• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.2
• /
• pp.61-69
• /
• 2022

The study intends to investigate a short-run and a long-run causality among money, income, and prices in the Keynesian and Monetarists framework. This study emphasizes the importance of unrecorded money, which exists alongside legal monetary assets and plays a dual function in determining economic prosperity. The underground economy, which is a hidden component of aggregate economic activity, is determined using Tanzi's monetary approach (Tanzi, 1980). This research uses a time series of annual data from 1990 to 2019 for this purpose. The data is extracted from the World Bank database for the monetary and development indicators. The study keeping in view the trending nature in data follows a unit root testing followed by the Autoregressive Distributive Lag Model (ARDL) to assess the long and short-run dynamics of causality among the variables. In both the pricing and income equations, the study finds a significant level link among the variables; however, there is no evidence of the presence of a level association in the money equation. The short-run causal relationship provides evidence of bi-directional causation between the supply of money and national income. The outcome of this study advise that though the view point of both the Monetarist and Keynesian school holds in both short and long run, however, in Pakistan only the Monetarists' role of money supply and income holds in Pakistan. This evidence would be of precise interest to the policy-makers.

• Journal of Korea Trade
• /
• v.24 no.1
• /
• pp.146-170
• /
• 2020

Purpose - This paper addresses the concepts of FDI-Trade-Growth nexus in Myanmar's economy and empirically investigates the interrelationships of trade, investment and economic growth to reveal the growth model of Myanmar's economy. Additionally, this paper also addresses the cooperative strategies between Myanmar and South Korea through a case study related to South Korea's economic growth. Design/methodology - Our empirical model considers the interrelationship among FDI, trade, growth, labor force and inflation in Myanmar. This study employs ARDL (Autoregressive Distributed Lag) to conduct an analysis of the FDI-Trade-Growth relationships using the time series data from 1970 to 2016 and a conducted case study of South Korea provided for practical implication on cooperative strategies between Myanmar and Korea. Findings - Export equation was chosen through the diagnostic tests. Our main findings can be summarized as follows: Export in Myanmar is positively influenced by labor force, FDI, capital formation and negatively impacted by import and instable inflation rate in the long run. In the short run, GDP and import positively influence export. The Granger causality test proves that Myanmar is an FDI/labor force-led Growth economy, where FDI and labor force are main drivers of export followed by GDP in Myanmar. The case study of South Korea provided that Korea's tax and credit system for promoting export-led FDI industries and cooperative units for joint ventures between Korea and Myanmar in export-led FDI industries are recommended. Originality/value - No study has yet to be conducted on the interrelationships of macroeconomic factors from the perspectives of FDI-Trade-Growth Nexus in Myanmar under the assumption of labor force and inflation rate as fundamental conditions. The current study also covered a relatively longer period of time series data from 1970 to 2016. This paper also conducts a case study of South Korea's experience in order to evaluate the findings and provide better policy implications.

• Journal of Korea Trade
• /
• v.24 no.4
• /
• pp.1-17
• /
• 2020

Purpose - Since China has been South Korea's biggest export destination, uncertainty shocks originating from it would influence South Korea's exports. This paper evaluates the effects of China's economic policy uncertainty on Korea's exports to explore the transmission channels. Design/methodology - Incorporating endogeneities and nonlinearities, this study employs a quarterly time-varying parameters vector autoregressive model to investigate the relationships between China's economic policy uncertainty and Korea's exports, where the overparameterization due to time-varying specifications is overcome by a novel stochastic model specification search framework. According to previous theoretical studies, this paper assesses two channels, demand shock channel and exchange rate channel, through which foreign uncertainty affects Korea's exports. This paper identifies the primary drivers of Korea's aggregate exports and analyzes the rationales for the time-variant impacts of China's economic policy uncertainty on Korea's exports to China. Findings - Our empirical results reveal that Korea's aggregate exports are less responsive to China's economic policy uncertainty shocks and significantly move together with global demand. In contrast, its bilateral exports to China are highly responsive in a negative and time-variant way. Moreover, Chinese investment is an important channel through which China's economic policy uncertainty affects Korea's exports to China after 2010. Further, the time-variant effects of China's economic policy uncertainty on Korea's exports to China are related to changes in China's foreign trade policies, global economic conditions, and China's degree of economic freedom. Originality/value - Few previous studies touch the effects of external uncertainty shocks on South Korea's exports. This paper attempts to fill this gap and explicitly investigate the impacts of China's economic policy uncertainty on Korea's exports from a time-varying perspective. As Korea is an export-oriented economy, this study provides insights for the Korean government to understand the transmissions of external uncertainty better.

