1Department of Statistics, Cotton University, Guwahati-781 001, Assam, India.
2Department of Statistics, Gargaon College, Simaluguri-785 686, Assam, India.
*Corresponding Author: Gourab Jain, Department of Statistics, Cotton University, Guwahati-781 001, Assam, India. Email: gourabjaingj12@gmail.com
Assam has always upheld a leading position in terms of India’s total tea production, but continues to face challenges such as declining businesses, closure of tea factories, low wages, periodic job cuts and increasing migration among the workers. Therefore, to understand the relationship between productivity and wages is crucial for both industrial profitability and welfare of the workers.
The present article explores the dynamic relationship between tea yield and wages by employing an advanced time series approach, namely Toda-Yamamoto non-causality test. The analysis is based on annual observations within this time frame from 1989 to 2022.
The findings of the test reveal a feedback causal association between tea yield and wages, indicating both variables contain some information that can be used to predict each other. By doing so, the study provides empirical evidence to the government to adopt a balanced approach between industrial profitability and welfare of the workers.
Phillips-Perron test, Tea yield, Toda-Yamamoto test, Wages
