ECM604 Econometrics I

ECM651 Economic Data Analysis

Autumn Term 2024-2025

Econometrics Project and Computer Lab Sessions

Overview

This individual project is designed to give you an opportunity to apply the econometric techniques you have learned in this module to real-world data. You will begin your project with a raw dataset and are expected to create the relevant variables, conduct estimations and tests, justify the methods you use, and critically analyze the results you obtain.

The dataset

You are required to use the 2013 Annual Population Survey (APS) dataset for this project. The dataset and related documents are available for download on Blackboard.

Computer lab sessions

Computer lab sessions area core component of this module and play a vital role in successfully completing the project. These sessions are structured to provide comprehensive instruction, not just on STATA commands for econometric estimations, but also on foundational techniques for generating relevant variables from a raw dataset, conducting estimations, and performing tests, all with the support of ChatGPT as an additional tool. We have a total of eight computer lab sessions,  each designed to build your skills progressively:

First Four Sessions: These sessions will focus on generating relevant variables from a raw dataset in response to a specific research question. You'll learn how to manipulate and prepare data to align it with your analytical needs.

Remaining Four Sessions: These sessions will centre on performing estimations and conducting various econometric tests. Through practical exercises, you'll apply the techniques you've learned, reinforcing your understanding and ability to implement them in real-world scenarios.

Generative AI

Generative AI, such as ChatGPT, is a valuable tool for researchers, offering assistance in generating ideas, summarizing information, and exploring different perspectives. However, it's important to recognize that it can sometimes provide misleading or incorrect solutions or answers. Therefore, developing the skill to use AI tools critically is essential for conducting effective research. In our computer lab sessions, we will practice using ChatGPT to support your work on this project, with a focus on developing a critical approach to evaluating its outputs.

The research question

Since this is not a dissertation module, Ido not expect you to spend excessive time identifying a research question or topic for this project. Instead, you are expected to address the following question using the 2013 APS dataset:

"Does marital status affect income? Are there any gender differences in this effect?"

If you wish to pursue a different research question, please discuss it with me and obtain approval by the end of October.

What doI expect you to do?

This project is intended to showcase your ability to apply the econometric techniques covered in this module. It is not meant to be a dissertation or a research paper, so there is no need to employ advanced econometric methods beyond those discussed in the course. Effective and careful handling of the data is paramount, rather than the use of complex techniques. You should avoid replicating results from existing research papers. While a comprehensive literature review is not required, reviewing related research papers may offer useful insights. As outlined in the project  overview, your tasks are to:

1.    Generate the relevant variables.

2.    Perform. estimations and tests.

3.   Justify your methods.

4.    Critically review the results obtained.

5.    Use ChatGPT to facilitate your research, applying it critically.

During your estimation process, you may face challenges in identifying the effect you are interested in. It is expected that you address these issues using the techniques and knowledge acquired from this module. It is important to acknowledge that not all problems can be resolved and that your results will have limitations and potential weaknesses. These should be clearly and concisely explained in your report. Furthermore, while ChatGPT (or other generative AI) can be a valuable tool, it is important to use it critically. Simply copying and pasting ChatGPT output without thoughtful engagement is not acceptable and will not meet the pass requirements for this project.

What do you have to submit?

You are required to submit a single Word file via Turnitin. Your submission should be concise and focused, with a maximum of 800 words for sections 1 through 4 and 200 words for section 5, totalling no more than 4 pages. The document should include the following sections:

1.    Introduction:  Provide an explanation of the variables used in your analysis and justify your chosen methods.

2.    Summary Statistics Table: Include a table presenting the summary statistics of your data.

3.    Main Table: Present your STATA estimation results and any test results if applicable.

4.    Results  Interpretation and Discussion: Interpret your findings and discuss the limitations of your analysis.

5.    Reflection on ChatGPT Usage: Reflect on your use of ChatGPT in the following aspects:

a.    What did you ask ChatGPT?

b.   The pros and cons of ChatGPT’s answers.

c.    The limitations of ChatGPT.

d.    Cite specific questions and answers from your interactions with ChatGPT, including the page number in section 8.

6.    Reference List: Include a list of references, if applicable.

7.    Do File: Attach your STATA “do file” containing all commands used in your analysis.

8.    ChatGPT Conversations: Include your conversations with ChatGPT.

Please ensure that your Word file is clear, well-organized, and adheres to the specified word limits.

For (2) and (3), you should take Tables 1 and 2 in my paper “An economic analysis of tiger parenting: Evidence from child developmental delay or learning disability” as examples.

The do file is a STATA script that includes all the commands necessary for your project, from generating the relevant variables  to  performing estimations and tests. It should be organized so that I can replicate the results presented in your PowerPoint file simply by running the do file with the 2013 APS dataset. Please ensure that your do file is well-organized and tidy. Afterward, copy and paste the contents of your do file into the Word document you are submitting.