The effect of national income on technology and innovation indicators: Panel data analysis method

Within todays prevailing system in the world, mutual goal of all the countries is to maintain an economic growth by reaching their economic growth objectives and achieve an increase in the level of welfare. Economic growth, shows the increase in outputs in regard to increase in production factors in the produced materials and services, possible advancement in their technologies, an increase in labor productivity or an increase in the capacity usage ratio. The most important indicator of economic growth is acknowledged as the changes in gross domestic products. In order to measure the efects of technology and innovation on national dividend, research and developement spendings, global innovation index, information and communication exports of the country, information and communication imports of the country, manufacturing products exports, manufacturing products imports, university degree employed worker ratio and number of employed researchers in research and developement activities were used as variables. The efect and ratio of these variables on gross domestic products of the countries were taken into consideration. World Bank database, UNESCO and Global Innovation reports were used in collecting these data. 48 countries with various econmic situations among developing and developed countries were selected and the data from those countries were examined between years 2007 and 2016. It was noted during the data collecting process that the data from some of these countries were deficient. Missing data were added by verifying from the local resources in some of the countries. For the rest of the missing data, interpolation, regression estimate and regression assignment methods were used among the data completion methods. Before the panel data anlysis was performed, it was studied if the variables have unit roots. In order to state if the variables are static or not, Levin, Lin and Chu unit root test and Fisher unit root test were performed. Fixed effect panel data analysis model was applied. After the unit root tests were performed, cointegration tests were performed for the variables which were identified as not static. Pedroni panel cointegration test and Kao panel cointegration tests were performed to inquiry the existence of the cointegration. Existence of the cointegration was confirmed with the Pedroni panel cointegration test results. In order to examine the long term stationarity of the non-stationary variables, vector error correction model as one of the dynamic modelling methods and granger tests were used. The result about the effect of the technology and innovation indicators on economic growth was confirmed to be positive as expected. There are also other studies which measured the effects of these indicators seperately and they also support this research. The positive aspects of the research are that it constructs the world profile of 48 countries, analyses the short term changes and compares and evaluates the results with both static and dynamic panel analysis. Both methods have supported each other in their mutual variables. It has been a contribution that the effect on the economic growth was examined with multiple variables. The positive effect of the technology on growth was confirmed as the internal growth models suggest.