Iranian Economic Review
Volume:27 Issue: 73, Autumn 2023

Using the time-varying copula, we investigate the dynamic dependence between developed and BRICS stock market indices, digital assets, oil, and gold prices for January 2, 2016 to March 31, 2020. Our findings reveal that cryptocurrencies are considered hedge and diversifier assets before the 2020 global pandemic. Dash, Bitcoin, Monero, and Ripple may serve as good protectors against extreme stock markets’ co-movements during the COVID-19 outbreak in many countries. Risks among oil markets cannot be hedged by the kind of cryptocurrencies. In addition, the dynamic dependence between cryptocurrencies and Gold follows the same trend except for a couple of Gold-Dash. These results have important implications for investors and market participants to track the progress of the different safe-haven instruments. Thus, portfolio managers may take into account the few eligible cryptocurrencies for inclusion in their portfolios. Speculators in stock and cryptocurrency markets may use a spread technique to boost their portfolio return.

The contribution of this research is analyzing the effect of the quality of primary and secondary school service delivery on child labor practices, taking Indonesia as a case study. It is a non-trivial issue for a country like Indonesia, which achieved significant economic progress, but still faced the topic of child labor. The research used data of approximately 55,000 children sampled in the 2018 Indonesian Labor Force Survey (Sakernas), and primary and secondary school accreditation data of Indonesia. Regarding a probit regression model, this paper found that better quality of school service delivery reduces the chance of child labor. Robust to alternate specifications, the findings of this study confirm the hypothesis that quality of school service delivery influences the decision of Indonesian households to send their children to work. It is also found that the education level of the household head decreases the chance of child labor. The implication of this result is, improvement in the quality of school service delivery can serve as an important tool to eliminate child labor. For policy, the government should direct more technical support, and resources to increase the quality of school service delivery, especially in rural and disadvantaged areas. In addition to fulfilling  the UN Sustainable Development Goals (SDGs) target 8.7 on eliminating child labor, this policy is aligned with achieving SDGs target number 10; reducing inequality within a country.

Understanding the risks associated with faith-based equity investments assumes greater significance in the wake of the COVID-19 pandemic, which has once again exposed the susceptibility of the financial space to shocks. We use the nonlinear Markov regime-switching model to capture the time-varying beta and idiosyncratic volatility of the US Islamic, US Catholic and Switzerland Islamic equity portfolios provided by Morgan Stanley Capital International (MSCI) using daily index returns data during July 2017 to July 2021. Further complementing the country-level evidence, we refer to the global ACWI Islamic index and World Catholic Values Custom Index. The evidence suggests that the US and Switzerland Islamic portfolio have lower systematic risks during the calm and crisis period. Further, the global Islamic portfolio has lower systematic risks during the calm and crisis period, which signifies the robustness of the evidence. The US and global Catholic portfolio does not exhibit the same risk characteristics.

This study employed the Casella (1996) model and its extension Badinger and Breuss (2006) to examine the relationship between the size of a country and the effects of trade bloc enlargement on the extensive margin of trade. Therefore, export of large and small European countries to African, Caribbean, and Pacific (ACP) countries on the extensive margin were investigated to validate the effect of introducing an economic partnership agreement from 2004 to 2014. The empirical results from the fixed and random effect panel regression on HS 6 digit disaggregated data provided the evidence on the minor benefits of the small country over a large country. Hence, the interpretation of the results was in line with Casella’s (1996) hypothesis, which emphasized the importance of reducing domestic market differences between large and small countries by improving their market access. Our findings imply that the market access initiative will eventually play a vital role in helping the small countries. This in turn encourages firms in small countries to increase the quantity and diversity of the goods they produce. These findings urge the policymakers to pay more attention to the size of the country in improving the formulation of trade agreements in line with their benefits for different groups of countries.

The use of renewable energy has increasingly become a great concern for many countries due to environmental issues. One of the widely used sources of renewable energy nowadays is solar energy. The conversion of solar energy into electrical occurs through three main types of technology, namely photovoltaic (PV), solar thermal, and concentrating solar power (CSP). PV is the fastest-growing and widely used technology. In   Indonesia, the utilization of PV technology continues to rise especially in the use of rooftop PV. Indonesia currently imports PV components such as solar cells from abroad. Most of the PV cells are imported from high-income countries. This study analyzes the effect of differences in Gross Domestic Product (GDP) per capita between Indonesia and trading partner countries. It also analyzes the effect of the real exchange rate on imports of photovoltaic cells from 13 countries in 2004-2019. Meanwhile, analysis of the impulse response and panel variance decomposition obtained from the Panel Vector Error Correction Model (PVECM) was used to ascertain the import response to the independent shock variable. Therefore, it was concluded that the differences in GDP per capita of Indonesia together with trading partner countries significantly affect the importation of photovoltaic components in the long run. In contrast, Rupiah's real exchange rate against partner countries' currency has a significant effect on imports of photovoltaic cells in the short and long term.

