Stochastic Wealth Dynamics and Risk Management Among a Poor Population
By Travis J. Lybbert, Christopher B. Barrett, S. Desta, D. Coppock, J. Ellis, G. Holloway, Peter D. Little, Nancy Mccarthy, John Mcpeak, Gerard J. van den Berg. 2004
539 citations recorded by the source corpus.
Subfields: Management, Monitoring, Policy and Law, Sociology and Political Science, Soil Science
View Paper: https://www.semanticscholar.org/paper/602032e22a86b9f40d8ef9843481d81e7477b85e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management, Monitoring, Policy and Law
- Christopher B. Barrett
- Nathaniel D. Jensen
- Andrew G. Mude
- Michael R. Carter
- J. Skees
- John Hoddinott
- John Mcpeak
- B. Barnett
In Sociology and Political Science
- Christopher B. Barrett
- Michael R. Carter
- J. Skees
- Teevrat Garg
- B. Barnett
- Nathaniel D. Jensen
- L. McBride
- Andrew G. Mude
In Soil Science
- Christopher B. Barrett
- Michael R. Carter
- Nathaniel D. Jensen
- Andrew G. Mude
- Teevrat Garg
- L. McBride
- J. Skees
- B. Barnett
Citations in the corpus
- Rural poverty dynamics: development policy implications (2003, methodology): “Nonparametric methods can be very effective in locating thresholds, as demonstrated in Figure 1, taken from Lybbert et al. (2002). This graphic depicts the nonparametric autoregression of the natural logarithm of household herd size one and ten years ahead on current values using 17 years' herd hist”
- Poverty Traps and Safety Nets (2006, background): “(McPeak and Barrett 2001, Lybbert et al. forthcoming ).”
- Poverty Traps and Climate Risk: Limitations and Opportunities of Index-Based Risk Financing (2007, background): “…conditional on current wealth.5 That curve provides a heuristic representation of highly nonlinear wealth (or welfare) dynamics of the sort recently uncovered econometrically in Ethiopia, Kenya and South Africa (Adato et al. 2006, Barrett et al. 2006, Lybbert et al. 2004, Santos and Barrett 2006a).”
- The world's most deprived: Characteristics and causes of extreme poverty and hunger (2007, unknown): “132 World Bank 2005a. 133 Lybbert et al. 2004.”
- Contrasting income shocks with asset shocks: livestock sales in northern Kenya (2004, methodology): “15 As production externalities may exist in common property settings, milk production and herd size change estimations were conducted including a variable recording the average herd size per period of other herders in the area following the methodology of Lybbert et al. (2002). No evidence of a nega”
- The Economics of Poverty Traps and Persistent Poverty: Empirical and Policy Implications (2013, background): “By blending the resulting estimated state-conditional herd growth functions according to the observed probabilities of each rainfall state in the region, they almost exactly replicate the unconditional herd dynamics observed in the same region in other data (Lybbert et al., 2004) and can disentangle”
- Growth and Chronic Poverty: Evidence from Rural Communities in Ethiopia (2012, unknown): “( 2004 ), Carter and Barrett ( 2006 ), Adato et al.”
- Livelihood strategies, resilience and transformability in African agroecosystems (2014, background): “…and persistence of rural poverty in the African continent is often described in terms of ‘vicious cycles’, ‘downward spirals’ or ‘poverty traps’ (e.g., Lybbert et al., 2004) in the attempt to illustrate the causality at play between demographic processes, resource degradation, national or…”
- Designing Index Based Livestock Insurance for Managing Asset Risk in Northern Kenya (2013, background): “…African pastoral systems, characterized by multiple herd size equilibria such that losses that push a household below a critical threshold—typically 8–16 tropical livestock units (TLUs)4—tend to tip a household into destitution (McPeak and Barrett, 2001; Lybbert et al., 2004; Barrett et al., 2006).”
- Fractal Poverty Traps (2006, background): “For example, Lybbert et al. (2004) demonstrate that southern Ethiopian pastoralists face two strategies – migratory or sedentarized pastoralism – reflecting two different dynamic wealth equilibria.”
- Persistent poverty and informal credit (2011, background): “ern Ethiopia analyze Nonlinear wealth dynamics consistent with stylized poverty trap models were analyzed by Lybbert et al. (2004) among a poor population in southern Ethiopia, the Boran pastoralists.”
- Extreme Weather and Civil War: Does Drought Fuel Conflict in Somalia through Livestock Price Shocks? (2014, unknown): “Hence, maintaining a herd of any size becomes exceedingly difficult, meaning that sedentarization with a small herd corresponds to dire poverty in pastoralist communities (Lybbert et al. 2004).”
- Well-Being Dynamics and Poverty Traps (2016, background): “In search of the causal mechanisms of the herd dynamics observed in Lybbert et al. (2004), Santos & Barrett (2006) identify herder ability and livestock threshold levels that separate those rural pastoralists who increase their herd size over time from those who do not.”
- How Basis Risk and Spatiotemporal Adverse Selection Influence Demand for Index Insurance: Evidence from Northern Kenya (2014, background): “The empirical literature on poverty traps, which have been shown to exist among east African pastoralists (Barrett et al. 2006, Lybbert et al. 2004, Santos and Barrett 2011), indicates that demand may be non-linear with respect to wealth, changing dramatically across certain asset thresholds as…”
- Index Insurance Quality and Basis Risk: Evidence from Northern Kenya (2016, background): “First, there is a great deal of evidence that large covariate droughts are the largest cause of livestock mortality in the population for whom IBLI is available (e.g., Lybbert et al. 2004; Barrett et al. 2006; Santos and Barrett 2006; McPeak, Little, and Doss 2012).”
- Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity (2005, unknown): “However, studies of poverty traps in poor rural areas such as Lybbert et al. (2004) and Barrett et al. (2005) have used nonparametric methods with panel data and have found more sharply changing nonlinearities in their applications.”