Topics in Applied Econometrics from Coursera

In this course, you will discover models and approaches that are designed to deal with challenges raised by the empirical econometric modelling and particular types of data. You will:

– Explore the motivations of each approach by means of graphs, preliminary statistics and presentation of economic theories

– Discuss the problem of identification of the parameters, and how to address this problem by modelling simultaneous equations and causality in economics.

– Examine the key features of panel data, and highlight the advantages and disadvantages of working with panel data rather than other structures of data.

– Learn how to choose what econometric specification to adopt by introducing the test for poolability and the Hausman tests.

– Discuss models for probability that are used where the variable under investigation is qualitative, and needs to be treated with a different approach.

– Learn how to apply this approach to building an Early Warning system to forecast systemic banking crises using data from the World Bank.

It is recommended that you have completed and understood the previous two courses in this Specialisation: The Classical Linear Regression Model and Hypothesis Testing in Econometrics.

By the end of this course, you will be able to:

– Respond appropriately to issues raised by some feature of the data

– Resolve address problems raised by identification and causality

– Resolve problems raised by simultaneous equation and instrumental variables models

– Resolve problems raised by longitudinal data

– Resolve problems raised by probability models

– Manipulate and plot the different types of data.

What's inside

Syllabus

Random Regressors

This module presents models and approaches that are designed to deal with challenges raised by the regressors being random variables. We address the problems raising when regressors are correlated with the error term, ad when this problem is likely to raise. We look at modelling simultaneous equations and discuss causality in economics, with an application to returns to schooling. We will discuss the problem of identification of the parameters, and how to address this problem. We finally estimate a model for the demand and supply of fish.

Panel Data Models: The Basics

We describe the problems as raising when repeated observations are present in the sample, and it is possible to deal with unobserved heterogeneity in the sample. We analyse key features of panel data and highlight the advantages of working with panels of data instead of other structures of data. We analyse fixed effects models and estimators associated with this approach. A full example where the neoclassical growth model is estimated is presented and discussed using the PWT tables data. We see how to choose between fixed effects models and pooled models by introducing the test for poolability.

Further Analysis of Panel Data Models

This week we study random effects on models of panel data. We analyse the Hausman test, that helps study whether we should be adopting the fixed effects models of the random effects models. The two approaches are compared using the Solow growth model. We also analyse the role of time in panel data models by presenting the between estimator, the two ways estimators, where we have time effects, and we finally look at dynamic panel data models, where the lagged dependent variable enters the set of regressors.

Probability Models

We discuss models for probability, that are used where the variable under investigation is qualitative, and needs to be treated with a different approach. We analyse the difficulties raised by linear models when the dependent variable is binomial. We study logit and probit estimators. We apply probability models to the problem of building an Early Warning system to forecast systemic banking crises using data from the World Bank.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores approaches to econometric modelling and specific data types, which is common in economics

Taught by Leone Leonida, who is recognized for their expertise in econometrics

Develops skills relevant to identifying issues in empirical econometric modelling, which is a core skill in economics

Examines causality and identification in economics, which are highly relevant to economic research

Discusses econometric specification, which is crucial for accurate economic modelling

Assumes learners have foundational knowledge in econometrics so may not be suitable for absolute beginners

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Topics in Applied Econometrics with these activities:

Review: Econometric Analysis of Cross Section and Panel Data, 2nd Edition

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This book provides a comprehensive overview of econometric methods for analyzing cross-sectional and panel data, which will help you build a strong foundation for this course.

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Read the preface and introduction to get an overview of the book's content and structure.
Review the chapters on linear regression models, hypothesis testing, and estimation methods.
Focus on the chapters that cover topics related to the course, such as panel data models, simultaneous equation models, and probability models.

Review key concepts of probability and statistics

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This review will help you refresh your understanding of probability and statistics, which are essential foundations for econometric modelling.

Browse courses on Probability

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Revisit basic probability concepts such as conditional probability, Bayes' theorem, and random variables.
Review statistical concepts such as sampling distributions, hypothesis testing, and confidence intervals.

