogeneity.     

Technological paradigms,patterns of learning and development: An introductory roadmap

This paper presents an evolutionary microeconomic theory of innovation and production and discusses its implications for development theory. Using the notions of technological paradigm and trajectory, it develops an alternative view of firm behavior and learning. It is shown then how these are embedded in broader national systems of innovation which account for persistent differences in technological cappacities between countries. Finally, this bottom-up evolutionary analysis is linked with an institutional top-down approach, and the potential fruitfulness of this dialogue is demonstrated.We thank the discussants and participants at the workshop on Technology and Competitiveness in Developing Countries, Venice, 26/11/93, for their useful comments.The research leading to this work has benefited at various stages from the support of the Italian National Research Council (CNR, Progetto Strategico Combiamento Technologico e Crescita Economica) and of the International Institute of Applied System Analysis (IIASA, Austria).     

The contribution of trout fly fishing to the economy of Rhodes,North Eastern Cape,South Africa

Recent government legislation, which calls for the eradication of trout from ecosystems where they may cause harm, could damage the tourism appeal of many South African catchments. However, no South African studies have tried to quantify the economic impact of removing trout from rivers and streams. This study aimed first to value the Rhodes trout fishery, North Eastern Cape, South Africa, and second to assess whether the trout fly fishing industry in Rhodes could form the foundation for the implementation of a local economic development initiative. Overall, the study found that the trout fishing industry directly generates approximately R5 658 240 per annum, and sustains a minimum of 39 direct job opportunities for the community of Rhodes, and can therefore provide the impetus for the creation of a tourism-based local economic development programme.     

Markov decision processes under model uncertainty

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle, we obtain a local-to-global paradigm, namely solving a local, that is, a one time-step robust optimization problem leads to an optimizer of the global (i.e., infinite time-steps) robust stochastic optimal control problem, as well as to a corresponding worst-case measure. Moreover, we apply this framework to portfolio optimization involving data of the . We present two different types of ambiguity sets; one is fully data-driven given by a Wasserstein-ball around the empirical measure, the second one is described by a parametric set of multivariate normal distributions, where the corresponding uncertainty sets of the parameters are estimated from the data. It turns out that in scenarios where the market is volatile or bearish, the optimal portfolio strategies from the corresponding robust optimization problem outperforms the ones without model uncertainty, showcasing the importance of taking model uncertainty into account.     

Optimal insurance under maxmin expected utility

We examine a problem of demand for insurance indemnification, when the insured is sensitive to ambiguity and behaves according to the maxmin expected utility model of Gilboa and Schmeidler (J. Math. Econ. 18:141–153, 1989), whereas the insurer is a (risk-averse or risk-neutral) expected-utility maximiser. We characterise optimal indemnity functions both with and without the customary ex ante no-sabotage requirement on feasible indemnities, and for both concave and linear utility functions for the two agents. This allows us to provide a unifying framework in which we examine the effects of the no-sabotage condition, of marginal utility of wealth, of belief heterogeneity, as well as of ambiguity (multiplicity of priors) on the structure of optimal indemnity functions. In particular, we show how a singularity in beliefs leads to an optimal indemnity function that involves full insurance on an event to which the insurer assigns zero probability, while the decision maker assigns a positive probability. We examine several illustrative examples, and we provide numerical studies for the case of a Wasserstein and a Rényi ambiguity set.