Best Gemini prompts for Economists

I have a monthly time series dataset of GDP growth rates from 2000 to 2022, with missing values for the years 2005-2007. Using a combination of seasonal decomposition and ARIMA modeling, decompose the time series into trend, seasonal, and residual components, and generate a forecast for the next 6 months, including confidence intervals and a discussion of the limitations of the model. The dataset is in a CSV file named 'gdp_data.csv' and has the following columns: 'date', 'gdp_growth_rate'. Please provide the Python code for the analysis, including data visualization and model evaluation metrics.

I am analyzing the relationship between unemployment rates and inflation rates using a dataset of quarterly observations from 2010 to 2020. The dataset includes the following variables: 'unemployment_rate', 'inflation_rate', 'gdp_growth_rate', and 'interest_rate'. Using a combination of linear regression and model selection techniques, including stepwise regression and cross-validation, select the best model that explains the relationship between unemployment rates and inflation rates, and provide a discussion of the results, including coefficient estimates, p-values, and R-squared. Please provide the R code for the analysis and include a table of the model results.

I have a dataset of economic indicators, including GDP growth rates, unemployment rates, and inflation rates, for 10 different countries over the period 2010-2020. Using a combination of bar charts, line plots, and scatter plots, create a series of visualizations that tell a story about the economic performance of each country over time, including comparisons between countries and trends over time. Please provide the Python code for the visualizations, including the use of libraries such as Matplotlib and Seaborn, and include a brief discussion of the insights and patterns that emerge from the visualizations.

I am evaluating the costs and benefits of a proposed policy intervention to reduce carbon emissions, using a dataset of costs and benefits over a 10-year period. The dataset includes the following variables: 'costs', 'benefits', 'discount_rate', and 'emissions_reduction'. Using a combination of cost-benefit analysis and sensitivity analysis, including Monte Carlo simulations and scenario analysis, estimate the net present value of the policy intervention and provide a discussion of the results, including a sensitivity analysis of the discount rate and emissions reduction assumptions. Please provide the Excel formulae for the analysis and include a table of the results.