• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.11
• /
• pp.325-332
• /
• 2021

Foreign capital inflows play an essential role in each country's socio-economic growth, particularly for undeveloped and developing countries where capital accumulation is limited in the early stages of development, and Vietnam is no exception. The purpose of this article is to examine the impact of foreign capital inflows on economic growth in Vietnam. The empirical method employed secondary time-series data set during the period 1995-2018 to determine the impact of FDI, foreign aid, foreign loans, and exports on economic growth in Vietnam by using a linear approach. For this study, data was collected from the World Bank and relevant agencies in Vietnam. The results show that FDI (net inflows), foreign aid, foreign loans, exports, and GDP (current), have a positive effect at a 1% significance level on economic growth. Rather, an increase in FDI (net inflows), foreign aid, foreign loans, exports has beneficial effects on the Vietnamese economy in the study period. Based on the findings of this study, the article proposes several important policy implications for Vietnam in maintaining a high rate of economic growth via the contribution of FDI inflows, foreign aid, foreign loans, and exports.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.99-109
• /
• 2021

This study aims to examine the causal links between the fiscal components, i.e., government expenditures (GE) and government revenues (GR), and their impact on the economic growth of the Association of Southeast Asian Nations (ASEAN) region. This analysis considered secondary panel data from 1990 to 2019 at an annual frequency. The data is obtained from the Asian Development Bank (ADB) and World Bank Database. A panel cointegration and panel DH causality (Dumitrescu and Hurlin) approach was employed on financial data at an annual frequency from 1990 to 2019. The findings from panel unit root and panel cointegration tests demonstrate that, at first, all the variables are stationary and cointegrated. The panel ARDL disclosed that GE has a long-run connection with GDP, is significantly and positively associated with economic growth in the long run, whereas GR is significant in the short run. The contribution of GE is high in sustaining economic growth as compared to GR. Also, cointegration regression disclosed that GE is more sensitive toward GDP, while GR is less elastic. Lastly, the findings reveal that bidirectional causality exists between GE and GR variables. These results have policy implications for sustainable economic growth in the ASEAN region.

• Korea Trade Review
• /
• v.44 no.6
• /
• pp.187-199
• /
• 2019

Vietnam's economic growth has progressed rapidly since Doi Moi. Vietnam is a key driving force for global economic growth on behalf of China. Therefore, this study analyzed the factors of Vietnam's economic growth by using time series variables after Doi Moi. Study results show that educational expenditures affect ODA in the short term. In the long run, GDP and FDI are causally related to ODA. Based on the above findings, it can be seen that FDI and ODA played a significant role in Vietnam's economic growth. This finding suggests that in order for Vietnam's economy to grow further, the capital market should be more open to foreigners so that FDI and ODA can flow more smoothly. Since the inflow of FDI is also linked to educational expenditure, it is important to understand that the workforce is being upgraded in the Vietnamese labor market.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.809-820
• /
• 2021

The study aimed to investigate the impact of sectoral bank credit facilities provided by commercial banks on the non-oil economic growth in Saudi Arabia. Bank credit facilities are given for nine economic sectors: agriculture, manufacturing, mining, electricity and water, health services, construction, wholesale and retail trade, transportation and communications, services, and finance sector. The study employs annual data from 1970 to 2019. The study employs the Autoregressive Distributed Lag (ARDL) approach to identify the long-run and short-run dynamics relationships among the variables. The main results reveal that the overall impact of total bank credit has a significant and positive effect on non-oil economic growth in KSA. The results revealed that the effect of bank credit on the non-oil GDP growth in the short and long run was uneven. The study finds that all sectors have a positive and significant impact in the long run, except for the agricultural and mining sectors. Likewise, all sectors have a positive and significant impact in the short run, except for construction, finance, services, and transportation & communications. As a result, bank credit facilities in different sectors have played an important role in enhancing the non-oil economic growth in the KSA.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.206-212
• /
• 2022

The main purpose of the article is to study the peculiarities of the formation of information support mechanisms for economic growth and security under the influence of COVID-19. The cyclical nature of economic growth is a well-established and proven fact. In this context, one of the main tasks of the state is to develop measures to mitigate the impact of economic crises on the entire economic system of the state, individual economic entities, as well as to introduce anti-crisis mechanisms and tools to support the economy. When the cyclical nature of economic crises coincides with destabilizing processes in society, such as natural disasters, military actions or epidemics, the role of the state and adequate information support for economic growth is sharply actualized. As a result, an analysis was made of the main aspects of information support for economic growth and security in the context of COVID-19.

