Abstract
The labour productivity index is a mainstay measure for comparing countries’ relative economic performance, but the Covid-19 pandemic could expose some of its inherent limitations: it focuses on people in work and ignores unemployment, and it is not standardised. In theory, a country’s index value could increase, even though its GDP might fall, because of significant increased unemployment in low-productivity sectors such as tourism and retail. It follows that the index value could fall when these sectors recover. Also, high-performing countries could see their index value fall because of the pandemic’s impact in high-value sectors, such as demand for oil.Consequently, a wider perspective of productivity is necessary. This paper, therefore, proposes a complementary index which adjusts labour productivity for levels of unemployment—the social labour productivity index (SLPI)—and recommends that the labour productivity index itself should be standardised. The relationship between employment and productivity is complex. For example, the UK’s economic performance, involving comparatively low labour productivity and low unemployment, has been deemed a ‘productivity puzzle’. A literature review discusses this relationship, but it is clear that econometric worldwide evaluation requires very large data sets, that are unlikely to be routinely available in practice to monitor international performance. By contrast, data sets on national productivity are small and already available, although they contain little or no data on causal factors. SLPI values were calculated for differing levels of unemployment and relative labour productivity for newly employed workers for countries where data was available; with patterns over the period 1986–2016 established for the G7 countries, Portugal, Ireland, Greece, and Spain. There were marked variations between the two indices for countries with high unemployment. The SLPI presents a practicable measure which can be utilised quickly in these unprecedented times. Using available data to compare countries’ GDP with their total workforce, it arguably provides a better measure of their overall economic and social health. Sensitivity analyses varying assumptions can model differing potential scenarios to sit alongside GDP and labour productivity index predictions.
Developing and validating the qualitative labour productivity measurement in service industry
