Day 1 - Monday 19 August 2019
Presenter: Prof. Bob Breunig
Crawford School of Business, Australian National University
Robert Breunig is the director of the Tax and Transfer Policy Institute at the Crawford School of Public Policy. From 2015 to 2016 he was the Director of the Crawford School of Public Policy.
Professor Breunig is one of Australia’s leading Public Policy Economists. He has published in over 50 international academic journals in economics and public policy. Professor Breunig has made significant policy impact through a number of his research projects: the relationship between child care and women’s labour supply; the effect of immigration to Australia on the labour market prospects of Australians; the effect of switching to cash from food stamps in the U.S. food stamp program and the inter-generational transmition of disadvantage.
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Using Panel Data in Stata
Setting up the data
Descriptive statistics with panel data
Regression methods w/ panel data
a. Pooled OLS
b. First differences
c. Second (+higher) differences
d. Fixed Effects
e. Random Effects
Advanced panel techniques
a. Hausman-Taylor estimation
b. Arellano-Bond estimation
Presenter: Dr Con Menictas
Strategic Precision - https://strategicprecision.com.au/
Con is an accredited statistician (AStat, AUS) and (PStat, USA), a qualified researcher (QPR) and certified lean six-sigma black belt (LSSBB). His training is in behavioural economics, statistics and decision sciences, earning his PhD under Professor Jordan Louviere, the global authority on choice modelling. Con has trained extensively in data mining and big data modelling in the USA, under Professor Dan Steinberg, the founder of Salford-Systems, considered the benchmark in data science.
He has held national quantitative roles in research firms, and corporates in FMCG, utilities, finance and airline. Con has lectured and provided PhD supervision in statistics, machine learning, market research, price modelling, strategy and marketing theory and practice.
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Using Stata for Social Statistics
Stata provides powerful features for applied analysis and modelling of social data. Examples of social data include asset data, demographic, employment data, happiness measures, political, satisfaction, values, etc.
This course teaches social data analysis using Stata by:
Introducing participants to the different types of social data and the analysis of social data.
Teaching participants Stata and statistical skills to interrogate social data using a variety of routines to produce applied solutions.
Helping participants to look beyond aggregate models by looking deeper into the datasets to achieve better segmentation using Stata's powerful toolsets.
Providing “hands-on” experience writing Stata code and generating highly reproducible and meaningful output.
Giving participants insights to leading practices in the modelling, visualising and reporting of social data.