This study provides a selection of the house price prediction model for the Tehran city based on the area between the Lorenz curve (LC) and the concentration curve (CC) of the forecast price using 206,556 observed transaction data from March 21, 2018, to February 19, 2021. Several different methods such as generalized linear models (GLM) and recursive partitioning and regression trees (RPART), random forests (RF) regression models, and neural network (NN) models for predicting housing prices. We used 90% of all randomly selected data samples to estimate the parameters of pricing models and 10% of the remaining data sets to test the accuracy of the prediction. The results showed that the area between the LC and CC curves (known as the ABC criterion) of reals and forecast prices in the test data sample of the random forest regression model was less than that of other models examined. The comparison of the calculated ABC criteria leads us to conclude that the nonlinear regression, like the RF regression model, provides an accurate prediction of housing prices in Tehran City.

Unemployment is one of the most challenging problems faced by governments, particularly in developing countries. Due to the rapid increase in the population of Pakistan and less number of job opportunities the government needs to properly forecast the unemployment rate to make future policies. This paper aims to model statistical relationships between the unemployment rate and the inflation rate for the determination of any feasible trend of unemployment in the country. About twenty different interrelationships between unemployment and inflation have been investigated by using the curve fitting approach and their goodness of fit was analyzed. The unemployment trend of Pakistan depending only on inflation does not appear homogeneous; as there is an unexpected increase or decrease. The scattered nature of the data shows that there is a negative correlation between the unemployment rate and the inflation rate of Pakistan. However, the Fourier model with three terms, the Gaussian model with two terms, and the sum of the sine model with four terms appear to fit the data moderately.

The purpose of this study is to examine the impact of financial attitude (FA), parental financial socialization (PFS), financial literacy (FL), and financial education (FE) to ensure the success of prudent financial management practices (PFMP) among Malaysian Muslim youth. The research was designed to use the quantitative approach. Data were collected using self-administered questionnaires adopted from previous studies, which were disseminated among university students and were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to address the research hypotheses. The findings indicate that FA, PFS, FL, and FE have substantial and positive relations with PFMP. The results highlighted the importance of all constructs in determining Muslim youth's capability to prudently manage their financial affairs. As a result, the findings may help us understand how Malaysian Muslim youth need to improve their financial practices.

Countercyclical economic policy has recently been highly demanded to mitigate the risk of the COVID-19 pandemic, such as the credit restructuring in the banking sector. The policy is necessary, considering that the banking credit risk continues to rise due to increasing loan repayment default of debtors affected by the pandemic. The increasing credit risk in the banking sector could elevate the economic condition to a high level of systemic risk. Therefore, this study aims to analyze the impact of the credit restructuring policy from the Indonesian government on the systemic risk from the banks’ exposure. We use the Marginal Expected Shortfall (MES) estimation to measure banking systemic risk along with the amount of credit restructuring, loan, asset, and other influential variables. The results revealed that only banks with big assets benefit from the credit-restructuring program because their risk values decrease coincide with the rise of their credit-restructuring amount. However, the benefit is invisible from the banks with small and medium amounts of assets. However, the overall credit restructuring policy succeeded in reducing banking systemic risk during the COVID-19 pandemic. The policy permits the debtors to postpone their maturing credits so that the banking NPL level is still within a reasonable limit. The government response to the COVID-19 pandemic varies from one country to another, while the credit restructuring policy from the Indonesian government is highly rated for the research investigation. The policy should be a global concept for banking risk mitigation during this unprecedented pandemic.

This study examined the impacts of socioeconomic status and savings on income inequality, to verify the transitional changes in socioeconomic status and saving rate, which in turn may affect the level of income inequality in Nigeria. The study employed the Behavioral Mechanism Approach (BMA), incorporating the Structural Vector autoregressive (SVAR) technique, which uses impulse response function and variance error decomposition to trace the behaviors of the chosen variables over time. The empirical results show that peoples’ socioeconomic status negatively affected average income in the economy through their flair for conspicuous consumption. It also shows that socioeconomic status increases income inequality through a reduction in returns to capital and through changes in the levels of savings in the economy. The study recommends that the government may need to invest in behavioral changing policies such as education and enlightenment that can change conspicuous consumption. These can enhance income accumulation and alleviate inequality in the economy.

