Teaching
I am currently an academic tutor (teaching assistant in the US) in the School of Economics at The University of Queensland.
Teaching Assistantships
- ECON3350 Applied Econometrics for Macroeconomics and Finance
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The purpose of the course is to offer advanced students in finance and economics an understanding of the econometric tools that apply to financial and macroeconomics data. The approach is from an applied perspective. Lectures will introduce specific financial and macroeconomic models and the techniques required to estimate/predict/forecast with the model.
The course will make use of a suitable econometric package for purposes of analysing of the data.
Core content includes: statistical characteristics of time series data; capital asset pricing models; cointegrated models; volatility and volatility models; models of price changes.
Skills and Perspective provided by applications to: stock prices, derivatives, exchange rates, interest rates, high-frequency data analysis, market microstructure.
This course is best viewed as a stepping stone between introductory econometric methods and either advanced (e.g. graduate level) econometric studies or direct application of econometric methods in practice. This is a massive gap to fill; hence, the course in necessarily multi-faceted and rich in content.
Lectures introduce concepts and techniques related to stochastic processes as a framework for obtaining inference from economic and financial data. Specific models of stochastic processes and the techniques required to make predictions as well as to investigate dynamic relationships in economics and finance are presented and analysed. Mathematical tools such as polynomial methods are extensively used for this purpose. Labs are focused on applying the techniques in practice using the econometric package, R.
Core content includes: stochastic processes; models of macroeconomic and financial processes; trends, cycles and cointegration models; conditional heteroscedasticity and volatility models; multiple equation models.
- ECON3360 Causal Inference for Microeconometrics
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The purpose of the course is to offer advanced students in Economics, Commerce and Business an understanding of the econometric tools that apply to microeconomic data. The approach is from an applied perspective. Lectures will introduce specific cross-sectional and panel models and the techniques required to estimate/predict with the model. The course will make use of the econometric package, Stata, for purposes of analysing of the data. Core content includes the analysis of individual-level data on the economic behaviour of individuals or firms using regression methods for cross section and panel data. Skills and Perspective provided by applications in the area of labour economics, consumer choice, health and education.
Assumed Background: Students are expected to have an intermediate knowledge (second year undergraduate at least) of economic theory and econometrics or statistics and mathematics (see prerequisites).
The course covers concepts and methods that are widely employed in contemporary applied microeconomics. It will be centred around the estimation of causal or treatment effects using regression-based analysis. Empirical examples will be drawn from recent research in labour, development, education, and health.
- ECON2300 Introductory Econometrics
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Introductory applied econometric course for students with basic economic statistics background. Topics covered include: economic models and role of econometrics, linear regression with single and multiple regressors, hypothesis testing and confidence intervals, dummy variables and nonlinear regression functions, internal and external validity of regression models, panel data models, binary response models, instrumental variable regressions, experiments and quasi-experiments, as well as basic time series analysis. Practical problems are solved using the R econometrics software.
This is an introductory course in applied econometrics. It reviews and builds on the simple linear regression model taught in introductory statistics courses such as ECON1310 and ECON1320. The models studied in this course have numerous applications in economics, finance, marketing, management and related areas.ﾠA feature of the course is the way examples and exercises are drawn from these different discipline areas to illustrate the usefulness and limitations of certain econometric/statistical techniques. Hands-on experience in applying these techniques is gained through the use of R, an econometric computer software package available in the BEL computer laboratories. Note also that students can freely download R at [https://www.r-project.org].
- ECON2030 Microeconomic Policy
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Extends microeconomic theory and demonstrates application to microeconomic policy issues; welfare economics, trade practices legislation, tariff policy and public enterprises.
In this course, students will learn to analyse microeconomic policies using economic approaches and concepts. The course builds on the theoretical framework introduced in Microeconomic Theory (ECON2010 or ECON2011), and begins by identifying the different sources of market failure. By the end of the course, students should not only have a greater awareness of the role of government in an economy, but also be able to analyse and critically evaluate policy issues using basic microeconomic tools. Topics covered include environmental policy, competition policy, health insurance, taxation, redistribution, and political economics.
- ECON1310 Introductory Statistics for Social Sciences
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2022 summer (no survey)
Basic statistical concepts and techniques such as descriptive statistics, probability concepts, theoretical distributions, inferential statistics (confidence intervals and hypothesis testing) are applied in business and economics.
ECON1310 is an introductory course in quantitative analysis for business and economics. The course covers a variety of techniques applicable to the presentation, interpretation and use of data. The main emphasis is inferential statistics with estimation and hypothesis testing techniques being an important part of the course. Inferential statistics is continued in the simple linear regression topic. There is an emphasis on the use of Excel for analysis and presentation.