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This article tries to increase public awareness of a crucial but rarely discussed global challenge by introducing a novel economic analysis: drawing on insights from various disciplines, it studies policies regulating sand extraction and trade. While sand is essential for construction and land reclamation worldwide, its extraction causes severe ecological damage in oceans, in rivers and on beaches and thus has high social costs. To derive solutions to this paramount global challenge, this article focuses on sand exports from developing countries in Southeast Asian to Singapore as a prominent example. It evaluates output, export and import taxes as the means to reduce sand extraction and trade. To this end, it utilizes an Eaton and Kortum type trade model within a general equilibrium framework. Overall, an output tax can reduce sand extraction to a large extent, while the economic costs are small for Singapore and slightly positive for the Southeast Asian sand exporters. As a novel policy, the sand tax can be implemented as a Sand Extraction Allowances Trading Scheme (SEATS). This policy can help sustainably balance Singapore's economic growth with Southeast Asia's economic development.

Between 1990 and 2008, many industrializing countries have experienced tremendous economic growth, which coincided with a substantial increase in the use of materials. That poses the question how a continued economic convergence of developing nations will affect the use of biomass, fossil fuels, and minerals. Building on the Environmental Kuznets Curve hypothesis, this study investigates whether material use reaches a maximum at a certain level of economic development and declines in income thereafter. Two indicators operationalize material use. Domestic Material Consumption (DMC) measures the apparent use of materials in a country. The Material Footprint (MFP) quantifies all materials extracted to produce a country's final demand, including materials embodied in imports. Employing a panel consisting of 144 countries, initial estimations results suggest an S-shaped (cubic) relationship between GDP per capita and material use, but the relationship is monotonically positive over most of the income range. The coefficients of the cubic model tend to become nonsignificant once endogeneity and non-stationarity are accounted for. A linear specification yields a significant (positive) coefficient irrespective of the estimation method and can thus be considered a satisfactory approximation to the income-material use relationship. The linear models that account for endogeneity and non-stationarity suggest a greater income-materials elasticity for MFP than for DMC. The long-run income elasticity is estimated to be 0.562 for DMC and 0.752 for MFP.

This article presents an applied general equilibrium model which combines the theoretical foundations of an Eaton-Kortum type model of international trade with the complexity of a global multi-region, multi-sector Computable General Equilibrium (CGE) model of production and consumption. The Eaton-Kortum model features endogenous trade-induced productivity gains via Ricardian specialization and takes non-tariff trade costs into account. Model regions and sectors can be disaggregated, e.g., representing technology-specific electricity generation. The models is tailored to explicitly study the German Federal State of Lower Saxony, a prime location for renewable electricity generation in Germany with ambitious climate policy goals. The calibration utilizes the structural estimation of a gravity model with constraints, while the disaggregation adapts methods used in regional science and energy economics. With these features the model goes beyond standard CGE models and provides new insights in the nexus between trade policy and climate policy. Simulations suggest that the removal of tariffs creates smaller welfare gains than a comparable reduction of non-tariff barriers to trade but also a slightly smaller increase in global CO2 emissions. Trade policy-induced productivity gains and renewable energy subsidies significantly reduce carbon leakage from the EU to the rest of the world by making the EU more CO2-efficient. With its large wind power potential, Lower Saxony is less susceptible to negative effects of climate policy than the rest of Germany.

We investigate why governments restrict exports of exotic raw materials taking rare earth elements as a case study. Trade restrictions on exotic materials do not have immediate macroeconomic effects. Relocating rare earth intensive industries is found to be the main reason behind China's export barriers. They are part of a more extensive strategy aiming at creating comparative advantages in these sectors and at overcoming path dependencies. Moreover, export barriers serve as a second-best instrument to reduce pollution and to slow down the depletion of exhaustible resources. Growing domestic rare earth consumption renders those increasingly ineffective. Rising reliance on mine-site regulation indicates that this fact is taken into account. Rare earth extraction is dominated by a few large companies; the demand side is dispersed. That speaks against successful lobbying for export restrictions. It appears as if the export barriers are set up to compensate mining firms.

