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This paper empirically examines the characteristics of communities with successful time banking schemes. Dataset for this study consists of 909 counties in the U.S, 314 of these counties employ a time-banking currency. The selected factors in this study are captured by 13 variables that affect the number of exchanged hours, namely income inequality, social security, unemployment rate, a set of poverty and income variables and various industry composition indicators. This paper aims to statistically model which specific characteristics of local communities significantly impact the number of hours exchanged. The research especially focuses on the factors of inequality and poverty. The hypothesis tests the assumption that an increase in hours exchanged corresponds to higher income inequality, higher unemployment density, and social-security benefits to constituents. The outcome of the model partially contradicts this hypothesis. The findings indicate a higher portion of impoverished, low-income families as well as an increase in the income inequality variable to negatively affect the number of hours exchanged. Oppositely, in line with previous literature, the result of the model supports joblessness and social security as positive indicators and reveals retail-trade as a significant factor for the successful operation of a time bank. More thorough examination of such findings discloses reasons behind such patterns. A suitable policy is proposed in the end of this paper.
To cite this article: Katerina Gawthorpe (2017) ‘Which characteristics of communities boost time-banking? Case study of the United States’ International Journal of Community Currency Research 2017 Volume 21 (Summer) 51-64 <www.ijccr.net> ISSN 1325-9547. DOI http://dx.doi.org/10.15133/j.ijccr.2017.008