Explanations for the Productivity Puzzle

The calculations in the previous two sub-sections merely represent an attempt to gauge the quantitative impact of potential mismeasurement in some of the KIBS

industries. If wage-based deflators are replaced by either foreign SPPI or the Swiss core PPI, average labour productivity growth in the overall KIBS industries is lifted by 0.3 to 0.4 percentage points, but remains still low relative to other sectors.

Thus, our calculations cannot fully explain the productivity shortfall relative to other industries in Switzerland. One possible explanation for this is that theentire scope of measurement problemsis not captured by our calculations:

• In the application of foreign SPPI, not all wage-based deflators can be re-placed because SPPI are not available for some industries.

• In the overall KIBS industries, the share of value added that is deflated with wage indices is 36%. The simulation exercises therefore only apply to this fraction of the overall value added of the KIBS industries.

• In the financial industries, the adequate measurement of nominal value added still remains difficult. This issue could be relevant because the finan-cial industries constitute 42% of value added in the KIBS industries.

• Other deflators used for certain KIBS industries (CPI, SPPI or others) might also be prone to measurement error, especially if quality changes are not properly accounted for. Therefore, labour productivity growth in these in-dustries may also be too low due to mismeasurement.

• Finally, the evolution of labour input, the denominator of labour productiv-ity, may be more prone to measurement error in some industries compared to others.

Therefore, it is unclear how much labour productivity would rise if prices were measured correctly inallKIBS industries. According toOECD-Eurostat(2014), properly accounting for quality change continues to be challenging in many service industries even if SPPIs based on modern methods, such as model pricing, are used. It remains a matter of speculation to what extent the “productivity gap” be-tween KIBS industries and, say, manufacturing is attributable to measurement error.

Second, it is conceivable that the relatively poor performance of KIBS industries is at least partly related to “hard” economic factors rather than the result of mismeas-urement. Our analysis of productivity-related indicators across industry groups (Section4.4) does not provide evidence in favour of a productivity shortfall of the KIBS industries relative to manufacturing and traditional services, so there may be additional unobserved factors that play a role. A theoretical growth framework as the one presented in Box A can provide some guidance: the model suggests that labour productivity growth depends on the capital-labour ratio, the human capital intensity and technological progress (innovation). Below, we discuss a number of potential explanations:

• Capital deepening: It is possible that industries differ in their potential to in-crease the capital-labour ratio over time. For instance, if there is limited scope for the automation of tasks or other labour-saving measures in some service industries, the growth rate of the capital-labour ratio, and thus, the growth rate of labour productivity will be lower than elsewhere in the econ-omy.

• Innovation: The impact of innovation on productivity runs through two main channels (seeHall 2011). First, innovation increases the efficiency of pro-duction and improves the quality of goods and services. Second, innovating firms are likely to grow faster and will therefore displace non-innovating firms. If innovation activities are inherently industry-specific, different lev-els of innovation activities across industries will lead to different growth paths. If innovation activities had been low in the KIBS industries, there would have been a negative impact on labour productivity.

• Competition: Competition can affect the productivity of firms in two ways.

First, increasing competitive pressure will typically drive the least efficient firms out of the market and induce a re-allocation towards more efficient firms. This will increase labour productivity in the average firm. Second, more competition can induce a given surviving firm to become more effi-cient by reducing so-called “X-inefficiencies” that prevail under imperfect competition.Holmes & Schmitz(2010) provide a theory and empirical evi-dence for these effects. It is possible that the intensity of competition has been lower in the KIBS industries compared to other sectors – e.g. due to trade restrictions (see Section4.4.7) – and that this has led to slower produc-tivity growth.

• Initial Productivity Level: In 1997, the nominal value added per worker was much higher in the KIBS industries than elsewhere in the market economy (cf. Table4). Although differences in nominal levels are difficult to interpret in the cross-section, this finding could mean that the productivity in KIBS industries had grown faster than the other sectors prior to 1997. The poor productivity performance of the KIBS industries relative to other industries could therefore be the result of a catch-up of other industries. If this were the case, the productivity performance of the KIBS industries would improve if the analysis could be conducted over a longer time period. Unfortunately, older data are not available on the two-digit industry level.

The capital-labour ratio, innovation activities and the competitive environment all provide potential explanations why true labour productivity growth might differ across industries in the long run. At the same time, these factors are difficult to observe empirically. For example, there is no data on physical capital on the

indus-try level in Switzerland. To sum up, it remains difficult to assess the relevance of the above mentioned factors in explaining the weak productivity growth of the Swiss KIBS industries.