infrastructure and the diffusion of general-purpose technologies (GPTs) such as computers—to explain the technological progress of firms and inform policy design tailored to different firms in different contexts?
Measuring Adoption and Use of Technology by Firms Moving from Macro to Micro Analysis The importance of technology adoption has been emphasized by macro, sectoral, and micro studies, but the measures used at each level are difficult to reconcile. Macro-level studies tend to be based on cross-country analysis mostly focusing on GPTs, such as electricity, the internet, or computers, using information on adoption by individuals or firms that is aggregated at the country level. Sectoral studies tend to rely on firm-level or household-level data, with a focus on the diffusion and impact of sector-specific technologies at a very granular level (such as the diffusion of varieties of seeds in agriculture). Other firm-level studies tend to be broader in terms of sector and focus on the use of GPTs (such as cloud computing) without identifying the specific purpose for which technologies are being used, or examine very specific technologies that can be used by any firm (such as enterprise resource planning [ERP] systems). Despite different approaches and measures, studies at different levels of aggregation tend to converge on the importance of technology for firm performance and the overall economic development of countries. Recent findings from the macro literature support the need for better measures of the adoption and intensity of use of technologies by firms. A recent important finding is that while the lag between lower-income and high-income countries in the adoption of technology has narrowed, the gap in the intensity of use of adopted technologies has increased (Comin and Mestieri 2018). Thus, although the pace of technology diffusion has accelerated, diffusion is uneven, resulting in an increasing technology gap across firms and countries. A comparison of the diffusion of 25 GPTs in the past 200 years, as shown in figure 1.1, suggests that newer technologies, such as personal computers and the internet, are arriving more quickly in developing countries than older technologies, such as the telegraph and tractors (panel a). Yet, despite their earlier arrival in developing countries, the gap in the intensity of their use between developing countries and advanced economies is widening (panel b).2 At the sector level, agriculture is likely the most well covered in terms of studies measuring and assessing the diffusion of sector-specific technologies.3 There are several reasons for the predominance of technology adoption studies focusing on agriculture, including data availability, the large share of workers in low-income countries who are still in agriculture, and the increasing importance of total factor productivity (TFP) as a source of agricultural growth in the past few decades, as highlighted in Foster and Rosenzweig (2010) and the fourth volume in the World Bank Productivity Project series (Fuglie et al. 2020). More recently, an increasing number of studies have focused on sector-specific technologies used by manufacturing and services firms. Some of these studies 22
Bridging the Technological Divide
