Structural Change, Growth, and Volatility

Abstract

I construct a two-sector general equilibrium model of structural change to study the impact of sectoral composition of gross domestic product (GDP) on cross-country differences in GDP growth and volatility. For an empirically relevant parametrization of sectoral production functions, an increase in the share of services in GDP reduces both aggregate total factor productivity (TFP) growth and volatility, thus reducing GDP growth and volatility. When the model is calibrated to the US manufacturing and service sector, the rise of the service sector occurring as income grows can account for a large fraction of the differences in per capita GDP growth and volatility between high-income economies and upper middle income economies. (JEL E23, E25, E32, L60, L80) T his article puts forth the idea that the composition of GDP represents an important channel in shaping both GDP growth and volatility. Cross-country evidence suggests that: (i) per capita GDP of high-income economies grows slower than that of middle income economies; (ii) high-income economies display lower per capita GDP volatility than middle income ones; and (iii) the share of services in GDP increases with income per capita. These facts together suggest that both the growth rate and the volatility of an economy might be related to its productive structure. To address this issue, I first report empirical evidence on the three observations above. Next, I present a two-sector general equilibrium model qualitatively consistent with such evidence. Finally, I use a calibrated version of the model to assess the importance of structural change between the broadly defined manufacturing and service sector for observed differences in per capita GDP growth and volatility between upper middle and high-income economies. Even in the most conservative

Production Networks and Aggregate Fluctuations: Evidence, Theory, and Policy

“…This paper is different from Jones (2011), Bartelme and Gorodnichenko (2015), and Fadinger et al (2015) in that it studies countries' aggregate dynamics rather than aggregate productiv-8 Even though we take the input-output structure as given, without modeling or targeting the structural change, the results in this paper hold as long as developed economies are on average more service oriented than emerging economies along the period 1984-2014. This is indeed what is observed in the data in Moro (2015) when comparing middle income economies with high income economies.…”

“…This study complements the findings in di Giovanni and Levchenko (2012) by emphasizing the role of the structure of inter-sectoral linkages in the propagation and amplification of sectoral shocks. 7 Moro (2012), Moro (2015), Carvalho and Gabaix (2013) study how the structural change in the U.S. and other low and high income economies towards a more service-intensive economy reduces aggregate volatility. The cross-country analysis in this paper adds a new dimension in which aggregate volatility is smaller in a service-intensive economy.…”

“…The literature of structural transformation (Moro (2012), Carvalho and Gabaix (2013), and Moro (2015)) documents that developed economies tend to specialize in service sectors while emerging economies specialize in manufacturing, agriculture or mining activities. It is also well known that service sectors tend to be less volatile than non-service sectors (Koren and Tenreyro (2007)).…”

“…Figure 5 shows in the horizontal axis the logarithm of the average GDP per capita adjusted by PPP and in the vertical axis the service sectors' share over gross output in 2011. Developed economies are more service oriented, which reduces their aggregate volatility compared to emerging economies (Moro (2015)). …”

“…A 1% increase in the network density is associated with a 0.4% increase in volatility. Motivated by the findings in Moro (2015), in column (2) we add the service share as a regressor. As expected, countries with a larger service share are less volatile.…”