## 4 Materials and Methods
### Data  
A detailed description of the data for the construction of the MRIO of the German federal states is given in [PERSON] [44]. The MRIO is based on a hybrid approach [48], where, at first, the non-survey method CHARM [49] is used to construct a prior table which delivers a basic representation of the table's structure and initial estimates of its elements. Afterwards, the quality of this prior is improved through the integration of survey-based information on table elements of particular importance for this study by means of the KRAS algorithm [50; 51]. The approach taken here can be justified by the concept of holistic accuracy developed by [PERSON] [52], who found that the results of I-O models are driven by only a few large table elements. Regional income and consumption patterns are estimated from household level micro data from the income and expenditure survey (_Einkommens-und Verbrauchsstichprobe, EVS_), whereas input structures of industries are based on firm-level microdata from the German costs structure survey. Both datasets were provided by the federal statistical office. Finally, interregional trade flows between the federal states are estimated from freight transportation data.  
For an analysis of the demand-pull effects, it is particularly important to have precise data about the cost structures of the manufacturers and operators of facilities [53]. This paper applies information from a corporate survey, with technology- and region-specific data on intermediate demand, import shares, gross output, and value added as residual. These survey data have been used in numerous studies on the overall economic effects of renewables [6; 7; 8; 9; 15; 47]. Data on FiTs payment, divided according to federal state and technology, are provided by BDEW. These represent the gross output of RE sector, from which labor and intermediate inputs are derived. As a proxy for labor compensation for the production and operation of RE technologies, shares of labor sectors from comparable sectors were used (e.g., electrical equipment and machinery industry). EVS were used to estimate the impact of FiTs and labor income, as well as the electricity surcharge on available income and consumption of households.  
For the estimation of the cost-push effect from industries, it is necessary to estimate the direct effect of the surcharge on the costs of production. For this, the payments of households are subtracted from total regional surcharge payments, which delivers total payments by all industries in a region. For the allocation of this remainder across regional industries, this is carried out separately for energy-intensive industries, which pay a drastically reduced surcharge (0.05 ct for each kWh exceeding 10 GWh), and the remaining industries that pay the normal surcharge of 3.53 ct/kWh. The amount of electricity to which the reduced surcharge applies is provided by the Federal Office of Economics and Export Control (BAFA) for industries at the national level and regional totals. The estimation of the privileged electricity (electricity to which a reduced EEG surcharge applies) by regional industries assumes that the ratios of privileged to total electricity at the national and the regional level are equal, in a first step. In the second step, these estimates are adjusted to regional totals and the national values by industry using the RAS method. These estimates are then used to split total electricity consumption of regional industries provided by the federal statistical office into the amount of electricity to which the reduced surcharge applies and that amount to which the normal surcharge applies. Multiplying both by the respective surcharge and dividing the resulting monetary value of surcharge payments by an industry's gross output delivers, finally, the direct percentage increase in the cost of production.  
A detailed description of data sources, assumptions to derive the exogenous direct impacts, as well as a detailed discussion of the price and quantity input-output models can be found in the SI of Tobben [8].