A Technology-Gap Model of Premature Deindustrialization
This paper presents a simple model of what Rodrik (2016) called premature deindustrialization (PD); the
tendency that, compared to early industrializers, late industrializers reach their peaks of industrialization
later in time but at earlier stages of development, measured in per capita income, with the lower peak
manufacturing shares.
In the baseline version of the model, the hump-shaped path of the manufacturing share is driven
by the Baumol effect, with the productivity growth rates of the frontier technology being the highest in
agriculture and the lowest in services. The countries are heterogeneous only in the “technology gap,”
their capacity to adopt the frontier technology, which might affect adoption lags across sectors
differently.
In this setup, we show that PD occurs when the following three conditions are met; i) the impact
of the technology gap on the adoption lag is the largest in the service sector, ii) although the adoption lag
is shorter in the agriculture than in the service, the productivity growth rate is sufficiently higher in
agriculture than in service that the cross-country productivity differences are larger in agriculture than in
service; and iii) the impact of the technology gap on the adoption lag is not too large in manufacturing.
It turns out that these conditions jointly imply that the cross-country productivity differences are the
largest in agriculture.
Then, we consider two extensions. In the first extension, we introduce the Engel effect on top of
the Baumol effect by letting the hump-shaped path of the manufacturing share driven also by
nonhomothetic demand with the income elasticities being the largest in services and the smallest in
agriculture, which shows that the main results carry over. However, if we had relied solely on the Engel
effect without the Baumol effect, PD would occur only under the conditions that would generate some
counterfactual implications. In the second extension, we allow late industrializers to catch up by
narrowing the technology gaps over time and show that the main results carry over for an empirically
plausible range of the catching up speed.
Date: 19 October 2021, 14:30 (Tuesday, 2nd week, Michaelmas 2021)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room A or https://zoom.us/j/93987778529?pwd=czZQUFh6aTVLNk9QQjd6RnNxNmtpQT09
Speakers: Ippei Fujiwara (Keio University), Kiminori Matsuyama (Northwestern University)
Organising department: Department of Economics
Part of: Macroeconomics Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Emma Heritage