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Impacts of Flooding on the Rice Prod...

Hassan, S. M. Kamrul.

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Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study./
作者:	Hassan, S. M. Kamrul.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	78 p.
附註:	Source: Masters Abstracts International, Volume: 81-04.
Contained By:	Masters Abstracts International81-04.
標題:	Climate change. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13904884
ISBN:	9781088332634

Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study.
Hassan, S. M. Kamrul.

Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 78 p.

Source: Masters Abstracts International, Volume: 81-04.

Thesis (M.A.)--Colorado State University, 2019.

This item must not be sold to any third party vendors.

This paper attempts to measure the impact of flooding on rice production in Bangladesh by using two versions of econometric model, namely a total production model and a yield model. The production model uses tons of production as the dependent variable while the yield model uses the log of yield which has been defined as tons per acre. The findings from the production model suggest the vulnerability of the boro variety of rice, as it appears to have meaningful coefficients with flood damage indicator variables. The spatial dimensions of vulnerability become apparent as some districts appear to have more damaging impacts on several varieties of rice even while the national level estimates do not reveal the fact. But with both negative and positive flooding effects, the overall trend of rice production signifies the resilience and development achieved in this sector. The yield model uses similar variables to the production model, but normalizes them and drops some control due to the presence of multicollinearity. But while this second model has theoretically appealing attributes, the findings are not meaningful or significant as only one of the concerned variables gives the expected effects signs. This puts a caution in the transformation of the variables used in panel data regression.

ISBN: 9781088332634Subjects--Topical Terms:

2079509
Climate change.
Subjects--Index Terms:

Aman

Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study.
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245 1 0 $a Impacts of Flooding on the Rice Production of Bangladesh: A Panel Data Study.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 78 p.
500 $a Source: Masters Abstracts International, Volume: 81-04.
500 $a Advisor: Kling, Robert.
502 $a Thesis (M.A.)--Colorado State University, 2019.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a This paper attempts to measure the impact of flooding on rice production in Bangladesh by using two versions of econometric model, namely a total production model and a yield model. The production model uses tons of production as the dependent variable while the yield model uses the log of yield which has been defined as tons per acre. The findings from the production model suggest the vulnerability of the boro variety of rice, as it appears to have meaningful coefficients with flood damage indicator variables. The spatial dimensions of vulnerability become apparent as some districts appear to have more damaging impacts on several varieties of rice even while the national level estimates do not reveal the fact. But with both negative and positive flooding effects, the overall trend of rice production signifies the resilience and development achieved in this sector. The yield model uses similar variables to the production model, but normalizes them and drops some control due to the presence of multicollinearity. But while this second model has theoretically appealing attributes, the findings are not meaningful or significant as only one of the concerned variables gives the expected effects signs. This puts a caution in the transformation of the variables used in panel data regression.
590 $a School code: 0053.
650 4 $a Climate change. $2 bicssc $3 2079509
650 4 $a Ecology. $3 516476
650 4 $a Agricultural economics. $3 3172150
653 $a Aman
653 $a Aus
653 $a Bangladesh agriculture
653 $a Boro
653 $a Disaster
653 $a Flooding
690 $a 0503
690 $a 0404
690 $a 0329
710 2 $a Colorado State University. $b Economics. $3 1677537
773 0 $t Masters Abstracts International $g 81-04.
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793 $a English
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