Quantifying the soil erosion legacy of the Soviet Union
David Wuepper,
Pasquale Borrelli,
Daniel Mueller and
Robert Finger
Authors registered in the RePEc Author Service: Daniel Müller
Agricultural Systems, 2020, vol. 185, issue C
Abstract:
We examine the historical legacy of the Soviet Union on the current rate of human-induced soil erosion in its successor countries. We use a spatial regression discontinuity design and high-resolution soil erosion data. Our results suggest strong discontinuities in current soil erosion rates along the former border of the Soviet Union. We find that soil erosion in countries that were part of the former Soviet Union is 26% lower than in neighboring countries (0.77 tons per hectare and year). In contrast, we do not find such discontinuity in potential soil erosion under natural vegetation, underlining that this effect is man-made. We show that the main mechanism is a sharp discontinuity in forest dynamics, whereas general economic and demographic differences are less important.
Keywords: Soil erosion; RUSLE; Farmland abandonment; Forest dynamics; Historical legacies; Spatial regression discontinuity (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0308521X20308015
Full text for ScienceDirect subscribers only
Related works:
Journal Article: Quantifying the soil erosion legacy of the Soviet Union (2020) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:185:y:2020:i:c:s0308521x20308015
DOI: 10.1016/j.agsy.2020.102940
Access Statistics for this article
Agricultural Systems is currently edited by J.W. Hansen, P.K. Thornton and P.B.M. Berentsen
More articles in Agricultural Systems from Elsevier
Bibliographic data for series maintained by Catherine Liu ().