This paper concerns the net effects of promoting renewable energies on value added and disposable income in Germany, as well as their distribution among regions and income brackets. Since its entry ...into force, the German Renewable Energy Sources Act (EEG) has stimulated tremendous investments in renewable energy capacities by guaranteeing investors a fixed price per kWh as well as a preferred feed into the grid over electricity from conventional sources. The policy measures are financed by a surcharge on electricity prices. In recent years, a controversy has arisen about potentially negative regional and social distribution effects. In this paper, multiregional price and quantity input-output models with endogenous heterogeneous households are used to trace the indirect impacts of the EEG on value added and disposable income through the complex network of regional value chains. Our findings suggest that the generation of electricity from renewable sources itself leads to small positive impacts on industries, but leads to a significant drain on household income and has regressive distributive effects. However, investment in new capacities may possibly transform these negative impacts into a positive direction for the majority of households.
Cities are pivotal hubs of socioeconomic activities, and consumption in cities contributes to global environmental pressures. Compiling city-level multi-regional input-output (MRIO) tables is ...challenging due to the scarcity of city-level data. Here we propose an entropy-based framework to construct city-level MRIO tables. We demonstrate the new construction method and present an analysis of the carbon footprint of cities in China's Hebei province. A sensitivity analysis is conducted by introducing a weight reflecting the heterogeneity between city and province data, as an important source of uncertainty is the degree to which cities and provinces have an identical ratio of intermediate demand to total demand. We compare consumption-based emissions generated from the new MRIO to results of the MRIO based on individual city input-output tables. The findings reveal a large discrepancy in consumption-based emissions between the two MRIO tables but this is due to conflicting benchmark data used in the two tables.
Wider economic impacts of heavy flooding in Germany: a non-linear programming approach. Spatial Economic Analysis. This paper further develops a new methodology to estimate the wider, indirect ...impacts of major disasters, and applies it to the 2013 heavy flooding of southern and eastern Germany. We model the attempts of economic actors to continue their usual activities, as closely as possible, by minimizing the information gain between the pre- and post-disaster pattern of economic transactions of the economy at hand. Findings show that government support of local final demand substantially reduces the indirect losses of the floods, while having a disaster at the top of the business cycle increases them. Moreover, we find that assuming fixed trade origin shares and fixed industry market shares, as in all multiregional input-output models, leads to implausibly large estimates of the indirect losses.
Subnational multi-regional input-output tables (IOT) are important tools for studying interregional socio-economic and/or environmental interrelations that help to address a wide range of current ...societal, ecological and economic challenges. However, the lack of subnational input-output data is a major obstacle which leads to a wide use of non-survey methods. Like other non-survey methods, the cross-hauling adjusted regionalization method (CHARM) was originally developed for the construction of single-regional IOT. In this paper, we extend CHARM to the case of bi- and multi-regional IOT. We find that the original CHARM formula has two limitations that are also of great importance for the single-regional case: First, cross-hauling in interregional trade is implicitly set to zero and, second, accounting balances may be violated owing to structural differences between the regional and national economies. We present a modified formula addressing these issues and examine its performance in terms of a case study.
Large databases mapping commodity flows measured in various units such as currency, tons or caloric values are the backbone of many recent environmental-economic studies. Their construction typically ...requires combining large amounts of partial information in a series of successive steps. These include the estimation of unobserved flows, transformations between units, handling aggregation re-classification and, finally, reconciling estimates with mass, financial and/or energy balances. This paper proposes a maximum entropy model that allows for the simultaneous estimation of unobserved commodity flows as well as corresponding prices such that data constraints in various units of measurement, levels of aggregation and possibly mismatching classifications are simultaneously satisfied. Its capability is assessed through a Monte-Carlo analysis and its performance compared with a simple step-wise approach. Our results suggest that the simultaneous approach performs significantly better in a vast majority of cases.
•A novel maximum entropy (Maxent) model is proposed for estimating spatially and sectorally disaggregated electricity load curves.•Model reconciles measured loads, national load curves and energy ...balances.•Model delivers information base for system planning of distributed generation.•Dual of Maxent reduces computational requirements substantially.•In a case study to Germany, results are found to be superior to pure Top-Down and Bottom-Up approaches.
Usually, disaggregated electricity load curves are estimated by using Top-Down or Bottom-Up approaches. The former requires estimating weightings for downscaling aggregated information, while the latter requires extrapolating micro-level information. In both cases, estimation would ideally be based on as much regional and sector specific information as possible, in order to obtain a realistic representation of the magnitude and temporal pattern of a regional sector’s electricity consumption. Typically, such attempts are significantly hampered by issues of limited and possibly inconsistent data, differing levels of detail, and mismatching data classifications.
This paper proposes a novel nonlinear programming model based on the maximum entropy approach. The model allows for electricity load curve estimation at arbitrary spatial, sectoral and temporal resolution, from partial and possibly inconsistent information. The proposed model integrates and systematically utilizes data usually used by either Top-Down or Bottom-Up approaches. In a case study using German data it is shown that the model combines the strength of both and, at the same time, overcomes the challenges specific to Top-Down or Bottom-up estimation.
