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Abstract
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Before
This study investigates whether financial support can improve energy efficiency among small and medium enterprises (SMEs) across 32 eligible European countries. Using a Randomized Controlled Trial (RCT), we assess the impact of providing €10,000 grants to 900 SMEs to implement energy-saving solutions alongside sustainability advisory services offered by the Enterprise Europe Network (EEN). Both treated and comparison firms receive standard EEN advisory services, but only the treated firms gain access to financial support, supporting (co-)investments in energy-efficient technologies, consultancy, and training for their employees. The study is set to also examine heterogeneous effects by firm type and industry sector, exploring the mechanisms driving these outcomes. By addressing financial constraints, this research contributes to understanding pathways for Europe’s transition to a sustainable, low-carbon economy.
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After
This study investigates whether financial support can improve energy efficiency among 1,964 small and medium enterprises (SMEs) across 34 eligible European countries. Using a Randomized Controlled Trial (RCT), we assess the impact of providing €10,000 grants to 986 SMEs to implement energy-saving solutions alongside sustainability advisory services offered by the Enterprise Europe Network (EEN). Both treated and comparison firms receive standard EEN advisory services, but only the treated firms gain access to financial support, supporting (co-)investments in energy-efficient technologies, consultancy, and training for their employees. The study is set to also examine heterogeneous effects by firm type and industry sector, exploring the mechanisms driving these outcomes. By addressing financial constraints, this research contributes to understanding pathways for Europe’s transition to a sustainable, low-carbon economy.
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Trial End Date
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December 31, 2026
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December 31, 2027
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Last Published
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Before
December 30, 2025 03:31 PM
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After
January 04, 2026 12:22 PM
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Intervention (Public)
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Before
The EENergy project, funded by the EU’s Single Market Program (SMP), supports small and medium enterprises (SMEs) in improving energy efficiency and sustainability, contributing to the EU’s goal of achieving climate neutrality by 2050. Implemented by the Enterprise Europe Network (EEN), the program offers advisory services to 1,800 SMEs, with 900 of them receiving up to €10,000 in direct financial support. This funding is earmarked for investments in renewable technologies, energy efficiency consultancy, and employee training. Eligible SMEs must collaborate with EEN’s sustainability advisors to create tailored action plans targeting reduction in energy consumption.
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After
The EENergy project, funded by the EU’s Single Market Program (SMP), supports small and medium enterprises (SMEs) in improving energy efficiency and sustainability, contributing to the EU’s goal of achieving climate neutrality by 2050. Implemented by the Enterprise Europe Network (EEN), the program offers advisory services to 1,964 SMEs, with 986 of them being offered up to €10,000 in direct financial support. This funding is earmarked for investments in renewable technologies, energy efficiency consultancy, and employee training. All eligible SMEs must collaborate with EEN’s sustainability advisors to create tailored action plans targeting reduction in energy consumption.
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Experimental Design (Public)
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Before
The design is a two-stage randomized trial, implemented over two calls (one between Feb-May 2024, one between Dec-Feb 2025). In the first stage, firms are assigned to treatment and control (max 900 T, 900 C). As a result of the first call for funding, 1,406 firms were randomized, with 707 firms allocated to the Cash Group (50.28%) and 699 firms to the Standard Group (49.72%). The second call randomization is planned for March 2025.
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After
The design is a firm-level randomized trial, implemented over two calls. The experiment was divided into two calls to manage operational capacity. Call 1 began with baseline surveys in February-May 2024, with 1,406 eligible firms participating. Call 2 began in December 2024 with 558 additional eligible firms.
The randomization was performed after the eligibility checks were completed. For Call 1, 1,406 firms were randomized, with 707 firms (50.3%) in the treatment group and 699 firms (49.7%) in the control group. Randomization was stratified by consortium and advisor characteristics to ensure balance. For Call 2, 558 firms were randomized into treatment vs. control (279 in each group).
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Randomization Method
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Before
Following the collection of application (baseline) data, a lottery was employed. Explored will be the comparison between SMEs that receive direct financial support of up to EUR 10k and those that “only” receive standard EEN advisory services. The randomization for the EENergy project was conducted after the eligibility checks were completed and ineligible firms were removed. The allocation of firms that applied for the first EENErgy call into the two groups — the Cash Group and the Standard Beneficiary Group — was performed on June 21st, 2024, using STATA (randtreat command).
Specifications:
1. Treatment vs control
2. Test for spillovers: compare control firms amongst high-intensity advisors with other control firms
3. Test for spillovers amongst treated firms: compare treated firms amongst high-intensity advisors with other treated firms
4. Advisor elasticity of effort, prices: regress prices, effort of advisors on high intensity dummy
Pool across calls with calls and strata dummies if specification comparable. PDS lasso to improve precision using baseline controls.
Correct for differential attrition using weighted regressions and check for differential attrition by baseline characteristics.
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After
The allocation of firms that applied for the EENErgy call into the two groups — the Cash Group and the Standard Beneficiary Group — was performed in two rounds (per call) using STATA.
