Four decades of rice water productivity in Bangladesh: A spatio-temporal analysis of district level panel data
Upali A. Amarasinghe and
Bharat R. Sharma
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Upali A. Amarasinghe: International Water Management Institute, Patancheru
Bharat R. Sharma: International Water Management Institute, New Delhi
No 518, Discussion Papers Series from University of Queensland, School of Economics
The bulk of the water productivity (WP) literature has focused on static cross-sectional analysis with inadequate attention given to long-term, time series analysis, either at the country level or at a lower level of aggregation (e.g., district). The present study fills this gap by analyzing WP in Bangladesh using panel data of 21 districts over 37 years (1968â€“2004) divided into three phases. It estimated levels of, and trends in, WPs of one irrigated rice (rabi) crop, and two mainly rain-fed (kharif ) rice crops, with occasional supplementary irrigation. Also examined were WPs for rice crops in irrigated and rain-fed ecosystems. The findings indicated that WP levels in Bangladesh were significantly lower than that by global standards. Overall, WP growth rates varied significantly among districts and between phases with no consistent pattern emerging. On the whole, WPs trended upwards while differing widely among districts and between phases, seasons, ecosystems and areas differentiated by physiographic characteristics. The 1980s represented a period of stagnation. Drought-prone areas grew faster while salinity-prone areas grew slower vis-a-vis non-drought and non-saline areas. In the Ganges-dependent area, WP grew faster than that in the non-Ganges-dependent area. Rice production in Bangladesh represented a highly groundwater-dependent and fossil fuel-using process with significant environmental implications suggesting that WP growth may be unsustainable. Sustaining WP growth required a range of market and non-market-based policy options.
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Journal Article: Four decades of rice water productivity in Bangladesh: A spatio-temporal analysis of district level panel data (2014)
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