Tag Archives: Variance Decomposition

The Analysis of Factors Affecting CPO Export Price of Indonesia (Published)

This study aims to determine and analyze the influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and the exchange rate of rupiah/US dollar towards the transmission on CPO export prices of Indonesia. This study uses quantitative analysis model with the approach of vector autogression model (VAR) which includes three main analysis tools namely Granger causality test, impulse response function (IRF) and forecast error decomposition of variance (FEDV). The variables which are used in this research are world petroleum price, world soybean oil price, CPO price of Rotterdam, CPO export price of Indonesia, fresh fruit bunch price and real exchange rate (real exchange rate). From Granger Causality test result, The price transmission process takes place the plot as follows: world crude oil prices significantly influence the CPO price of world (Rotterdam) which will significantly influence the world soybean oil prices and so on have a significant influence on the value of the real exchange rate which will influence the price of fresh fruit bunches and ultimately have a significant influence on CPO price export of Indonesia. From the estimation result of VAR model, there are significant influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and rupiah/US dollar exchange rates simultaneously to the transmission on CPO export prices of Indonesia. Based on analysis of Impulse response and variance decomposition, in the first period, one hundred percent average variability of CPO export price growth is significantly explained by the average growth of CPO export prices itself. In the subsequent period, the average variability of CPO export price growth is significantly explained by the average growth of CPO export price itself as well as other variables.

Keywords: : Petroleum Price, CPO export price, Granger Causality, Price Transmission, Real Exchange Rate, Soybean Oil Price, TBS, VAR, Variance Decomposition, impulse response function

Unemployment Rate, Gender Inequality and Economic Growth in Nigeria “A Short-Run Impact Analysis” (Published)

This paper examines the short-run impact of gender inequality (proxy by primary and secondary school enrollment) and economic growth (real gross domestic product) on unemployment rate in Nigeria, and also the study determines how much of the forecast error variance of unemployment can be explained by exogenous shocks from variables (gender inequality, economic growth, and population growth rate). Thus, the study using Engel Granger Error Correction Model and Dynamic Stochastic Variance Decomposition Model on a time series data collected from Central Bank of Nigeria Statistical Bulletin. The error correction results in both model 1 and model 2 are robust and consistent with their signs; the impact of gender inequality is positive in both short run models, but significant only in model 1 before the control variables were introduced. Again, the variance decomposition result indicates that gender Inequality emits the highest impulse on the rate of unemployment at 34.735% on average of the ten periods. While economic growth has a negative impact on the rate of unemployment for the two models and exerted only 8.438% impulse on average. The variance decomposition results also showed that unemployment rate transmitted on average of 78.453% impulse on itself for the 10periods under review. Exchange rate, inflation rate, and gross capital formation emitted 28.68%, 10.78%, and 6.81% respectively on average on unemployment rate. Finally, population growth rate transmitted 5.59% impulse on unemployment. There is a long run relationship between the variables and the speed of adjustment towards equilibrium is 52%.  Thus, we conclude that gender inequality is a strong factor of unemployment and policy makers and government should embark on developing laws that will reduce/eradicate gender disparity in Nigeria.

Keywords: Error Correction Model, Gender Inequality, Unemployment, Variance Decomposition, economic growth