ECO362H1 Lecture Notes - Lecture 8: Quarterly Journal Of Economics, Time Series, U.S. Route 30 In Pennsylvania
Structural Transformation
1 Introduction
Consider the production function:
Yit =AitKα
itN1−α
it
for country iin period t. In the first half of the course, we have focused on explaining and
interpretting cross-country differences in factors of production - notably Ktin the above
expression. However, as we saw in the development accounting exercise, most of cross-
country differences are a consequence of differences in productivity A.
With this in mind, the second half of the course will focus on explaining the causes and
evidence for cross-country differences in total factor productivity (TFP) A. We begin by
examing the role of sectoral composition.
Objectives:
1. Define structrual transformation and its contribution to productivity
2. Discuss the facts and evidence pertaining to Structual Transformation
3. Extend the neoclassical growth model to include multiple sectors
4. Examine the theoretical drivers of sectoral growth
References:
•Herrendorf, Rogerson and Valentinyi (2014, Handbook of Economic Growth)
•Duarte and Restuccia (2010, QJE)
•Restuccia, Yang and Zhu (2008, JME)
1
2 Facts and Discussion
Before discussing the model, it is useful to discuss the facts surrounding structural trans-
formation and the potential causes. We will define Structural Transformation as the
reallocation of economic activity across sectors. In particular, we will focus on the sectors:
agriculture, manufacturing and services.1
2.1 Facts
The topic of structural transformation is motivated largely by the systematic reallocation of
resources across sectors that is related to long-term changes in development.
Figure 1 highlights this trend in the cross-sectional data. The sectoral shares are measured
in terms of employment as a fraction of the total labour force. While we focus on this measure
as it is easiest to construct, the figures would be qualitatively identical if we used another
measure, such as share of total value added.
The striking pattern in Figure 1 is that countries at similar levels of development (as
measured by GDP per worker) employ a similar portion of their workforce to each sector.
Three trends are important. First, the share of employment in the agricultural sector is
decreasing in development. Second, the share of employment in the industry sector is hump-
shaped. Middle income countries have the largest share in the manufacturing sector while
developed and the most under-developed countries have relatively small shared. Third, the
share of employment in the service sector is increasing in development.
Figure 1 portrays a stark trend in the differences of employment allocations across coun-
tries. Next, we would like to know if these trends are a cause or consequence of development.
For example, it could be the case that developed countries now always had a larger share of
their population employed in non-agricultural sectors.
As a first step, we can examine the time-series experience of current developed countries
to see if in the past they experiences a similar reallocation of labour across sectors. Figure
2 shows the US experience. The figure is similarly striking and shows the same reallocation
of labour across sectors - albeit, to a smaller extent than in Figure 1. In fact, we see a
similar pattern across countries in the time series data. As countries develop they tend to
systematically reallocation economic activity out of agricultural towards manufacturing and
then again out of manufacturing and towards services.
1For our purposes, manufacturing is defined more broadly to include other related industry such as mining
or construction. Sometimes this group of sectors is refered to as industry.
2
Figure 1: Sectoral Differences across Countries (in 2000)
To fully address the question of cause versus consequence, we will need to use a model
to address the potential endogeneity of the problem. To simplify the discussion, we will
primarily focus on the transition from the agricultural sector to the non-agricultural sector
(manufacturing plus services). However, there are other types of structural transformation
that have been discussed in the literature. To give a short list, these include:
•Reallocation from unskilled intensive sectors to skill intensive sectors;
•Reallocation within the service sector from “traditional” (e.g. haircuts) to “modern”
(e.g. financial planning) services.
2.2 Importance
Now that we have documented that structural transformation is present in the data, we
want to examine its potential importance. Put simply, should we care about structural
transformation as a source of cross-country income differences?
Total output in an economy can be written as a combination of sectoral components:
pY =paYa+pmYm+psYs
where we use (a, m, s)for the agricultural, manufacturing and service sectors. Assuming that
all sectors use a Cobb-Douglas technology with capital share α, we can rewrite the above
3
Document Summary
However, as we saw in the development accounting exercise, most of cross- country di erences are a consequence of di erences in productivity a. With this in mind, the second half of the course will focus on explaining the causes and evidence for cross-country di erences in total factor productivity (tfp) a. We begin by examing the role of sectoral composition. Objectives: de ne structrual transformation and its contribution to productivity, discuss the facts and evidence pertaining to structual transformation, extend the neoclassical growth model to include multiple sectors, examine the theoretical drivers of sectoral growth. References: herrendorf, rogerson and valentinyi (2014, handbook of economic growth, duarte and restuccia (2010, qje, restuccia, yang and zhu (2008, jme) Before discussing the model, it is useful to discuss the facts surrounding structural trans- formation and the potential causes. We will de ne structural transformation as the reallocation of economic activity across sectors.
