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2. Outline. 1. Significance of the Study2. Key questions and objectives3. Data and Model Specifications4. Empirical Results 5. Policy Implications and Conclusions. 3. Jasmine rice of Thailand is of premium quality and its export share has increased substantially due to its high price.How
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2. 2 Outline 1. Significance of the Study
2. Key questions and objectives
3. Data and Model Specifications
4. Empirical Results
5. Policy Implications and Conclusions
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10. 10 Data on rice yield of crop year 1999/2000 were collected from two different methods:
1. Interviewing farmers (called survey data)
2. Measuring the rice weight from sample plots in the field
(called measurement data)
***The same 130 farmers provided two types of yield data***
3. Data and Model Specifications 3.1 Data on Rice Farmer Samples
11. 11 Sampling procedure 1. Three selected major Jasmine rice production areas in the
upper north, lower north and north east regions (Chiang Mai
Province, Pitsanuloke Province and TungGula Rongha
rice Plane)
2. Districts of most intensive Jasmine rice were selected
3. For the survey:- Simple random sampling of farm unit of
observations
For the measurement:- three-one square meter plots along the
diagonal of a rice field were randomly selected
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18. 18 Production function
For the measurement data model (Model 1):
* The major production variables: Seed(+)
* The dummy variables: dummy variables for neck blast(-), severe drought(-)
TGR(-), irrigation(+) and chemicals(+)
For the survey data model (Models 2 and 3):
* Model 2:- There is no single variable affect the management efficiency of
farmers
* Model 3:- Generally the significant variables have the expected sign except
fertiliser and labour variables
The dummy variables: dummy variables for neck blast(-), severe
drought(-), Phitsanuloke Province(-), and
chemicals(+)
4.2 Production frontier estimates
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20. 20 Inefficiency equation
For the measurement data model (Model 1):
* Education(-), Age(-) ? the higher formal education and older farmers
tended to reduce the TI in Jasmine rice
production
For the survey data model (Models 2 and 3):
* Model 3:- Human resource variables became highly significant
Labour Ratio(-) ? Higher labour force ratio in Jasmine rice
tended to have smaller TI
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26. 26 * Apart from the robust variables, the remaining weak
determinants would generate different values of estimate and
which are highly sensitive to model specification.
* Agricultural economists and users of survey data, therefore,
should be cautioned to pay special attention to survey design so
as to minimize error.
* The test of model specification might be an effective means to
detect the errors in estimation due to the choice of variables. 5. Policy implications and conclusions (cont.)
27. 27 Thank you very much