The Recent Growth Boom in Developing Economies: A Structural-Change Perspective

Abstract

Growth has accelerated in a wide range of developing countries over the last couple of decades, resulting in an extraordinary period of convergence with the advanced economies. We analyze this experience from the lens of structural change—the reallocation of labor from low- to high-productivity sectors. Patterns of structural change differ greatly in the recent growth experience. In contrast to the East Asian experience, none of the recent growth accelerations in Latin America, Africa or South Asia was driven by rapid industrialization. Beyond that, we document that recent growth accelerations were based on either rapid within-sector labor productivity growth (Latin America) or growth-increasing structural change (Africa), but rarely both at the same time. The African experience is particularly intriguing, as growth-enhancing structural change appears to have come typically at the expense of declining labor productivity growth in the more modern sectors of the economy. We explain this anomaly by arguing that the forces that promoted structural change in Africa originated on the demand side, through either external transfers or increase in agricultural incomes. In contrast to Asia, structural change was the result of increased demand for goods and services produced in the modern sectors of the economy rather than productivity improvements in these sectors.

Appendix: Methodological Notes on Growth Decompositions

Equation (9.2) in Sect. 2indicates that the growth decomposition is an accounting exercise which can have various economic interpretations. Besides Eq. (9.2), there are a few different ways to decompose economywide labor productivity. In general, we are facing three sets of choices: (1) which weights to use, (2) whether to use annual data or simply period end points and (3) how to annualize the growth rates. While aggregate labor productivity growth rates are little affected by these choices, they could influence the magnitude of labor productivity growth rates within sector and from structural change. The difference in results among the three choices disappears only in the limit where the length of a period is infinitely short.

The following discussion explains how different choices could possibly affect the magnitude of growth in both the within and between components of the growth decomposition. A few examples based on the GGDC data are also provided. We then explain our preferred methodology for decomposing labor productivity growth into its within and between components.

Equation (9.6) is a starting point that describes a change in economywide labor productivity in a given period of (t-k, t) with k years:

$$ {y}^t-{y}^{t-k}=\varDelta {y}^t=\sum \limits_i{y}_i^t{\theta}_i^t-\sum \limits_i{y}_i^{t-k}{\theta}_i^{t-k} $$

(9.6)

where ${y}^t$ and ${y}^{t-k}$ are economywide labor productivity at time t and t-k respectively, ${y}_i^t$ and ${y}_i^{t-k}$ are sector i’s labor productivity at t and t-k, ${\theta}_i^t=\frac{L_i^t}{L^t}$ and ${\theta}_i^{t-k}=\frac{L_i^{t-k}}{L^{t-k}}$ are share of labor (L) employed in sector i at t and t-k, and $t>k.$

By rearranging (9.6), we can express the growth decomposition as

$$ \varDelta {y}^t=\sum \limits_i{\theta}_i^{t-k}\varDelta {y}_i^t+\sum \limits_i{y}_i^t\varDelta {\theta}_i^t $$

(9.7)

or

$$ \varDelta {y}^t=\sum \limits_i{\theta}_i^t\varDelta {y}_i^t+\sum \limits_i{y}_i^{t-k}\varDelta {\theta}_i^t $$

(9.8)

where $\varDelta {y}_i^t={y}_i^t-{y}_i^{t-k}$ and $\varDelta {\theta}_i^t={\theta}_i^t-{\theta}_i^{t-k}.$ Equation (9.7) is identical to Eq. (9.2) in Sect. 2 and is the version of the decomposition most commonly used in the literature (as in McMillan and Rodrik 2011, and de Vries et al. 2015).

In (9.7), weights in the “within term” are sectors’ labor shares at the beginning of the period (start-point weight) and weights in the “between term” are sectors’ labor productivity at the end of the period (end-point weight). In (9.8), weights are the opposite of those in (9.8), that is, the within term uses end-point weights and the between term uses start-point weights. Both $\varDelta {y}_i^t$ and $\varDelta {\theta}_i^t$ can be positive or negative for a given sector, while $\sum \varDelta {\theta}_i^t=0.$

Assuming $\varDelta {y}_i^t\ne 0$ and $\varDelta {\theta}_i^t\ne 0,$ for a given sector i, there are four possibilities for combined $\varDelta {y}_i^t$ and $\varDelta {\theta}_i^t$ with different signs, that is, (a) $\varDelta {y}_i^t>0$ & $\varDelta {\theta}_i^t<0,$ (b) $\varDelta {y}_i^t>0$ & $\varDelta {\theta}_i^t>0,$ (c) $\varDelta {y}_i^t<0$ & $\varDelta {\theta}_i^t>0,$ and (d) $\varDelta {y}_i^t<0$ & $\varDelta {\theta}_i^t<0.$ Under different situations, the choice of the weights affects the magnitudes of the two components at the sector level. We consider each case below.

