Pengaruh Instabilitas Makroekonomi Terhadap Non-Performing Financing Perbankan Syariah di Indonesia

This study aims to identify the determinants of non-performing financing (NPF) in Islamic banks in Indonesia. The study objects are the Islamic banking industry during the first quarter of 2008 until the third quarter of 2019. The variables in this study are inflation, growth of Gross Domestic Product (PDB), and Bank Indonesia rate. The statistic method used is the Vector Error Correction Model (VECM). The result shows that inflation shock significantly affects the trend of NPF, while others do not give significant effect to NPF of Islamic Banking.

Impact of noncommunicable diseases on direct medical costs and worker productivity, Saudi Arabia

Background: The prevalence of noncommunicable diseases (NCDs) has been increasing in Saudi Arabia. Aim: Our objective was to estimate the effect of NCDs on direct medical costs and workforce productivity in Saudi Arabia. Methods: To estimate direct medical costs, we estimated the unit cost of treating 10 NCDs, then multiplied the unit cost by disease prevalence and summed across diseases. To estimate workforce productivity losses, we multiplied gross domestic product per person in the labour force by the loss in productivity from each NCD and the prevalence in the labour force of each NCD. Results: We estimated annual direct medical costs of 11.8 billion international dollars (Int$) for the 10 NCDs assessed (13.6% of total annual health expenditure). We estimated workforce productivity losses of Int$ 75.7 billion (4.5% of gross domestic product). Conclusion: The economic burden of NCDs in Saudi Arabia – particularly the effect on worker productivity – is substantial.

On Exports and Economic Growth: Revisiting Export-Led Growth Hypothesis Including North-South Divide

Objective: The purpose of the present study is to revisit the export-led growth hypothesis in the wake of globalization. This will help in trade policy decisions and make it possible to standpoint whether the export promotion is a good idea to accelerate economic growth. Design: The ELG hypothesis is examined for 107 countries through panel data analysis using cointegration and panel regression tests from 1990 to 2018. The study finds strong support for the long-run relationship between exports and gross domestic product and the export-led growth hypothesis in a two-variable regression framework. Findings: It is evident from the long-run coefficient of dynamic ordinary least squared that a 1.0 percent increase in real exports increases the real gross domestic product by 0.53 percent. The long-run coefficient of real exports for the Global South (0.55) is found higher than that of the Global North (0.51), which indicates that in the wave of globalization, the evidence of export-led growth hypothesis is stronger for comparatively poor Global South than the richer Global North. Practical Implications: The results indicate implications for export promotion policy in the Global South countries to accelerate economic growth and increase real gross domestic product. Originality: The study is the first to explore the ELG hypothesis using a big pool of 107 countries, including the global north-south divide.

Determining the Impact of Economic Factors to the Gross Domestic Product in Bangladesh

Gross Domestic Product (GDP) is believed to be an indicator of a country’s economic condition. Bangladesh’s GDP increased at a pace of 8.15% in fiscal 2018-19 as per the base year 2005-06. By the year 2019, Bangladesh has become the seventh fastest-growing economy in the world. This paper used multiple regression analysis model for the macroeconomic factors. The aim of this study is to measure the effects of macroeconomic factors considering GDP as the dependent variables and inflation rate, import, and export are considered as independent. This paper represents that import and export are positively associated factors with GDP whereas inflation rate is a negatively associated factor. This study concluded with revealing the importance of conducting further study by considering more economic variables to measure the economic growth as a whole.

Back-Propagation Neural Network and ARIMA Algorithm for GDP Trend Analysis

GDP (gross domestic product) is a key indicator for assessing a country’s or region’s macroeconomic situation, as well as a foundation for the government to develop economic development strategies and macroeconomic policies. Currently, the majority of methods for forecasting GDP are linear methods, which only take into account the linear factors that affect GDP. GDP (gross domestic product) is widely regarded as the most accurate indicator of a country’s economic health. GDP not only reflects a country’s economic development over time but can also reflect its national strength and wealth. As a result, the GDP trend forecast partially reflects China’s transformation and future development. The time series ARIMA (Autoregressive Integrated Moving Average) model and the BPNN (BP neural network) model are combined in this article to create the ARIMA-BPNN fusion prediction model. The predicted values of the two models were then weighted averaged to obtain the predicted values of the linear part of the improved fusion model. To get the predicted values of the improved fusion model, we weighted average the residual parts of the two models, predict the nonlinear residual with BPNN, and add the predicted values of the two parts. It is applied to the actual GDP forecast in H province from 2019 to 2022, and the actual forecast verifies the effectiveness of the fusion forecast model in the actual forecast.

