Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity
Spatial analysis in economics is becoming increasingly important as more spatial data and innovative data mining technologies are developed. Even in Africa, where data often crucially lack quality analysis, a variety of spatial data have recently b...
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World Bank, Washington, DC
2017
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| Online Access: | http://documents.worldbank.org/curated/en/594661496768891454/Spatial-autocorrelation-panel-regression-agricultural-production-and-transport-connectivity http://hdl.handle.net/10986/27289 |
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okr-10986-272892021-06-14T10:14:00Z Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity Iimi, Atsushi You, Liangzhi Wood-Sichra, Ulrike AGRICULTURAL PRODUCTIVITY TRANSPORT SPATIAL ANALYSIS RAIL PORTS Spatial analysis in economics is becoming increasingly important as more spatial data and innovative data mining technologies are developed. Even in Africa, where data often crucially lack quality analysis, a variety of spatial data have recently been developed, such as highly disaggregated crop production maps. Taking advantage of the historical event that rail operations were ceased in Ethiopia, this paper examines the relationship between agricultural production and transport connectivity, especially port accessibility, which is mainly characterized by rail transport. To deal with endogeneity of infrastructure placement and autocorrelation in spatial data, the spatial autocorrelation panel regression model is applied. It is found that agricultural production decreases with transport costs to the port: the elasticity is estimated at -0.094 to -0.143, depending on model specification. The estimated autocorrelation parameters also support the finding that although farmers in close locations share a certain common production pattern, external shocks, such as drought and flood, have spillover effects over neighboring areas. 2017-06-21T16:38:48Z 2017-06-21T16:38:48Z 2017-06 Working Paper http://documents.worldbank.org/curated/en/594661496768891454/Spatial-autocorrelation-panel-regression-agricultural-production-and-transport-connectivity http://hdl.handle.net/10986/27289 English en_US Policy Research Working Paper;No. 8089 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa Ethiopia |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
AGRICULTURAL PRODUCTIVITY TRANSPORT SPATIAL ANALYSIS RAIL PORTS |
| spellingShingle |
AGRICULTURAL PRODUCTIVITY TRANSPORT SPATIAL ANALYSIS RAIL PORTS Iimi, Atsushi You, Liangzhi Wood-Sichra, Ulrike Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| geographic_facet |
Africa Ethiopia |
| relation |
Policy Research Working Paper;No. 8089 |
| description |
Spatial analysis in economics is
becoming increasingly important as more spatial data and
innovative data mining technologies are developed. Even in
Africa, where data often crucially lack quality analysis, a
variety of spatial data have recently been developed, such
as highly disaggregated crop production maps. Taking
advantage of the historical event that rail operations were
ceased in Ethiopia, this paper examines the relationship
between agricultural production and transport connectivity,
especially port accessibility, which is mainly characterized
by rail transport. To deal with endogeneity of
infrastructure placement and autocorrelation in spatial
data, the spatial autocorrelation panel regression model is
applied. It is found that agricultural production decreases
with transport costs to the port: the elasticity is
estimated at -0.094 to -0.143, depending on model
specification. The estimated autocorrelation parameters also
support the finding that although farmers in close locations
share a certain common production pattern, external shocks,
such as drought and flood, have spillover effects over
neighboring areas. |
| format |
Working Paper |
| author |
Iimi, Atsushi You, Liangzhi Wood-Sichra, Ulrike |
| author_facet |
Iimi, Atsushi You, Liangzhi Wood-Sichra, Ulrike |
| author_sort |
Iimi, Atsushi |
| title |
Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| title_short |
Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| title_full |
Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| title_fullStr |
Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| title_full_unstemmed |
Spatial Autocorrelation Panel Regression : Agricultural Production and Transport Connectivity |
| title_sort |
spatial autocorrelation panel regression : agricultural production and transport connectivity |
| publisher |
World Bank, Washington, DC |
| publishDate |
2017 |
| url |
http://documents.worldbank.org/curated/en/594661496768891454/Spatial-autocorrelation-panel-regression-agricultural-production-and-transport-connectivity http://hdl.handle.net/10986/27289 |
| _version_ |
1764464118418374656 |