• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.566-574
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• 2000

Although a numbed of variants of 2D HMM have been proposed in the literature, they are, in a word, too simple to model the variabilities of images for diverse classes of objects; they do not realize the modeling capability of the 1D HMM in 2D. Thus the author thinks they are poor substitutes for the HMM in 2D. The new model proposed in this paper is a hidden Markov lattice or, we can dare say, a 2D HMM with the causality of top-down and left-right direction. Then with the addition of a lattice constraint, the two algorithms for the evaluation of a model and the maximum likelihood estimation of model parameters are developed in the theoretical perspective. It is a more natural extension of the 1D HMM. The proposed method will provide a useful way of modeling highly variable patterns such as offline cursive characters.

• Journal of Distribution Science
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• v.12 no.6
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• pp.49-57
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• 2014

Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

• KDI Journal of Economic Policy
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• v.36 no.2
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• pp.65-101
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• 2014

This paper estimates and characterizes expected inflations using an affine term structure model based on the empirical stochastic process of the interest rates in Korea. The empirical results show that the expected inflation which marked above 4% before the global financial crisis has dampened and stabilized after the crisis. Moreover, we investigate the rationality of the various expected inflation measures in terms of the unbiasedness and efficiency and find that unbiasedness is not rejected across the all measures, while the efficiency cannot be empirically warranted. Besides, we run Granger causality tests and conclude that the expected inflations compiled from the Consensus, BOK-Expert have the cross-causality with the long-run actual inflation, while the expected inflation estimated from the term structure model has the cross-causality with the short-run actual inflation. These results connote that expected inflations collected from different sources and methods have their targets and horizons and the central bank needs to watch all of them with a balanced view instead of preferring one to the other.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.871-883
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• 2015

Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

• The Journal of Fisheries Business Administration
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• v.52 no.1
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• pp.47-63
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• 2021

The purpose of this study is to identify the leading price between Jeju and Wando's oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando's oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.271-282
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• 2021

In recent years, a significant number of empirical studies have examined the relationship between export and economic growth in India. However, this study analyses the relationship between exports and economic growth through the time series model. The main aim of this study is to investigate the causal relationship between exports and economic growth in India. The VAR model was used for the period 1961 to 2015 after verifying the stationarity of the variables through using Augmented Dickey-Fuller and Phillip-Perron tests. The Indian export sector has been found to have a significant and positive impact on economic growth and other long-term economic activities. The study also employed the Granger causality test to check the direction of causality and found that RXGS, RGDP, RPFC, and RGFC had a unidirectional relationship and RXGS and RMGS had a bidirectional relationship in long run. Also, the findings of this study suggest that a steady-state between exports and economic growth can be achieved in India over a long period. The overall outcome of this study provides a testimony of the fact that the export sector plays a vital role in economic growth in India and also leads to the long-term growth of other economic activities.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.869-880
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• 2004

The purpose of this study is to examine relationship between water consumption and economic growth in Korea, and to obtain policy implications of the results. To this end, we attempt to provide more careful consideration of the causality issues by applying rigorous techniques of Granger causality. Tests for unit roots, co-integration, and Granger causality based on an error-correction model are presented. The existence of bi-directional causality between water consumption and economic growth in Korea is detected. This finding has various implications for policy analysts and forecasters in Korea. Economic growth requires enormous water consumption, though there are many other factors contributing to economic growth, and water consumption is but one part of it. Thus, this study generates confidence in decisions to invest in the water supply infrastructure. Moreover, this study lends support to the argument that an increase in real income, ceteris paribus, gives rise to water consumption. Economic growth results in a higher proportion of national income spent on water supply services and stimulates further water consumption.

• 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.3 no.3
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• pp.79-91
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• 2016

This paper is the first of its kind using a non-linear approach based on cross-correlation function (CCF) to investigate the information arrival hypothesis in crude palm oil (CPO) futures market. Based on daily data from 1986 to 2010, our empirical results reveal that: First, the volume of volatility is not a proxy of information flow. Second, dependence causality running from current return to future volume in conditional variance exhibit an asymmetric pattern of time span with different signs of correlation between price and volume series. This finding indicates the presence of noise traders' hypothesis of price-volume interaction in CPO futures market. Both findings suggest that this futures market is weak-form inefficiency. In terms of investors' behavior, they tend to change their expectations on current return based on errors made in previous trade in generating abnormal volume in the subsequent period. As implied, it is advisable for the investors devise their future trading strategies according to time span and changes of return.

• Asia Pacific Journal of Business Review
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• v.1 no.2
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• pp.1-16
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• 2017

The fundamental goal of the research was to verify if the Twin Deficits Hypothesis holds for the economy of Zambia using time series data from 1980-2014. The current account and budget deficit were employed as key variables. The exchange rate was also used as a transmission mechanism to see how it contributes in the nexus. Cointegration tests confirmed a long run association of the variables. After fitting the VECM model, Granger causality tests confirmed the existence of twin deficits for Zambia. The results supported uni-directional reverse causality. The exchange rate was shown to be more significant in the long run than in the short run. The implosion of the time series as shown by the predicted cointegration equation implies that unless drastic measures are taken to cure the deficits, using the current account as the major target variable, twin deficits will persist for some time. The major policy implication of this research is that given that Zambia is a primary commodity-dependent developing country subsisting largely on copper revenues to sustain the economy, there is a need to move away from "copper addiction," given the recent volatility of earnings of primary commodities (e.g. through diversification of the economy, import substitution, and other strategies).