Specifications:
1. Treatment vs control
2. Test for spillovers: compare control firms amongst high-intensity advisors (exploring exogenous variation) with other control firms
3. Test for spillovers amongst treated firms: compare treated firms amongst high-intensity advisors with other treated firms
4. Advisor elasticity of effort, prices: regress prices, effort of advisors on high intensity dummy
Pool across calls with calls and strata dummies if specification comparable. PDS lasso to improve precision using baseline controls.
Correct for differential attrition using weighted regressions and check for differential attrition by baseline characteristics.
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Planned Number of Clusters
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Before
Randomization is at the firm level, but we considered 62 strata of EEN advisory service providers in call 1. Additionally, we plan to control for the fact randomization occurred after two separate calls.
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After
Randomization is at the firm level, but we considered strata of EEN advisory service providers/ partners.
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Planned Number of Observations
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1,800 SMEs
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1,964 SMEs.
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Sample size (or number of clusters) by treatment arms
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Before
Planned: 900 treatment vs. 900 control (in two calls).
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Treatment Group: 986 SMEs,.
Control Group: 978 SMEs.
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
Using the indicator "share of electricity produced with own renewables (e.g., solar panels)", a sample size of 1,800 firms (900 in each group), and assuming a significance level of 0.05, and a delta (expected change) of 10 percentage points between control and treatment groups (from about 21% to 31%), the resulting power for detecting an increase in the renewable indicator is 0.998.
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After
Power calculations use the full experimental sample (N=1,964) with one endline survey, 1:1 balanced assignment, two-sided tests at α=0.05, compliance/take-up of 75% (so ITT = 0.75×ATE), and attrition scenarios of 15% and 30%. For continuous outcomes, we compute MDEs under an ANCOVA specification using the control-group SD (benchmarking 0.10/0.15/0.20 SD), and for binary extensive-margin outcomes we use two-sample proportion tests with the baseline control-group mean as (p_0). Under these assumptions, we are powered to detect ITT effects of about 0.20 SD for grant attainment and about 0.15 SD for energy and other continuous outcomes (power roughly 0.85–0.94 across attrition scenarios).
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Intervention (Hidden)
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Before
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After
All 1,964 SMEs receive comprehensive sustainability advisory services through EEN, the development of tailored energy efficiency action plans based on support with needs analysis. In addition to advisory services, the Treatment Group (986 SMEs) receive direct
financial support of up to €10,000. Eligible expenses include for instance: (a) Hard/ Capital Investments: Solar panels, heat pumps, insulation, LED lighting, HVAC upgrades, energy management systems; (b) Consultancy: Energy audits, technical assessments, investment
roadmaps; (c) Training: Employee education on energy efficiency practices. The grant operates as a reimbursement mechanism: firms implement measures and submit invoices for reimbursement up to €10,000. In the Control Group (978 SMEs), firms receive only the standard EEN advisory services without financial support.
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Secondary Outcomes (Explanation)
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Before
1. Final firm outcomes:
Index comprising:
a) Total number of FTE (full-time employees)
b) Value of total capital stock
c) Employees working on sustainability-related tasks
d) Formal sustainability practices: Adoption of sustainability targets (binary); Regular monitoring of energy usage (binary); Obtaining energy performance certificates (binary); Assignment of sustainability responsibilities (binary).
e) Revenues
f) Profits
2. Intentions for future energy investments
3. Satisfaction with energy advice: index comprising
a) How closely did they follow the baseline report’s advice
b) Agreement with statement “the EEN energy spent enough time to implement suggestions from the baseline report”
4. Support for climate mitigation policy:
Index comprising agreement with the following statements:
a) Climate change will have a serious impact on the quality of life of people in the EU during my lifetime
b) Human activities are a significant cause of climate change
c) On balance, the transition to renewable energy solar from fossil fuels like coal and gas will be beneficial for the EU economy in the next 10 years
d) The E.U. government should do more to reduce greenhouse gas emissions
e) E.U companies should do more to reduce greenhouse gas emissions
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After
1. Final firm outcomes:
Index comprising:
a) Total number of FTE (full-time employees)
b) Value of total capital stock
c) Employees working on sustainability-related tasks
d) Formal sustainability practices: Adoption of sustainability targets (binary); Regular monitoring of energy usage (binary); Obtaining energy performance certificates (binary); Assignment of sustainability responsibilities (binary).
e) Revenues
f) Profits
2. Intentions for future energy investments
3. Satisfaction with energy advice: index comprising
a) How closely did they follow the baseline report’s advice
b) Agreement with statement “the EEN advisor(s) spent enough time to support the establishment's implementation of energy efficiency plans”
4. Support for climate mitigation policy:
Index comprising agreement with the following statements:
a) Climate change will have a serious impact on the quality of life of people in the EU during my lifetime
b) Human activities are a significant cause of climate change
c) On balance, the transition to renewable energy solar from fossil fuels like coal and gas will be beneficial for the EU economy in the next 10 years
d) The EU should do more to reduce greenhouse gas emissions
e) European companies should do more to reduce greenhouse gas emissions
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