• 재무관리연구
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• 제19권2호
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• pp.211-231
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• 2002

본 연구의 목적은 VECM(Vector Error Correction Model)과 인공지능모형(Artificial Neural Networks)을 이용하여 우리나라 증권시장과 거시경제 변수들과의 장기적 관계에 대한 설명력을 비교해보고자 함에 있다. VECM이 APT(Arbitrage Pricing Theory)에 기초를 둔 선형동학모형이라고 한다면, 인공지능모형은 비모수적 비선형모형이라는 점에서, 두 방법론의 분석결과를 직접 비판하는 것은 의미있는 연구라고 할 수 있다. 인공지능모형을 주로 활용하는 선행연구들에 의하면, 증권시장은 시장의 특이패턴들로 인해 계량경제학적 접근인 선형 모형보다는 인공지능모형을 통해 증권시장의 움직임을 설명하고 예측하는 것이 더 바람직할 수도 있다는 것이다. 따라서, 본 연구에서는 VECM분석에서 자료의 안정성을 검증하고, 공적분 백터를 발견한 이후, 장기적 균형관계의 실증적 분석을 하였다. 그리고, 인공지능모형에서는 delta rule과 Sigmoid 함수를 이용한 GRNN(General Regression Neural Net)과 Back-Propagation등의 방법들을 활용하였다. 이러한 분석결과, Back-Propagation 모형이 다른 모든 모형들보다도 더 우수한 설명력을 보여주고 있었다. 이러한 결과들은 인공지능모형이 동태적인 선형 모형보다도 더 우수한 설명력을 제공할 수 있는 가능성을 보여주고 있었다.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.141-154
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• 2002

Foreign investors'shares and their influences on the Korean stock market have never been larger and greater before since the market was completely open to foreign investors in 1992 Quantitatively and qualitatively as well, as a result, changes in the patterns of foreign investments have caused enormous effects on the interactions of major macroeconomic indices of the Korean economy. This paper is intended to investigate the causal relations of the four variables, foreigners'buy-sell ratios, stock returns, ￦/＄ exchange rates and $\yen$/＄ exchange rates, over the two time periods of the pre-IMF (1996.1.1-1997.8.15) and the post-IMF (1997.8.16-2000.6.15) based on the daily data of the variables. Granger Causality Test, Forecast Error Variance Decomposition(FEVD) using VAR model and Impulse Response Function were implemented for the empirical analysis.

• KDI Journal of Economic Policy
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• 제42권2호
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• pp.57-84
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• 2020

This study analyzes global inflation synchronization and derives policy implications for the Korean economy. Unlike previous studies that assume a single global inflation factor, this study investigates if inflation in Korea can be explained further by other global inflation factors. Our principal component analysis provides three principal components for global inflation that are linked to the Korea inflation rate - the first component is closely related to OECD inflation, and the second and third components reflect China's inflation. This study empirically demonstrates via in-sample fitting and out-of-sample forecasting that the three principal components of global inflation play a significant role in explaining and predicting Korean inflation in the short-term, while their role is limited in the mid-term. Domestic macroeconomic variables are found to be more important for the mid-term movements of the Korean inflation rate. The empirical results here suggest that the Bank of Korea should focus more on domestic economic conditions than on global inflation when implementing monetary policy because global factors are likely to be already reflected in domestic macro-variables in the mid-term.

• East Asian Economic Review
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• 제22권4호
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• pp.507-529
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• 2018

This paper evaluates the whole impact of quantitative easing on inflation in Korea implemented by the central banks in four major advanced economies, the U.S., Euro Area, U.K. and Japan. According to the analysis employing a VAR-X model with the security holdings of those central banks an exogenous variable, quantitative easing is estimated to exert downward pressures on inflation in Korea. Considering the impulse responses of Korean macroeconomic variables to a quantitative easing shock, the spillover effect is transmitted through exchange rate channel while trade channel turns out to be ineffective. In an additional analysis assessing the impact of each quantitative easing program of the central banks, only those of the Fed and European Central Bank are estimated to be significant. The empirical results prove to be robust even if using long-term interest rates as an alternative indicator of quantitative easing.

• Communications for Statistical Applications and Methods
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• 제26권5호
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• pp.497-506
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• 2019

Forecasting the U.S. employment level is made using machine learning methods of the artificial neural network: deep neural network, long short term memory (LSTM), gated recurrent unit (GRU). We consider the big data of the federal reserve economic data among which 105 important macroeconomic variables chosen by McCracken and Ng (Journal of Business and Economic Statistics, 34, 574-589, 2016) are considered as predictors. We investigate the influence of the two statistical issues of the dimension reduction and time series differencing on the machine learning forecast. An out-of-sample forecast comparison shows that (LSTM, GRU) with differencing performs better than the autoregressive model and the dimension reduction improves long-term forecasts and some short-term forecasts.