Solve practice problems on econometric models

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Solving practice problems will help you apply the econometric concepts and techniques covered in the course to real-world scenarios, improving your understanding.

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Find practice problems from textbooks, online resources, or past exams.
Attempt to solve the problems independently, using the concepts and techniques learned in the course.
Check your answers and identify areas where you need further clarification.
Repeat the process to reinforce your understanding and identify gaps in your knowledge.

Four other activities

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Attend a study group or discussion forum

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Participating in discussions with peers can help you clarify concepts, share insights, and identify areas where you need further understanding.

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Find or join a study group or discussion forum dedicated to the course or related topics.
Actively participate in discussions, ask questions, and share your own perspectives.
Engage with other participants to exchange knowledge and clarify concepts.

Create a visual representation of an econometric model

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Creating a visual representation of an econometric model can help you visualize the relationships between variables and improve your understanding of their interactions.

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Choose an econometric model from the course material.
Identify the key variables and their relationships.
Create a visual representation using tools like graphs, charts, or diagrams.
Explain the relationships between the variables and the model's assumptions in a clear and concise manner.

Develop a data analysis project using econometric techniques

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Developing a data analysis project will allow you to apply the econometric techniques learned in the course to a real-world problem, deepening your understanding and practical skills.

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Identify a research question or problem that can be addressed using econometric techniques.
Gather and prepare the necessary data.
Choose appropriate econometric models and methods to analyze the data.
Conduct the analysis and interpret the results.
Write a report or presentation summarizing your findings and conclusions.

Mentor a junior learner in econometrics

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Mentoring a junior learner can help you reinforce your understanding of econometric concepts while also contributing to their learning journey.

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Identify opportunities to mentor a junior learner, such as through tutoring or peer support programs.
Provide guidance and support to the learner on econometric concepts, techniques, and problem-solving.
Share your own experiences and insights to help the learner navigate challenges and develop their skills.

Career center

Learners who complete Topics in Applied Econometrics will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts collect, clean, and analyze data to help organizations make informed decisions. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Data Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical modeling to analyze financial data and make investment decisions. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing financial data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Quantitative Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Quantitative Analyst

Econometrician

Econometricians use statistical methods to analyze economic data and develop economic models. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing economic data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of an Econometrician. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Econometrician

Market Researcher

Market Researchers collect and analyze data to understand consumer behavior and market trends. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing market data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Market Researcher. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Market Researcher

Risk Analyst

Risk Analysts assess and manage risks for organizations. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing risk data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Risk Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Risk Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical modeling to improve the efficiency of organizations. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing operational data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of an Operations Research Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Operations Research Analyst

Statistician

Statisticians collect, analyze, and interpret data. This course provides a strong foundation in econometric modeling, which is a specialized field of statistics. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Statistician. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Statistician

Financial Analyst

Financial Analysts use financial data to make investment decisions. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing financial data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Financial Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Financial Analyst

Data Scientist

Data Scientists use data to solve business problems. This course provides a strong foundation in econometric modeling, which is a specialized field of data science. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Data Scientist. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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Management Consultant

Management Consultants use data to help organizations solve problems and improve performance. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing business data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Management Consultant. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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Actuary

Actuaries use mathematical and statistical models to assess and manage risks. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing risk data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of an Actuary. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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Business Analyst

Business Analysts use data to improve the efficiency and profitability of organizations. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing business data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Business Analyst. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Business Analyst

Economist

Economists use economic data to analyze economic trends and make policy recommendations. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing economic data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of an Economist. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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Investment Banker

Investment Bankers use financial data to make investment decisions. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing financial data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of an Investment Banker. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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Data Engineer

Data Engineers build and maintain the infrastructure that supports data analysis. This course provides a strong foundation in econometric modeling, which is essential for understanding and analyzing data. The course covers topics such as random regressors, panel data models, and probability models, which are all relevant to the work of a Data Engineer. By taking this course, you will develop the skills and knowledge necessary to succeed in this role.

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