• Journal of Korea Trade
• /
• v.25 no.3
• /
• pp.116-133
• /
• 2021

Purpose - Intra-industry trade of agricultural products can eliminate the disadvantage of Korea's traditional agriculture and improve its lack of comparative advantage. The main purpose of this paper is to measure the level and index of intra-industry trade of Korean agricultural products and to explore the spatial dependence and spillover effect associated with this type of trade. The main factors influencing intra-agricultural trade are analyzed from two perspectives: the population and the classification of agricultural products. Design/methodology - First, the level of intra-industry trade of Korean agricultural products is measured. Second, to obtain a more accurate estimate of the influence of various factors, and based on two types of weight matrices, a spatial econometric model is constructed from two aspects: population and classification of agricultural products. The status and the factors influencing intra-industry trade are also studied. Findings - It is concluded that there is a positive spatial correlation between Korea's intra-industry trade in agricultural products and that of its trading partners. The spatial spillover effect of this type of trade is verified by using the spatial autoregressive model (SAR). Labor-intensive agricultural products are found to have a positive spillover effect on intra-industry trade, while land-intensive products do not have a significant effect. Originality/value - In this paper, the two types of agricultural products are meticulously distinguished, and the spatial effect of the intra-industry trade of agricultural products as well as the influence of various factors are analyzed. In addition, the accuracy of the estimation of the coefficients of the factors by using the spatial econometric model is higher than that of the ordinary panel data model.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.243-251
• /
• 2022

In this paper, we propose a phenomenon that analyze the impact of market sentiment on China's real estate market through the perspective of behavioral economics. Previously, real estate market analyzation basically focus on some fundamental principles which include market price, monetary policies and income, etc. However, little research has explored market sentiment and its influence. By using principal components analysis (PCA), this study first creates buyer's sentiment and seller's sentiment to measure the heat of China's real estate market. Different from using traditional estimation method, the vector autoregressive model (VAR) is used to analyze how both sentiments affect real estate return. The overall results show that from unit root test and impulse response analyzation, the impact of seller's sentiment is positive to real estate market while buyer's sentiment is negative. At the same time, the higher seller's sentiment will have different influence on the housing market compared with the higher buyer's sentiment.

• Journal of Korea Trade
• /
• v.27 no.3
• /
• pp.103-118
• /
• 2023

Purpose - This study aims to examine the dynamic relationship between the variables impacted by the Regional Comprehensive Economic Partnership (RCEP) and the level of intra-industry trade among member states, with the ultimate objective of deducing the short- and long-term effects of RCEP on trade. Design/methodology - This study focuses on tariffs, GDP growth rates, and the proportion of regional FDI to total FDI as research variables, and employs a panel vector autoregression model and GMM-style estimator to investigate the dynamic relationship between RCEP and intra-industry trade among member countries. Findings - The study finds that the level of intra-industry trade between member states is positively impacted by both tariffs and intra-regional FDI. The impulse response graph shows that tariffs and FDI within the region can promote intra-industry trade among member countries, with a quick response. However, the contribution rates of tariffs and intra-regional FDI are not particularly high at approximately 1.5% and 1.4%, respectively. In contrast, the contribution rate of GDP growth can reach around 8.5%. This implies that the influence of economic growth rate on intra-regional trade in industries is not only long-term but also more powerful than that of tariffs and intra-regional FDI. Originality/value - The originality of this study lies in providing a new approach to investigating the potential impact of RCEP while avoiding the limitations associated with the GTAP model. Additionally, this study addresses existing gaps within the research, further contributing to the research merit of the study.

