Review of the Dominican Republic's Enabling Environment for the Semiconductor and Microelectronics Industries

Annex C. Shift-share decomposition analysis

A shift-share decomposition can be employed to better disentangle the drivers of labour productivity growth. This method allows for the identification of whether aggregate labour productivity growth in a sector can be attributed to improvements within individual subsectors (within effect), shifts in employment towards more productive subsectors (shift effect), or the interaction of these two forces. Following Molnar and Chalaux (2015[1]), aggregate labour productivity growth can be expressed as:

$\frac{∆LP}{{LP}_{t-1}}= \sum _i{S}_{it-1}\frac{∆{LP}_i}{{LP}_{t-1}}+ \sum _i∆S_i \frac{{LP}_{it-1}}{{LP}_{t-1}}+\sum _i∆S_i\frac{∆{LP}_i}{{LP}_{t-1}}$

where $LP$ denotes labour productivity, $i$ indexes the individual subsectors, $S$ denotes the employment share of subsector $i$ in the other manufacturing sector, and $∆$ denotes the change between periods $t$ and $t-1$.

The first term of the right-hand side of the equation denotes the within-sector effect, i.e. the sum of industry productivity growth rates, weighted by the initial employment shares. The second component is the shift effect, i.e. the sum of changes in employment shares, weighted by the initial productivity level. The third component is the interaction effect, which is positive when the restructuring of the economy is beneficial, i.e. when industries experiencing productivity growth are also attracting more employment.

References

[1] Molnar, M. and T. Chalaux (2015), “Recent trends in productivity in China: shift-share analysis of labour productivity growth and the evolution of the productivity gap”, OECD Economics Department Working Papers, No. 1221, OECD Publishing, Paris, https://doi.org/10.1787/5js1j15rj5zt-en.