| Course title | |||||
| 農業数量経済分析 [Economic analysis of agricalture] | |||||
| Course category | Requirement | Credit | 2 | ||
| Department | Year | 3～ | Semester | Fall | |
| Course type | Fall | Course code | 01AN3506 | ||
| Instructor(s) | |||||
| 草処 基, 山浦 紘一 [KUSADOKORO Motoi, YAMAURA Koichi] | |||||
| Facility affiliation | Faculty of Agriculture | Office | 2-209 | Email address | |
| Course description |
|
The goal of this course is to understand fundamental theory and methods to conduct quantitative and statistical analyses on the topics related to agricultural economics and farm management. Modern agriculture has various problems to be solved such as changes in economic environment and policy, environment issues, poverty of farmers in developing countries and etc. The aims of agricultural economics are to extract fundamental factors of a problem in agriculture and to propose and evaluate policies to solve the problem. Statistical analysis can be an effective analytical tool, because it affords us to present objective evidence obtained from data. Outline of this course is as follows. First, fundamental theory of statistics and descriptive statistics will be introduced. Second, students will learn linear regression models and the ordinary least squares (OLS) as a favorable estimation technique. Third, students will learn various statistical tests which can be used for testing your hypothesis based on the estimated model and how to treat with violation of some assumptions necessary for the OLS to be a good estimator. Finally, some application examples of regression models in agricultural economics will be introduced. Students will discuss the results and learn how to start doing independent research using economic data. |
| Expected Learning |
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Students are expected to learn fundamental theory and methods of statistics and regression models and have greater confidence in its application on real problems in agriculture. |
| Course schedule |
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1. Oct. 5 Guidance, quantitative analysis in agricultural economics 2. Oct.12 Fundamentals of statistics 1: representative value 3. Oct.19 Fundamentals of statistics 2：distribution of data and correlation 4. Oct.26 Fundamentals of statistics 3: Gini coefficient and contribution 5. Nov. 2 Single linear regression models 6. Nov. 9 Multiple linear regression models 7. Nov.16 Hypothesis testing for linear regression models 8. Nov.23 Midterm examination 9. Nov.30 Dummy variables in regression models 10 Dec. 7 Time series data and serial correlation 11 Dec.14 Structural equation and endogeneity 12 Dec.21 Input-output analysis 13 Jan.11 Application of regression model with economic theory 1 14 Jan.18 Application of regression model with economic theory 2 15 Jan.25 Final examination ** The above schedule may change depending on the progress. |
| Prerequisites |
| Required Text(s) and Materials |
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Shirasago, T. (2007) Econometrics, 2nd edition. Nihon hyouron sya (in Japanese). |
| References |
| Assessment/Grading |
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Grades will be given with the following weights: Class attendance/assignment (20%), Midterm examination (30%), Final Examination (50%) |
| Message from instructor(s) |
| Course keywords |
| Office hours |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| Japanese |
| Language Subject |
| Last update |
| 3/22/2017 4:52:00 PM |