Technology, Wages and Skill Shortages: Evidence from UK Micro Data

Why have skill shortages continue to persist despite increases in training and the skill levels of the workforce? We argue that technical progress has raised the demand for skilled labour to mach the observed increase in supply. We provide econometric evidence in support of this hypothesis, showing that skill shortages are higher for establishments that use advanced technology in the production process. We also provide econometric evidence that hiring difficulties are inversely related to the relative wage, as theory would suggest. Our results have clear implications for policy. If technological progress continues to be skill biased, policies that address skills deficiencies will only be successful if they produce a continual, rather than a temporary, increase in levels of skills among the workforc

How does big data affect GDP? Theory and evidence for the UK

We present an economic approach to measuring the impact of Big Data on GDP and GDP growth. We define data, information, ideas and knowledge. We present a conceptual framework to understand and measure the production of “Big Data”, which we classify as transformed data and data-based knowledge. We use this framework to understand how current official datasets and concepts used by Statistics Offices might already measure Big Data in GDP, or might miss it. We also set out how unofficial data sources might be used to measure the contribution of data to GDP and present estimates on its contributions to growth. Using new estimates of employment and investment in Big Data as set out in Chebli, Goodridge et al. (2015) and Goodridge and Haskel (2015a) and treating transformed data and data-based knowledge as capital assets, we estimate that for the UK: (a) in 2012, “Big Data” assets add £1.6bn to market sector GVA; (b) in 2005-2012, account for 0.02% of growth in market sector value-added; (c) much Big Data activity is already captured in the official data on software – 76% of investment in Big Data is already included in official software investment, and 76% of the contribution of Big Data to GDP growth is also already in the software contribution; and (d) in the coming decade, data-based assets may contribute around 0.07% to 0.23% pa of annual growth on average

Understanding 'The Essential Fact about Capitalism': markets, competition and creative destruction

This paper examines two ways in which competition works in modern capitalist economies to improve productivity. The first is through incentives: encouraging improvements in technology, organisation and effort on the part of existing establishments and firms. The second is through selection: replacing less-productive with more productive establishments and firms, whether smoothly via the transfer of market shares from less to more productive firms, or roughly through the exit of some firms and the entry of others. We report evidence from the UK suggesting that selection is responsible for a large proportion of aggregate productivity growth in manufacturing, and that much of this is due in turn to selection between plants belonging to multi-plant firms. We also investigate whether the nature of the selection process varies across the business cycle and report evidence suggesting that it is less effective in booms and recessions. Finally, although in principle productivity catch-up by low-income countries ought to be easier than innovation at the frontier, in the absence of a well functioning competitive infrastructure (a predicament that characterises many poor countries), selection may be associated with much more turbulence and a lower rate of productivity growth than in relatively prosperous societies. We report results of a survey of firms in transition economies suggesting that, particularly in the former Soviet states (excluding the Baltic states), poor output and productivity performance has not been due to an unwillingness on the part of firms to change and adapt. On the contrary, there has been a great deal of restructuring, much new entry and large reallocations of output between firms; but such activity has been much more weakly associated with improved performance than we would expect in established market economies

Constructing a price deflator for R&D: calculating the price of knowledge investments as a residual

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What happened to the knowledge economy? ICT, intangible investment and Britain's productivity record revisited

A major puzzle is that despite the apparent importance of innovation around the "knowledge economy", UK macro performance appears unaffected: investment rates are flat, and productivity has slowed down. We investigate whether measurement issues might account for the puzzle. The standard National Accounts treatment of most spending on "knowledge" or "intangible" assets is as intermediate consumption. Thus they do not count as either GDP or investment. We ask how treating such spending as investment affects some key macro variables, namely, market sector gross value added (MGVA), business investment, capital and labour shares, growth in labour and total factor productivity, and capital deepening. We find (a) MGVA was understated by about 6% in 1970 and 13% in 2004 (b) instead of the nominal business investment/MGVA ratio falling since 1970 it is has been rising (c) instead of the labour compensation/MGVA ratio being flat since 1970 it has been falling (d) growth in labour productivity and capital deepening has been understated and growth in total factor productivity overstated (e) total factor productivity growth has not slowed since 1990 but has been accelerating

Trade, Technology and U.K. Wage Inequality

The U.K. skill premium fell from the 1950s to the late 1970s and then rose very sharply. This paper examines the contributions to these relative wage movements of international trade and technical change. We first measure trade as changes in product prices and technical change as TFP growth. Then we relate price and TFP changes to a set of underlying factors. Among a number of results, we find that changes in prices, not TFP, were the major force behind the rise in inequality in the 1980s. We also find that although increased trade pressure has raised technical change, its effect on wage inequality was not quantitatively significant.

Does the Sector Bias of Skill-Biased Technical Change Explain Changing Wage Inequality?

This paper examines whether the sector bias of skill-biased technical change (sbtc) explains changing skill premia within countries in recent decades. First, using a two-factor, two-sector, two-country model we demonstrate that in many cases it is the sector bias of sbtc that determines sbtc's effect on relative factor prices, not its factor bias. Thus, rising (falling) skill premia are caused by more extensive sbtc in skill-intensive (unskill-intensive) sectors. Second, we test the sector-bias hypothesis using industry data for many countries in recent decades. An initial consistency check strongly supports the hypothesis. Among ten countries we find a strong correlation between changes in skill premia and the sector bias of sbtc during the 1970s and 1980s. The hypothesis is also strongly supported by more structural estimation on U.S. and U.K. data of the economy-wide wage changes mandated' to maintain zero profits in all sectors in response to the sector bias of sbtc. The suggestive mandated-wage estimates match the direction of actual wage changes in both countries during both the 1970s and the 1980s. Thus, the empirical evidence strongly suggests that the sector bias of sbtc can help explain changing skill premia.