The changes in the behaviour of the innovating firm that would not have been the case in the absence of the public support, behavioural additionality, is investigated in this thesis. The theoretical foundations of the concept along with the existing evaluation attempts worldwide are analysed. The need for evaluation in Turkey is established. The design of the T&Uuml / BiTAK-TEYDEB programme in question along with the related policy context is described to form a basis for the evaluation of the behavioural additionality. It is revealed that the need for an evaluation of behavioural additionality for the legitimacy of the programme from the data analysis. Finally, given such inputs, the thesis develops a methodological proposal for a framework to evaluate the behavioural additionality of the public support to private R&amp / D in Turkey.

This thesis aims to produce short-term forecasts for the economic activity in Turkey. As a proxy for the economic activity, industrial production index is used. Univariate autoregressive distributed lag (ADL) models, vector autoregressive (VAR) models and combination forecasts method are utilized in a pseudo out-of-sample forecasting framework to obtain one-month ahead forecasts. To evaluate the models&rsquo / forecasting performances, the relative root mean square forecast error (RRMSFE) is calculated. Overall, results indicate that combining the VAR models with four endogenous variables yields the most substantial improvement in forecasting performance, relative to benchmark autoregressive (AR) model.