Ec 823 Applied Econometrics Boston College

Ec 823 Applied Econometrics Boston College EC 823 Applied Econometrics Boston College Course EC 823 is a graduatelevel course in applied econometrics focusing on the practical application of econometric techniques to realworld economic data The course builds upon foundational econometric theory delving deeper into advanced topics and equipping students with the skills necessary to conduct rigorous empirical research Course Objectives By the end of this course students will be able to Understand and apply advanced econometric methods including panel data models time series analysis and limited dependent variable models Evaluate and select appropriate econometric techniques based on the nature of the data and the research question Develop and implement robust econometric models employing statistical software to analyze realworld datasets Interpret and present empirical results effectively communicating findings to a nontechnical audience Conduct independent econometric research applying acquired skills and knowledge to design and execute empirical studies Course The course is organized around the following modules Module 1 to Applied Econometrics Review of basic econometric concepts linear regression hypothesis testing and statistical inference to data types and model specifications Overview of commonly used econometric software packages Stata R Module 2 Panel Data Models Understanding panel data and its advantages Fixed effects and random effects models 2 Estimation techniques and interpretation of results Applications in economics finance and other disciplines Module 3 Time Series Analysis Time series data properties and models Autoregressive AR and Moving Average MA models Autoregressive Integrated Moving Average ARIMA models Forecasting and analysis of dynamic systems Module 4 Limited Dependent Variable Models to discrete choice models Probit and logit models for binary and multinomial outcomes Tobit and censored regression models Applications in areas such as labor economics health economics and marketing Module 5 Advanced Topics in Applied Econometrics Instrumental variables and endogeneity Generalized method of moments GMM estimation Nonparametric and semiparametric methods Applications in various fields including microeconomics macroeconomics and development economics Course Requirements Problem sets Students will be required to complete a series of weekly problem sets applying the learned econometric techniques to practical scenarios Midterm exam The midterm exam will assess students understanding of the first half of the course material Research paper Students will undertake an independent research project collecting and analyzing data to answer a specific economic question using the acquired econometric skills Final exam The final exam will comprehensively assess students knowledge and ability to apply econometric techniques to various contexts Software and Resources Students will have access to statistical software packages such as Stata and R along with relevant datasets and online resources The instructor will provide guidance on software usage and data management Course Schedule 3 The course will run for Number weeks with Number lectures and Number discussion sections per week The specific schedule will be provided by the instructor at the beginning of the semester Prerequisites EC 822 Econometrics or equivalent Strong foundation in statistics and mathematics Proficiency in a statistical software package Stata R preferred Assessment Problem sets Percentage Midterm exam Percentage Research paper Percentage Final exam Percentage Grading The final grade will be based on a weighted average of the individual components with the weights allocated according to the course policy Course Instructor Professor Name Email Address Office Hours Office Location Location Course Website Course Website URL Important Note This course description is intended as a general overview and may be subject to change at the discretion of the instructor Students are encouraged to consult with the instructor for the most uptodate information 4