Ricardian Framework in single-crop modelling for climatic impact assessment: A discrete choice approach of adaptation behaviours for tea economy in India

This paper adopts a two-stage framework by extending the Ricardian approach towards single crop modelling to understand the climatic impact on India's tea plantation sector and evaluate the economic effectiveness of farmer adaptation. The first stage employs a multinomial logit model examining tea growers' rational choice of adaptation technologies based on farm size, terrain characteristics, and climatic conditions. Second stage examines how climate affects the net revenue of each technology. Results indicate that estate size and precipitation are primary factors determining the technology adopted. Each adaptation choice exhibits a very different net revenue response, identifying rainfall as the main stressor while revealing a significant synergistic interaction between winter temperature and precipitation that exceeds their individual effects. Marginal effects and climate simulations demonstrate that optimal adaptation flattens and shifts the profit function, minimizing projected revenue losses under extreme events. Study findings clearly indicate that the climate vulnerability of tea plantation systems can be mitigated by the adoption of optimal farming practices.

Authors

Institutions

Publication Details

Journal
Climate Change Economics
Published
2026-08-25
DOI
https://doi.org/10.1142/s2010007826500144
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ricardian Framework in single-crop modelling for climatic impact assessment: A discrete choice approach of adaptation behaviours for tea economy in India

Nimai Das
Climate Change Economics
Climate change impacts on agriculture
article

Ricardian Framework in single-crop modelling for climatic impact assessment: A discrete choice approach of adaptation behaviours for tea economy in India

Nimai Das
article en

Abstract

This paper adopts a two-stage framework by extending the Ricardian approach towards single crop modelling to understand the climatic impact on India's tea plantation sector and evaluate the economic effectiveness of farmer adaptation. The first stage employs a multinomial logit model examining tea growers' rational choice of adaptation technologies based on farm size, terrain characteristics, and climatic conditions. Second stage examines how climate affects the net revenue of each technology. Results indicate that estate size and precipitation are primary factors determining the technology adopted. Each adaptation choice exhibits a very different net revenue response, identifying rainfall as the main stressor while revealing a significant synergistic interaction between winter temperature and precipitation that exceeds their individual effects. Marginal effects and climate simulations demonstrate that optimal adaptation flattens and shifts the profit function, minimizing projected revenue losses under extreme events. Study findings clearly indicate that the climate vulnerability of tea plantation systems can be mitigated by the adoption of optimal farming practices.

Climate Change Economics
Twitter (United States) (US)
Climate action
Openalex Percentile: Top 7%
Climate change impacts on agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Ricardian Framework in single-crop modelling for climatic impact assessment: A discrete choice approach of adaptation behaviours for tea economy in India — Nimai Das · Climate Change Economics (2026) | TGRS Research Map | TGRS