• Journal of the Korean Data and Information Science Society
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• 제18권1호
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• pp.73-80
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• 2007

Cointegration(together with VARMA(vector ARMA)) has been proven to be useful for analyzing multivariate non-stationary data in the field of financial time series. It provides a linear combination (which turns out to be stationary series) of non-stationary component series. This linear combination equation is referred to as long term equilibrium between the component series. We consider two sets of Korean bivariate financial time series and then illustrate cointegration analysis. Specifically estimated VAR(vector AR) and VECM(vector error correction model) are obtained and CV(cointegrating vector) is found for each data sets.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.647-654
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• 2021

This study examines the non-performing loans of rural banks and macroeconomic factors in Indonesia, including inflation, exchange rates, and interest rates. Theoretically, the existence of erratic macroeconomic conditions can affect the level of non-performing credit risk in rural credit banks in Indonesia. The effect of macroeconomic conditions on non-performing loans has a different response for each economic sector. The main objective of this study is to determine the effect of macroeconomic factors (inflation, exchange rates, and interest rates) and bank-specific factors (credit) on the Non-Performing Loans (NPL) of Rural Banks in Indonesia for the period from January 2015 to December 2018. This study uses a Vector Error Correction Model (VECM) estimation to determine the effect of independent variables consisting of macroeconomic factors and bank-specific factors. Based on the estimation results of the Vector Error Correction Model, three variables that have a positive and significant effect on long-term non-performing loans are credit, inflation, and interest rates. Meanwhile, in the short term, there are only two variables that have a positive and significant effect on non-performing loans, namely, credit and interest rates. Inflation and exchange rate variables have a negative and insignificant effect on bad credit in the short term.

• 산경연구논집
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• 제9권5호
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• The Journal of Asian Finance, Economics and Business
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• 제5권4호
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• pp.85-94
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• 2018

The cultural industry is treated as the sunrise industry in modern society. It has taken an increasing role in promoting the economic growth. Due to this, this paper attempts to explore the dynamic relationship between cultural industry and the economic growth. On the grounds of Cobb-Douglas production function, the cultural industry is regarded as a determinant such as the labor input and the capital input to impact the economic growth. Meanwhile, the quarterly datum form 2000-Q1 to 2017-Q4 are employed to perform an empirical analysis via the vector error correction model. The GDP is treated as an independent variable. The input of capital, the input of labor and the total input of cultural industry are treated as dependent variables. Furthermore, a menu of statistical approaches such as the co-integration test and the impulse response function will be used to testify the dynamic relationship between cultural industry and economic growth. Via the Johansen co-integration test, the results report that the cultural industry has a obviously positive effect on economic growth. Through the vector error correction estimation, the results also report that the cultural industry also has a significantly positive effect on economic growth, but less than that of the Johansen co-integration test. This paper provides a view that the cultural industry is a kind of a determinant to promote the economic growth. Therefore, the China's government should pay much attention to the cultural industry construction.

• Ocean and Polar Research
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• 제34권2호
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• pp.185-195
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• 2012

This paper focused on forecasting a short-term production of oysters, which have been farmed in Korea, with distinct periodicity of production by year, and different production level by month. To forecast a short-term oyster production, this paper uses monthly data (260 observations) from January 1990 to August 2011, and also adopts several econometrics methods, such as Multiple Regression Analysis Model (MRAM), Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Vector Error Correction Model (VECM). As a result, first, the amount of short-term oyster production forecasted by the multiple regression analysis model was 1,337 ton with prediction error of 246 ton. Secondly, the amount of oyster production of the SARIMA I and II models was forecasted as 12,423 ton and 12,442 ton with prediction error of 11,404 ton and 11,423 ton, respectively. Thirdly, the amount of oyster production based on the VECM was estimated as 10,425 ton with prediction errors of 9,406 ton. In conclusion, based on Theil inequality coefficient criterion, short-term prediction of oyster by the VECM exhibited a better fit than ones by the SARIMA I and II models and Multiple Regression Analysis Model.

