Towards a comprehensive framework of the relationships between resource footprints, quality of life and economic development

The relationship between economic affluence, quality of life and environmental implications of production and consumption activities is a recurring issue in sustainability discussions. A number of studies examined selected relationships, but the general implications for future development directions of countries at different development stages are hardly addressed. In this paper, we use a global dataset with 173 countries to assess the overall relationship between resource footprints, quality of life and economic development over the period of 1990-2015. We select the Material Footprint and Carbon Footprint and contrast them with the Human Development Index, the Happiness Index and GDP per capita. Regression analyses show that the relationship between various resource footprints and quality of life generally follows a logarithmic path of development, while resource footprints and GDP per capita are linearly connected. From the empirical results, we derive a generalised path of development and cluster countries along this path. Within this comprehensive framework, we discuss options to change the path to respect planetary and social boundaries through a combination of resource efficiency increases, substitution of industries and sufficiency of consumption. We conclude that decoupling and green growth will not realise sustainable development, if planetary boundaries have already been transgressed.Series: Ecological Economic Paper

Do mining activities foster regional development? Evidence from Latin America in a spatial econometric framework

Against the backdrop of steadily increasing global raw material demand, the socio-economic implications of metal ore extraction in developing countries are of major interest in academic and policy debates. This work investigates whether mining activities relate to the economic performance of mining regions and their surrounding areas. Usually, subnational impact assessments of mining activities are conducted in the form of qualitative in-field case studies and focus on a smaller sample of mining properties and regions. In contrast, we exploit a panel of 32 Mexican, 24 Peruvian and 16 Chilean regions over the period 2008 - 2015 and, in doing so, relate mine-specific data on extraction intensity to regional economic impacts. The study employs a Spatial Durbin Model (SDM) with heteroskedastic errors to provide a flexible econometric framework to measure the impact of natural resource extraction. The results suggest that mining intensity does not significantly affect regional economic growth in both short-run and medium-run growth models. Popular arguments of the mining industry that the extractive sector would trigger positive impulses for regional economic development cannot be verified. Rather, the findings support narratives that mining regions do not benefit from their wealth in natural resources due to low labour intensity, loose links to local suppliers and profit outflows.Series: Ecological Economic Paper

A review and comparative assessment of existing approaches to calculate material footprints

Effective implementation of resource policies requires consistent and robust indicators. An increasing number of national and international strategies focussing on resource efficiency as a means for reaching a green economy call for such indicators. As supply chains of goods and services are increasingly organised on the global level, comprehensive indica-tors taking into account upstream material flows associated with internationally traded products need to be compiled. Particularly in the last few years, the development of con-sumption-based indicators of material use also termed material footprints has made considerable progress. This paper presents a comprehensive review of existing methodol-ogies to calculate material footprint-type indicators. The three prevailing approaches, i.e. environmentally extended input-output analysis (EE-IOA), coefficient approaches based on process analysis data, and hybrid approaches combing elements of EE-IOA and process analysis are presented, existing models using the different approaches discussed, and advantages and disadvantages of each approach identified. We argue that there is still a strong need for improvement of the specific approaches as well as comparability of re-sults, in order to reduce uncertainties. The paper concludes with recommendations for further development covering methodological, data and institutional aspects

Erste Zeichen einer Entkoppelung

Neue Daten zeigen, dass sich der Ressourcenverbrauch der Weltwirtschaft kontinuierlich erhöht. Während Industrieländer nach wie vor am produktivsten mit Ressourcen wirtschaften, haben sie auch die höchsten Pro-Kopf Extraktionsraten. Um langfristig die Sicherung von Wohlstand in allen Weltregionen zu gewährleisten, muss eine absolute Entkoppelung von Wirtschaftswachstum und Ressourcenverbrauch erreicht werden

Globale Effekte einer ökologischen Steuerreform in Europa

Eine ökologische Steuerreform erhöht die Preise des Naturverbrauchs und nutzt die Mehreinnahmen zur Verringerung der Lohn- nebenkosten. Dadurch werden Umweltbelastungen verringert und mehr Beschäftigung generiert. Wie würde sich diese Reform in Europa auf den Rest der Welt auswirken

Unveiling Drivers of Deforestation: Evidence from the Brazilian Amazon

Deforestation of the Amazon rainforest is a threat to global climate, biodiversity, and many other ecosystem services. In order to address this threat, an understanding of the drivers of deforestation processes is required. Indirect impacts and determinants that eventually differ across locations and over time are important factors in these processes. These are largely disregarded in applied research and thus in the design of evidence-based policies. In this study, we employ a flexible modelling framework to gain more accurate quantitative insights into the complexities of deforestation phenomena. We investigate the impacts of agriculture in Mato Grosso, Brazil, for the period 2006-2017 and explicitly consider spatial spillovers and varying impacts over time and space. Spillover effects from croplands in the Amazon appear as the major driver of deforestation, with no direct effects from agriculture in later years. This suggests moderate success of the Soy Moratorium and Cattle Agreements, but highlights their inability to address indirect effects. We find that neglect of spatial dynamics and the assumption of homogeneous impacts leads to distorted inference. Researchers need to be aware of the complex and dynamic processes behind deforestation, in order to facilitate effective policy design.Series: Ecological Economic Paper

