If developing countries can no longer rely on structural transformation toward the manufacturing sector as the engine of growth, what are alternative options? Some recent studies argue that in contrast to the earlier literature’s stance, the services sector does present significant opportunities for productivity and economic growth (Maroto-Sánchez and Cuadrado-Roura 2009; Lee and McKibbin 2014; di Meglio et al. 2015). Similarly, Nayyar, Cruz and Zhu (2018) suggest that the productivity-enhancing role of the manufacturing sector that led to the development of early industrializers is not unique to the sector. More specifically, the authors find that crucial features of manufacturing growth that make it an important source of productivity growth – that is, the production of tradable goods, the scope for “learning-by-doing” through global integration, and the facilitation of technology diffusion – are also shared by the services sector. However, the authors argue that any given service subsector is unlikely to provide simultaneous opportunities for both productivity growth and job creation for unskilled labor. In addition, they posit that the development of some services subsectors requires a robust manufacturing base, as intermediate demand for many services is derived from manufacturing. These findings, as well as those by other studies on productivity growth in services, suggest that the services sector can be a particularly strong driver of productivity growth if linkages to the manufacturing sector are maintained and strengthened.

In addition to the large international literature on structural transformation, there has been a smaller but significant literature more specifically on Malaysia. This literature has largely focused on the country’s rapid industrialization and subsequent relative deindustrialization process (Jomo and Edwards 1993; Jomo 1994; Rasiah 2011a), as well as on concerns of premature (Tan 2014) or even negative (Rasiah 2011b) deindustrialization. A related literature has documented that Malaysia’s productivity growth engine has stalled after the year 2000 and argued that restarting it will be key for Malaysia’s economic development toward a highincome economy (Khazanah Research Institute 2017; World Bank 2018c).

This rest of this paper is organized as follows. Section 2 presents the study’s research methodology and data. Section 3 illustrates the patterns of growth in output, employment, and output per capita across sectors in Malaysia from 1987 to 2018. The results of the decomposition of output per capita into contributions from within- and between-sector labor productivity growth, employment growth, and changes in the demographic structure are presented in Section 4. Section 5 discusses implications for policy and research and concludes.

# **2. Methodology and Data**

# **2.1. Shapley and Canonical Decomposition**

This study follows World Bank (2012) and Martins (2018) and first and foremost utilizes the Shapley decomposition method (Shorrocks 2013) to decompose growth in output per capita into within-sector labor productivity growth, between-sector labor productivity growth, employment growth, and changes in the demographic structure.<sup>3</sup> The Shapley decomposition is a simple additive method that links changes in a variable like output per capita to changes in a particular component of this variable, taking into account both the relative size of the component and the magnitude of the change.

As visualized in Figure 1, in practical terms growth in output per capita is decomposed in several consecutive steps. _First_ , growth in output per capita is decomposed into changes in the aggregate output per worker, changes in the aggregate employment rate and changes in the share of the working age population among the entire population. _Second_ , changes in the aggregate employment rate are further decomposed into changes in the employment rate by sector. _Third_ , changes in the aggregate output per worker are decomposed into changes linked to variations in output per worker within sectors (within-sector productivity growth) and changes linked

> 3 For reasons of data availability, this study uses output (or value-added) instead of GDP. In contrast to GDP, output does not include taxes and subsidies; differences between GDP and output are usually very small. The sum of sectoral outputs from DOSM is used to compute aggregate output.

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