# **1 Introduction**

There has been a re-emergence of catch-up in productivity by emerging markets and developing economies (EMDEs) to advanced economies (World Bank (2020)). Understanding how the sector-specific source or the changing sectoral composition (i.e., structural change) has contributed to the aggregate beta convergence in productivity is an area that has so far been under-explored.

In low-income countries (hereafter “LICs”), a high share of employment and low labor productivity in agriculture are mainly responsible for low aggregate productivity.<sup>1</sup> The average share of employment in the agriculture sector in LICs is high, at over 65 percent in 2018, compared to just 3 percent in advanced economies. The level of agricultural productivity in LICs is only 4 percent of advanced-economy productivity (Figures 1 and 2). This reflects that slow technology adoption in the agriculture sector in LICs is due to the high proportion of smallholder ownership and family farms (Lowder et al., 2016).<sup>2</sup> However, even if agricultural labor productivity does not converge to the frontier, the labor reallocation to other sectors with higher productivity levels could be an important engine of aggregate convergence. For example, the East Asia and Pacific (EAP) region has experienced a rapid ‘de-agriculturalization’ over 40 years. Within countries, the productivity gaps across sectors in LICs have remained larger than advanced economies over the last 20 years.<sup>3</sup> There is a large body of literature on the determinants of structural change using the multi-sector general equilibrium model. Two traditional explanations for structural change are the representative household with non-homothetic preference (Kongsamut et al. (2001)) and the firms with differential productivity growth rates (Ngai and Pissarides (2007)). Their basic mechanism is that the relative price related to the differential productivity allocates total expenditures across any goods and services. Given these demands, relatively higher productivity growth sheds labor and due to gross complementarity, labor shifts to slower-productivity growth. For example, Alvarez-Cuadrado and Poschke (2011), Duarte and Restuccia (2010), and Herrendorf et al. (2013)

> 1Unless otherwise indicated, productivity is defined in this paper as value added per worker. The classification by income follows World Bank (2021). Low-income countries are part of emerging markets and developing economies (EMDEs).

> 2Although mechanization increases agricultural labor productivity due to both capital deepening and total factor productivity(TFP), mechanization in poor countries is hindered by frictions such as untitled land, which is a prevalent feature of poor countries (Chen, 2020). Furthermore, Restuccia et al. (2008) show that agricultural labor productivity is positively associated with the use of intermediate inputs (e.g., modern fertilizers and high-yield seeds) and argue that certain distortions in factor markets may severely dampen the incentives for their use.

> 3As agricultural workers often do not work full time in agriculture, the sectoral gap is diminished if productivity is measured per hours instead of per worker (Gollin et al., 2014). However, even after taking hours and human capital per worker by sector, a large sectoral gap remains for a large number of countries Hamory et al. (2021).

2