• Environmental and Resource Economics Review
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• v.17 no.1
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• pp.3-22
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• 2008

We study nonlinearities of $CO_2$ emissions and economic growth m Korea using the Smooth Transition Autoregressive (or STAR) model. We find evidence for nonlinearities and cyclical regime changes of both time series. In the extended nonlinear empirical work, we characterize dynamic properties of the two time series and then find mutually significant Granger causality between $CO_2$ emissions and economic growth. All these empirical evidences together reinforce long standing concern that economy-wide restrictions on $CO_2$ emissions would hurt economic growth for Korean styled medium industrialized countries.

• STI Policy Review
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• v.8 no.1
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• pp.1-22
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• 2017

There has been a pronounced increase in research and development (R&D) expenditure in Singapore over the last two decades, with government spending accounting for a sizeable share. This increase has been spurred by public policy emphasis on research and innovation as engines of economic growth. This paper analyses the impact of R&D on economic performance in Singapore from 1978 to 2012 through the use of time series analysis. The Cobb-Douglas based analysis shows a long-run equilibrium relationship between Total Factor Productivity (TFP) and R&D investments. We found that the short-run productivity of R&D in Singapore is comparable to smaller advanced economies in the Organisation for Economic Co-operation and Development (OECD). However, in terms of long-run R&D productivity, Singapore lags slightly behind the smaller OECD nations and far behind the G7 countries. This suggests leakage of value capture and low absorptive capacity in local firms. Possibility of productivity improvements induced by policy changes in the 1990s was considered, but no evidence of significant structural breaks was found. Lastly, Granger causality analysis reveals that public sector R&D augments private sector R&D capital, thus playing an important role in generating externalities and spillover effects. Policy implications and lessons for other middle-income countries are discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.49-63
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• 2015

Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

• 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.7 no.11
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• pp.619-627
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• 2020

This study measures the relationship between labor productivity and national competitiveness. Through the shift- share analysis method, the paper has separated labor productivity into three factors: static shift effect, dynamic shift effect and endogeneous effect. Next, in combination with the Granger causality test, the paper examines the relationship between the factors constituting labor productivity and competitiveness during the period from 2005 to 2017. Research data is collected from General Statistics Office and annual global competitiveness reports. The results show that the interaction between labor productivity with global competitiveness index (GCI) in Vietnam has similar variation. Nevertheless, when separating labor productivity into three effects, this relationship shows more clearly that the impact of labor productivity on GCI scores is mainly caused by endogeneous effect, not by static shift effect or dynamic shift effect. Therefore, in order to improve its competitiveness, Vietnam should focus on a number of solutions: reforming the education system towards developing thinking capacity and creative capacity; fostering industrial manners to create dynamic and flexible workers; building the State with sufficient capacity to implement consistent and transparent policies; formulating policies to attract all economic sectors so that they actively participate in the field of human resource training for the country.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.543-553
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• 2020

This paper examines the effect of COVID-19 pandemic on the Philippine stock exchange, peso-dollar rate and retail price of diesel using robust least squares regression and vector autoregression (VAR). The robust least squares regression using MM-estimation method concluded that COVID-19 daily infection has negative and statistically significant effect on the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. This is consistent with the results of correlation diagnostics. As for the VAR model, the lag values of the independent variable disclose significance in explaining the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. Moreover, in the short run, the impulse response function confirmed relative effect of COVID-19 daily infections and the variance decomposition divulge that COVID-19 daily infections have accounted for only minor portion in explaining fluctuations of the Philippine stock exchange index, peso-dollar exchange and retail pump price of diesel. In the long term, the influence levels off. The Granger causality test suggests that COVID-19 daily infections cause changes in the Philippine stock exchange index and peso-dollar exchange rate in the short run. However, COVID-19 infection has no causal link with retail pump price of diesel.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.1
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• pp.57-69
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• 2020

Purpose - This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), M3, real rate of interest (IR_REAL) and household credits (LOAN). We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology - Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration, Granger causality test, and impulse response function and variance decomposition analysis by EViews 11.0. Results - The statistical tests show that all variables under consideration have one unit root and there is a longterm equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK and LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions - It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.567-576
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• 2020

One of the main challenges receiving much attention in the Rwandan agriculture and food industry in recent decades is the increases in maize prices. Indeed, a rise in maize prices causes higher living expenses for households because maize, which is a major staple food crop, constitutes a significant share of total food consumption among households in Rwanda. The aim of this study was to assess the extent of integration and how prices are transmitted between retail and wholesale markets of domestic maize in Rwanda. This study used monthly data of retail and wholesale prices of maize from January 1995 to December 2019. This empirical investigation was based on a linear cointegration approach and an asymmetric error correction model framework. Using the augmented dickey-fuller residual-based test and the Johansen Maximum Likelihood cointegration test, the results revealed that the retail and wholesale markets of maize are integrated. Hence, prices in these markets do not drift apart in the long run. The results of the Granger causality test revealed that there is a unidirectional causal relationship flowing from wholesale prices to retail prices, i.e., wholesale prices influence retail prices. Accordingly, the results from the asymmetric error correction model confirmed the presence of a positive asymmetric price transmission between wholesale and retail prices of maize in Rwanda. Thus, we suggest that policymakers take a critical look at the causes and factors that may influence asymmetry price transmission.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.37-41
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• 2021

This study aims to investigate the relationship between the exchange rate and Trade Balance. Trade Balance is used as the dependent variable, and the independent variables are Exchange Rate, Gross Domestic Product, and Inflation. Augmented Dickey-Fuller unit root test was adopted to test the stationary property of time series data, Auto Regressive Distributed Lag model was employed to find the long run and short-run relationship and long-run adjustment, Bound test approach, the unrestricted Error Correction Model and Granger Causality Test are used to analyze the data from 1977 to 2019. The research findings suggest that inflation has a positive impact on the trade balance in the short run. The exchange rate and the Gross Domestic Product have adverse effects on Trade balance in the long run. The coefficient of ER in the previous year is negative, and the coefficient of TB in the previous year is positive and significant. This is consistent with the J-Curve phenomenon, which states that devaluation may not improve trade balance in the immediate period, but will significantly impact the trade balance improvement in subsequent periods. Hence Marshall Lerner Condition exists in Sri Lanka.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.53-60
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• 2021

Foreign direct investment (FDI) is especially important for developing countries. This study investigates the determinants of FDI in the case of Indonesia. Most empirical researches in this field used time series data of a single country or panel data of several countries. Although panel data analysis is more comprehensive, however results taken from cross-country analysis cannot be directly applied to any specific country in the dataset and therefore lacks practicality. In this research, panel data analysis of a single country is performed to overcome the aforementioned shortcomings. Five determinants of FDI are tested using panel data of 33 Indonesian provinces over 10-year period of time. Two methodologies are adopted, random/fixed effects model and Granger Causality. The results show that only market size significantly affects FDI when tested using both methodologies. Human capital and financial market development show significant result in one of the two methodologies. While, economic growth and infrastructure did not show any significant results at all. This research stresses the importance of comprehensive single country analysis since only one out of five commonly discussed determinants is applicable in the case of Indonesia. Governments should therefore carefully reconsider the use of cross-country analysis as a basis of their policy formulations.