The effect of asset quality, profit and loss sharing on Sharia Banking Liquidity in Indonesia

This study aims to determine the effect of asset quality variables (Non-Performing Financing), Profit and Loss Sharing (profit-loss sharing investment and profit-sharing investment account), capital adequacy ratio, bank size, return on assets, and gross domestic product on Islamic banking liquidity in Indonesia. The analysis was conducted using a sample of 7 Islamic commercial banks from the period March 2015 to December 2019. This study uses 2 multiple regression models of panel data with the results showing that Non-Performing Financing, profit-loss sharing investment, bank size, gross domestic product affect the liquidity of Islamic banks. , then for-profit sharing investment account, capital adequacy ratio, return on assets, does not affect the liquidity of Islamic banks.

Time Series Analysis of Global Energy Indices: Logarithmic and Normalized Techniques for Developmental Studies

Diverse opinions exist in the time series analysis of energy and related indices, difference in methodology, sample size, and time variation. This paper will make a conscious effort to converge the divergent outlooks. To accomplish this essential task, five energy indices consisting of energy consumption (EC), gross domestic product (GDP), carbon dioxide emission (CDE), the human development index (HDI), and oil price (OP) were selected. Two analytical methods were adopted, namely logarithmic and normalized techniques, which are designed to complement each other in drawing unfalsified statistical inference concerning the causality between the energy indices. The methods were subjected to four statistical tests and analyses: the augmented Dickey-Fuller, cointegration, pairwise Granger causality, and vector error correction model (VECM). Irrespective of prevailing challenges, both logarithmic and normalized techniques unanimously filtered out causalities. This consisted of neural flow between oil price and energy consumption, gross domestic product and carbon dioxide emission, and energy consumption and the human development index, unidirectional flow between energy consumption and the human development index, oil price and energy consumption, gross domestic product and carbon dioxide emission, and the human development index and oil price, whereas a normalized technique established bidirectional flow between gross domestic product and the human development index, and the human development index and oil price. Pertinently, the research suggests appropriate policies that will generate sustainable development in all the causal directions. Assiduously, the overwhelming agreement between both techniques at the 0.05 level is recommended for further validation with more modern econometric tests.

Socio-biomedical predictors of child nutrition in India: an ecological analysis from a nationally representative Demographic and Health Survey, 2015–2016

Background Despite significant economic growth and development, undernutrition among children remains a major public health challenge for low- and middle-income countries in the twenty-first century. In Millennium Development Goals, India committed halving the prevalence of underweight children by 2015. This study aimed to explain the geographical variation in child malnutrition level and understand the socio-biomedical predictors of child nutrition in India. Methods We used the data from India’s National Family Health Survey 2015–2016. The survey provided estimates of stunting, wasting, and underweight at the national, state, and district level to measure nutritional status of under-five children. Level of stunting, wasting and underweight at the district level are considered as outcome variables. We have used variance inflation factor to check the multicollinearity between potential predictors of nutrition. In this study, we performed spatial analysis using ArcGIS and multiple linear regression analysis using Stata version 15. Results Five states (Uttar Pradesh, Bihar, Madhya Pradesh, Jharkhand and Meghalaya) had very high prevalence of stunting (40% and above). High prevalence of wasting was documented in Jharkhand, Madhya Pradesh, Chhattisgarh, and Karnataka (23 to 29%). Jharkhand, Madhya Pradesh, Maharashtra, and Chhattisgarh had the highest proportion of underweight children in the country. We found that electricity and clean fuel use in the household, use of iodized salt, and level of exclusive breastfeeding had significantly negative influence on the stunting level in the districts. The use of iodized salt has similar effect on the wasting status of under-five children in the districts (b: − 0.27, p < 0.10). Further, underweight level had a negative association with clean fuel use for cooking (b: − 0.17, p < 0.01), use of iodized salt (b: − 0.36, p < 0.10), breastfeeding within one hour (b: − 0.18, p < 0.10), semisolid/solid food within 6–8 months (b: − 0.11, p < 0.05) and Gross Domestic Product of the districts (b: − 0.53, p < 0.10). Conclusion In the study, a variety of factors including electricity and clean fuel use in the household, use of iodized salt, level of exclusive breastfeeding, breastfeeding within one hour, semisolid/solid food within 6–8 months and Gross Domestic Product of the districts have a significant association with nutritional status of children.

An Exploratory Study on Personal Finance in the Context of COVID-19

The world is currently experiencing a dramatic crisis that has not yet reached bottom. In Mexico, in the second quarter of 2020, there was a drop in the gross domestic product of 18.9% compared to the same quarter of 2019. In this context, the objective is to identify types of personal expenses in households located in Culiacán, Sinaloa, Mexico as of July 15, 2020. The main results were that most of the respondents' budgets spend according to their income, have had no problem paying their bank loans on time, would consider a fund for future contingencies, have not purchased health insurance, have not bought a computer or cell phone, among other issues analyzed. The main findings are oriented to the fact that the studied population has not acquired additional medical insurance despite the pandemic. It is also concluded that the population under study has become aware of having savings for contingency funds and that digital life still shows resistance in making personal financial decisions.