• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.55-67
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• 2021

This study aims to measure the lower tail dependence as risk contagion from the U.S. economy to 18 developing countries affecting FDI inflows using time-series data from 2005 to 2019. Firstly, we utilize four dynamic copula models, namely, Student-t, Clayton, rotated survival Gumbel, and rotated survival Joe, to measure the tail dependence structure between the U.S. and each developing country's real GDP growth. Secondly, we use the regression model to explore the contagion effects on FDI inflows. The results show that there is evidence of the tail dependence between the U.S and developing economies, indicating the presence of the contagion effects. Primarily, we observe that the degree of contagion effects of the global financial crisis varies across countries; a strong impact is observed in Chinese, South African, Russian, Colombian, and Mexican economic growth. Furthermore, we found significant contagion risk affecting FDI inflows positively in China, Indonesia, Columbia, Morocco, and negatively in the Philippines, Bulgaria, and South Africa. This study demonstrates the usefulness of the copulas model in terms of examining contagion. Our findings shed light on the influence of sound policies and regulations to cope with both positive and negative consequences of the contagion on the capital movement.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.171-180
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• 2021

The purpose of this paper is to estimate the impact of credit rationing on the amount of trade credit used by farmers in Vietnam. This study employs a survey data collected through direct interviews with heads of 1,065 rice households randomly selected out of provinces and city in the Mekong River Delta (MRD). In each province or city, the village with the largest area of land devoted to rice production from the district with the largest area of land devoted to rice production was picked up for survey. In each village, 200 rice farmers were randomly chosen for interview. Based on a probit model and a semi-parametric propensity score matching (PSM) estimator while controlling socio-demographic traits of rice farmers, the estimated results show that non-credit rationed farmers use less trade credit to finance production compared to their credit rationed counterparts. Moreover, the amount of trade credit used by farmers decreases as the degree of credit rationing drops. This paper provides evidence of the substitutive relationship between bank credit and trade credit. It also implicitly suggests that banks can drive trade creditors out of the market if they manage to solve the problem of information asymmetry and transaction cost.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.845-853
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• 2021

The stock market shows the current health of an economy, and investment performance represents it. This study aims to clarify the relationship between financial behavior and investment decisions as well as its impact on investment results. Determine the influence of behavioral factors on individual investors' investment decisions and investment performance on the Vietnam stock market. The study surveyed 250 investors. The main analytical methods used are Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). Research results show that Heuristic, Prospect, Market, and Herding directly and positively affect investment decision-making. Besides, the above factors have a direct and positive effect on investment performance. In particular, the Prospect factor has the strongest influence on investment decision-making and investment performance. The major findings of this study suggested that the important role of Heuristic, Prospect, Market, and Herding on Investment Decision-making and Investment Performance. Prospect had the strongest impact on Investment decision-making (β = 0.275). Heuristic had the second strongest impact (β = 0.257), then Herding (β = 0.202), and finally Market (β = 0.189) had the weakest effect. Regarding Investment Performance, the Prospect factor has a higher degree of impact than Heuristic Herding and Market.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.75-90
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• 2019

As the 24-hour society arrives, human activities in daytime and nighttime urban spaces are changing drastically, and the need for new urban management policies is steadily increasing. This study analyzes the types and characteristics of Seoul's human dynamics using location-based big data and the results are summarized as follows. First, the pattern of human dynamics in Seoul repeats itself every 7 days. Second, the types of human dynamics in Seoul can be classified into five types, and each of type has its own unique time-series and local characteristics. Third, the degree of match between human dynamics and zoning system in urban planning legislation was highest in 'Type 1' residence pattern and low in other types. The following implications can be drawn from these results. First, This paper examined the methodology of analyzing the regional characteristics of Seoul through the human dynamics and obtained meaningful results. Second, This paper can derive reliable and objective pattern analysis results using Big data that reflect the overall population characteristics. Third, the scale of night-time activity in the urban space of Seoul was understood, and its distribution, patterns and characteristics identified.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.267-275
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• 2021

This study investigates the relationship between cultural distance and entry mode choice, where the foreign investor firm and the host country are both from emergent economies. Within this framework, research is limited and the issue is whether companies, regardless of their specific situations, have the same strategy when they meet a high degree of uncertainty in the host environment. In this study, we focused on the influence of informal institutional factors: cultural distance, that has been extensively analyzed in international business, measured by Kogut and Singh index and defined according to Hofstede, Globe Project and Schwartz approaches. The general trend derived from prior research proves that when a company from a developed country is involved; overall more enthusiasm is shown for wholly-owned subsidiaries rather than joint venture. This result still stands validated for corporations from this emergent economy area. Our analysis of a sample of 163 FDI in the Kingdom of Saudi Arabia (KSA) using logistic binary regression model reveals that the foreign firms prefer to establish wholly-owned subsidiaries in the host country over entering into a joint venture with a local firm, taking into consideration the large cultural distance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1143-1152
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• 2021

