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  <controlfield tag="001">UP-8027390931316279185</controlfield>
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  <datafield tag="100" ind1="1" ind2=" ">
   <subfield code="a">Sentones, Shem Rufus Q.</subfield>
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  <datafield tag="245" ind1="0" ind2="0">
   <subfield code="a">Measuring the economic impact of weather determinants on agriculture of Davao region</subfield>
   <subfield code="b">a Ricardian approach</subfield>
   <subfield code="c">Shem Rufus Q. Sentones; Pedro A. Alviola IV., adviser.</subfield>
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   <subfield code="c">2017</subfield>
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   <subfield code="a">36 leaves</subfield>
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   <subfield code="a">Thesis (BS Agribusiness Economics) -- University of the Philippines Mindanao, May 2017</subfield>
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   <subfield code="a">Thirty-two percent of the Filipino workforce are employed in agriculture-related activities. Thirty-seven percent of the employment of Davao region is on agriculture-related jobs. Many studies show that a change in weather variables affects the net revenue of a farm per hectare. Farmers are very dependent on weather and weather variables such as rainfall because of its effects on farm yield of their farms. However, erratic weather patterns make agricultural production vulnerable. This research aimed to measure the impact of weather determinants to the net income of rice and corn farmers in Davao Region. This research used a Ricardian Approach as a method to identify the impact of weather on the net income of farmers. Two wets of models were estimated, one set of models uses the average values for weather variables and the other uses standard deviation. The models consist of two Ordinary Least Squares (OLS) models and one Least Absolute Deviation (LAD) model. An OLS model with robust standard errors and the other with bootstrapped standard errors. The results of all models showed that selecting rice farming over corn farming can affect the net income of farms per hectare and five models showed that membership of livelihood associations has positive effect in net income. Using Akaike information criterion, the LAD model with standard deviation of weather variables is identified as the model that best fits the data. The model shows that both rice and air humidity significantly affects the net income of farmers. Those who are into rice farming have more net income by around Php 44,000 per hectare compared to those who are into corn farming. An additional 1 unit (%) of the variability of the air humidity can decrease the net income of farmers by around  Php 20,400 per hectare. The study concludes that an increase in the variability of weather patterns can significantly affect the net income. It also concludes that choices in a commodity can affect net income.</subfield>
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   <subfield code="a">Undergraduate Thesis</subfield>
   <subfield code="c">ABE 200b.</subfield>
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   <subfield code="a">Alviola, Pedro A. IV</subfield>
   <subfield code="e">adviser.</subfield>
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   <subfield code="a">UPMIN</subfield>
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   <subfield code="h">LG993.5 2017 A3</subfield>
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