Akademik Veri Yönetim Sistemi
Rize Ticaret ve Ekonomi Kongresi, Rize, Türkiye, 22 - 23 Ekim 2025, ss.56-57, (Özet Bildiri)
In
recent years, sustainable agricultural practices have been promoted not only
due to environmental concerns but also with the aim of improving productivity,
cost-efficiency, and labor sustainability in rural economies. In this context,
tea farming—widely practiced in Türkiye’s Eastern Black Sea Region—has also
begun to experience a technological transformation. Particularly in Rize
province, the increasing adoption of tea harvesting machines (motorized shears)
has attracted attention for their potential to reduce production costs and
lessen dependence on seasonal labor. This study aims to evaluate the effects of
mechanization on productivity, cost, and labor use in tea farming through both
descriptive and causal analytical approaches. Data were collected from 248 tea
producers across six districts in Rize. Initially, descriptive statistics and
multiple regression models were employed. These analyses revealed that
producers who use machinery tend to achieve higher productivity, employ less
labor, and lower their cost per kilogram of output. Furthermore, due to
potential correlations among the error terms of the three dependent variables,
supplementary estimations were conducted using the Seemingly Unrelated
Regression (SUR) method. However, in order to determine whether these observed
differences stem directly from mechanization or are instead driven by
structural differences among producers, causal inference methods were applied.
Specifically, Propensity Score Matching (PSM) and Treatment Effects models were
used to match producers with similar characteristics—such as age, farming
experience, education level, and land size. The findings indicate that, when
comparing producers with similar attributes, mechanization does not create a
statistically significant difference in productivity, cost, or labor use. These
results suggest that the seemingly positive effects of mechanization diminish
when producer heterogeneity is accounted for, underscoring the importance of
using causal methods to evaluate the impact of technological change in tea
agriculture.