Annex 6C Commodity-driven productivity developments: Methodology

394 C H A P T E R 6 G L O B A L P R O D U C T I V I T Y

To summarize, demand drivers can have smaller, but still important, longer-term effects on labor productivity, particularly in economies with little fiscal space and in commodity exporters. Historically, with the exception of agricultural goods exporters, these longer-run effects have occurred primarily through capital deepening, with evidence of some negative effects of positive demand shocks on the overall efficiency of production (TFP).

A local projection model was used to estimate the effects of commodity price changes on GDP, labor productivity, capital deepening, and TFP. The model follows Jordà (2005) in estimating impulse responses over a series of horizons, in this case from 1 to 10 years. Agricultural, metals, and energy exporters are separately estimated in panel specifications using fixed effects. Commodity price (real U.S. dollar indexes) changes are assumed to be exogenous to each country in the specification. However, this property may be violated when individual economies are associated with the price change, for example, because of supply disruptions in individual economies that are large enough to influence global commodity prices.

In addition, the local projection specification controls for changes in global demand conditions that may be driving the commodity price change, including those that occur before and after the commodity price shock under examination. This control is constructed as an export-weighted aggregate of global GDP growth of each country under consideration.

The outcome variable yt reflects the log level of GDP, labor productivity, the cumulative contribution of capital deepening to labor productivity growth, and the log level of TFP. In addition to controlling for global demand (Dt), the specification controls for lagged values of the growth of the outcome variable (dyt–1) and lagged values of the commodity ∆price series ( ) to reduce bias associated with serial correlation of commodity price changes and the productivity variables. The estimation is performed for each period h from 1 to 10 years.

It has been argued that, for a true IRF representation, subsequent developments in the shock of interest should be controlled for (Alloza, Gonzalo, and Sanz 2019). Including leading changes in commodity price changes results in larger impacts but does not alter the qualitative channels through which price shocks operate, or the qualitative differences between the transmission channels in each type of commodity exporter.

p1 com t −

1

h i com p com y d 1 d t h t h h t h t h t i t i i t j t h1y y p p dy D D+ − − − − + +1 − = + ∆ + ∆ + + + + ∈   α β γ γ γ γ i 0 j 0