Challenge 2: Inflation Measures Analysis

Objectives

You have access to the

• Statistics Sweden (SCB) data through the scb-opendata-mcp server. You can query economic data using the scb_* tools.

• Rikskbanken data through the swemo-mcp for CPI, CPIF, GDP, and other economic indicators.

The goal is to analyze and compare different inflation measures in Sweden.

Use case

Challenge

Retrieve and compare the following inflation measures for Sweden for the years 2020-2025:

• CPI (Consumer Price Index)

• CPIF (Consumer Price Index with fixed interest rate)

• CPIF-XE (CPIF excluding energy products)

• HICP (Harmonized Index of Consumer Prices)

Calculate the annual inflation rate for each measure and visualize the trends.

Important

Example workflow

• Start by searching for tables showing the different inflation measures.

• Retrieve the monthly or annual data for the specified measures. Aggregate them if needed.

Ground truth: SCB report: Different measures of inflation

Further improvements

Optional Challenges

1. Interactive Visualization: Create an interactive plot showing the trends of different inflation measures over time.

Tip

• Instruct which library to use:

  • Generate a Python app which uses libraries like Plotly, Matplotlib, Gradio, Streamlit, Holoviz, Altair, Seaborn, or Bokeh

  • Use Javascript (either front-end only or full-stack) app which uses D3.js, Chart.js, Vega-Lite, Observable Plot, or Pico.css

  For data handling, SCB returns JSON-stat responses which can be processed using:

  • Python: pyjstat

  • JavaScript: jsonstat-toolkit

2. Extended Analysis: Extend the analysis to include more years (e.g., 2010-2025) to identify longer-term trends.

3. Correlation Analysis: Analyze the correlation between different inflation measures and the GDP (Gross Domestic Product).

Tip

• Instruct which library to use:

  • Generate a Python app which uses libraries like Pandas, NumPy, Scipy, Seaborn etc.