Gig Economy as a Matching Shock in Agriculture
Keywords:
dual-sector model matching efficiency agricultural transformation welfare dynamics employment absorptionAbstract
This study reconceptualizes Indonesia’s agricultural labor market as a dual internal economy comprising a traditional on-farm segment and a modern upstream–downstream agribusiness sector, each characterized by distinct search and matching frictions. Building on the Mortensen–Pissarides framework, we model the digital gig economy as a technological shock that enhance the job-matching efficiency parameter within the traditional segment. Using a Monte Carlo equilibrium simulation (10,000 draws) calibrated with Indonesian labor statistics, the study evaluates counterfactual scenarios representing 10–50% improvements in matching efficiency to simulate progressive digital diffusion. Results indicate that improved matching efficiency can reduce aggregate unemployment by 0.3–1.0 percentage points, create over 300,000 additional jobs, and increase agricultural GDP by up to 1.8%. Approximately 70–90% of these gains originate from on-farm employment, while the remainder reflects spillovers to modern agribusiness through induced demand and digital linkages. Sensitivity analysis underscores that sectoral composition and spillover elasticity shape the magnitude of macroeconomic gains. Conceptually, the study integrates labor-market frictions into theories of technological diffusion and structural change. As a simulation-based theoretical experiment, it offers a plausible framework for understanding how gig platforms can function as transitional accelerators of inclusive rural transformation.
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