Skip to main content

Price Index Calculator using bilateral and multilateral methods

Project description

PriceIndexCalc

Calculate bilateral and multilateral price indices in Python using vectorized methods Pandas or PySpark. These index methods are being used or currently being implemented by many statistical agencies around the world to calculate price indices e.g the Consumer Price Index (CPI). Multilateral methods can use a specified number of time periods to calculate the resulting price index; the number of time-periods used by multilateral methods is commonly defined as a “window length”.

Bilateral methods supported: Carli, Jevons, Dutot, Laspeyres, Paasche, Lowe, geometric Laspeyres, geometric Paasche, Drobish, Marshall-Edgeworth, Palgrave, Fisher, Tornqvist, Walsh, Sato-Vartia, Geary-Khamis, TPD and Rothwell.

Multilateral methods supported: GEKS paired with a bilateral method (e.g GEKS-T aka CCDI), Time Product Dummy (TPD), Time Dummy Hedonic (TDH), Geary-Khamis (GK) method.

Multilateral methods simultaneously make use of all data over a given time period. The use of multilateral methods for calculating temporal price indices is relatively new internationally, but these methods have been shown to have some desirable properties relative to their bilateral method counterparts, in that they account for new and disappearing products (to remain representative of the market) while also reducing the scale of chain-drift.

Directory layout:

.
├── pandas_modules                    # Pandas modules
│   ├── index_methods.py         
│   ├── chaining.py
│   ├── extension_methods.py    # New timeseries extension methods (experimental)                 
│   ├── helpers.py             
│   ├── bilateral.py            
│   ├── multilateral.py
|   └── weighted_least_squares.py                 
├── pyspark_modules                    # PySpark modules (experimental)
│   ├── index_methods.py              
│   ├── chaining.py             
│   ├── helpers.py             
│   ├── multilateral.py
|   └── weighted_least_squares.py
└── README.md

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PriceIndexCalc-0.1.dev9.tar.gz (21.6 kB view details)

Uploaded Source

File details

Details for the file PriceIndexCalc-0.1.dev9.tar.gz.

File metadata

  • Download URL: PriceIndexCalc-0.1.dev9.tar.gz
  • Upload date:
  • Size: 21.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for PriceIndexCalc-0.1.dev9.tar.gz
Algorithm Hash digest
SHA256 dc66d449e10ac4dbd6c6315ba7bce762cd11bae7475036a70b491fcaf661d6e6
MD5 1e2a0c8fadcccaa824876e17327547cb
BLAKE2b-256 f36d226b985b41afbf1a733a9ab8deee3db3f8157fd70748ca0a78cc45b2d42c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page