Can Mobile Technologies Enhance Productivity? A Structural Model and Evidence from Benin Food Suppliers
IMF Working Papers, July 26, 2024
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Bibliographic details
- Authors: Pierre Nguimkeu, Cedric I Okou
- Published: July 26, 2024
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798400284335.001
Overview
- Research objective: Analyze drivers of digital technologies adoption and how adoption affects productivity of small scale businesses in Africa.
- Context: Data collected from two semi-rural markets in Benin, where grains and legumes are key staple foods and one-third of the population has internet access.
- Definition: Digital technologies adoption is defined as the use of mobile broadband internet connection through smartphones.
- Methodology: Develop a structural model to rationalize adoption, usage patterns, and outcomes; empirically test model implications using both reduced-form and structural maximum likelihood estimations.
Data and Methods
- Sample setting: Two semi-rural markets in Benin focused on grains and legumes suppliers.
- Empirical strategy:
- Structural model of digital technologies adoption and usage.
- Reduced-form estimations.
- Structural maximum likelihood estimations.
Key Findings
- Adoption correlates:
- Younger suppliers are more likely to adopt digital technologies.
- Wealthier suppliers are more likely to adopt digital technologies.
- More educated suppliers are more likely to adopt digital technologies.
- Suppliers closely surrounded by other users are more likely to adopt digital technologies.
- Adoption and productivity:
- Adopters perform 4-5 more business transactions each month than non-adopters on average.
- Digital technologies adoption could raise the monthly frequency and amounts of trades by up to 50%.
- Gender differences:
- Most adopters are women.
- Women’s productivity gains from adoption are lower than those of their male counterparts.
Counterfactual Policy Simulations
- Main simulated interventions and effects:
- Upgrading the broadband internet quality yields the largest improvement in adoption rate and productivity gains.
- Reducing broadband cost for a given connection quality has only a moderate effect on adoption and productivity.
- Improving access to credit increases the adoption rate of constrained suppliers (limited to those facing credit constraints).
Policy Implications
- Priority intervention: Improve broadband internet quality to maximize adoption rates and productivity gains among small-scale suppliers.
- Complementary measures:
- Cost reductions in connectivity alone are less effective than quality upgrades.
- Financial interventions (improved access to credit) mainly boost adoption among credit-constrained suppliers and should be targeted accordingly.
- Targeting and equity:
- Programs aiming to increase digital adoption should account for gender differences in productivity gains and consider complementary support to enhance women’s returns to adoption.
Source: Can Mobile Technologies Enhance Productivity? A Structural Model and Evidence from Benin Food Suppliers — Pierre Nguimkeu and Cedric I Okou, July 26, 2024 (IMF Working Paper No. 2024/163).
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