• Journal of Korea Trade
• /
• v.27 no.3
• /
• pp.147-160
• /
• 2023

Purpose - This paper aims to investigate the competitiveness and complementarity of the agricultural products trade between Korea and Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) countries. The study evaluates the opportunities and challenges that Korea's agricultural sector faces after joining the CPTPP, and suggests strategies to deepen cooperation and expand Korea's agricultural products trade. Design/methodology - To achieve these objectives, we analyze the trade competition and cooperation relationship between Korea and CPTPP countries in the agricultural products trade. This study uses data from Chapters HS1-24 in UN Comtrade from 2012 to 2022, and applies the indices of revealed comparative advantage, export similarity, and trade complementarity to examine the trade dynamics. Furthermore, we use an Autoregressive Integrated Moving Average (ARIMA) model to predict the agricultural products trade complementarity index between Korea and CPTPP countries from 2022 to 2031. Findings - The findings of our analysis reveal that Korea's agricultural products trade competitiveness is weak compared to that of CPTPP countries, and Korea's agricultural products are at a competitive disadvantage. On the whole, the similarity index of agricultural products trade exports between Korea and CPTPP countries is low, the structure of agricultural products export is quite different, and trade competition is relatively moderate. The trade complementarity index between Korea and CPTPP countries is generally high, with strong complementarity and a large space for cooperation and development. The ARIMA model shows that in the next ten years, although the agricultural products trade complementarity index fluctuates, but is generally high, there will still be a complementarity advantage in the future. Originality/value - This study is the first attempt to investigate the competitiveness and complementarity of the agricultural products trade between Korea and CPTPP countries. We also introduce an ARIMA model to forecast and analyze the future agricultural products trade complementarity index. Our study provides new perspectives and solutions for the future development of Korea's agricultural products trade after joining the CPTPP.

• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.127-139
• /
• 2023

Numerous genuine issues, for example, financial exchange expectation, climate determining and so forth has inalienable arbitrariness related with them. Receiving a probabilistic system for forecast can oblige this dubious connection among past and future. Commonly the interest is in the contingent likelihood thickness of the arbitrary variable included. One methodology for expectation is with time arrangement and auto relapse models. In this work, liner expectation technique and approach for computation of forecast coefficient are given and likelihood of blunder for various assessors is determined. The current methods all need in some regard assessing a boundary of some accepted arrangement. In this way, an elective methodology is proposed. The elective methodology is to gauge the restrictive thickness of the irregular variable included. The methodology proposed in this theory includes assessing the (discretized) restrictive thickness utilizing a Markovian definition when two arbitrary factors are genuinely needy, knowing the estimation of one of them allows us to improve gauge of the estimation of the other one. The restrictive thickness is assessed as the proportion of the two dimensional joint thickness to the one-dimensional thickness of irregular variable at whatever point the later is positive. Markov models are utilized in the issues of settling on an arrangement of choices and issue that have an innate transience that comprises of an interaction that unfurls on schedule on schedule. In the nonstop time Markov chain models the time stretches between two successive changes may likewise be a ceaseless irregular variable. The Markovian methodology is especially basic and quick for practically all classes of classes of issues requiring the assessment of contingent densities.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.13-13
• /
• 2020

