TY  - JOUR
A1  - Warchold, Anne
A1  - Pradhan, Prajal
A1  - Kropp, Jürgen
T1  - Variations in sustainable development goal interactions
BT  - population, regional, and income disaggregation
JF  - Sustainable development
N2  - To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross-sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade-off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade-offs and linear outweigh non-linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non-linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to "leave no one behind."
KW  - development pathways
KW  - disaggregation
KW  - inequalities
KW  - non‐ linearity
KW  - SDG interactions
KW  - SDGs
KW  - synergies and trade‐ offs
Y1  - 2020
U6  - https://doi.org/10.1002/sd.2145
SN  - 0968-0802
SN  - 1099-1719
VL  - 29
IS  - 2
SP  - 285
EP  - 299
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Warchold, Anne
A1  - Pradhan, Prajal
A1  - Thapa, Pratibha
A1  - Putra, Muhammad Panji Islam Fajar
A1  - Kropp, Jürgen
T1  - Building a unified sustainable development goal database
BT  - why does sustainable development goal data selection matter?
JF  - Sustainable development
N2  - The 2020s are an essential decade for achieving the 2030 Agenda and its Sustainable Development Goals (SDGs). For this, SDG research needs to provide evidence that can be translated into concrete actions. However, studies use different SDG data, resulting in incomparable findings. Researchers primarily use SDG databases provided by the United Nations (UN), the World Bank Group (WBG), and the Bertelsmann Stiftung & Sustainable Development Solutions Network (BE-SDSN). We compile these databases into one unified SDG database and examine the effects of the data selection on our understanding of SDG interactions. Among the databases, we observed more different than similar SDG interactions. Differences in synergies and trade-offs mainly occur for SDGs that are environmentally oriented. Due to the increased data availability, the unified SDG database offers a more nuanced and reliable view of SDG interactions. Thus, the SDG data selection may lead to diverse findings, fostering actions that might neglect or exacerbate trade-offs.
KW  - inequalities
KW  - SDG indicator databases
KW  - SDG interactions
KW  - SDG networks;
KW  - SDGs
KW  - synergies and trade-offs
Y1  - 2022
U6  - https://doi.org/10.1002/sd.2316
SN  - 0968-0802
SN  - 1099-1719
PB  - Wiley
CY  - Hoboken
ER  -