Abstract
The call for a decent life for all within planetary limits poses a dual challenge: provide all people with the essential resources needed to live well and, collectively, not exceed the ...source and sink capacity of the biosphere to sustain human societies. We examine the corridor of possible distributions of household energy and carbon footprints that satisfy both minimum energy use for a decent life and available energy supply compatible with the 1.5 °C target in 2050. We estimated household energy and carbon footprints for expenditure deciles for 28 European countries in 2015 by combining data from national household budget surveys with the environmentally-extended multi-regional input–output model EXIOBASE. We found a top-to-bottom decile ratio (90:10) of 7.2 for expenditure, 3.1 for net energy and 2.6 for carbon. The lower inequality of energy and carbon footprints is largely attributable to inefficient energy and heating technologies in the lower deciles (mostly Eastern Europe). Adopting best technology across Europe would save 11 EJ of net energy annually, but increase environmental footprint inequality. With such inequality, both targets can only be met through the use of CCS, large efficiency improvements, and an extremely low minimum final energy use of 28 GJ per adult equivalent. Assuming a more realistic minimum energy use of about 55 GJ ae
−1
and no CCS deployment, the 1.5 °C target can only be achieved at near full equality. We conclude that achieving both stated goals is an immense and widely underestimated challenge, the successful management of which requires far greater room for maneuver in monetary and fiscal terms than is reflected in the current European political discourse.
After the publication of various multi-regional input-output (MRIO) databases over the past years and related environmental and socio-economic footprint analyses, the interest in these global value ...chain analyses is ever increasing. In order to provide forward-looking analysis of policy impacts, it is necessary to take MRIO data one step further, projecting them into the future. This paper introduces a simple approach to implementing existing climate change scenarios, such as the IEA energy technology perspective scenarios, in MRIO models. Rather than forecasting the world economy, the methodology is based on a mix of econometric estimations on the demand side and using specific information regarding technology development and its classical implementation in input-output tables. We apply this 'what if' scenario approach to the most recent version of the MRIO system EXIOBASE. We compare the development of consumption- and production-based CO2 emissions up to 2030. As an additional example, we show that the energy dependency of Europe is reduced in the 2-degree scenario compared to the 6-degree scenario, while the material dependency is higher. We discuss the major shortcoming of the model, the assumption of constant shares if no better information is available, and suggest that this actually is an advantage for deducing policy implications.
The economic impacts of the German Renewable Energy Act (EEG) are of considerable importance for the discussion of the energy transition in Germany (Energiewende). The Energiewende implies structural ...changes of the energy system by deploying Renewable Energy (and energy efficiency) Technologies (RET), but it also may induce structural changes for the overall economy, with uneven effects on a sub-national level. North-Rhine Westphalia (NRW) is an ideal case to study such regional disparities, since this federal state has scarce per-capita renewable energy sources, whereas it stands out for its energy intensive industry and fossil-fuel based power plants. In order to support renewable energy policies, mostly gross impact assessments of RET deployment have been carried out both on national and regional levels. By definition, such analyses result in positive assessments, since only expansionary effects resulting from additional demand for RET are accounted for. This paper, in contrast, presents a net impact assessment of the EEG on the NRW economy of both expansionary and contractionary effects. The latter consist of negative income effects, increased production costs and, the crowding-out of conventional energy due to the renewable energy financing mechanism (i.e., electricity surcharge), as well as its preferential status for feed-in. Our findings show how North-Rhine Westphalia, with regard to the operation of RET, suffers disproportionally from negative effects in relation to the value addition of its economy in comparison to the rest the country, whereas it benefits marginally from the production of such facilities.
•We use a new high-resolution model of the German economy.•We simulate the post-disaster economic shock of the 2013 flood in Germany.•We find the economic impact to be much higher as in previous ...studies.
During May and June 2013 heavy rains caused disastrous floods in several countries in Europe. In this study we use a new high-resolution model of the German economy to simulate the post-disaster economic shock of the flood. Due to the heavy reliance of modern economies on inter regional supply chains, substantial economic impacts are felt in states and industries outside the flooded area. Cessation of export from one industry, for example in Bayern, in the wake of the flood affects many other industries and regions. Trade links are broken immediately and cause shortages. Supply restrictions from those industries spread further, reducing production possibilities in the national and global economy. Industry- and region specific direct impacts are estimated from time series data about compensations of lost working hours from social insurance schemes in the case of external events such as business cycles and natural disasters. We estimate the total indirect loss of production possibilities that affect in particular the motor vehicle and food industries in Baden-Württemberg, Nordrhein-Westfalen and Niedersachsen, but also foreign production, to be €6.2 billion. Regions and industries outside the flooded area experience around €400 million of the loss. We find the economic impact of the flood to be much higher as in previous studies and mitigation is more likely to be considered if this effect is taken into account.
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