Forecasting of the National Wholesale Price and Wage Rate Index for Price Adjustment Factor Analysis
Student: Sanjog Shrestha
Supervisor: Er. Subash Kumar Bhattarai,Asst. Prof. Manoj Kunwar
Submitted Date:
December, 2025
Abstract
Nepal's construction industry, contributing 10.19% to GDP, relies on the National
Wholesale Price Index (materials/equipment) and National Salary and Wage Rate Index
(labor) for contract price adjustments in multi-year projects. However, unpredictable
inflation and inadequate index coverage of construction-specific costs lead to arbitrary
provisional sums, resulting in budget overruns, disputes, and compromises in time and
quality. This study forecasts these indices to align provisional budgets with realistic cost
fluctuations and mitigate systemic risks across project stakeholders.
Using quantitative methods and Nepal Rastra Bank data (1999-2023 for
materials/equipment; 2004-2023 for labor), this research employs ARIMA time series
analysis following Box-Jenkins methodology to forecast Nepal's construction indices over
five years. Two modeling approaches are compared: partial-data validation (80%
training/20% testing) versus full-data forecasting. A sensitivity analysis evaluates how
fluctuations in these indices impact the construction price adjustment factor.
Results indicate that forecasts using 100% available data as training data better captured
reliable trends than the 80/20 approach. ARIMA models project steady growth over five
years: construction materials (13.63%), machinery/equipment (14.86%), and labor
(21.87%). Consequently, the 100% data model's projections were used for sensitivity
analysis, showing price adjustment factors rising from 0-1% (2024/25) to 13-14% (2028/29)
across all scenarios of varying labor, material, and equipment weightings, peaking in labor-
intensive projects.
This study contributes methodologically by demonstrating the superiority of full-data
ARIMA modeling in volatile economic contexts and practically by providing the first
comprehensive forecast of Nepal's construction cost indices. The findings emphasize the
necessity of thorough escalation risk assessment during bidding, using projections for cash
flow planning, assigning realistic weightings per project type, and optimizing costs through
early design and procurement strategies. These evidence-based approaches can enhance
financial predictability and reduce disputes in Nepal's construction sector.
Keywords
price adjustment factor, ARIMA, forecast, sensitivity analysis, National
Wholesale Price Index, Construction Material, Machinery and Equipment, Labor, Nepal
construction industry