The study aims to assess the impact of factors on the access to financial services by Vietnamese farmers. The number of respondents in this study is 402 household heads participating in six diverse agricultural value chains in Vietnam. The explanatory variables of the Multinomial Logit model estimates variables at the individual characteristics while the Mixed Logit model can combine the two types of variables together to estimate the effects simultaneously. On the other hand, the Ordinal Logit model is used to evaluate the determinants of the increase in the quantity of financial services used by individuals. The estimation results show that male-headed households have more access to financial services than females. Younger farmers are more likely to use formal financial services than the elderly. Financial literacy, land ownership, and shocks in agricultural production all have a positive impact on the probability of dealing with banks. In addition, the degree of linkage and credibility of the value chain have a significant positive impact on the accessibility of financial services to farmers. The findings of this study suggest that limiting gender inequality, focusing on youth marketing and developing agricultural value chains will have a positive impact on farmers' access to financial services.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.363-373
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• 2021

The present study seeks to investigate the degree of awareness that constitutes the audit gap expectations (AEG) to determine which audit responsibilities can be narrowed or even eliminated. The author had surveyed a sample comprising four groups including auditors, auditees, the financial community, and other interest groups. In this survey, 1400 questionnaires were sent to the respondents, and the total number of responses was 454. The collected data was processed using statistical software SPSS, version 22. The Chi-Square test was used to analyze the effect of professional differences on AEG. The results of this study indicate that AEG cannot be eliminated due to the occupational impact of each survey group (about 46%), but it can be narrowed down to 54%, including a reduction of 11% in the knowledge gap (lack of public knowledge), 13% in the reasonable expectations gap (unqualified audit quality), 30% in the deficient standards gap (limited auditing standards). These results could be attained by improving training, communicating, and adding more responsibilities. This is the first study that provides another method of measuring the contribution of the knowledge gap through professional differences and professional gaps that make up each of the AEG's components.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.15-23
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• 2021

This study investigates the presence of the day-of-the-week anomaly in exchange rate for 30 developing countries with free floating exchange rate regimes using daily data from January 2, 2011 to December 31, 2019. First, we apply the GARCH panel to estimate the intraday effect for all the sampled countries. Second, we run poolability test to check whether the coefficients of the GARCH panel are the same for all countries sampled. The result of poolability test rejects the homogeneity assumption. This implies that our sample countries contain heterogeneity. Third, we apply mean-group estimation by averaging the coefficients for all individual GARCH estimations. Fourth, we divided our sample of developing countries into three groups based on capital restriction index for the reason that the effect of monetary policy on the exchange rate depends on the degree of capital account liberalization. The empirical evidence for the return equation suggests that Mondays are connected with lower volatility whereas Thursdays experiences higher return compared to Tuesdays. The lowest estimated coefficient for full sample, group 1 and group 2, is Friday, but for group 2 is Thursday. We find similar result for the volatility equations, which show that Monday returns are lower compared to Tuesday.

• Journal of Korean Society of Forest Science
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• v.110 no.1
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• pp.106-115
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• 2021

The aim of the study was to analyze the spatial characteristics of the main producing areas of nontimber forest products. We analyzed the spatial aggregations of the main producing area and their changes using the Moran's I index. We found that 45% of nontimber forest products were significanty spatially clustered. Additionally, in five major products, we observed that the main producing area has expanded and the degree of aggregation has also strengthened over the last ten years. The results of this study can be effectively used for forest policies, such as determining the location and size of the distribution centers of specific forest products.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.886-893
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• 2022

Outlier detection refers to the task of detecting data that deviate significantly from the normal data distribution. Most outlier detection methods compute an outlier score which indicates the degree to which a data sample deviates from normal. However, setting a threshold for an outlier score to determine if a data sample is outlier or normal is not trivial. In this paper, we propose a binary prediction method for outlier detection based on spectral clustering and one-class SVM ensemble. Given training data consisting of normal data samples, a clustering method is performed to find clusters in the training data, and the ensemble of one-class SVM models trained on each cluster finds the boundaries of the normal data. We show how to obtain a threshold for transforming outlier scores computed from the ensemble of one-class SVM models into binary predictive values. Experimental results with high dimensional text data show that the proposed method can be effectively applied to high dimensional data, especially when the normal training data consists of different shapes and densities of clusters.