The purpose of this study is to identify the leading price between Jeju and Wando’s oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando’s oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

This study aims to analyze the effect of public spending, macroeconomic variables, and BPK opinion on economic growth. This study is motivated by the inequality of fiscal policy effectiveness between regions in Indonesia in influencing the economic growth of different regions, the ability of local governments to attract foreign investors, and the transparency of regional financial management in designing development programs to encourage regional economic growth. The analytical tool in this study is a dynamic panel regression model with data from 2008 to 2017. The results of this study show that, in the short term, the population affects regional economic growth, while in the long term, the economic growth is affected by the number of people, the poor, General Allocation Fund, health budget, foreign investment and BPK opinion. The findings of this study are that in the long term the General Allocation Fund becomes an obstacle to economic growth, this is because the general allocation funds is widely used to cover the lack of funds for routine regional activities, thereby reducing activities for development programs. Another research finding is that fiscal policies carried out by local governments make a small and ineffective contribution to promoting economic growth.