@article{Holloway:177817,
      recid = {177817},
      author = {Holloway, Garth and Shankar, Bhavani and Rahman, Sanzidur},
      title = {Bayesian spatial probit estimation: a primer and an  application to HYV rice adoption},
      journal = {Agricultural Economics: The Journal of the International  Association of Agricultural Economists},
      address = {2002-11},
      number = {968-2016-75922},
      pages = {20},
      year = {2002},
      abstract = {Increasingly, spatial econometric methods are becoming  part of the standard toolkit of applied researchers in  agricultural,
environmental and development economics.  Nonetheless, applications in discrete-choice settings  remain few and despite its
appeal, applications of the  Bayesian paradigm in these settings are still fewer. We  provide a primer to the Bayesian spatial
probit with the  objective of making accessible to non-users a class of  iterative estimation methods that have become  fairly
routine in Bayesian circles, offer an extremely  powerful addition to applied researchers toolkits, and are  essential in Bayesian
implementation of spatial econometric  models. We demonstrate the methods and apply them to  estimate the 'neighbourhood
effect' in high-yielding  variety (HYV) adoption among Bangladeshi rice producers. We  estimate the strength of this relationship
using a  standard, spatial probit model and compare the policy  conclusions with and without the neighbourhood effect  included.
© 2002 Published by Elsevier Science B.V.},
      url = {http://ageconsearch.umn.edu/record/177817},
      doi = {https://doi.org/10.22004/ag.econ.177817},
}