This paper examines whether there is a J-curve phenomenon and an asymmetric effect of the exchange rate on the Indonesia-China bilateral industry trade balance. An asymmetric response occurs when the exchange rate affects trade balance differently during periods of currency depreciation or appreciation. An Autoregressive Distributed-Lag (ARDL) and Nonlinear Autoregressive Distributed-Lag (NARDL) models were applied using data from 50 Indonesian export industries between 1Q 1993 and 4Q 2019. We found that in the short run, there are 14 industries impacted by the real exchange rate changes (under the ARDL model), while the NARDL comes with more cases (22 industries). In the long run, the ARDL model reveals 13 industries with a significant impact on exchange rate changes. With a NARDL model, in the case of exchange rate depreciation, there are 15 industries, which experience significant influence on their trade balance, while in the case of exchange rate appreciation, the effect was found in 17 industries. From the perspective of J-Curve, the ARDL model came out with two industries, while with the NARDL model, a J-Curve effect occurs in nine industries. We also found empirical evidence for short-run asymmetric effects in 15 industries. The policy implication of this finding is the importance of maintaining exchange rate stability through monetary policy to reduce the adverse effect of sharp changes in exchange rates on the trade balance.

Studying travel behavior is one of the fundamental necessities for the managers involved in strategic and marketing plans. Due to the scarcity of research on the Iranian tourism market, addressing the current status of the households’ tourism expenditure and its determinants might contribute to increasing this expenditure. The present study thus explores the determinants of the Iranian households' total expenditure and expenditure per person/night on domestic trips, using a systematic approach at the microeconomic level. These determinants consist of economic, demographic, psychological, and trip-related factors that affect different sectors of the trip expenditure, including accommodation, transportation, food and beverages, shopping, recreation, and visiting tourist attractions. Using an electronic questionnaire, the information about the last trip before the outbreak of COVID-19 was collected from 629 Iranian households and analyzed by linear regression methods. The results demonstrated the effect of indicators such as income, age, education, type of occupation, the householder’s conservativeness, the number of dependent and independent children, the household size traveling, duration of stay, the importance of recreational trips in the consumer basket of the family, use of personal vehicles, and stay in the relatives’ houses, on total family expenditure and expenditure per person/night on the trip.

This work analyzes the networks of personal, institutional, associative, and professional relationships in which the entrepreneur is involved and the resources that are integrated into them, and it proposes that social capital resources are determinants of the performance of his business. The effect of social capital resources is moderated by the experience of the entrepreneur. A questionnaire survey and a quota sample of 310 small and medium-sized enterprises in Tunisia were used to test the proposed hypotheses during the period from May to December 2019. The results show that economic performance is positively influenced by the resources of the institutional and professional network than through other resources. However, in the sector, the experience of the entrepreneur reinforces the impact of institutional and professional resources.

Technology transfer in the oil industry in developing countries faces many obstacles due to cultural, economic, and political barriers. Therefore, besides preparing the existing infrastructure, the technology transfer process should be undertaken with a managerial focus. On the other hand, as far as the more effective transfer of imported technology is concerned, Iran's oil industry faces political constraints related to economic sanctions in addition to cultural and economic constraints. In this study, an attempt was made to identify critical variables affecting technology transfer in the Iranian oil industry by the qualitative method using the content analysis technique. The relevant literature review is in the form of a library study. The technology transfer approach in the Iranian oil industry has been based on classifying and presenting the structure based on previous research. An interview with a group of oil industry experts, sampled by the judgmental and snowball techniques, was conducted to review and answer the research question. Finally, the final qualitative model of the research was designed based on causal factors, intervening context, leader, and outcome.

This paper examines the main institutional determinants of central bank credibility (CBC) from 1990 to 2014. As the CBC is highly concentrated in the right tail of the distribution, the mean-based approaches are an incomplete description of CBC reaction when the parameters are not uniform over the conditional distribution of the credibility. In departing from the problem, I use a Quantile Regression approach, providing superior information on the institutional determinants nexus across various parts of the credibility distribution. Covering 25 inflation targeting economies, I find institutional determinants are prominent and significant at the lower quantiles. This evidence could be attributed to the less sensitivity of the private sector’s expectations to the institutional characteristics. Central bankers, aiming to stabilize the economy, credibility growth, or target inflation, could reduce public expectations by taking into account the non-linear impact of institutional factors on their credibility.