• Case (a): ${y}_i^t>{y}_i^{t-k}$ and ${\theta}_i^t<{\theta}_i^{t-k}.$ This is commonly seen for i = agriculture among developing countries.

  In this case, sector i positively contributes to within-sector growth and negatively contributes to growth from structural change. Moreover, since ${\theta}_i^{t-k}\varDelta {y}_i^t>{\theta}_i^t\varDelta {y}_i^t$ and $\mid {y}_i^t\varDelta {\theta}_i^t\mid >\mid {y}_i^{t-k}\varDelta {\theta}_i^t\mid$, compared to Eq. (9.8), Eq. (9.7) could overstate the contribution of sector i’s (agricultural) within-sector productivity growth and hence also overstate the negative contribution of this sector to structural change.

• Case (b): ${y}_i^t>{y}_i^{t-k}$ and ${\theta}_i^t>{\theta}_i^{t-k}.$ This is commonly seen among East Asian countries for i = manufacturing.

  In this case, ${\theta}_i^{t-k}\varDelta {y}_i^t<{\theta}_i^t\varDelta {y}_i^t$ and ${y}_i^t\varDelta {\theta}_i^t>{y}_i^{t-k}\varDelta {\theta}_i^t.$ Compared to Eq. (9.8), Eq. (9.7) could understate the contribution of sector i’s (manufacturing) within-sector productivity growth and overstate the contribution of this sector to structural change.

• Case (c): ${y}_i^t<{y}_i^{t-k}$ and ${\theta}_i^t>{\theta}_i^{t-k}.$ We have seen this in this chapter in the case of African countries for many nonagricultural sectors.

  In this case, $\varDelta {y}_i^t<0,$$\mid {\theta}_i^{t-k}\varDelta {y}_i^t\mid <\mid {\theta}_i^t\varDelta {y}_i^t\mid$, but ${y}_i^t\varDelta {\theta}_i^t<{y}_i^{t-k}\varDelta {\theta}_i^t,$ which implies that Eq. (9.7) could understate both the negative contribution of sector i to within-sector productivity changes and its positive contribution from structural change in comparison with Eq. (9.8).

• Case (d): ${y}_i^t<{y}_i^{t-k}$ and ${\theta}_i^t<{\theta}_i^{t-k},$ which is a rare case, but we do see it in Hong Kong for the construction sector for the period 1990–2010 in the GGDC data.

  Because both $\varDelta {y}_i^t<0$ and $\varDelta {\theta}_i^t<0$, $\mid {\theta}_i^{t-k}\varDelta {y}_i^t\mid >\mid {\theta}_i^t\varDelta {y}_i^t\mid$ and $\mid {y}_i^t\varDelta {\theta}_i^t\mid <\mid {y}_i^{t-k}\varDelta {\theta}_i^t\mid,$ Eq. (9.7) could overstate sector i’s negative contribution within sector and understate the negative contribution to structural change in comparison with Eq. (9.8).

The discussion of these four cases is for individual sectors. There is never a situation where all sectors of a country follow a single case, and thus, combined effects across sectors often produce ambiguity. In general, there is less concern for which equation should be used when productivity gaps across sectors are small or changes in employment structure over time are modest. In the examples shown in Fig. 9.18, however, it is clear that the choice between these two equations affects the decomposition in the African and Latin American country groups significantly, while there is little effect for the high-income country group or for Asian countries.

Fig. 9.18

Comparison of two methods in Eqs. (9.7) and (9.8) for labor productivity growth in 2000–2010 (percentages)

Source: Authors’ calculations using GGDC data

We have checked the robustness of the main findings discussed in the body of the chapter by comparing them with the results when we use Eq. (9.8) instead of Eq. (9.7). As expected, we get a somewhat different quantitative decomposition into the between and within terms. But we still have a negative correlation between the magnitudes of the within and between terms. In addition, Latin America’s growth acceleration is due overwhelmingly to the improvement in the within terms, while Africa’s is due to the between terms, as discussed.

