The Chinese Stata Users Group Meeting was held on 19–20 August 2018 in the Shunde District, Foshan City, Guangdong Province at Shunde Vocational and Technical College, but you can view the program and presentation slides below.
Big-data, high-dimension regression with Stata
Spatial autoregressive models using Stata
Abstract: How close you are to something else matters. Minneapolis and St. Paul may be separate cities, but they are so near each other that they are highly related. What happens in one strongly affects what happens in the other. But Minneapolis and Houston have much less effect on each other. Spatial autoregression allows you to model and understand the effects of distance, whether that distance be miles or number of friends separating you in a social network. In any case, Stata's Sp suite of commands lets you account for the spatial relationships in your data. I will introduce spatial concepts and show you how to use Stata's new spatial autoregression features. See how you can fit spatial autoregressive models, handle distance relationships, and measure the effects neighbors have on each other.
Policy evaluation and causality inference: An outline of application in Stata
Sun Yat-sen University
Spotlight time: Technical discussion
Report generation with putdocx, putexcel, putpdf, and dyndoc
Abstract: Part of reproducible research is eliminating manual steps such as having to edit documents. Several commands in Stata facilitate automated document production, including putdocx for creating Word documents, putpdf for creating PDF files, putexcel for creating Excel spreadsheets, and dyndoc for converting dynamic Markdown documents to webpages.
These commands allow you to mix formatted text and Stata output. They also allow you to embed Stata graphs, inline Stata results, and tables containing the output from selected Stata commands. We will show these commands in action, demonstrating how to automate the production of documents in various formats and how to include Stata results in those documents.
A simple way of using Stata (Implied cost of capital: A calculation with Stata)
Sample selection problem and its estimation in Stata
Application of DSGE in Stata
Workshop: Stata application method and case practice intermediate training course
Thursday–Saturday, 16–18 August, Qunyong Wang, Nankai University
This training course is mainly application-oriented and does not involve any complicated mathematical formulas and statistical derivation. It mainly focuses on teaching various quantitative methods that are widely used by mainstream economic journal and industrial research organizations at home and abroad. Based on a brief introduction of these econometric methods' principles and applicability, more emphasis will be put on using Stata to replicate the quantitative results that were published in some classic articles. Because most of the examples are selected from classic papers and textbooks, this course could help students improve their empirical hands-on ability. The whole training course will use Stata 15.0 for demonstration, and the Stata code for empirical analysis will also be provided. These examples can be used in your own papers, greatly improving the analysis efficiency.
Workshop: Stata application method and case practice advanced training course
Tuesday–Thursday, 21–23 August, Yujun Lian, Lingnan (University) College, Sun Yat-sen University
This training course covers some of the most frequently used measurement models and analysis methods in empirical analysis, including virtual variables, cross terms (regulatory effects), group regression, fixed-effect models, and dynamic panel models. Three articles published in AER, JF, and QJE are elaborated so that you can master common estimation methods while experiencing first-rate research and design. In short, the goal of this course is to help trainees gain the ability to independently conduct normative emipirical research work. The training will use Stata 15.0 software for demonstration. The courseware will provide many codes and commands used in empirical analysis. These examples can be directly transplanted into the analysis of your own papers, greatly improving the efficiency of your analysis.
Registration is closed.
|Training course||元 3600|
Visit the official site for more information.