Modeling & Analytics

1. Draft the Paper: A Structured Approach

A research paper follows a logical narrative. Each section builds upon the last to create a compelling argument.

Title

Make it concise, descriptive, and impactful. It should clearly state the paper's core topic and contribution. Avoid jargon where possible.

Abstract

This is your 150-250 word elevator pitch. It must contain:

• Motivation/Problem: What gap does your research fill?
• Methodology: What data and methods did you use?
• Key Findings: What is the single most important result?
• Contribution/Implications: Why does this result matter?

Introduction

Structure this section like a funnel:

• Start broad, introducing the general topic and its importance
• Narrow down to the specific problem or question your paper addresses
• Briefly review what the literature has said (or failed to say) about this problem
• Clearly state your contribution (e.g., "This paper is the first to...")
• Provide a roadmap for the rest of the paper

Literature Review

Do more than just list papers. Synthesize the existing research:

• Group related studies by theme, methodology, or conclusion
• Actively point out the research gap. Use phrases like, "While prior work has established X, the impact of Y remains underexplored." or "A limitation of these studies is their reliance on..."

Methodology

This section must be a blueprint for reproducibility:

• Data: Describe your data sources, sample period, and any cleaning or transformation processes. Justify your choices.
• Model: Clearly define your empirical model and all its variables. Justify why this model is appropriate for your research question over other alternatives.

Results

Present your findings without interpretation:

• Start with your main finding. Present it clearly in a well-formatted table or figure
• Move on to secondary results or robustness checks (e.g., using alternative data, time periods, or model specifications)
• Ensure all tables and figures have descriptive titles and notes that allow them to be understood on their own

Discussion

This is where you interpret the "so what?" of your results:

• Explain what your results mean. How do they answer your research question?
• Connect your findings back to the literature. Do they support, contradict, or extend previous work?
• Discuss the economic or practical significance of your findings
• Acknowledge the limitations of your study. No study is perfect; being transparent builds credibility

Conclusion

Summarize and look forward:

• Briefly restate the research question, your main finding, and your primary contribution
• Discuss the broader implications for theory, practice, or policy
• Suggest specific, actionable directions for future research that arise directly from your findings or limitations

2. Revise and Edit

• Structural Edit: Read through your draft focusing only on the logic and flow. Does the argument make sense? Is the evidence sufficient?
• Seek Feedback: Share your paper with mentors, colleagues, or peers. Ask them to be critical. Be prepared to make substantial changes based on their feedback.
• Language and Grammar: Use tools like Grammarly and the Hemingway Editor to polish your writing for clarity, conciseness, and correctness.
• Formatting: Meticulously format your paper according to your target journal's specific guidelines (e.g., APA, Chicago). Check references, citations, tables, and figures.

3. Select Target Journals

• Relevance and Scope: Does the journal publish papers on your topic and with your methodology? Read the journal's "Aims and Scope" section and browse recent issues.
• Impact and Reputation: Consider the journal's prestige (e.g., Impact Factor, ranking) but be realistic about your work's fit. It's often better to get a fast "desk reject" from a top journal than to wait months for a rejection from a less-suitable one.

Top Journals in Economics and Finance:

4. Submission and Peer Review

• Prepare Your Package: This includes the final manuscript, a compelling cover letter explaining your work's contribution and fit with the journal, and any supplementary materials (e.g., data appendices, code).
• Handling Feedback: If you receive a "Revise and Resubmit," celebrate! Address every single reviewer comment methodically in a detailed "Response to Reviewers" letter. Explain how you've changed the manuscript for each point, or respectfully justify why you chose not to.

1. Brainstorming and Idea Generation

Use large language models (LLMs) like ChatGPT, Claude, or Perplexity AI to explore the research landscape.

• Use Case: Identify research gaps and formulate questions

2. Literature Discovery and Synthesis

Go beyond simple keyword searches.

Tools:

• Elicit.io: Ask a research question, and it will find relevant papers and summarize their key findings in a table
• Connected Papers / ResearchRabbit: Input a key "seed paper," and these tools will generate a visual graph of related, influential, and recent works
• Scite.ai: See how a paper has been cited by others, specifically whether it was supported, contradicted, or mentioned

3. Writing and Drafting Assistance

Overcome writer's block and refine your language.

• Use Case: Outlining, paraphrasing, and improving clarity

4. Data Analysis and Coding

Accelerate your empirical work.

• Tools: GitHub Copilot, ChatGPT (with Code Interpreter), Claude
• Use Case: Generate code snippets, debug errors, add comments, and translate code between languages (e.g., Stata to R)

5. Editing and Proofreading

Go beyond basic grammar checks.

• Use Case: Ask an LLM to review a paragraph for clarity, flow, and consistency

Ethical AI Usage: A Non-Negotiable Checklist

• Verify Everything: LLMs can "hallucinate" facts, figures, and, most dangerously, academic citations. Always cross-reference every claim and find the original source for every citation.
• Disclose Your Use: Check your target journal's policy on AI. Many now require authors to disclose if and how they used AI tools in the research process. Transparency is key.
• Avoid Plagiarism: AI is a tool for paraphrasing and idea generation, not for copying. The intellectual contribution must be your own. You are responsible for every word in your paper.
• Maintain Data Privacy: Do not upload sensitive, proprietary, or confidential data to public AI models.

Exemplary Papers

• The Cross-Section of Expected Stock Returns - Eugene F. Fama and Kenneth R. French (1992)
• Empirical Asset Pricing via Machine Learning - Shihao Gu, Bryan T. Kelly, and Dacheng Xiu (2018)
• Do Liquidity Measures Measure Liquidity? - Ruslan Y. Goyenko, Craig W. Holden, and Charles A. Trzcinka (2009)
• Profitable Momentum Trading Strategies - Sebastian Müller and Martin Weber (2014)
• Liquidity and Market Structure - Sanford J. Grossman and Merton H. Miller (1988)

Essential Books and Guides

• The Student's Guide to Writing Economics - Robert H. Neugeboren
• Writing Economics: A Guide for Harvard Economics Concentrators - Harvard University
• A Guide to Writing in Economics - Paul Dudenhefer

Tools for Streamlining the Process