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The objective of this paper is to contribute to research on the determinants of Genuine Savings (GS) by investigating its relationship to the Resource Curse (RC). The substantial empirical evidence confirming that resource-abundant countries are often characterised by slower economic growth can be traced back to the argument that natural resources generate rents independent of economic performance. Recent studies show a negative relation of this so-called RC to GS, a concept that is meant to measure sustainability by considering reinvestments of exactly these rents from natural capital into physical and human capital. Our cross-country analysis examines the influence of determinants and transmission channels identified to cause the RC on GS and its components. Results show that factors leading to the RC are also useful explanatory variables for GS: A clear influence of the share of primary exports in GNI as well as of trade, consumption, quality of institutions, etc. is found. Via the migration of employees and appreciation of the exchange rate, Dutch disease is used to show how the RC works through the different types of capital that make up GS. As a side effect, this combination of dependent variables can explain the RC more comprehensively than GDP growth

This paper shows the strong relation between the factors that lead to the resource curse (RC) and factors that lead to a decline of genuine savings (GS). There is substantial empirical evidence that economies that rely predominantly on their natural resources are also characterized by slower economic growth. This so-called RC is commonly traced back to the fact that natural resources' generate rents that are independent of a country's economic performance, which can lead to suboptimal reinvestments of this consumed natural capital. We argue that the factors responsible for the RC also have a negative effect on GS, a concept that measures "weak" sustainable development by considering reinvestment of natural capital rents in physical and human capital. We discuss whether the RC hampers possibilities for resource abundant countries to obtain sufficiently high rates of GS, and find indeed many reasons why resource-dependent countries have problems achieving positive GS rates. We survey both areas of research, emphasizing the influence of the exogenous and endogenous determinants of economic growth, which are usually used to theoretically and empirically explain the RC on the three different forms of capital considered by GS. We specify why most countries suffering from the RC have negative GS rates and explain in detail where the linkages are. This overview could help with potential advancements in the explanation of GS through the inclusion of RC effects.

The location of first generation processing plants for biogas using bulky inputs is a prominent example of locational decisions of plants that face high per unit transport costs of feedstock and simultaneously depend to a large extent on feedstock availability. Modelling the resulting regional feedstock markets then requires a spatially explicit representation of demand. With production capacities of plants small in comparison to market size, large numbers of possible type-location combinations need to be considered, requiring considerable computation time under existing integer programming-based approaches. Therefore, in this paper we aim to present an alternative, faster and more flexible iterative solution approach to simulate location decisions for processing plants. And with greater flexibility, this approach is able to take into account spatially heterogeneous transport costs depending on total demand. The approach is implemented in a modelling framework for biogas production from green maize in Germany, which currently accounts for ca. five percent of Germany's agricultural area. By modifying green maize prices, demand functions are derived and intersected with regional supply functions from an agricultural model to simulate market clearing prices and quantities. The application illustrates that our approach efficiently simulates markets characterised by small-scale demand units and high, spatially heterogeneous transport costs.