Examining the effect of policy instruments such as feed-in tariffs on renewable energy capacity has always been a task of both enthusiasm and frustration for statisticians and economists. The 2008 wave of subsidies, designed to jump-start investment in solar and wind power, produced a flurry of new entrants and a patchwork of output gains, but disentangling the true relationship between public incentives and private response is anything but straightforward. For those tracking this sector with official classifications, ISIC 3510—Electric power generation, transmission, and distribution—serves as the anchor point, but the real work begins once one moves beyond the boundaries of that category.
ISIC 3510, by its nature, sweeps together all manner of electricity producers: wind farms, solar parks, hydroelectric stations, even fossil fuel plants in some cases. Identifying which firms to include when measuring the impact of feed-in tariffs requires a stepwise, layered approach. It starts with the registry itself. Extracting all entities under ISIC 3510 gives a sense of the sector’s composition just before and after policy changes. Often, this raw list is more cumbersome than helpful, so supplementary filters are needed. Project-level information, business descriptions, and licensing records—when available—help to differentiate solar and wind firms from the rest.
Most countries maintain some form of licensing for renewable energy projects, especially those eligible for subsidy. Cross-referencing ISIC 3510 lists with regulatory filings or subsidy program databases adds a critical layer of specificity. Subsidy eligibility lists, published by energy ministries or tariff administrators, are particularly valuable, as they often include both awarded firms and approved capacities. In a few jurisdictions, this data can be downloaded directly; elsewhere, it is a matter of trawling through annual reports, legislative summaries, or even news articles.
Measuring the impact itself requires linking subsidy amounts—usually stated in currency per megawatt-hour, or in lump-sum payments—with subsequent changes in installed and operational capacity. The timing here is key. Policy announcements may precede new capacity by a year or more, depending on the permitting and construction cycle. A careful timeline must be reconstructed for each relevant firm: date of subsidy approval, project commissioning, first power sold to the grid. Lag effects often matter as much as headline figures.
A further challenge is that not all growth is attributable to feed-in tariffs alone. Macroeconomic shifts, falling equipment costs, or parallel incentives (like tax credits or loan guarantees) muddy the waters. Isolating the impact of a single policy demands both quantitative and qualitative steps. One method is to compare capacity growth rates for ISIC 3510-coded solar and wind firms before and after the introduction of feed-in tariffs. Another is to benchmark these changes against regions or countries that did not implement similar subsidies, allowing for broader contextual control.
Capacity data, when available, can be gleaned from grid operator statistics, market regulator publications, or company disclosures. Some firms publish annual reports with installed and operational capacity figures, while others only release them in filings or press statements. Cross-checking these sources helps fill inevitable gaps—an exercise in persistence and, at times, improvisation. Firm-level interviews, where possible, sometimes reveal informal data that never makes it to the public record, particularly for smaller operators.
Correlating subsidy amounts with capacity growth is rarely a clean exercise. At the aggregate level, scatterplots of approved subsidy rates versus new installed capacity offer a first glimpse of the relationship. Some periods show a clear uptick in projects following a boost in feed-in tariffs; other times, capacity growth lags as developers await regulatory clarity or improvements in technology costs. It is not uncommon to see a flurry of project registrations ahead of announced changes to subsidy regimes, followed by consolidation and adjustment in subsequent years.
One persistent finding is that firms respond unevenly to subsidies. Larger players often move first, leveraging established financing relationships and project pipelines. Smaller firms, or those new to the sector, may enter on the back of attractive tariffs, but only after the pioneers have navigated the initial uncertainty. Tracking these dynamics through ISIC 3510-coded records and subsidy approvals can reveal both the breadth of market participation and the concentration of capacity additions.
Keeping a clear record of the methodology is vital. Every step—data source, matching process, exclusion or inclusion criteria—becomes important when results are scrutinized or compared across studies. Ambiguities in classification or reporting are nearly unavoidable. Making note of them as part of the analytic process serves both transparency and analytical rigor.
By mapping output and correlating with subsidy flows, the relationship between policy and capacity growth becomes clearer, if never entirely simple. The data rarely speaks with one voice, but careful integration and methodical tracing can reveal underlying patterns in the sector’s transformation.