The impact of climate change on labour demand in the plantation sector: the case of tea production in Sri Lanka

Abstract

Limited opportunities for crop switching and lengthy preharvesting periods make the plantation sector particularly vulnerable to climate change. Surprisingly, however, the economic consequences of climate change on plantation crops are seldom analysed. Drawing on a unique primary panel data set from a representative cross section of 35 tea estates in Sri Lanka over the period 2002-2014, this study implements a structural model of estate profit maximisation to estimate the elasticity of labour demand with respect to different components of weather. Results indicate a negative relationship between labour demand and rainfall in the south-west monsoon, the north-east monsoon and the second inter-monsoon. A positive relationship is found between labour demand and rainfall in the first inter-monsoon. Overall, predicted changes in rainfall by 2050 are anticipated to reduce labour demand by approximately 1,175,000 person-days per year across Sri Lanka's tea plantation sector. This is likely to have considerable social and welfare implications, particularly for the Indian Tamil women who comprise the majority of the sector's workforce.

Adoption of climate‐smart practices and its impact on farm performance and risk exposure among smallholder farmers in Ghana

“…The vulnerability has been attributed to structural, technological and institutional weaknesses, higher poverty, as well as relative proximity to the equator (IPCC ). The impact of climate change on agricultural productivity especially in developing countries is well documented (IPCC ; Di Falco and Veronesi ; Gunathilaka et al ). The key issue is not whether climate change will have adverse impact on crop productivity, but the extent of productivity losses from climate variability or uncertainties and the prospect of mitigating the negative impacts through adoption of appropriate climate‐smart practices.…”

Evaluation of influencing factors on tea production based on random forest regression and mean impact value

“…In the end, 320 original samples from 32 countries were obtained and integrated. According to existing literature (Gunathilaka et al 2018;Xiao et al 2018), area harvested, gross production value, export quantity, import quantity, net production value, gross domestic product (GDP) deflator, value-added deflator and exchange rate were chosen as economic system variables prepared for inputs (Table 1). Total population and rural population are regarded as social system variables, while temperature change reflects environmental system.…”

“…Tea has the great potential to increase income and social benefits for resource-poor small-scale farmers. Many existing studies in the literature have focused on the impacts of various variables related to the economic system, social system and environmental system on tea production (Qiao et al 2016;Gunathilaka et al 2018;Xiao et al 2018). Compared with other factors, the increase in the tea plantations area is considered to be the most important factor leading to the increase in tea production (Xiao et al 2018).…”

“…Compared with other factors, the increase in the tea plantations area is considered to be the most important factor leading to the increase in tea production (Xiao et al 2018). Limited opportunities for crop switching and lengthy pre-harvesting periods, make the plantation sector particularly vulnerable to climate change (Gunathilaka et al 2018). Changes in temperature, rainfall, and the occurrence of extreme weather events, for instance, have adversely affected tea production (Gunathilaka et al 2017).…”

Can satellite‐based weather index insurance improve the hedging of yield risk of perennial non‐irrigated olive trees in Spain?*

“…In perennial cropping systems production cannot be adapted to climate change as easily as in systems with annual crops (Gunathilaka et al . 2018b). The high capital costs upfront, the frequent non‐irrigated cultivation and the long life span of plantation crops make it difficult to adapt to climate change (Gunathilaka et al .…”