• KDI Journal of Economic Policy
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• 제42권4호
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• pp.27-58
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• 2020

This paper intends to examine the extent of the fiscal contribution of immigrants to Korea. According to this analysis, the aim is to derive implications pertaining to the direction of Korea's immigration policy as a response to fiscal problems caused by population aging. For this purpose, a macroeconomic model is designed to measure the lifetime net fiscal contribution of immigrants in Korea by visa type, age, and other characteristics. According to this analysis, the sum of the lifetime fiscal contribution for all immigrants in Korea is negative. This implies that immigration policy reforms that increase the inflow size while maintaining the current structure of the foreign population characteristics can rather worsen Korea's fiscal problems. This finding suggests that immigration policy reform may exacerbate Korea's fiscal soundness if it simply targets the maintenance of the numerical balance of the demographic structure.

• The Journal of Asian Finance, Economics and Business
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• 제9권7호
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• pp.197-203
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• 2022

The agricultural sector has an important contribution to the economic development of Vietnam in particular and other countries in general. The growth of enterprises in the industry is an important bridge in promoting the economic development of the country. Currently, the policies of the Government of Vietnam always create favorable conditions for enterprises to conduct business, especially enterprises in the agricultural sector. The study aims to assess factors influencing the profitability of listed firms in Vietnam's stock market. Using 40 enterprises in the agricultural industry listed on the Ho Chi Minh City Stock Exchange and the Hanoi Stock Exchange and using advanced econometric modeling, dealing with defects in the regression model, the research results show that large-scale firm has higher economic efficiency than small-scale firm. In addition, a firm with higher use of loan capital is associated with a more efficient firm, reflected in the relatively good debt management ability of enterprises in the agricultural sector. Adversely, growth and age do not have any impact on firm performance. Macroeconomic factors do not impact profitability. Finally, the study has some policy implications for developing agricultural businesses in the case of Vietnam.

• KDI Journal of Economic Policy
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• 제44권1호
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• pp.77-98
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• 2022

This paper empirically verifies that the types of capital adjustment costs serve as an important mechanism in relation to investment decision-making after confirming that the investment dispersion of Korean firms is pro-cyclical and can affect business cycles. Specifically, it is found through empirical methods using corporate financial data that capital adjustment costs generally assumed to take a quadratic form in macroeconomics are asymmetric and irreversible in the Korean economy. In particular, capital adjustment costs are empirically proven to cause investment dispersion to expand given that the substitution effect of the marginal value to the marginal cost for one unit of investment in the inter-temporal investment decision is affected by that cost with regard to the resale of owned equipment assets, as opposed to new investments in equipment assets. We ultimately show, albeit indirectly, that investment dispersion can affect business cycles as capital adjustment costs influences investment decisions. What is implied is that the capital adjustment cost is not merely an exogenously deep parameter that fits the dynamics of business cycles in a macroeconomic model but could instead be a policy variable that can be endogenized through government policies.

• East Asian Economic Review
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• 제28권1호
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• pp.95-140
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• 2024

This study empirically investigates the international transmission of China's uncertainty shocks. It estimates a time-varying parameter Bayesian global structural vector autoregressive model (TVP-BGVAR) using time series data for 33 countries to evaluate heterogeneous international linkage across countries and time. Uncertainty shocks are identified via sign restrictions. The empirical results reveal that an increase in uncertainty in China negatively affects the global economy, but those effects significantly vary over time. The effects of China's uncertainty shocks on the global economy have been significantly altered by China's WTO accession, the global financial crisis, and the recent US-China trade conflict. Furthermore, the effects of China's uncertainty shocks, typically on inflation, differ significantly across countries. Moreover, Trade openness appears crucial in explaining heterogeneous GDP responses across countries, whereas the international dimension of monetary policy appears to be important in explaining heterogeneous inflation responses across countries.

• 인터넷정보학회논문지
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• 제15권6호
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• pp.99-106
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• 2014

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험 모형의 기반이 된다. 하지만 대부분의 지식 모델은 특정 지표나 정제된 데이터를 수동적으로 모델링하여 분석에 활용한다. 본 논문에서는 텍스트 마이닝 기술을 통해 방대한 비정형 정보로부터 지식 모델을 구성하는 토픽인자와 관계 노드를 생성하고 이를 통합하는 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다.