• Korea Trade Review
• /
• v.46 no.6
• /
• pp.191-209
• /
• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.

• Journal of Environmental Policy
• /
• v.10 no.4
• /
• pp.3-37
• /
• 2011

This paper investigates the existence of the environmental Kuznets curve (EKC) for carbon dioxide $CO_2$ emissions and its causal relationships with economic growth and openness by using time series data (1971-2006) from China (an emerging market), Korea (a newly industrialized country), and Japan (a developed country). The sample countries span a whole range of development stages from industrialized to newly industrialized and emerging market economies. The environmental consequences according to openness and economic growth do not show uniform results across the countries. Depending on the national characteristics, the estimated EKC show different temporal patterns. China shows an N-shaped curve while Japan has a U-shaped curve. Such dissimilarities are also found in the relationship between $CO_2$ emissions and openness. In the case of Korea, and Japan it represents an inverted U-shaped curve while China shows a U-shaped curve. We also analyze the dynamic relationships between the variables by adopting a vector auto regression or vector error correction model. These models through the impulse response functions allow for analysis of the causal variable's influence on the dynamic response of emission variables, and it adopts a variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the causal variables over time. Results show evidence of large heterogeneity among the countries and variables impacts.

• 대한공업교육학회지
• /
• v.36 no.1
• /
• pp.131-148
• /
• 2011

The purpose of this study was to development of the green information technology practical method and verify the impact of classes which applied green information technology practical method on the students' practice on green information technology to enhance the study related to green growth education for Technology Home Economics Education. In order to achieve the purpose, first, the green information technology practical method and measurement instrument were developed. Second, green information technology practical method applied in class. Third, D middle school students(male 62, female 59) in Daejeon city were tested by green information technology practical method measurement instrument and the comparison between pretest and posttest results were made. There were three results conduced from this study. First, green information technology practical method had positive impact on the students' green information technology practice on the items which they directly face in their daily lives, such as computers, monitors, and data. Through this point, when green growth curriculum developed in Technology Home Economics, we must consider the more closely related in lives contents. Second, green information technology practical method not impact on the practice on the items such as printers, peripherals, and other items. But in the future we expect more students hold printers and peripherals so the study for these items needed the more. Third, there were no gender differences in green information technology practice. Through this point, when green growth curriculum organized, there was no needed to separete students' gender.

• Journal of Korean Home Economics Education Association
• /
• v.26 no.1
• /
• pp.81-99
• /
• 2014

Student teaching is equivalent to an egg just before oviposition. There is a growing acting voice that teaching profession is not necessarily required as the years go by. I developed a process that 55 student teachers search for their identity as a teacher during four-week student teaching program according to Clandinin and Connelly(2000)'s narrative inquiry. The procedure consisted of three stages such as access to the field, field text writing, and research text writing. The student teachers wrote journals by week to search for their identity as a teacher with a focus on what they observed in the field and what they were motivated by teachers and students. Free and truthful 220 stories conducted in a student teaching online cafe were collected as a field text. And the research text was reliving and retelling through poetic writing on each week's themes of exploration, growth, reflection, and pledge to complete the narrative inquiry. Student teachers, an absolute majority, including home economics student teachers aimed for the teaching profession and waited for their hatching.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.5
• /
• pp.61-72
• /
• 2020

The purpose of this study is to investigate the determinants of the capital structure of firms operating in a developing economy, Pakistan. The quantile regression method is applied on a sample of 183 non-financial companies listed on the Pakistan Stock Exchange during the period of 2008-2017. Specifically, the empirical analysis focuses on changes in the coefficients of the determinants according to the leverage ratio quantiles of the examined listed firms. The findings show that the capital structure of Pakistan listed firms differs between firms in different quantiles of leverage. These differences are significant with the sign of explanatory variables changes with the level of leverage. The research result found tangibility, profitability and age to be positively related to leverage among listed firms in Pakistan. However, size, liquidity and non-debt tax shield (NDTS) are negatively related to leverage. A firm's growth and risk are found to be insignificant predictors of capital structure in Pakistan listed firms. Moreover, the study also found a significant impact of industry characteristic on leverage. The findings of this study indicate that an individual firm's finance policy needs to be responsive to the firm's characteristics and should match with the different borrowing requirements of listed firms.