随着线性回归模型的发展，人们的注意力逐渐集中到联立方程建模问题，时间序列分析以及经济预测上来。学好计量经济学需要有扎实的经济学知识基础。宏观经济学、微观经济学以及stata数据分析等基本功。Econ 321 这门课是新西兰奥克兰大学the university of Auckland所开设的 advanced econometrics高阶计量经济学课程。作为新西兰数一数二的高等学府，世界知名名校。奥克兰大学高阶经济学的课程难度可想而知。课程是基于基础计量经济学，统计学和数学的基础上开设的深入计量经济学学习旨在更好的了解计量经济学的特性模型和技术。课程要求较高的独立分析，收集数据以及分析数据的能力。难度比较大，因此，我们收到过很多econometrics代写的求助。
econometrics代写 Course Prescription
Development of the linear regression model, its basis, problems, applications and extensions. Attention is also given to techniques and problems of instrumental variables, simultaneous equations, panel data and time-series analysis.
econometrics代写Programme and Course Advice
Prerequisites: ECON 221 Introduction to Econometrics or STATS 207 or STATS 208 or STATS 210 and MATHS 108, 150, 153 This course leads on to the econometrics postgraduate courses ECON 721 (Econometrics I), ECON 723 (Econometrics II) and ECON 726 (Microeconometrics). It also complements ECON 322 Applied Econometrics. Students require ECON 301 (Advanced Microeconomics), ECON 311 (Advanced Macroeconomics) ECON 321 before embarking on postgraduate study in Economics. Students should also note that econometrics at this level requires a reasonable level of mathematical expertise.
econometrics代写 Goals of the Course
The aim of this course is to provide a good understanding of the properties of econometric models and techniques. Econometrics can be described as the science and art of building and using models in economics. More specifically it is concerned with the use of statistical methods to attach numerical values to the parameters of economic models and also with the use of these models for prediction. The techniques of econometrics consist of a blend of economic theory, mathematical modelling and statistical analysis.
econometrics代写 Learning Outcomes
By the end of this course it is expected the student will be able to:
- 1. derive properties of some important estimators such as least squares, maximum likelihood and instrumental variables in a number of specific modelling contexts of a sort which arise frequently in econometric work;
- 2. analyse certain classes of single and multiple equation models, including some time series models;
- 3. demonstrate an ability to explain the essential features of such models by reference to specified definitions and concepts, including notions of identification, specific classes of structural and reduced form estimators, and stationary and non-stationary time series.
- 4. access and manipulate data electronically using a combination of computer packages, including spreadsheets and statistical software;