Turkey has 19.3 billion tons of lignite reserves and the vast majority of these Neogene lignite deposits are preferred for use in thermal power plants due to their low calorific value. The calorific value of lignite used in thermal power plants for electricity generation must be kept under constant control. In the control of calorific value, the estimation of the lower and higher heating values (LHV and HHV) of lignite is of great importance. In the literature, there are many studies that establish a relationship between the heating values of coal and proximate and ultimate analysis variables. In the studies dealing with proximate analysis data, it is observed that although the coefficients of the obtained multiple linear regression models (MRM) are statistically insignificant, these models are used to predict heating values because of the meaningful correlation coefficient. In this study, it is investigated whether moderator variables are effective on LHV estimation with proximate analysis data collected from forty-one lignite basins in different regions of Turkey, and a moderator variable analysis (MVA) model is developed to be used for the prediction of LHV. As a result of the study, it is found that the proposed MVA model is in accordance with observation values (coefficient of determination R ² = 0.951), and absolute and standard errors are also small. Therefore, it is concluded that the use of MVA to estimate the LHV of Turkey’s lignite is found to be more statistically meaningful.

The mining sector played an important role in the economic growth of the developed countries with rich natural resources in the past, and in recent years, it is important for the economic growth of developing countries. Also, it is generally supported by the incentives due to the fact that mining sector causes other related sectors to grow. Incentives have been the most important economic policy instrument imposed by governments to boost economic growth in developed and developing countries. Incentives or supports given by Turkish state in order to increase the mining investments can be analyzed under two categories; incentives or supports based on the Turkish Mining Law, incentives or supports provided under the Investment Incentive Program. The effect of investment incentives applied to the mining sector in Turkey between the years of 2001 and 2017 on mining production index (MPI) and also the indirect effect of these on gross domestic product (GDP) are investigated by using Granger Causality Test and regression analysis. In this study, the data belonging to the number of investment incentive certificates received by firms operating in Mining Sector and the amount of total fixed investment were used. According to the findings obtained from this study, it has been determined that encouraging the fixed investments of the firms operating in the Mining Sector with incentives has a significant and positive impact on MPI and GDP in a short period of 1 year. H owever, the incentives applied to the mining sector did not increase the production index of the mine in parallel with the increase in the GDP.