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This study analyses the impact of the use of digital technology on economic growth for 39 African countries from 2012 to 2016. This analysis applies a system GMM estimator to understand the extent to which the usage of digital technology facilitates growth using a measure of digitalisation from the Networked Readiness Index. Unlike previous research, we distinguish between the impact of individual, business, and government ICT usage on growth and show that only individual usage has a positive impact. Furthermore, a disaggregated analysis of the types of usage reveals that two indicators, social media and the importance of ICTs to government vision, are significant for growth.

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Abstract. The effect of technological innovation on employment is of major concern for workers and their unions, policy makers and academic researchers. We meta-analyse 570 estimates from 35 primary studies that estimate a derived labour demand model. We contribute to existing attempts at evidence synthesis by addressing the risks of selection bias and that of data dependence in observational studies. Our findings indicate that: (i) hierarchical meta-regression models are sufficiently versatile for addressing both selection bias and data dependence in observational data; (ii) innovation's effect on employment is positive but small and highly heterogeneous; (iii) only a small part of residual heterogeneity is explained by moderating factors; (iv) selection bias tends to reflect preference for upholding prevalent hypotheses on the employment effects of process and product innovations; (v) country-specific effect-size estimates are related to labour market and product market regulation in six OECD countries in a U-shaped fashion; and (vi) OLS estimates reflect upward bias whereas those based on time-differenced or within estimators reflect a downward bias. Our findings point out to a range of data quality and modelling issues that should be addressed in future research.

We investigate the effect of domestic market competition on firmlevel export intensity. We employ a comprehensive dataset of Belgian firms from [2005][2006][2007][2008], when the fall in the number of firms engaged in trade was accompanied by a growing amount of transactions. The resulting increase in the domestic concentration of Belgian firms has sparked numerous debates, since the direction of causality between domestic market structure and export performance is unclear. We apply the fractional logit estimator and control for both self selection and simultaneity bias. We find that a positive linkage exists between the level of competition and export intensity.JEL Classification: C23, F14, L16, L40.

Business research and development (R&D) expenditures in the UK is low by international standards. To encourage investment, the UK government has been providing both direct and indirect support. The aim of this paper is to address four inter-related and policy-relevant questions: (i) what do we know about the UK regime for direct grant schemes? (ii) is the UK subsidy complementary or substitute for privately-funded R&D? (iii) does the UK funding regime differ from the EU regime in terms of selection and effect? (iv) does the scope for complementarity/additionality differ between different rates of funding? We address these questions using a rich dataset for more than 44 thousand UK firms from 1998-2012; and a range of treatment-effect estimators with and without control for selection. We report that the EU selection regime is more likely to support firms with long-term R&D plans. In addition, the UK subsidy is not associated with additionality, but the EU subsidy is. Finally, leverage estimations indicate that targeting a particular rate of subsidy is not likely to make a difference to private R&D effort in the UK subsidy case; but an increase in EU subsidy intensity does create leverage among firms that fall between the median and 75 th percentile of the subsidy intensity distribution.

The volume of work on productivity effects of research and development (R&D) investment has expanded significantly following the contributions of Zvi Griliches and others to microeconometric work in late 1970s and early 1980s. This study aims to meta-analyse the research findings based on OECD firm and industry data, with a view to establish where the balance of the evidence lies and what factors may explain the variation in reported evidence. Drawing on 1,262 estimates from 64 primary studies, we report that the average effect of R&D capital on productivity and the average rate of return on R&D investment are both positive, but smaller than the summary measures reported in previous narrative reviews and meta-analysis studies. We also report that a range of moderating factors have significant effects on the variation among productivity and rates-of-return estimates reported in primary studies. Moderating factors with significant effects include: (i) measurement of inputs and output; (ii) model specifications; (iii) estimation methods; (iv) levels of analysis; (v) countries covered; and (vi) publication type among others. JEL Classification: D24, O30, O32, C49, C80

This data article is related to the research article entitled “Inverted-U relationship between R&D intensity and survival: Evidence on scale and complementarity effects in UK data” (Ugur et al., In press) [1]. It describes the trends in R&D expenditures, employment of R&D personnel and firm entry and exit rates in the UK from 1998 to 2012. We also provide statistics on net employment creation and net R&D investments due to firm entry and exits. In addition, we compute the correlation coefficients between entry and exit rates at the two digit industry level so as to examine whether the correlations are contemporaneous or inter-temporal. Finally, we provide information about the underlying dataset to which secure access is available through UK Data Service Archive 7716 at http://dx.doi.org/10.5255/UKDA-SN-7716-1.