Jordan Journal of Economic Sciences

The Impact of Export Volatility on Economic Growth in Algeria during 1992-2016: An Econometric Study

Mohamed Moussa Traore — 2024-07-01

Objectives: The issue of export volatility in the economies of less developed countries (LDCs) is a significant topic of debate in economic literature. This paper aims to investigate the potential effect of export volatility on economic performance in Algeria.

Methods: The study utilizes an econometric model to estimate the impact of export volatility on economic growth in Algeria for the period 1992-2016. Additionally, another regression model is used to analyze the effects of fluctuations in export prices and quantities on economic growth in Algeria.

Results: The findings show that there is no significant relationship between the export instability index and real GDP.

Conclusion: The study concludes that fluctuations in the prices and quantities of exports do not influence Algeria’s real GDP. Policymakers should reduce the dependency of the export sector on oil products and improve industrial performance in Algeria. Implementing price stabilization schemes and allocating more oil precautionary funds are also needed to mitigate any possible damaging effects of export volatility on Algeria’s economy in the future.

The Impact of Trade Openness on Gender Pay Gap

Taleb Awad Warrad — 2024-07-01

Objective: The objective of this study is to assess the impact of trade openness (among other variables) on gender pay gap in twenty selected Arab and non-Arab countries. A panel data covering the period 2010-2019 is utilized..

Method: A two panel regression models are employed. One model examines the impact of trade percentage of GDP, foreign direct investment (FDI) percentage of GDP, women's labor participation, and women's participation in parliament on the gender pay gap. The same model is applied first to all countries in the sample, and second to the sample dividing countries according to size as large and small countries.

Results: The findings indicate that, in the overall sample, trade percentage of GDP positively and significantly influences the gender pay gap percentage, while FDI percentage of GDP has a negative and significant impact. Additionally, women's participation in parliament is found to have a negative and significant effect on the gender pay gap, whereas women's labor participation shows no significant correlation. In the context of large countries, trade percentage of GDP has a positive and significant impact on the gender pay gap, and women's labor participation is negatively associated with the gap. However, FDI percentage of GDP and women's parliamentary participation are not statistically significant in these countries. For small countries, only women's participation in parliament exhibits a negative and significant relationship with the gender pay gap.

Conclusion: The study's results highlight the complex dynamics between trade openness and gender wage inequality, emphasizing the varying effects based on country size. Policymakers should consider these findings to develop targeted strategies addressing gender pay disparities within the context of trade openness

The Dynamic Interaction between Inflation and Inflation Uncertainty: Evidence from Jordan

Omar M. Al-Zoabi — 2024-07-01

Objective: This paper investigates the dynamic interaction between inflation and inflation uncertainty in Jordan using quarterly data from 1976: Q1 to 2023: Q1. This is important because achieving price stability and managing inflation expectations are crucial issues in modern monetary policy analysis. It assumes that central banks should consider the interaction between inflation and inflation expectations in designing an appropriate objective function and/or reaction function.

Method: Three types of time series models are used to investigate the dynamic interaction between inflation and inflation uncertainty: Autoregressive Moving Average (ARMA), Autoregressive Conditional Heteroskedasticity (ARCH), and Generalized Autoregressive Conditional Heteroskedasticity (GARCH).

Results: The results of the mean equation show that past inflation has a significant effect on current inflation. Conversely, the results of the variance equation indicate a high degree of uncertainty persistence in response to inflationary shocks. The Wald VAR Granger causality test provides evidence showing bidirectional causality from inflation-to-inflation uncertainty and from inflation uncertainty to inflation, supporting the "Friedman-Ball Hypothesis" and the "Cukierman-Meltzer Hypothesis".

Conclusions: The price stabilization commitment of monetary policy has not reduced the impact of current inflation on future inflation uncertainty, nor has it lessened the feedback effect from future inflation uncertainty to current inflation. This suggests that the private sector in Jordan may need more trust in the efficacy of the monetary policy's stabilization approach. Therefore, the study suggests that the Central Bank of Jordan should enhance the credibility of monetary policy and attempt to control inflation and inflation uncertainty through restrictive, proactive, and robust disinflationary measures.

Using ARIMA Model to Forecast Electricity Load in Jordan

Sameh A. Ajlouni — 2024-07-01

Objectives: This study aims to forecast the daily peak electricity load in Jordan using a dataset of hourly peak load data for the period from January 1, 2010, to December 31, 2022, compiled by the National Electric Power Company (NEPCO).

Methods: This study employs the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to make forecasts. The data exhibits an upward trend, seasonality, and non-constant variance. To address these features, the SARIMA model is used to account for the trend and seasonality, while a Box-Cox transformation is applied to manage the non-constant variance.

