University of Jordan
Faculty of Agriculture
Dept. of Agricultural Economics & Agribusiness
Lecturer: Dr. Amani Alassaf
Agricultural Econometrics (605450)
Pre- requisite: Ag. Statistics (605150)
Second Semester 2011 / 2012
Office hr's: Su, Teu: 9:00-10:00
Wed: 13:00 – 14:00
COURSE DESCRIPTION
This course will provide an introduction to modern methods of analyzing data used in
economics, business and many other social sciences. This course will be divided into six
chapters. The first chapter will cover the introduction. The second chapter will cover some
fundamentals of models and data. The third chapter will deal with regression analysis using
summation and matrices approaches. The fourth chapter will deal with the properties of
ordinary least squares estimators. Chapter five will cover the violations of the assumptions of
the regression model and problems in regression analysis. Finally, chapter six will deal with
selecting the best regression equation.
Week
1&2
COURSE CONTENT
INTRODUCTION: STATISTICAL BACKGROUND
 Test of hypothesis - Parametric tests ( Z- & t- tests),
 Test of hypothesis - Non-parametric tests:  2 -test, Wilcoxon test, Mann 
3&4
5-6
7-10
11-14
15
16
Whitney test
Analysis of Variance One Way Analysis of Variance, Two Way Analysis of
Variance
INTRODUCTION TO ECONOMETRICS:
 Introduction to econometrics, the nature of statistics,
 The methodology of econometrics.
THE FUNDAMENTALS OF MATRIX OR LINEAR ALGEBRA
 Determinants, non-singularity & High - order determinants
 Determinant, cofactor & adjoint matrices
 Solving matrix equations with the inverse
 Cramer’s rule for matrix solutions
SIMPLE ECONOMETRIC (REGRESSION ) MODEL
 The two variable linear model
 The ordinary least - square method
 Test of significance of parameter estimates
 Test of goodness of fit and correlation
 Properties of least - squares estimators
MULTIPLE LINEAR REGRESSION MODEL
 The three - variable model
 Tests of significance of parameter estimates
 The coefficient of multiple determination
 Test of overall significance of regression
 Partial – correlation coefficients
 Predictions
FURTHER TECHNIQUES AND APPLICATIONS IN REGRESSION ANALYSIS
 Functional form
 Dummy Variables
PROBLEMS IN REGRESSION ANALYSIS
 Multicollinearity
 Autocorrelation
2
COURSE OUTCOMES
Successful completion of this course should lead to the following learning outcomes:
A- Knowledge and Understanding ( students should )
A1) Be able to discuss/ explain the importance of a wide range of models and
quantitative tools.
A2) Be able to use econometric, statistical, and economic models as a basis for
estimating key economic parameters, testing economic hypotheses, and predicting
economic outcomes.
B- Intellectual Skills- with ability to
B1) Employ analytical skills to be used for data analysis.
B2) Identify a range of statistical, economic, and econometric models and evaluate
and justify them through suitable proposed solutions.
B3) Analyze a wide range of econometric tools and provide solutions through suitable
models.
C- Subject Specific Skills- with ability to
C1) Use appropriate econometric support tools.
C2) Use the econometric scientific literature effectively.
C3) Give technical presentations suitable for the time, place, and audience (students).
C4) Prepare and deliver structural verbal and written technical reports or assignments.
D- Transferable Skills- with ability to
D1) Display an integrated approach to the development of communication skills.
D2) Create self-reliance and team work when necessary.
D3) Display personal responsibility to the course requirements.
CLASS PARTICIPATION
Students are expected to attend classes on time, and fully participate in class work and
discussions. Your attendance is crucial, as each class builds upon the previous class session.
Actual participation in class work is a very important part of your learning experience in this
course, so you are expected to come and to be prepared to do the work, ask questions, and
fully engage with the course.
EXAMS AND GRADES
Exam
First Exam
Second Exam
Final Exam
Grade
Day
Date
30
20
50
REFERENCES:
1. Gujarati, D. N., “ Basic Econometrics “, 3rd ed., McGraw-Hill Company Inc., New York,
1995.
2. Gujarati, D. N., “ Essentials of Econometrics “, McGraw-Hill Company Inc., New York,
1992.
3. Johnston, J. “Econometric Methods “, 2nd Edition, McGraw-Hill Book Co., New York, 1972.
4. Salem, M. A., “ Introduction to Agricultural Econometrics “, University of Jordan/
Faculty of agriculture, Amman, 1997 ( in Arabic ).
5. Salvatore, D. “Theory and Problems of Statistics and Econometrics” , Schaum’s Outline.
6. Series in Economics, McGraw-Hill Book Company, New York, 1982.
7. Wonnacott, R. J., and T. H. Wonnacott, “ Econometrics “, 2 nd ed., John Wiley & Sons, New York,
1979.