The global cropland footprint of the non-food bioeconomy. ZEF - Discussion Papers on Development Policy No. 253

A rapidly growing share of global agricultural areas is devoted to the production of biomass for non - food purposes. The derived products include, for example, biofuels, textiles, detergents or c osmetics. Given the far - reaching global implications of an expanding non - food bioeconomy, an assessment of the bioeconomy's resource use from a footprint perspective is urgently needed. We determine the global cropland footprint of non - food products with a hybrid land flow accounting model combining data from the Food and Agriculture Organization and the multi - regional input - output model EXIOBASE. The globally interlinked model covers all cropland areas used for the production of crop - and animal - based non - food commodities for the years from 1995 to 2010. We analyse global patterns of raw material producers, processers and consumers of bio-based non-food products, with a particular focus on the European Union. Results illustrate that the EU is a major processer and the number one consumer region of non-food cropland, despite being only the fifth largest producing region. Two thirds of the cropland required to satisfy EU non-food consumption are located in other world regions, giving rise to a significant depe ndency on imported products and to potential impacts on distant ecosystems. With almost 29% in 2010, oilseed production, used to produce, for example, biofuels, detergents and polymers, represents the dominant share in the EU's non-food cropland footprint. There is also a significant contribution of more traditional non-food biomass uses such as fibre crops (for textiles) and animal hides and skins (for leather products). Our study emphasises the importance of comprehensively assessing the implications of the non-food bioeconomy expansion as envisaged in various policy strategies, such as the Bioeconomy Strategy of the European Commission

Spatially explicit assessment of water embodied in European trade: A product-level multi-regional input-output analysis

Responsible water management in an era of globalised supply chains needs to consider both local and regional water balances and international trade. In this paper, we assess the water footprints of total final demand in the EU-27 at a very detailed product level and spatial scale - an important step towards informed water policy. We apply the multi-regional input-output (MRIO) model EXIOBASE, including water data, to track the distribution of water use along product supply chains within and across countries. This enables the first spatially-explicit MRIO analysis of water embodied in Europe's external trade for almost 11,000 watersheds world-wide, tracing indirect ("virtual") water consumption in one country back to those watersheds where the water was actually extracted. We show that the EU-27 indirectly imports large quantities of blue and green water via international trade of products, most notably processed crop products, and these imports far exceed the water used from domestic sources. The Indus, Danube and Mississippi watersheds are the largest individual contributors to the EU-27's final water consumption, which causes large environmental impacts due to water scarcity in both the Indus and Mississippi watersheds. We conclude by sketching out policy options to ensure that sustainable water management within and outside European borders is not compromised by European consumption

Material Footprint Assessment in a Global Input-Output Framework

Material flow-based indicators play an important role in indicator sets related to green and resource-efficient growth. This paper examines the global flows of materials and the amounts of materials directly and indirectly necessary to satisfy domestic final demand in different countries world-wide. We calculate the indicator Raw Material Consumption (RMC), also referred to as Material Footprint (MF), by applying a global, multi-regional input-output (MRIO) model based on the GTAP database and extended by material extraction data. We examine world-wide patterns of material extraction and materials embodied in trade and consumption, investigating changes between 1997 and 2007. We find that flows of materials related to international trade have increased by almost 60% between 1997 and 2007. We show that the differences in Material Footprints per capita are huge, ranging from up to 100 tonnes in the rich, oil-exporting countries to values as low as 1.5 to 2 tonnes in some developing countries. We also quantify the differences between the indicators Domestic Material Consumption (DMC) and RMC, illustrating that net material exporters generally have a DMC larger than RMC, while the reverse is observed for net importers. Finally, we confirm the fact that most countries with stable or declining DMCs actually show increasing RMCs, indicating the occurrence of leakage effects, which are not fully captured by DMC. This challenges the world-wide use of DMC as a headline indicator for national material consumption and calls for the consideration of upstream material requirements of international trade flows

Ein neuer Ansatz des Umweltrechnungswesens

Wirtschaftliche Tätigkeiten verursachen vielfältige Umweltauswirkungen. Doch die Auswirkungen ihren Ursprüngen zuzuordnen ist oftmals schwierig. Dafür wurde nun ein um Umweltaspekte erweitertes multiregionales Input-Output-Modell entwickelt