CPIIW Forecast 2024–2025: How Machine Learning Predicts India's Industrial Worker Inflation
- ▸A study testing 28 machine learning and statistical models found a deep-learning model (LSTM), not classical statistics, best forecasts India's Consumer Price Index for Industrial Workers (CPIIW).
- ▸The winning model projects CPIIW climbing from 138.9 in January 2024 to about 149.8 by December 2025, rising roughly 3.4 points each summer/monsoon and staying flat over winter.
- ▸Because Dearness Allowance is pegged to CPIIW, the forecast implies DA/DR could rise from about 53.48% in July 2024 to roughly 59.26% by July 2025.
Why CPIIW matters
CPIIW (base year 2016 = 100) tracks the changing cost of a basket of goods and services that industrial workers typically buy: Food and Beverages (39.17% weight), Housing (16.87%), Clothing and Footwear (6.08%), Fuel and Light (5.5%), Pan, Supari, Tobacco and Intoxicants (2.07%), and a miscellaneous basket covering transport, healthcare, education, entertainment, and personal hygiene (30.31%). Published monthly by the Labour Bureau, Chandigarh (Ministry of Labour and Employment, Government of India), CPIIW is more than an inflation gauge — it directly determines Dearness Allowance and Dearness Relief for government staff, informs minimum wage fixation in scheduled employment, and helps policymakers track retail price pressure on industrial households.
28 models, one clear winner
The researchers used monthly CPIIW data from January 2006 to December 2023 — 216 data points — and ran it through 27 forecasting models via the PyCaret time-series library, plus a separately built LSTM (Long Short-Term Memory) neural network. Each model was scored on four metrics: Mean Absolute Error, Root Mean Square Error, Mean Absolute Percent Error, and R² (the share of variation the model explains). LSTM came out on top with an R² of 0.992 — explaining 99.2% of the variation in CPIIW. The next-best performers were far behind: a Huber regression model with deseasonalizing and detrending managed R² = 0.893, followed by linear regression (0.870) and exponential smoothing (0.867). Naive and seasonal-naive forecasters, and a basic grand-means model, performed dramatically worse, some with negative R² values.
The 2024–2025 forecast
Using the trained LSTM model, the study projects CPIIW month by month through December 2025. The index is expected to rise from 138.9 in January 2024 to 144.3 by December 2024, then continue climbing to 149.8 by December 2025. The more interesting pattern is seasonal: CPIIW stays nearly flat during the winter months (October to March) but jumps by roughly 3.4 points during the summer/monsoon stretch (April to September). The likely driver is food price behavior — food, beverages, and tobacco carry the heaviest weight in the basket, and monsoon variability tends to push food prices up sharply during those months.
| Month | CPIIW |
|---|---|
| January 2024 | 138.9 |
| December 2024 | 144.3 |
| December 2025 | 149.8 |
What it means for Dearness Allowance
Because DA/DR calculations for Central Government employees and pensioners are pegged to CPIIW under the formula recommended by the 7th Pay Commission, the forecast translates into real numbers for paychecks. The study estimates DA/DR at roughly 53.48% in July 2024, rising to 56.17% by January 2025, and reaching 59.26% by July 2025 — with each biannual revision adding up to about 3 percentage points. That's useful groundwork for government finance departments budgeting DA/DR payouts, and for analysts and policymakers watching inflation trends in India's industrial and wage-earning population.
CPIIW isn't an abstract statistic in India — it's the number that decides how much extra Central Government employees and pensioners actually receive twice a year through Dearness Allowance and Dearness Relief, under the formula recommended by the 7th Pay Commission. It also feeds into minimum wage fixation in scheduled employment and gives the Labour Bureau, RBI, and Ministry of Finance a read on inflation pressure facing industrial and wage-earning households specifically — a segment often more exposed to food and fuel price swings than the broader CPI captures. A more accurate CPIIW forecast means DA/DR revisions can be sized closer to what workers actually need to keep pace with the cost of living.
Frequently Asked Questions
What is CPIIW and who publishes it?
CPIIW is the Consumer Price Index for Industrial Workers, a monthly inflation measure (base year 2016 = 100) published by the Labour Bureau, Chandigarh, under India's Ministry of Labour and Employment.
Which machine learning model best predicts CPIIW?
LSTM (Long Short-Term Memory), a recurrent neural network architecture, outperformed 27 other models tested, achieving an R² of 0.992 on the CPIIW time series.
How is CPIIW connected to Dearness Allowance?
DA and DR for Central Government employees and pensioners are calculated from CPIIW movements using a formula set by the 7th Pay Commission, so CPIIW forecasts directly inform expected DA/DR revisions.
Why does CPIIW rise faster in summer than winter?
Food, Beverages and Tobacco make up nearly half the CPIIW basket. Monsoon-season rainfall variability tends to disrupt food production and push prices up between April and September, while winter prices stay comparatively stable.
What CPIIW level is forecast for December 2025?
The LSTM model projects CPIIW at approximately 149.8 by December 2025, up from about 138.9 in January 2024.
Primary Sources
Cite This Article
EconoLens Research Desk. (2026, August 6). CPIIW Forecast 2024–2025: How Machine Learning Predicts India's Industrial Worker Inflation. EconoLens. https://www.econolens.co.in/news/cpiiw-forecast-2024-2025-lstm-india-industrial-worker-inflation
The EconoLens Research Desk reviews academic papers in economics and econometrics, translating cutting-edge research into accessible analysis. Full credit is given to original authors in every review.