Between 1995 and 2008, the global extraction of biomass, fossil fuels, and minerals grew from 48 to 69 billion metric tons. This study investigates how changing consumption and investment patterns affected the aforementioned increase. A series of Structural Decomposition Analyses at a global level as well as for 38 major economies is conducted. The analyses disentangle the drivers of Raw Material Consumption, which measures the extraction of materials necessary to produce a country's final demand. Data is taken from the World Input-Output Database. The results suggest that rising final demand is the predominant driver of growing Raw Material Consumption. Furthermore, final demand shifted into countries that consume material intensive goods. This shift was particularly pronounced for construction minerals and investment, indicating that infrastructure investment in industrialising nations was a key driver. The mix of goods in final demand slightly dematerialised. Falling material intensities in extractive industries as well as changes in production and trade patterns decelerated the growth of Raw Material Consumption. The country-level Structural Decomposition Analyses obtained qualitatively similar results.

The amount of materials used worldwide in production and consumption increased by 56 per cent from 1995 to 2008. Using an index decomposition analysis based on the logarithmic mean divisia index, we investigate the drivers of material use, both on a global and a country scale. We exploit a panel dataset of 40 countries, accounting for 75 per cent of worldwide material extraction and 88 per cent of GDP, from 1995 to 2008. The results show that economic growth and structural change towards material-intensive countries explain most of the growth in global material use. Slight gains in material efficiency and falling importance of material-intensive sectors have decelerating effects. The country-level analysis reveals substantial heterogeneity. Some nations exhibit stable or falling material use, while it increases notably in most countries. Improving material efficiency is able to dampen growth of material use in important industrializing nations like China or India.

This report presents the Basic WIOD CGE model. The model represents the first implementation of the World Input-Output Database (WIOD) into the CGE framework and is tailored to provide a maximum fit with WIOD data. The model is specifically designed such that it can serve as the basis for research in fields like environmental, climate and trade policy. It incorporates key features of WIOD such as bilateral and bisectoral trade ows, satellite accounts for energy consumption, greenhouse gas as well as other emissions to air on a sectoral level. As all WIOD data is available in the form of a consistent time series ranging from 1995 to 2009, the model can be calibrated to any year within this time period. The model relies on substitution elasticities which are consistently estimated from the same dataset the model itself is calibrated to. Moreover, the data preparation facilities and model are designed deliberately as exible as possible in order to allow researchers to use them as a basis for various applications. This enables researchers to secure the numerous advantages of the WIOD dataset when using CGE models for future research.

Der deutsche Strommarkt ist im Umbruch. Strom aus erneuerbaren Quellen verdrängt solchen aus konventioneller Erzeugung. Die bestehende Marktordnung fördert zwar effektiv den Ausbau der erneuerbaren Elektrizitätserzeugung, geht aber mit hohen Kosten einher. Zudem entstehen regionale Ungleichgewichte zwischen Elektrizitätserzeugung und -nachfrage. Im Folgenden wird eine neue Marktordnung für den deutschen Strommarkt skizziert, die einen kosteneffizienten Ausbau der Erneuerbaren und die Stabilität der Netze gemeinsam berücksichtigt. Das zentrale Instrument für eine neue Strommarktordnung sind Knappheitspreise. Stromerzeuger müssen Anreize erhalten, ihr Verhalten an die Knappheit von Strom am Markt anzupassen. Dazu müssen die Preise widerspiegeln, wann und wo Elektrizität knapp ist. Die Kombination aus einer Marktprämie zur Förderung der Erneuerbaren und Market Splitting zum Management von Netzengpässen kann dies erreichen.

