• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.37-60
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• 1992

This paper applies a Structural VAR approach to a 4 variable system in real GNP, M2, GNP deflator and nominal monthly earnings, disentangling 4 structural shocks, i.e., aggregate demand and supply shocks, wage pushes and various forms of regulations reinforced especially during stabilization process. Preliminary diagnostic tests confirm that the log level of each time series has at least one unit root, though the evidence is somewhat ambiguous for real GNP. One co-integration relationship is found among 4 variables, while no co-integration is found in a subsystem consisting of nomina) variables. The absence of co-integration among nominal variables strongly suggested that money is not neutral even in the long-run. The reduced form is estimated and the structural form is recovered using 6 additional identifying restrictions. Recovered structural shocks are able to capture main episodes of past 20 years, ranging from first and second oil shocks, to strong stabilization policy of early 80's and rapid wage hikes of late 80's. Overall responses of the economy to each structural shock are usually consistent with the standard Keynesian predictions, though some responses seem to be specific to Korean economic environment.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.179-185
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• 2016

This study verifies whether speculative trading in commodity markets acted as the primary cause of the increase in commodity prices after the global financial crisis using the Structural Vector Autoregressive (SVAR) model. The effects of speculative trading on commodity prices increased by a factor of 3 to 6 after the crisis compared to those before the crisis. Although the demand related variables, such as industrial production, affected commodity prices significantly before the crisis, their effects decreased after the crisis. Consequently, the rebound of commodity prices after the crisis was mainly caused by the increase in speculative money, fortified by the expansion of the global liquidity supply. The global liquidity may well increase in the future, because the U.S. Federal Reserve Board is likely to continue to increase its interest rate. This study claims that when global liquidity shrinks as a result of a change in the Fed's monetary policy stance, speculative trading will slow down, leading to a decline in commodity prices.

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

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.3-62
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• 2004

This paper estimates Korea's natural rate of unemployment using various estimation methods such as pure time-series methods, reduced-form methods, and structural form methods, with discussion about relative advantages and disadvantages of each estimation method. This paper also provides the confidence interval of the estimated natural rate of unemployment by the Monte Carlo integration method. Though multivariate unobserved component model exhibits better performance in many aspects than other estimation methods, awareness should be raised for a potential misspecification problem of a multivariate unobserved component model. Considering that each method has its own advantages and disadvantages, it is recommended to make an inference on the natural rate of unemployment based on common results among various methods. Korea's natural rate of unemployment was estimated to be around 3.8~4.0% on average in the period of 1979:I~1987:IV, and to decline to 2.5~2.9% in the period of 1988:I~1997:IV. During the Asian crisis, it is estimated to peak at near 4.8% and to have been on a downward trend since then.

• Journal of Environmental Policy
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• v.10 no.4
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• pp.3-37
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• 2011

This paper investigates the existence of the environmental Kuznets curve (EKC) for carbon dioxide $CO_2$ emissions and its causal relationships with economic growth and openness by using time series data (1971-2006) from China (an emerging market), Korea (a newly industrialized country), and Japan (a developed country). The sample countries span a whole range of development stages from industrialized to newly industrialized and emerging market economies. The environmental consequences according to openness and economic growth do not show uniform results across the countries. Depending on the national characteristics, the estimated EKC show different temporal patterns. China shows an N-shaped curve while Japan has a U-shaped curve. Such dissimilarities are also found in the relationship between $CO_2$ emissions and openness. In the case of Korea, and Japan it represents an inverted U-shaped curve while China shows a U-shaped curve. We also analyze the dynamic relationships between the variables by adopting a vector auto regression or vector error correction model. These models through the impulse response functions allow for analysis of the causal variable's influence on the dynamic response of emission variables, and it adopts a variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the causal variables over time. Results show evidence of large heterogeneity among the countries and variables impacts.

• Korea Trade Review
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• v.42 no.2
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• pp.145-174
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• 2017

Recently, due to the worsening global economic recession, Korea which is a small, export-oriented economy has decreased exports and the domestic economy also continues to stagnate. Therefore, for continued growth of our economy through export growth, we need to analyze the validity of export support system such as export insurance and prepare ways to expand exports. This study is to investigate the effects of Export Insurance on the exports of SMEs as well as LEs. For this purpose, this study conducted Time Series Analysis using data such as export, export insurance acquisition, export price index, exchange rate, and coincident composite index(CCI). First, as a result of the Granger Causality Test, the exports of LEs has found to have a causal relationship with the CCI, and CCI is to have a causal relationship with the short-term export insurance record. Second, the results of VAR analysis show that the export insurance acquisition result and the export price index have a positive effect on the exports of LEs, while the short - term export insurance has a negative effect on the exports of LEs. Third, as a result of variance decomposition, the export of LEs has much more influenced for mid to long term by the short-term export insurance acquisition compared to SMEs. Fourth, short-term export insurance has a positive effect on exports of SMEs. In order to activate short-term export insurance against SMEs, it is necessary to expand support for SMEs by local governments. This study aims to suggest policy implications for establishing effective export insurance policy by analyzing the effects of export insurance on the export of SMEs as well as LEs. It is necessary to carry out a time series analysis on the export results according to the insurance acquisition results by industry to measure the export support effect of export insurance more precisely.

• Management & Information Systems Review
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• v.34 no.4
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• pp.67-81
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• 2015

The purpose of this study was to evaluate the effect of this factor on the macroeconomic variables for the healthcare industry market. First, the government bond interest rates and the exchange rate is the cause variable of drug industry index. Drug industry index is a mutual influence between the Call interest rate. Second, the medical equipment index haver mutual cause variable such as call rate index, government bond interest rates, and exchange rate. A current account balance variable is the cause variable of drug industry index. Third, the drug industry index has a negative relationship with a Call interest rate and an exchange rate. but it has a positive relationship with a government bond interest rates. the medical equipment index has a negative relationship with an exchange rate. but it has a positive relationship with a government bond interest rates.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.457-467
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• 2015

Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.206-213
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• 2024

This paper aims to investigate the causal relationship between geopolitical risk and stock price volatility in the shipping industry. Given its international nature and dependence on global trade, this industry is exposed to various uncertainties and risk factors. This study specifically focuses on the impact of geopolitical risk, which has gained significant attention in recent years due to events such as the Russia-Ukraine War and the Israel-Hamas War. To analyze this relationship, the study utilizes vector autoregressive model-based causality tests. The research estimates the causal relationship between geopolitical risk indicators and the stock price volatility of five shipping companies listed on the Korea Exchange. The study covers the period from 2000 to 2023. The results indicate the following: Firstly, an increase in geopolitical risk leads to a rise in stock price volatility for shipping companies. Moreover, the impact of actual geopolitical events, rather than just diplomatic disputes, is statistically significant. Lastly, the impact of geopolitical risk is particularly significant in the bulk shipping sector.