Geography of Investment
Germany's feed-in tariff didn't just increase wind power—it reshaped the geography of investment. Using county-level data from 1996–2010, this study estimates how guaranteed prices, wind endowments, and grid access jointly determine where turbines get built. The headline is simple: incentives work. The deeper finding is sharper: changing who pays for grid upgrades can erase scarcity signals—and push deployment ahead of integration.
+764 MW
per 1 €-cent/kWh (1996–2010)
+1,528 MW
per 1 €-cent/kWh (2005–2010)
402
counties analyzed
15 yrs
1996–2010 panel data
The German Wind Revolution
German wind capacity underwent exponential growth as successive policy instruments created bankable investment conditions. The transformation from a niche technology to a pillar of the energy system happened in three distinct phases.
Installed Wind Capacity in Germany
Two Policy Regimes
German wind support has two distinct regimes. The 1991 Stromeinspeisungsgesetz (StrEG) introduced a largely uniform remuneration rule. It created bankable cash flows—and therefore rapid early diffusion—while also concentrating projects where wind quality is naturally highest.
StrEG Era
Stromeinspeisungsgesetz
Uniform tariff based on average electricity prices. Simple, predictable, but spatially blind—investment concentrated in high-wind coastal areas.
- Uniform remuneration (90% of avg. retail price)
- Grid costs often developer-borne
- High-wind sites strongly favored
- Geographic concentration in north
EEG Era
Erneuerbare-Energien-Gesetz
Location-aware tariffs using 'reference yield' logic. High-wind sites receive premium for shorter duration; low-wind sites receive it longer.
- Wind-quality differentiated tariffs
- Grid upgrade costs socialized
- Spatial redistribution enabled
- Broader political constituency
The EEG kept the guarantee, but made support effectively location-aware. Under the “reference yield” logic, high-wind sites receive the high tariff for a shorter period, while low-wind sites receive it longer. The aim is not maximum MWh per turbine; it's a broader spatial equilibrium: fewer windfall rents in the north and more viable investment inland.
What Moves Investment
The marginal effects are striking. The econometric analysis reveals that wind investors are highly responsive to guaranteed revenue signals—and that the regulatory environment dramatically shapes spatial outcomes.
Marginal Effects: FIT Response Elasticity
A 1 €-cent/kWh increase leads to 764 MW additional annual capacity
Response nearly doubles as industry matures and financing deepens
Key Finding: The 2× increase in responsiveness during the later period reflects industry maturation—deeper project pipelines, standardized financing, and swifter developer reaction to price signals.
The Grid Paradox
The most diagnostic result concerns the structural break in grid infrastructure significance. This finding reveals a fundamental tension in Germany's energy transition.
StrEG Period (1996–1999)
Grid density is a positive siting factor
Developers preferentially located turbines near existing transmission infrastructure. Connection costs were often borne by developers, creating a natural incentive for grid-proximate sites.
EEG Period (2000–2010)
Grid density loses relevance
After the EEG shifted upgrade costs to grid operators, local transmission availability ceased to matter. Investment became decoupled from infrastructure reality.
The Copper Plate Fiction
By socializing grid upgrade costs, the EEG treated the transmission network as a free public good—a “copper plate” with infinite capacity. This fiction accelerated deployment but created a legacy of infrastructure misalignment: congestion, curtailment, redispatch costs, and politically fraught projects like SuedLink.
The Policy Trade-off
How would Germany's wind landscape differ under alternative policy designs? The counterfactual analysis compares the actual differentiated EEG with a hypothetical uniform tariff calibrated to achieve identical total capacity.
Counterfactual Comparison (2000–2010)
| Metric | EEG (Actual) | Uniform (Simulated) | Winner |
|---|---|---|---|
| Total Capacity | 8.81 GW | 8.81 GW | |
| Total Output | 86.65 TWh | 88.93 TWh | |
| Total Subsidy Cost | €7.55 B | €7.83 B | |
| Output Efficiency | 11.47 kWh/€ | 11.36 kWh/€ | |
| CO₂ Abatement | 27.17 Mt | 27.16 Mt | |
| Abatement Efficiency | 3.60 kg/€ | 3.47 kg/€ |
Uniform Tariff
Concentrates investment in windy coastal north. Schleswig-Holstein and Lower Saxony dominate. Southern Germany sees negligible development.
- Maximum physical output
- Higher total subsidy cost
- Geographic concentration
- Higher developer rents
EEG (Differentiated)
Spreads investment nationwide. By subsidizing low-wind sites with longer tariff duration, inland development becomes viable.
- Better cost efficiency
- Broader political support
- Reduced rent extraction
- Higher CO₂ abatement per €
The differentiated EEG design acts as implicit rent extraction. By paying less to infra-marginal high-yield sites and reserving higher effective support for marginal sites, it minimizes windfall profits. The result: modestly higher efficiency per public euro and stronger environmental impact per unit of subsidy.
Policy Implications
FITs mobilize capital at scale
Small changes in guaranteed prices translate into large changes in build rates. Assured revenue unlocks project pipelines and standardizes financing.
Design shapes geography
Location-aware support reshapes the spatial equilibrium—not just national totals. The choice between uniform and differentiated incentives has distributional consequences.
Integration needs a signal
If investors are insulated from grid scarcity, deployment can outrun system coherence. The 'copper plate' assumption creates efficiency debt.
Efficiency is multidimensional
Maximizing physical output differs from maximizing public value. The EEG demonstrates that rent-reducing design can outperform on cost-effectiveness.
Original Paper
The Impact of a Feed-In Tariff on Wind Power Development in Germany
ZEW - Centre for European Economic Research Discussion Paper No. 14-035
Co-Authors:
Claudia Hitaj (EC Joint Research Centre) · Andreas Löschel (University of Münster)