|Venue:||University of Sydney Business School
|Dates:||February 13–17, 2017|
You may attend any one or any combination of the following days:
Monday, February 13:
Working Efficiently with Stata by Demetris Christodoulou, MEAFA General Convener
This day assumes no previous knowledge of Stata 14. It describes the environment of Stata, its limitations and strengths, and core syntactic features. It demonstrates ways of working efficiently with Stata, including the use of logs and do-files. It discusses key principles and presents tools for developing work that is reproducible and verifiable. The day is of interest to those who are new to Stata 14 or have limited experience with earlier versions of Stata. It is also useful to more experienced users who wish to attain a more structural understanding of Stata from first principles.
Tuesday, February 14:
Introduction to Programming by Demetris Christodoulou, MEAFA General Convener
This day assumes working knowledge of Stata 14 but no knowledge of programming with Stata or any other software. By the end of this day, you will be able to produce efficient, tractable, and automated routines for data management, statistical analysis and estimation, and the creation of tables and graphs. The day covers key programming tools (saved results, stored results, macros, scalars, loops) and the fundamentals of building your own commands in Stata (programs or ado-files). This day is appropriate to those who wish to attain a deeper knowledge of Stata and achieve the aforementioned attributes in their work. This day assumes knowledge of the material presented in Day 1.
Wednesday, February 15:
Management of Raw Data by Demetris Christodoulou, MEAFA General Convener
This day assumes working knowledge of Stata and basic programming skills but not of data management. The day demonstrates ways to import and export different data formats. It demonstrates the management of numerical variables, string variables and date/time variables, and the implications of missing values. It explores key data structures, including cross-sectional, time-series, and panel data in long and wide formats. It covers the management of data attributes, the organization of data, and the importance of metadata. It also demonstrates strategies for working efficiently with very large datasets. Dataset organization, archiving, combinations, and transformations will also be discussed. If you have no or limited experience with Stata 13, then you are strongly advised to attend Day 1 first. Some programming tools will also be applied from Day 2 (stored results, macros, scalars, and loops).
Thursday–Friday, February 16–17:
Stochastic Frontier Analysis by Artem Prokhorov, Discipline of Business Analytics at The University of Sydney
These two days assume working knowledge of Stata and basic knowledge of econometrics. We start with the basic stochastic frontier models of production with a single output and multiple inputs and discuss estimation using cross-sectional data and technical-efficiency score calculation. We then extend the model to include environmental variables that affect inefficiency. Then, we allow for time-varying technical inefficiency and for unobserved effects and consider estimation of stochastic frontier models using panel data. Finally, we consider important extensions such as estimation of stochastic frontier models when production inputs are endogenous, when there are multiple outputs, and when a cost frontier is considered instead of a production frontier. The type of applications we cover include dairy and rice farm production, power generation, efficiency of airlines, mine production, and banks. By the end of the two days, you will be able to estimate stochastic frontier models, test hypotheses about them, interpret the estimates, and obtain efficiency scores. If you have no experience with Stata, then you are required to attend at least Day 1.
For more information, including a detailed program, or to register, visit sydney.edu.au/business/research/meafa/workshops/feb2017.