Impact of the Investments in Information and Communication Technologies on Total Factor Productivity in the Context of the Economies in Transition

The goal of this research is to establish a link between investments in information and communication technology (ICT) and economic growth in the context of countries that are currently classified by the international community as transitional economies (TE). More specifically, in this study we focus on the relationship between ICT and one of the determinants of economic growth, total factor productivity (TFP). Neoclassical growth accounting and the theory of complementarity provide the theoretical framework on which we build this research. By combining the data obtained from two sources, the World Bank Database and the IT Yearbook, we were able to construct a 10-year data set for 18 TEs spanning the period from 1993 to 2002.Our inquiry is structured as a seven-step process that utilizes six data analytic methods. The first step in our investigation involves Cluster analysis (CA) with the purpose of determining whether or not the selected set of TEs is homogenous. Use of CA allowed us to identify two distinct groups of TEs in our sample, which suggests the heterogeneity of the sample.In the second part of our inquiry, we employ Decision Tree (DT) analysis with the goal of investigating the differences between the clusters of TEs that were generated by the CA in the previous step. We were able to determine that one of the groups of TEs, the leaders, appears to be wealthier than the other group, the majority. In the next step of our investigation, we perform Data Envelopment Analysis (DEA) to determine the efficiency of the TEs in our set. We were able to determine that the leaders are more efficient than the majority not only in terms of the production of the output, but also in terms of the utilization of the inputs.The fourth part of our investigation takes advantage of the DT analysis with the purpose of obtaining the insights into the nature of the differences between the efficient and inefficient TEs. By incorporating the results of the CA into DT analysis we were able to construct the model that suggests, with the high degree of precision, some of the criteria according to which the efficient TEs differ from the inefficient ones.The fifth stage of our investigation involves the use of the Translog regression model for the purpose of determining whether or not there exists a set of investments that are complementary to the investments in ICT. We have determined that there exists a statistically significant interaction effect between the investments in ICT and other variables, representing state of labor, as well as capital investments.The sixth part of our investigation relies on using Structural Equation Modeling (SEM) implemented with Partial Least Squares(PLS)to test for the presence of the relationship between the investments in ICT and the unexplained part of the macroeconomic growth, TFP. We were able to establish the presence of the relationship between the two constructs of our conceptual model, ICT Capitalization and TFP for the leaders group of our sample. The construct ICT Capitalization was represented by the three ratio measures, all of which contain variable Annual investment in telecom in the denominator, while the Malmquist Index and its components, TC and EC., represented the construct TFP. Thus, it allows us to state that we have established the presence of the relationship between the investments in ICT and TFP.The last step of the data analysis involves using Classification DT and Neural Network (NN) analyses with the aim of investigating the reasons why some of the TEs exhibit statistically significant relationship between the investments in ICT and TFP, while other TEs do not. We were able to determine that one of the reasons why the leaders exhibit the statistically significant relationship between the investments in ICT and TFP is that they have higher level of inputs and more efficient processes of converting the inputs into the outputs than the majority