Forecasting the Monthly Real Wage Rate of the Public Sector in Sri Lanka

Abstract

This study assesses the monthly real wage rate of the public sector of Sri Lanka by elaborati ng a suitable ti me series model to identi fy the future trends associated with the real wage rates of Sri Lanka. The sample data set consists of monthly real wage rate data from January 2018 to March 2024 from the Central Bank of Sri Lanka (CBSL). The real wage rate has been calculated selecti ng 2016 as the base year. Suitable parsimonious models were identi fi ed through the patt erns of the sample parti al autocorrelati on functi on (PACF) and sample auto-correlati on functi on (ACF) of the stati onary series. Based on the indicati ons such as Akaike informati on criterion (AIC), Schwarz Criterion (SC) and log likelihood an autoregressive integrated moving average (ARIMA) model of the type (0,1,2) was disti nguished as the best fi tt ed model. The residuals of the best fi tt ed model were ascertained to be white noise. The model has been validated for the fi rst three months of 2024. The Mean Absolute Percentage Error (MAPE) for the validati on data is 9.59%. The forecasted wage rate values from April 2024 to September 2024 are 54.562, 54.096, 53.631, 53.165, 52.7 and 52.234 respecti vely. The study’s fi ndings can be uti lized by policymakers, economists, and government workers to improve their fi nancial planning.