**5. Conclusions**

The objective of this study was to examine the profitability determinants of unlisted German renewable energy firms that produce electricity. The models with firm-specific determinants had a higher explanatory power than models with the industry-specific determinants only. The results are mostly in line with results from previous similar studies. German private RE companies during a period of active remuneration have not been studied before from the same perspective and the results should be useful in understanding

what determines the profitability of these companies. The results are usable in forecasting the same also in other countries that have applied Feed-in-Tariff-based support to boost the production of renewable electricity. Furthermore, a separate analysis was conducted for the SMEs and Large companies which offers insight into the differences between these size cohorts.

The results of the study are of use to managers of the RE companies when the effects of different industry environments and states of business life cycle are considered, as the authors found that the smaller and medium sized companies in terms of returns on total assets might be more affected by market concentration. Moreover, the result implying that the larger companies are negatively affected by size, and that the effect is the opposite with smaller companies, is of interest to managers and investors alike. For German policymakers, the results mean that within the scope of this research, no remarkable difference between listed and unlisted companies was uncovered in terms of the determinants that drive profitability. This information is important from the (rate-of-return) regulation point of view as it means the same regulation model can be used for both company types, from the point of view of this context.

One of the limitations of the analysis was the quality of data, as the number of observations was limited. This was especially true for the data on large companies. The analysis did not include the largest companies on the market as they were few in number (nine out of 733 companies). In addition, according to the names and descriptions of the companies, the data did not include any companies producing energy from geothermal sources. The sample sizes differed depending on the model, as typically is the case with unbalanced panel data.

There are certainly many other determinants—not addressed in this paper—that could explain firm profitability, such as managerial capabilities, other management-related variables, and investment intensity. As a topic of future research, the corporate-parent and dynamic effects and the more technical variates related to the capacity of the power facility, etc., could be added to the analysis if relevant data become available. The analysis conducted in this paper could not distinguish the firms that benefited or suffered from the FIT support, hence, the observed negative effect of the average FIT, calculated with the annual FIT level of all the RE sectors, is somewhat debatable. This is another topic for further research and for repetitive studies to understand the reasons behind these differences. Possible methodological additions and avenues for further study would be opened by using a correlated random effects model, which can provide an option for estimating the random effects model even if the assumptions of the random effects model do not hold (see, e.g., [40,43,44]) and by using the generalized method of moments, which would provide yet another methodological perspective to the study.

**Author Contributions:** Conceptualization, M.-K.L. and J.S.; methodology, M.-K.L.; validation, M.-K.L. and J.S.; formal analysis, M.-K.L.; investigation, M.-K.L.; writing—original draft preparation, J.S.; writing—review and editing, M.C.; visualization, M.-K.L.; supervision, M.C.; project administration, J.S.; funding acquisition, M.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research has received support from the Finnish Strategic Research Council (SRC) at the Academy of Finland through the Manufacturing 4.0-project, grant #335980 and # 335990.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.



**Table A1.**Panel Data Fixed Effects models for the SMEs.

*Sustainability* **2021**, *13*, 13544

(df = 7; 134)

 (df = 5; 511)

 (df = 12; 129) Note: Robust SEs used; \* *p* < 0.1; \*\* *p* < 0.05; \*\*\* *p* < 0.01.

 (df = 7; 167)

 (df = 5; 659)

 (df = 12; 162)

 (df = 7; 164)

 (df = 5; 594)

 (df = 12; 159)


Note: Robust SEs used; \* *p* < 0.1; \*\* *p* < 0.05; \*\*\* *p* < 0.01.