'20년 3월 현재 전국 3,502개 읍면동 중 73개 읍면동이 지하수를 상수원으로 급수 중이며, 48개 산업단지에서 지하수를 주 수원으로 사용 중이다. 또한 급수 소외지역의 물 공급을 위해 주로 사용되는 소규모수도시설 14,811개 중 12,073개(81.5%)는 지하수를 이용하고 있으며, 그 위치는 전국에 산재해 있다. 이처럼 지하수는 댐, 저수지 및 하천과 더불어 생·공용수의 중요한 수원이라 할 수 있다. 본 연구에서는 급수 소외지역의 주요 수원인 지하수위 현황을 이용한 가뭄 모니터링 및 전망 기법을 개발하고자 하였다. 국가 지하수관측망 중 10년 이상 장기 관측 자료를 보유한 253개 관측소의 일단위 관측자료를 기반으로, 과거 관측수위 분포를 핵밀도함수로 추정하고 Quantile Function을 이용해 현재 수위의 높고 낮은 정도를 Percentile 값으로 산정하였다. 관측소별 지하수위 Percentile은 티센망을 이용해 167개 시군별로 공간평균하고 Percentile의 범위에 따른 가뭄등급을 설정하여 지하수 가뭄 정도를 모니터링 할 수 있는 기법을 제시하였다. 또한 지하수 가뭄을 전망하기 위해 강수와 지하수위의 거시적인 응답특성을 이용하였다. 관측소별로 추정된 핵밀도함수의 누적확률을 표준정규분포의 Quantile로 변환하여 표준지하수지수I(Standardized Groundwater level Index, SGI)를 산정하고, 시군별로 공간을 일치시킨 1~12개월 지속기간별 표준강수지수(Standardized Precipitation Index, SPI)와의 상관관계를 이용해 NARX(nonlinear autoregressive exogenous) 인공신경망 예측모형을 구축하였다. 이를 통해 기상청 정량전망 강수량을 이용해 전국의 1~3개월 후 지하수 가뭄을 빠르게 전망할 수 있는 체계를 구축하고, 생·공용수 분야 국가 가뭄 예·경보의 미급수지역 가뭄현황 및 전망에 활용중이다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.326-326
• /
• 2021

장기간에 걸쳐 넓은 지역에 대해 발생하는 가뭄을 예측하기위해 많은 학자들의 기술적, 학술적 시도가 있어왔다. 본 연구에서는 복잡한 시계열을 가진 가뭄을 전망하는 방법 중 시나리오에 기반을 둔 가뭄전망 방법과 실시간으로 가뭄을 예측하는 비시나리오 기반의 방법 등을 이용하여 미래 가뭄전망을 실시했다. 시나리오에 기반을 둔 가뭄전망 방법으로는, 3개월 GCM(General Circulation Model) 예측 결과를 바탕으로 2009년도 PDSI(Palmer Drought Severity Index) 가뭄지수를 산정하여 가뭄심도에 대한 단기예측을 실시하였다. 또, 통계학적 방법과 물리적 모델(Physical model)에 기반을 둔 확정론적 수치해석 방법을 이용하여 비시나리오 기반 가뭄을 예측했다. 기존 가뭄을 통계학적 방법으로 예측하기 위해서 시도된 대표적인 방법으로 ARIMA(Autoregressive Integrated Moving Average) 모델의 예측에 대한 한계를 극복하기위해 서포트 벡터 회귀(support vector regression, SVR)와 웨이블릿(wavelet neural network) 신경망을 이용해 SPI를 측정하였다. 최적모델구조는 RMSE(root mean square error), MAE(mean absolute error) 및 R(correlation Coefficient)를 통해 선정하였고, 1-6개월의 선행예보 시간을 갖고 가뭄을 전망하였다. 그리고 SPI를 이용하여, 마코프 연쇄(Markov chain) 및 대수선형모델(log-linear model)을 적용하여 SPI기반 가뭄예측의 정확도를 검증하였으며, 터키의 아나톨리아(Anatolia) 지역을 대상으로 뉴로퍼지모델(Neuro-Fuzzy)을 적용하여 1964-2006년 기간의 월평균 강수량과 SPI를 바탕으로 가뭄을 예측하였다. 가뭄 빈도와 패턴이 불규칙적으로 변하며 지역별 강수량의 양극화가 심화됨에 따라 가뭄예측의 정확도를 높여야 하는 요구가 커지고 있다. 본 연구에서는 복잡하고 비선형성으로 이루어진 가뭄 패턴을 기상학적 가뭄의 정도를 나타내는 표준강수증발지수(SPEI, Standardized Precipitation Evapotranspiration Index)인 월SPEI와 일SPEI를 기계학습모델에 적용하여 예측개선 모형을 개발하고자 한다.