| Literature DB >> 36141567 |
Delia-Elena Diaconașu1, Ionel Bostan2,3, Cristina Căutișanu4, Irina Chiriac1.
Abstract
The increasing awareness of the impact of global climate change has brought bio-based projects back into consideration. Thus, having as supports the reality of the troubling scenario that threatens the entire ecosystem and the up-to-date theoretical discourse and debate on sustainable development, this article aims to investigate the socio-economic and institutional determinants that trigger the dynamics of the bioeconomy value added indicator-a valuable instrument developed and recently launched by the EU's BioMonitor project. Using a panel corrected standard errors framework, we find that investment in human development along with innovation, the growing role of women and sound public governance have a positive effect on the transition towards a durable and resilient bioeconomy at the European level. This naturally implies that a combination of social and technological innovation can ensure the rise of a sustainable bioeconomy.Entities:
Keywords: bioeconomy value added; economic-social-environmental trinity; human capital; informal institutions; panel corrected standard errors estimator; role of women; sustainable development
Mesh:
Year: 2022 PMID: 36141567 PMCID: PMC9517428 DOI: 10.3390/ijerph191811286
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Summary statistics, source for the analyzed variables and Levin–Lin–Chu panel unit root test results.
| Variable | Source | Obs. | Mean | Std. Dev. | Min | Max | LLC |
|---|---|---|---|---|---|---|---|
|
| DataM dashboard | 209 | 3.93 | 0.53 | 2.57 | 4.81 | −5.10 *** |
|
| Eurostat | 209 | 3.30 | 1.03 | 1.43 | 5.67 | −2.63 *** |
|
| UNDP–Human Development Reports | 209 | −0.06 | 0.02 | −0.12 | −0.03 | −4.69 *** |
|
| Eurostat | 144 | 38.84 | 8.04 | 24.00 | 57.70 | −6.13 *** |
|
| Eurostat | 133 | 32.11 | 6.56 | 12.20 | 48.80 | −4.78 *** |
|
| UNDP–Human Development Reports | 209 | −0.83 | 0.25 | −1.35 | −0.04 | −9.24 *** |
|
| World Bank–WGI database | 209 | 0.88 | 0.77 | −0.26 | 2.47 | −2.73 *** |
Notes: LLC test presents empirical statistics of the Levin–Lin–Chu panel unit root test (AIC criteria). *** Indicates significance at 1% level.
Results from panel analysis estimated with PCSE.
| Dependent Variable: logBE-VA | ||||
|---|---|---|---|---|
| Independent Variables | Model (1) | Model (2) | Model (3) | |
|
| logGERD | 0.368 *** | 0.406 *** | 0.409 *** |
| logHDI | 3.012 *** | 4.441 *** | 1.634 | |
|
| W_res | 0.022 *** | 0.021 *** | |
| W_mng | 0.005 * | 0.006 ** | ||
| logGII | −0.392 ** | −0.340 ** | ||
|
| CC | 0.094 *** | ||
| Cons | 2.922 *** | 1.537 *** | 1.305 *** | |
| N | 209 | 127 | 127 | |
| R2 | 0.572 | 0.637 | 0.641 | |
|
| 41,767.06 *** | 3533.63 *** | 6131.78 *** | |
Notes: The Wald test verifies the null hypothesis of non-significance of the set of parameters in the. model. Panel corrected standard errors are reported in squared brackets. *** p < 0.01, ** p < 0.05, * p < 0.1.