Data

Efficient participatory irrigation institutions to support productive and sustainable agriculture in south Asia - Datasets 14-22

University of South Australia
Dr Bethany Cooper (Enriched by) Prof Lin Crase (Enriched by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://researchoutputs.unisa.edu.au/11541.1/64b46a84-ec7a-4814-9ce0-392bc6f109f4&rft.title=Efficient participatory irrigation institutions to support productive and sustainable agriculture in south Asia - Datasets 14-22&rft.identifier=http://research.unisa.edu.au/dataset/661639&rft.publisher=University of South Australia&rft.description=The project, funded by the Australian Centre for International Agricultural Research (ADP-2014-045), focuses on the devolution of responsibilities in irrigation to farmers. Broadly referred to as Participatory Irrigation Management/Irrigation Management Transfer (PIM/IMT), the project looked at the merits of this approach in different settings in south Asia. The research uses economics to help local irrigation managers better understand where and when PIM/IMT works and consider if a different approach is needed. The project uses empirical data drawn from four jurisdictions, Assam and Bihar in India and Sindh and Punjab in Pakistan, all with some unique characteristics. A large dataset has been assembled using both paper-based and mobile tablet surveys. The data covers: overall institutional performance and its relationship to agro-economic variables; drivers of compliance; gender differences and their impact on participation in water groups and perceptions of performance; data on preferred charging regimes and broader institutional arrangements for managing water at the local level. These data are unique, having been collected simultaneously across the four jurisdictions.&rft.creator=Anonymous&rft.date=2021&rft.coverage=Pakistan and India&rft_subject=910200&rft_subject=140200&rft_subject=Applied economics&rft_subject=Participatory irrigation management&rft_subject=South Asia&rft.type=dataset&rft.language=English Access the data

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Contact Information

Lin.Crase@unisa.edu.au

Full description

The project, funded by the Australian Centre for International Agricultural Research (ADP-2014-045), focuses on the devolution of responsibilities in irrigation to farmers. Broadly referred to as Participatory Irrigation Management/Irrigation Management Transfer (PIM/IMT), the project looked at the merits of this approach in different settings in south Asia.

The research uses economics to help local irrigation managers better understand where and when PIM/IMT works and consider if a different approach is needed. The project uses empirical data drawn from four jurisdictions, Assam and Bihar in India and Sindh and Punjab in Pakistan, all with some unique characteristics.

A large dataset has been assembled using both paper-based and mobile tablet surveys. The data covers: overall institutional performance and its relationship to agro-economic variables; drivers of compliance; gender differences and their impact on participation in water groups and perceptions of performance; data on preferred charging regimes and broader institutional arrangements for managing water at the local level.

These data are unique, having been collected simultaneously across the four jurisdictions.
Reuse Information

Existing data was sourced from:
local : DSET_EXISTING_DATA
No

The following instruments/equipment were used to generate or capture the data:
local : DSET_INST_DATA_CAPTURE
Hand-held tablets were used. We recommended Samsung devices but any non-apple device was used in the field.

The following software (and version) was used to analyse the data:
local : DSET_SW_DATA_ANALYSIS
Various software was used to analyse the data across research teams (SPSS, STATA, NLOGIT & XLS).

The following software (and version) was used to generate or capture the data:
local : DSET_SW_DATA_CAPTURE
The choice survey was captured using a mobile app generated by a proprietary company called AgImpact. The app was developed using CommCare V1. The choice sets were generated using STATA.

The following discipline-specific metadata standards describe the data:
local : DSET_METADATA_STANDARDS
No

Data time period: 07 2016 to 31 12 2020

This dataset is part of a larger collection

Spatial Coverage And Location

text: Pakistan and India

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