AI for economics students

<case>
[paste the case study from your seminar]
</case>

You're a management teacher running a seminar on this case study. Don't tell me the solution. Ask me step by step: what the main problem is, what the options are, what each would cost and what risks it carries, what I recommend and why.
Respond to my answers with a follow-up question, the way a good teacher does. At the end, sum up what I overlooked.
Work only with the facts in the case. If we need a figure that's missing, say so and don't fill it in.

<plan>
[paste the business plan or its summary]
</plan>

You're an investor assessing this business plan. Find its 5 weakest points: market, competition, financial assumptions, team, risks.
For each one, ask the question I'll get when I defend it, and say what figure or calculation would back up my answer.
Don't rewrite the plan. Don't make up numbers that aren't in the plan.

Explain the [AD-AS / IS-LM / supply and demand] model to me:
1. What's on the axes and what the curves mean.
2. What assumptions the model makes.
3. Then give me 3 situations (such as "the central bank raises interest rates") and let me say which curve shifts, which way and what happens to price and quantity. Show the explanation only after I answer.
If schools of economic thought disagree on the interpretation, say so.

<materials>
[paste your notes or the exam topics]
</materials>

Quiz me on [microeconomics]. Alternate questions on concepts, short problems with calculations and "what happens if…" questions. Ask one at a time.
For calculations, show the correct working after I answer. After 8 questions, tell me what to review.
Stay within the materials.

Works best with web search turned on.

For my seminar paper I need data on [unemployment by region in my country for 2015–2025].
Tell me which institutions publish such data (for example the national statistics office, the central bank, Eurostat), what the indicator is called exactly and how to find it in their database. Point out differences in methodology between the sources.
Don't give the numbers themselves, I'll download them from the source.

I'm calculating [the NPV and IRR of an investment] in Excel. My data: [cash flows by year, discount rate].
1. Write the Excel formulas and explain what each argument does.
2. Point out common mistakes (such as Excel's NPV function already discounting the first cash flow).
3. Show how I can check the result by hand or with a different formula.
Don't calculate the result yourself, I'll do it in Excel.

<output>
[paste the regression output from Excel, Gretl, R or Python]
</output>

Explain this regression output to me: what the coefficients, standard errors, p-values and R² mean, how to describe the result in one sentence in my paper, and what I mustn't claim from it (causation, results outside the range of the data).
Tell me which model assumptions I should check and how.
Work only from the numbers in the output.

<statements>
[paste a company's balance sheet and income statement, for example from the business register]
</statements>

Calculate the basic profitability, liquidity, debt and activity ratios from the statements. For each one, show the formula, the numbers plugged in and the result, so I can check the calculation.
Then say what the ratios tell us about the company and what can't be concluded from them.
Use only the numbers from the statements. If an item is missing, say so.