Economic Adjustments: Currency & Inflation Tools

This page covers utilities for currency conversion and inflation correction in pre-processing, from pybalmorel.economics.prices.

These tools use official Eurostat data sources to:

Load annual currency-to-euro conversion rates
Load harmonised consumer price indices (HICP)
Correct values for inflation between years/regions
Convert Euros to/from other currencies for modeling

Data Sources

[TEC00033] Eurostat Currency Conversion Rates: https://ec.europa.eu/eurostat/web/products-datasets/-/TEC00033
[PRC_HICP_AIND] Harmonised Index of Consumer Prices: https://ec.europa.eu/eurostat/databrowser/product/page/PRC_HICP_AIND

Requirements

Download/untar files from official Eurostat links.
Place in a directory and provide path to all loader functions.

API Overview

`get_conversion_rate(path, filename="estat_tec00033.tsv")`

Loads exchange rates (currency→EUR, annual).

path: str — Directory with Eurostat file
filename: str — e.g. ‘estat_tec00033.tsv’
Returns: DataFrame (currencies/rates by year)

`get_harmonised_price_index(path, filename="estat_prc_hicp_aind$defaultview_filtered.tsv", index_choice="CP00")`

Loads HICP for consumer price inflation (all-items default).

path: str — Directory with Eurostat file
filename: str — e.g. ‘estat_prc_hicp_aind$defaultview_filtered.tsv’
index_choice: str — HICP code, default ‘CP00’
Returns: DataFrame (annual indices)

`inflation_correction(value, year_to, year_from, inflation_table, region="EU")`

Inflation-correct value from year_from → year_to using regional index.

value: float — Initial value
year_to: int
year_from: int
inflation_table: pd.DataFrame — HICP (from above)
region: str — HICP region, default ‘EU’
Returns: float — Corrected value

`euro_conversion_rate(year, currency, currency_table)`

Get currency/Euro rate for year/currency combo.

year: int
currency: str — e.g. ‘USD’, ‘DKK’
currency_table: DataFrame — as from get_conversion_rate
Returns: float rate

Example

from pybalmorel.economics.prices import (
    get_conversion_rate, get_harmonised_price_index,
    inflation_correction, euro_conversion_rate
)

currency_table = get_conversion_rate("tests/output")
hicp = get_harmonised_price_index("tests/output")
converted_value = inflation_correction(10, 2016, 2024, hicp)
print(f"10 € converted from €2024 to €2016: {converted_value}")
in_usd = converted_value * euro_conversion_rate(2016, "USD", currency_table)
print(f"Then, convert this to USD2016: {in_usd}")

Official Eurostat links above describe file formats and variables in detail.

Average Fuel Prices CLI

pybalmorel.economics.get_average_prices is a small command-line tool that prints annual average fuel prices from downloaded market data, for use as static fuel prices in Balmorel backcasting. It requires the entso-e extra (pip install pybalmorel[entso-e]) for click, and openpyxl for the oil bulletin.

python -m pybalmorel.economics.get_average_prices naturalgas
python -m pybalmorel.economics.get_average_prices coal
python -m pybalmorel.economics.get_average_prices fueloil

Each command reads a fixed file name from the current working directory:

Command	Input file	Source	Output
`naturalgas`	`natural_gas_TTF_2024.csv`	TTF futures, Yahoo Finance	Average price in €/MWh
`coal`	`Rotterdam Coal Futures Historical Data.csv`	Rotterdam coal futures, investing.com	Average price in USD/t and USD/GJ (bituminous coal, 30.2 GJ/t)
`fueloil`	`Weekly_Oil_Bulletin_Prices_History_maticni_4web.xlsx`	EU Weekly Oil Bulletin	Average heavy fuel oil price per country in €/GJ (39 GJ/t)

To convert the USD coal price to euros, or a price to another year’s money, use the functions above. For season- and hour-resolved fuel prices in a backcasting scenario, see the backcasting fuelprices command.

Technology Catalogues

The TechData class, also in pybalmorel.economics, downloads and loads the Danish Energy Agency’s technology catalogues. See Downloading Technology Catalogues.