In this study, it is aimed to examine the determinants of the industrial production index, which is necessary for sustainable growth. Even though the share of the industrial sector in the total output is around 20%, it is still significant as a precursor to the gross domestic product. The industrial production affects the economy in many ways. The increase in industrial production through both domestic consumption and exports is closely related to economic growth. The fact that industrial production is sensitive to both consumption demand and interest rates makes the industrial production index closely related to growth. The importance of the manufacturing industry sector, which has a weight of more than 80% in the industrial production index, is enormous. One of the first studies which reveal the impact of the manufacturing industry sector on economic growth is Kaldor’s 1966 study. The first rule accepted as Kaldor’s laws of growth reveals that the manufacturing industry is the main factor of economic growth. The increase in the share of the manufacturing industry sector, which has a high multiplier effect, will also increase the growth.

When the literature on the industrial production index is examined, it is seen that the factors affecting the industrial production index and the analysis methods differ from each other. In this study, the relationship between the leading indicators of the industrial production index, which is one of the most important leading indicators of economic growth, is examined with the ARDL (Autoregressive Distributed Lag) Model using monthly data between 2007 and 2020 in the Turkish Economy. In this model, electricity consumption, white goods production and manufacturing industry capacity utilization rate are used as independent variables to explain the industrial production index. 

According to the results of the study, electricity consumption and manufacturing industry capacity utilization rate are significant in explaining the industrial production index in the long run. The leading variable which is most effective in explaining the industrial production index is the electricity consumption. According to the results, 1% increase in electricity consumption increases the industrial production index by 1.2%. In addition, 1-unit change in the capacity utilization rate increases the industrial production index by 0.5%. On the other hand, in the short run, it is concluded that 1% increase in electricity consumption will increase the industrial production index by 0.6%. Also, 1% increase in white goods production will increase the industrial production index by 0.3% and 1- unit change in the capacity utilization rate increases the industrial production index by 0.6%. Since the error correction coefficient is significant and negative in the short-term model indicates that the system will return to equilibrium if there is a deviation from the long-term equilibrium. Accordingly, the error correction coefficient being -0.28 indicates that if there is a deviation from the long-term balance in the industrial production index due to a shortterm shock, the system will stabilize in approximately 3.5 months. In other words, it shows that 28.2% of the deviation that will occur in the long-term balance due to a shock in the short-term might be eliminated at the end of the 1-month period. Effect of white goods production, which had an impact on the industrial production index in the short term, disappeared in the long term. Furthermore, the effect of capacity utilization rate is very limited in both the long and short run.

In future studies, the relationship of industrial production index with leading indicators such as exports, imports of intermediate goods and capital goods, manufacturing industry purchasing managers index (manufacturing PMI), automobile production can be analyzed.