ChatGPT Optimized

Best ChatGPT prompts for Economists

A specialized toolkit of advanced AI prompts designed specifically for Economists.

Professional Context

With a 25% quarterly increase in data analysis demands, economists are under pressure to optimize their workflow efficiency, ensuring high-quality insights within tight deadlines, all while maintaining error rates below 5%

💡 Expert Advice & Considerations

Don't rely on ChatGPT for novel research findings, but rather use it to automate routine data cleaning and visualization tasks, freeing up time for more complex, high-value analysis

Advanced Prompt Library

4 Expert Prompts
1

Macroeconomic Forecast Adjustment

Terminal

Given the latest GDP growth rate of 2.5% and an inflation rate of 3.2%, adjust the existing macroeconomic forecast model to account for the recent changes in monetary policy, incorporating the impact of a 0.5% increase in interest rates on consumer spending and business investments, and provide a revised projection for the next two quarters, including confidence intervals and a sensitivity analysis for key variables

✏️ Customization:User must update the GDP growth rate, inflation rate, and interest rate values to reflect current economic conditions
2

Cost-Benefit Analysis of Policy Intervention

Terminal

Conduct a cost-benefit analysis of a proposed policy intervention aimed at reducing carbon emissions by 10% within the next 5 years, considering the costs of implementing renewable energy sources, increasing energy efficiency, and promoting sustainable land use, as well as the benefits of reduced healthcare costs, improved air quality, and increased economic competitiveness, and provide a concise report including a break-even analysis, net present value calculation, and a discussion of potential uncertainties and risks

✏️ Customization:User must specify the policy intervention details, including the target emission reduction, timeline, and relevant cost and benefit parameters
3

Time Series Analysis of Financial Markets

Terminal

Perform a time series analysis of the daily stock prices of the S&P 500 index over the past 12 months, using a combination of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) models to forecast future price movements, and evaluate the performance of the models using metrics such as mean absolute error, mean squared error, and root mean squared percentage error, providing a detailed report including the estimated model parameters, residuals analysis, and a discussion of the implications for investment strategies

✏️ Customization:User must update the time series data to reflect the most recent market trends and adjust the model parameters as needed
4

Microeconomic Evaluation of Firm Performance

Terminal

Evaluate the financial performance of a firm in the technology sector, using a combination of financial ratios such as return on assets, return on equity, and debt-to-equity ratio, as well as non-financial metrics such as research and development expenditures, employee productivity, and customer satisfaction, to assess the firm's competitive position and identify areas for improvement, providing a concise report including a SWOT analysis, benchmarking against industry averages, and recommendations for strategic adjustments

✏️ Customization:User must provide the firm's financial statements and relevant industry data to enable accurate analysis and comparison