The second and third choices related to the growth decomposition exercise are whether we just calculate changes in labor productivity growth within sector and from structural change in a given period (e.g., over ten years) as shown in Eq. (9.7) or (9.8), or whether we compute their annual growth rates. Reporting annual growth rates in labor productivity growth within sector and from structural change has the advantage that we can relate these to annual growth rates in GDP as we do in Table 9.4 of this chapter. A commonly used method is to first get the changes in within and between terms across sectors over an entire period, and then annualize them to get an average annual growth rate. This method is used by McMillan and Rodrik (2011) and de Vries et al. (2015). One advantage of this method is that we only need value added and employment data across sectors at two data points (two years). The disadvantage is that when time series data are available, this method simply ignores all the data between the initial and end points in a growth decomposition analysis. Again, when sectoral labor productivity and shares of employment do not fluctuate over time and follow a monotonic trend in growth (a trend either up or down) during the period in question, different methods of annualizing matter little. Indeed, we do not see much difference for the two different methods of annualizing the data for the high-income and Asian country groups, but there are some differences for African countries (Fig. 9.19).

Fig. 9.19

Comparison of different approaches to annualize labor productivity growth rate in 2000–2010 (percentages). (Note: Equation (9.2) is used in both approaches)

Source: Authors’ calculations using GGDC data

In this chapter, we focus on recent growth accelerations in African and Latin American countries. Therefore, we decided to use a year-by-year calculation using the weights defined in Eq. (9.7) but to calculate each year’s growth rate for the within and between components at sector level across countries as follows:

$$ {g}_y^t=\sum \limits_i{\theta}_i^{t-1}{\pi}_i^{t-1}{g}_{y_i}^t+\sum \limits_i\varDelta {\theta}_i^t{\pi}_i^{t-1}\left(1+{g}_{y_i}^t\right). $$

(9.9)

where ${g}_y^t=\frac{\varDelta {y}^t}{y^{t-1}},$${g}_{y_i}^t=\frac{\varDelta {y}_i^t}{y_i^{t-1}},$ and ${\pi}_i^t$ is relative labor productivity for sector i defined as ${\pi}_i^t=\frac{y_i^t}{y^t}.$ We then calculate the average annual growth rates for the within and between terms in a given period (e.g., over ten years) for each sector by taking a simple average as follows:

$$ {\overline{g}}_i^{within}=\frac{1}{10}\sum \limits_{10}^{t=1}{\theta}_i^{t-1}{\pi}_i^{t-1}{g}_{y_i}^t $$

and

$$ {\overline{g}}_i^{between}=\frac{1}{10}\sum \limits_{10}^{t=1}\varDelta {\theta}_i^t{\pi}_i^{t-1}\left(1+{g}_{y_i}^t\right) $$

where ${\overline{g}}_i^{within}$ and ${\overline{g}}_i^{between}$ are the average labor productivity growth rates of sector i within sector and from structural change in a given ten-year period, and where both ${\overline{g}}_i^{within}$ and ${\overline{g}}_i^{between}$ are measured as fractions of the average annual growth rate of economywide labor productivity in this period. Thus, the annual economywide labor productivity growth rate and its two components in this given period are defined as follows:

$$ \overline{g}=\sum \limits_i{\overline{g}}_i^{within}+\sum \limits_i{\overline{g}}_i^{between} $$

(9.10)

Tables 9.9 and 9.10 present $\overline{g},$$\sum \limits_i{\overline{g}}_i^{within},$ and $\sum \limits_i{\overline{g}}_i^{between}$ at the country level, while the details for ${\overline{g}}_i^{within}$ and ${\overline{g}}_i^{between}$ at the sector level across countries can be obtained from the authors upon request.

Table 9.9 Labor productivity growth within sector and due to structural change, before and during growth accelerations—LAC, Africa and India (ten years in each period, annual average)

Table 9.10 Labor productivity growth within sector and due to structural change, before and during growth accelerations—Asia (ten years in each period, annual average)