The present study empirically investigates the long-run nonlinear relationship between the shadow economy and financial development targeting developing small open countries, such as Jordan. The study applied the cointegration test as an estimation technique in order to achieve its aim. The data used were mainly taken from Jordanian economy during the period (1990-2019). According to the test of Johanson cointegration, the empirical results of this study showed evidence of a long run inverted U-shaped relationship between the shadow economy and financial development. The results also showed that there is a long run positive relationship between inflation and the shadow economy. Consequently, these results lead to a profound implication when adopting policies to reduce the size of the shadow economy.

The purpose of this study is to identify the key macroeconomic variables that affected stock price fluctuations in Amman Stock Exchange during the period 1980-2018. Using Augmented Dickey-fuller (ADF) test, it was found that the variables did not have the same degree of integration. According to Breusch-Pagan-Godfrey test, the residuals violated the constant variance assumption under Ordinary Least Square (OLS) model. Therefore, the study employed Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methodology to analyze the model after taking the first difference of natural logarithm for all variables to be stationary at the same level and to show the fluctuation in the variables. It was found that fluctuations in portfolio investment and in industrial production index are statically significant to lead fluctuations in the stock price index in Amman Stock Exchange and they follow the same direction, whereas fluctuations in real effective exchange rate, real interest rate, and Brent crude oil prices were statically significant to lead fluctuations in the stock price index but in the opposite direction.

This study investigates the determinants of private investment in Jordan for the period 1976-2012. The ARDL (Autoregressive Distributed Lag) approach to cointegration is employed to test the existence of a long run relationship, as well as to study the short run dynamics of private investment in Jordan. To that end, demand for private investment is estimated as a function of real Gross Domestic Product (real GDP), real interest rate, and real public investment. The original problem focuses on the assessment of factors that have either stimulated or dampened private sector investment in Jordan during the study period. The results of this study confirm some results found elsewhere in the empirical literature. Econometric evidence indicates that private investment is positively related to real GDP growth, and negatively related to real interest rates, and real public investment. The study concluded that improving the productive sectors in the national economy may enhance private investment in the long run, and the government capital expenditures have insignificant role in boosting private sector investment initiatives, implying that public investment projects should be reviewed, reassessed, and prioritized so that crowd in private investment.

The purpose of this paper is to examine whether shocks to the consumption of petroleum products in Jordan have permanent or temporary effects. This has been accomplished by applying Lee and Strazicich (2003) test of unit root with structural breaks to investigate the stationarity properties related to the time series of petroleum products consumption over the period 1961 to 2019. Empirical findings lend evidence that the consumption of petroleum products is a unit root process, implying that shocks to petroleum products consumption has permanent impact, and this consumption does not turn back to its time trend path following a shock. This indicates that there are high possibilities of energy demand management and conservation policies targeted towards achieving the intended goals in the long-run. In fact, this is compatible with the government energy strategies aimed at reducing the consumption of fossil oils. Doi: 10.28991/esj-2021-01279 Full Text: PDF

The purpose of this paper is to forecast monthly gasoline prices in Jordan by applying Gaussian process regression on monthly prices of two types of gasoline (octane-90 and octane-95) during the period January 2008-December 2019. Accurately predicting gasoline prices have several fiscal policy implications concerning fuel subsidies and taxes. Also, they affect the consumption and the production of decisions. Moreover, they are crucial for designing and analyzing environmental policies. The Gaussian process model was able to treat a geometric Brownian motion with a deterministic unknown drift function. The performance of prediction was measured using the Root Mean Square Error (RMSE) and the Mean Average Percentage Error (MAPE). Where the numerical results show that the model predictions of gasoline prices were accurate.