• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.27-37
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• 2016

This study uses an endogenous economic growth model to determine the long run relationship between trade openness and economic growth in China by using the data 1975-2009.It contributes to the literature by developing trade openness index. An autoregressive distributed lag approach to cointegration and rolling regression method are employed. This study tests the link between trade openness and economic growth in the case of China by using the framework of endogenous economic growth model. This study also employs the rolling window regression method in order to examine the stability of coefficients throughout the sample span. The autoregressive distributed lag (ARDL) cointegration technique and rolling regression method are used. The empirical findings indicate that trade openness (i.e. Both individual trade indicator and composite trade openness index) are positively related to economic growth in the long run and short run. Our results indicate that trade openness as measured by individual trade indicator and composite trade openness index are positively related to economic growth in the long run and short run. However, results from the rolling window suggest that trade openness is negatively linked to economic growth only for a number of years.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.693-702
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• 2020

The present study aims to investigate the impact of tourism growth on human development in Indian economy. For this purpose, the study uses annual data from 1980 to 2018 and utilizes two proxies for tourism growth - tourism receipt and tourist arrivals - and uses human development index calculated by UNDP. The study uses control variables such as government expenditure and trade openness. The study employs auto regressive distributed lag (ARDL) approach to investigate the cointegrating relationship among the variables in the model. Further, the study also explores the causal nexus between tourism sector and human development by using the Toda-Yamamoto Granger non-causality test. The result of ARDL bounds test reveals the existence of cointegrating relationship between human development indicators, government expenditure, trade openness, and tourism sector growth. The cointegating coefficient confirms a positive and significant relationship between tourism sector growth and human development in India. The causality result suggests that economic growth and tourism have a positive impact while trade openness has a negative impact on human development in India. The major findings of this study suggest that tourism plays an important role in the socio-economic development of Indian economy in recent years and the country must develop this sector to achieve sustainable development.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.127-135
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• 2020

This study aims to measure the effects of real interest rate (RIR), gross domestic savings (GDS), and net exports (EN) shocks on Indonesia's economic growth (EG). The focus on Indonesia is unique due to the abundant resources available in the nation, but they are unsuccessful in boosting economic growth. This study applied a quantitative method to comprehensively analyze the correlation between variables by employing Vector Autoregression Model (VAR) combined with Vector Error Correction Model (VECM). Various procedures are preformed: Augmented Dickey-Fuller test (ADF), Optimum Lag Test, Johansen Cointegration Test, Granger Causality Test, as well as Impulse Response Function (IRF) and Error Variance Decomposition Analysis (FEVD). The data were collected from the World Bank and the Asian Development Bank from 1986 to 2017. The findings of the study indicated that economic growth responded positively to real interest rate shocks, which implies that when the real interest rate experiences a shock (increase), the economy will be inclined to growth. While, economic growth responded negatively to gross domestic savings and net export shocks. Policymakers are expected to consider several matters, particularly the economic conditions at the time of formulating policy, so that the prediction effectiveness of a policy can be appropriately assessed.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.21-30
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• 2021

This study examines the role of the manufacturing sector in stimulating economic growth in the Saudi economy. Even though the economic literature shows how the manufacturing sector stimulates economic growth, it does not clearly show the role of the manufacturing sector in economic growth. The study employed annual time-series data spanning the 1980-2018 period from the databases of the Saudi Arabian Monetary Authority. Moreover, the cointegration and VECM approaches were employed to examine the short- and long-run relationship causality between variables. The results show a two-way causal relationship exists between the manufacturing sector and economic growth. Furthermore, the results indicate that a unidirectional causal relationship exists, running from the manufacturing sector to the services sector. The study recommends that the determinants of the growth of the Saudi manufacturing sector must be investigated. Moreover, the most productive Saudi manufacturing industries must be identified, and the productivity of other sectors must be increased in a way that contributes to economic plans and policies. Thus, adopting economic policies that stimulate investment in the manufacturing sector contributes to increasing non-oil exports to diversify sources of income to achieve vision 2030 of the Kingdom of Saudi Arabia.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.681-693
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• 2020