We scrutinize the impact of international productivity gains (spillovers) induced by imports and exports on optimal tariffs. First, we solve a stylized 2x2 trade model of a large open economy and show that (a) productivity gains via exports and imports both reduce the strategically optimal tariff, (b) there exists a certain strength of productivity gains such that the incentive to manipulate the terms of trade strategically vanishes, (c) the welfare gain that can be achieved via a tariff is lower in the presence of productivity gains than in their absence, and (d) these results even hold without power on international markets. Second, we apply this model to a panel data set covering 40 countries, 29 sectors and the years 1995 to 2009. We find that importdriven productivity gains are stronger than export-driven productivity gains. Third, we extend our 2x2 model to a multi-region, multi-sector model that we calibrate to the data set used in the econometric analysis and to the econometrically estimated productivity gains. Optimal tariffs are reduced by 17% for the US and China and 40% for Brazil when taking trade-induced productivity gains into account. The USA are the only model region that gains from European optimal tariff policy. Thus, trade-induced productivity gains have empirically relevant effects on optimal tariffs.

Der deutsche Strommarkt ist im Umbruch. Strom aus erneuerbaren Quellen verdrängt solchen aus konventioneller Erzeugung. Gleichzeitig wird immer mehr Elektrizität im Norden Deutschlands produziert und muss zu den Verbrauchern im Süden transportiert werden. Die bestehende Marktordung fördert zwar effektiv den Ausbau erneuerbarer Elektrizitätserzeugung, geht aber mit hohen Kosten einher. Zudem entstehen regionale Ungleichgewichte zwischen Elektrizitätserzeugung und -nachfrage. Einerseits durch den Ausbau erneuerbarer Stromerzeugung vor allem im Norden, anderseits durch den Rückgang konventioneller Kapazitäten im Süden. Es verwundert nicht, dass momentan zahlreiche Vorschläge zur Reform des Erneuerbaren-Energien- Gesetzes und des Netzausbaus entwickelt und diskutiert werden. Die meisten bestehenden Vorschläge betrachten entweder den Ausbau der Erneuerbaren oder der Netze, gehen aber nicht auf die Interaktion zwischen beiden ein. Wir skizzieren eine neue Marktordung für den deutschen Strommarkt, die einen kosteneffzienten Ausbau der Erneuerbaren und die Stabilität der Netze gemeinsam berücksichtigt. Eine Prämie auf den Börsenstrompreis fördert die Erneuerbaren, während die Aufteilung des deutschen Strommarktes in mehrere Preiszonen hilft, effzient mit regionalen Kapazit äts- und Netzengpässen umzugehen. Durch die gezielte Stärkung von zeit- und regionalspezifschen Preissignalen erwarten wir eine deutliche Kostensenkung, sowohl im Vergleich zum bisherigen System als auch zu Vorschlägen, die den Ausbau der erneuerbaren Energien nicht mit Netzausbau und Rückgang an konventionellen Kapazit äten integrieren.

This paper presents the METal ResOurces (METRO) model, a partial equilibrium model tailored for metal markets. It allows for a disaggregated representation of the mining sector and endogenous investment in extractive capacities. It can be calibrated to a large number of metal markets. Rare Earth Elements are the first group of metals for which the model is implemented. A new dataset on Rare Earth mines is compiled to calibrate it. First results on key developments of Rare Earth markets are presented. Extensive sensitivity analyses indicate their robustness.

A diverse set of tools has been developed in Industrial Ecology to tackle the problems caused by human economic activity. These instruments include Life Cycle Assessment (LCA) and Material Flow Analysis (MFA). Especially LCA is now increasingly used in policy making. Design and Evaluation of policy measures necessitates careful weighing of costs and benefits. One has to consider the complex economic effects imposed by regulation, like costs for the industries affected by regulation, indirect effects on other industries and ecologically important rebound effects. This article discusses to what extent this evaluation is possible within LCA and MFA models. It is found that these models do not sufficiently incorporate the overall consequences of regulation and hence are not very suitable to measure the advantages or disadvantages of regulations. Therefore, adding economic aspects to Industrial Ecology models seems promising. In policy making, the effects imposed on the whole economy have to be captured, which calls for a general equilibrium framework. A Life Cycle based Computable General Equilibrium Model is proposed as a tool to assess the economic effects of regulation while remaining in life cycle thinking.