ICT and economic growth: a dynamic non-parametric approach

One of important issues of the policymakers is to improve output and/or productivity growth associated with information and communication technology (ICT) adoption, where total factor productivity (TFP) growth related with ICT in the 1990s appeared in the US but not in the UK (Jorgenson and Stiroh, 2000; Oliner and Sichel, 2000). The general agreement is that ICT can raise output and/or productivity growth via an increase in productivity growth in the ICT-producing sectors due to rapid technological progress, through capital deepening driven by high levels of investment in ICT equipments, and via increases in efficiency in ICT-using sectors that successfully adopt this new technology by ICT spillover effects (David, 1990). Due to the small size of ICT-producing industries and relatively low level of ICT investments in the UK (Colecchia and Schreyer, 2001; Daveri, 2002; Vijselaar and Albers, 2002), the utilization of ICT spillover effects was crucial to improving output and/or productivity growth for the UK. However, in most of the previous studies, while many concluded ICT spillover effects existed in the US, they had mixed results as to whether ICT spillover effects existed in the UK (Schreyer, 2000; Basu et al., 2003; Inklaar et al., 2005; Jorgenson et al., 2005). The objective of this thesis is to contribute to the existing literature by investigating the existence of ICT spillover effects in the US and the UK and exploring the reasons for the different effects between them. This thesis argues that the mixed findings in the previous studies are due to the ignorance of the General-purpose technology (GPT) theory and weakness in methodology. Thus, the first step is to build a new framework of measuring ICT spillover effects to solve the problems from the existing studies. The main ignorance of the GPT theory is the lack of guidance for the proxy of co-invention related to ICT investments and for the length of lag. The new framework no longer has this ignorance because it uses efficiency as a proxy of co-invention and captures the length of lag by years with negative return on ICT capital. The methodology employed in the previous studies was inappropriate mainly because of the small sample size taken in the ICT study, the two-stage approach used to explore the effect of the environmental variables on efficiency and the linear and concavity assumptions on the frontiers without taking account of ICT as a GPT. The new framework uses Bayesian technique, one-stage approach and non-parametric frontiers to avoid these three drawbacks. In addition, the new framework introduces the persistent level of inefficiency, using a first-order autoregressive (i.e. AR(1)) structure of inefficiency itself, as one of factors that influence ICT spillover effects. In order to model the new framework which takes into account the non-parametric frontiers for capturing negative return of ICT capital, an AR(1) structure of inefficiency, the small sample size and factors that influence ICT spillover effects, this thesis has developed two non-parametric dynamic stochastic frontier analysis (SFA) models with an AR(1) structure and performed the analysis via Bayesian inference. The first model was a semi-parametric dynamic stochastic frontier with a time-variant non-parametric frontier at the basic level along with a time-invariant linear function for the technical inefficiency at the higher-level. The second model relaxed the time-invariant linear functional form for technical inefficiency at the higher level. The results of the new framework showed strong ICT spillover effects in the US with a lag of about 6-8 years during 1982-83 to 1988-89, while relatively weaker ICT spillover effects in the UK. This can be evidenced by the fact that the UK has been in the process of organizational adjustment up to 2000 due to a longer lag. Thus, in the 1990s, there was a lack of TFP growth in the UK. Related to the different ICT spillover effects between the US and the UK, the results from the new framework suggested that the various persistent levels of inefficiency between the two countries was important, apart from the different levels of ICT investment between them mentioned in the previous studies (Inklaar, O Mahony and Timmer, 2003). JEL Classifications: C51, E13, O30, O33