• 응용통계연구
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• 제26권6호
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• pp.1043-1051
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• 2013

본 논문에서는, 구조적 오차수정모형을 한국의 노동시장 자료에 적용함으로써, 실업률에 미치는 구조적 충격의 영향을 분석한다. 이를 위하여 기술력, 노동수요, 노동공급, 임금 부문에서의 충격을 정의하였으며, 이를 각각 노동생산성, 취업자 수, 실업률, 실질임금과 연결하였다. 그 결과로서, 노동수요 및 노동공급 충격이 각각 장기적 및 단기적으로 실업률에 유의한 영향을 미치는 것으로 나타났다.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.25-32
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• 2022

This study analyzes the impact of occupational accidents on economic growth and labor productivty losses in Korea between January 2008 and July 2018, using the Vector Error-Correction Model (VECM). According to the analysis, the occurrence of occupational accidents was revealed to reduce the number of employed workers and also hinder economic growth. This can be reinterpreted as the reduction of occupational accidents does not cause labor losses in the industry, rather may induce economic growth. Also, the findings discovered that an increase in the number of workers may lead to increase in the probability of occupational accidents in the short term. This suggests that greater number of work-related accidents may occur during the early stages- due to new employees' lack of knowledge related to safety at workplace.

• 지역연구
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• 제35권1호
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• pp.47-57
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• 2019

본 연구의 목적은 계량분석을 통해 우리나라 지역내총생산에 영향을 미치는 주요 요인별 영향력을 분석하는 것이다. 본 연구는 분석대상 지역으로 대구광역시를 선정했는데 대구광역시는 영남 지역의 중추기능을 지속적으로 수행해 왔으며, 우리나라 섬유 화학제품 등의 수출 전략기지로 지위하고 있다. 또한 영남 지역에 도달하는 주요 수입화물의 기종점 역할을 수행하는 등 이처럼 대구 지역은 우리나라 수출입 무역 확대와 국가경제 성장에 기여하는 바가 높다. 이를 위해 본 연구는 공적분모형(Co-integration Model)과 벡터오차수정모형(Vector Error Correction Model; VECM)을 사용하여 대구 지역내총생산에 영향을 미치는 장기균형함수를 추정하였다. 본 연구는 우리나라 지역내총생산에 영향을 미치는 주요 요인들의 영향력을 정량적인 방식을 통해 추정하고 장기 균형 시점의 총생산으로부터 괴리가 발생했을 때 얼마나 빠른 속도로 장기균형으로 수렴하는가를 추정하였다는 점에서 의의가 있다.

• 응용통계연구
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• 제29권1호
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• pp.61-73
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• 2016

본 논문에서는 다변량 시계열 모형 진단을 위해 잔차의 자기상관성 유무를 확인하기 위한 와일드 붓스트랩(wild bootstrap) Ljung-Box(LB) 검정통계량을 연구하였다. 일반적으로 LB 검정은 오차가 서로 독립이며 동일한 분포를 따른다는 IID 가정 하에 유도되는 점근적 카이제곱 분포를 이용한다. 한편 금융시계열 자료는 분산에 조건부 이분산성이 존재하기 때문에 오차의 IID 가정을 만족시키지 못하며 이에 따라 점근적 분포를 이용한 LB 검정은 제1종의 오류를 만족시키지 못하게 된다. 이를 극복하기 위해 와일드 붓스트랩을 이용한 LB 검정법을 제안하고 그 성질을 연구하고자 한다. 벡터자기회귀 모형과 벡터오차수정 모형 등의 다양한 다변량 시계열 모형을 이용하여 모의실험을 실시하는 한편, 코스피 200지수와 지수선물 자료를 이용한 실증분석을 통해 와일드 붓스트랩을 이용한 LB 검정법이 조건부 이분산성의 부정적인 영향을 효과적으로 제거할 수 있음을 입증하였다.

• The Journal of Asian Finance, Economics and Business
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• 제5권3호
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• pp.7-17
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• 2018

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the Korea Stock Exchange. The data is restricted to the period for which monthly data are available from January 1986 to October 2016 (370 observations) retrieved from the Economic Statistics System database sponsored by the Bank of Korea. The study employs unit root test, cointegration test, vector error correction estimates, impulse response test, and structural break test. The results of the Johansen cointegration test indicate at least three cointegrating equations exist at the 0.05 level in the model, confirming that there is a long-run equilibrium relationship between stock prices and macroeconomic variables in Korea. The results of vector error correction model (VECM) estimates indicate that money supply and short-term interest rate are not related to stock prices in the short-run. However, exchange rate is positively related to stock prices while the industrial production index and inflation are negatively related to stock prices in the short-run. Furthermore, the VECM estimates indicate that the external shock, such as regional and global financial crisis shocks, neither affects changes in the endogenous variables nor causes instability in the cointegrating vector. This study finds that the endogenous variables are determined by their own dynamics in the model.