This study sees a critical gap in the previous body of research, which it seeks to fill; the disclosure of the unemployment ratio correlation has only been measured by the level of economic growth. This study is to add investment variables and government expenditure variables that objectively aim to measure the level of effectiveness in handling the unemployment ratio, which is then a measurement of the effectiveness of unemployment. Economic growth is measured by its impact on income inequality through empirical, conceptual relationships as a critical review and economic strategy for the future. The research uses secondary data on Indonesian macro and microeconomics since 2003-2018, then testing uses a quantitative approach to correlation, regression, and scatterplot. The results of this study show correlations between variables, and volatiles on the graphs show a similar trend. In other words, variables are bound together and support each other. The strategy of prioritizing the scale of government expenditure and investment to reach the target is the primary concern, so that the economic cycle can be optimal and equipped to face the possibility of an economic recession in the future. Many factors cause complex income inequality, though investment does not show a correlation to income inequality.

• KDI Journal of Economic Policy
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• v.37 no.4
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• pp.55-74
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• 2015

Using the Census on Establishments collected by Statistics Korea, we analyze how the patterns of job creation and destruction differ across counties (si-gun-gu). We measure aggregate employment changes due to establishment startups, expansions, contractions, and shutdowns for each county and quantify the role of such reallocations in explaining variation in employment growth across counties. Overall we find that both rates of net entry and job creation play an important role in explaining differences in net job creation rates across regions. Moreover, counties with high employment growth rates also tend to have high exit and job destruction rates, which suggests that an active process of job reallocation is a key source of regional employment growth.

• East Asian Journal of Business Economics (EAJBE)
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• v.2 no.4
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• pp.1-8
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• 2014

This study examines the relationship between population growth and carbon dioxide emissions in the context of Africa perspective. Population growth and carbon dioxide emissions helped identify the key driving forces of environmental impacts by including other predictors in all the different income levels of all sampled countries in Africa. To explore the role of population growth in the emissions of carbon dioxide, this research employed a panel data set of 52 Africa countries from 1960 to 2012 using fixed effects, random effects and GLS/FGLS estimators to estimate the modified STIRPAT model. The results found that a 1% increase in population growth suggests an increase in carbon dioxide emission loads by about 0.33%, 1.08%, 0.57% and 2.32% on the average, controlling for all other anthropogenic driving forces, for LICA, LMICA, UICA and HICA respectively. There is a significant relationship between population growth and carbon dioxide emissions in all the national income levels in Africa.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.43-52
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• 2020

This paper examines how macroeconomic variables, such as interest rate differences, inflation, exchange rates, economic growth and external debt growth, affect capital flight in the ASEAN-8 countries. We apply a panel data model with fixed effect estimation for the data for eight countries from the period 1994 to 2018. We use the residual approach used by the World Bank to measure the value of capital flight. The results show that the interest rate differences, exchange rates, economic growth and foreign debt growth had a positive and significant effect on outward capital flight. A further implication of this finding is that the interest rate differences, exchange rate, economic growth and foreign debt growth are factors that trigger an increase in capital outflow in the ASEAN-8 countries. Nonetheless, inflation rate is not considered to be the main factor influencing capital flight, as average inflation in the ASEAN-8 countries remains relatively stable. This paper will be beneficial for policymakers in the ASEAN-8 countries and encourage them to constantly pay attention to these four variables, as they significantly influence capital flight, whereas they can disregard the impact of the inflation variable that is not significant in influencing capital flight.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.717-725
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• 2020

The purpose of this paper is to highlight the impact of the performance of private wealth management (PWM) on the growth of retail banking in Indonesia. The variables used are bank's competitiveness, risk management, performance of private wealth management, and growth of retail banking business. The data were collected from 60 respondents from 32 banks over five months, from October 2018 to March 2019. Using partial least square path modeling, the analysis shows that the performance of private wealth management has an impact on the growth of retail banking sector in Indonesia. Bank competitiveness and risk management affect the performance of personal wealth management and have an impact on the growth of the retail banking business. Bank competitiveness is the variable that most influences the performance of private wealth management in Indonesia. This research found that market share is the most significant indicator of bank competitiveness. For risk management, significant indicators are the level of bank confidence, increased bank competitiveness, and the creation of new products. In the performance of the private wealth management variable, the most significant indicator is the revenue fee-based income. For the growth of retail banking business, a clear indicator is profit growth.