Results: Following the standard Box-Jenkins methodology (identification, estimation, diagnostic checking, and forecasting) and utilizing the “(auto.arima)” function in the RStudio software package, the resulting SARIMA model is ARIMA(1,0,1)(2,1,2)[7]. This model is used to forecast 7 future values of the electricity load. The Mean Absolute Percentage Error (MAPE) and the Root Mean Square Error (RMSE) values, as measures of forecast accuracy, support the precision of our forecasts.

Conclusion: Based on empirical results, electricity companies in Jordan are encouraged to use time series models for forecasting electricity loads instead of relying on simple spreadsheet models.

Capital Adequacy and Its Determinants in Jordanian Islamic and Traditional Banks

Abdalla Mohammad Al Badarin — 2024-07-01

Objectives: The study aims to analyze capital adequacy in the Jordanian Islamic and traditional banks and determine the factors affecting capital adequacy during the period 2012-2022.

Methodology: The study adopted the descriptive analytical approach. It generated cross-sectional data for 15 banks, including 3 Islamic banks, based on the banks’ published financial statements. It applied the random effects model to analyze the collected data.

Results: The study revealed a high capital adequacy ratio among Jordanian banks. It identified a negative impact of Return on Assets, Operating Efficiency, and Size, and a positive impact of Provision for Financing Losses and Economic Growth on the capital adequacy ratio. Additionally, it found no significant impact on the capital adequacy ratio from Financing to Deposits Ratio, Non-Performing Finance, and Inflation. The study also highlighted differences between Islamic and conventional banks regarding the capital adequacy ratio and its determinants.

Conclusion: To effectively manage the capital adequacy ratio, it is recommended to leverage the inverse relationship between profitability and the capital adequacy ratio to enhance bank profitability. This can be achieved by strategically reducing the capital adequacy to near the minimum required levels, increasing the volume of invested funds, and improving operational efficiency. Moreover, efforts should focus on minimizing non-performing financing, enhancing asset quality, and reducing provisions for financing losses to subsequently lower capital adequacy requirements.

The Relationship between Oil Prices and Stock Market: Evidence from Jordan

Hanna Waleed Alrabadi — 2024-07-01

Objectives: This study aims to investigate the dynamic short- and long-run relationship between oil returns and stock market returns.

Methods: Daily data from the Amman Stock Exchange (ASE) spanning the period from 2013 to 2022 is analyzed using the vector autoregression (VAR) model. The VAR model is employed to assess the short-run dynamic impact of oil returns on stock market returns. Granger causality tests are conducted to examine the causal relationship between oil returns and stock market returns. Additionally, the Johansen-Juselius integration test is utilized to investigate long-run cointegration between the two variables.

Results: The results from the vector autoregression model (VAR) reveal a statistically significant positive effect of oil returns on the returns of the general index, industry index, and financial index of the ASE. The analysis does not conclusively establish causality between oil prices and stock market returns. However, it identifies highly significant long-run cointegration between oil returns and the returns of all stock market indexes in the ASE. The robustness of these findings is confirmed across different data frequencies and macroeconomic conditions.

Conclusions: The study finds that oil prices exert a positive influence on market returns in the Amman Stock Exchange both in the short and long run. These findings hold important implications for academics and investors in Jordan, suggesting potential avenues for further research and informing investment strategies in relation to oil price fluctuations.

The Impact of the Transportation Sector on the Jordanian Economy

Saeed Mahmoud Tarawneh — 2024-07-02

Objectives: This study aimed to assess the impact of the transport sector on the Jordanian economy. The study explores the interdependence between transport sector and other sectors.

Method: two main indices were adopted by analyzing the input-output tables for 2006 and 2019. The first indicator focused on forward and backward inter-sector linkages, while the second indicator examined the sector’s impact on output, income, employment, taxes, and imports through multipliers.

Results: The results of the first indicator revealed that the transport sector played a key role in terms of forward linkages, ranking fourth in 2006 and third in 2019. However, it did not fare well with respect to backward linkages, with its ranking dropping from fifth in 2006 to ninth in 2019. These findings emphasize the significance of the sector in driving growth, enhancing competitiveness, and attracting foreign investments. Additionally, the results indicated an apparent decline in the sector’s indicators for 2019 compared to 2006. This decline may be attributed to low efficiency, as indicated by global competitiveness reports, and the government’s energy policy, which liberalized the prices of oil products and imposed additional taxes on these products.

Conclusions: In view of the study findings, it is imperative for decision-makers to prioritize creating a conducive environment that supports and develops the sector, allowing it to achieve its desired goals of growth, competitiveness, foreign investment attraction, and tourism promotion, among others. Furthermore, the study recommends encouraging investment in an industrial base that strengthens backward linkages with the transport sector, such as the spare parts industry. Moreover, there is a need to stimulate the adoption of energy-efficient electric vehicles. Finally, the study recommends that future input-output tables include four detailed transport sectors, similar to other countries.