• 응용통계연구
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• 제25권4호
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• pp.553-561
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• 2012

Various statistical models to Estimate GDP (measured as a nation's economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.

• 한국산림과학회지
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• 제84권2호
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• pp.121-130
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• 1995

미국 미시간주의 여행수요(旅行需要)를 예측(豫測)하기 위하여 사용되어진 여러 모델들의 예측정확성(豫測正確性)이 검토되었다. 8가지의 연년(連年)모델들은 2년까지 예측하는데 그리고 9가지의 분기(分期)모델들은 4분기(分期)까지 예측하는데 사용되어 졌다. 연년(連年)모델의 예측정확성(豫測正確性) 평가(評價)에서, 중회귀(重回歸)모델은 1년과 2년을 예측(豫測)하는데 있어 다른 방법들 보다 더 정확(正確)했다. 분기(分期)모델에 있어서는, Winters' exponential smoothing와 Box-Jenkins 방법이 1 분기예측(分期豫測)에 있어 naive 1 s 보다 더 정확(正確)했으나 2분기(分期), 3분기(分期), 4분기(分期)를 예측(豫測)하는데 이 방법(方法)들은 naive 1 s 보다 정확(正確)하지 않았다. 정교(精巧)한 모델들은 분기별(分期別) 예측(豫測)을 하는데 있어서 단순(單純)한 모델들보다 더 정확(正確)하지 않았다. 연년(連年)모델과 분기(分期)모델을 이용한 1년간(年間) 예측비교(豫測比較)에서, 중회귀모형(重回歸模型)은 연간자료(年間資料)보다 분기자료(分期資料)에 적용(適用)할 때 더 좋은 결과(結果)를 얻었으나 그 차이(差異)가 미약(微弱)하며 다른 모델들은 일관성(一貫性)있게 좋은 결과(結果)를 갖지 않으므로 연년(連年)모델보다 分期모델을 사용하도록 강력하게 권장할 수 없다. 연년(連年)모델은 기대(期待)하였던 것처럼 예측기간(豫測期間)이 길어짐으로서 예측정확성(豫測正確性)이 감소(減少)하였으나 분기(分期)모델은 이같은 결과(結果)를 나타내지 않았다.

• 통상정보연구
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• 제16권3호
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• pp.73-96
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• 2014

본 연구는 우리나라 수출 상위 5개 품목 중 하나인 자동차 수출을 대상으로, 승용차 브랜드별 단기 수출수요에 영향을 미치는 이론적 잠재요인을 발굴 및 설계하여 이론적 수출수요예측모델을 개발하고, 다변량시계열분석 기반의 VAR(Vector Auto Regressive)모형을 이용한 실증분석을 통해 개별상품과 시장특성이 반영된 단기수출수요예측모델을 검정하고자 하였다. 따라서 미국에 수출되고 있는 우리나라 소형 승용차 2개 브랜드(엑센트, 아반떼)에 대해 VAR모형을 이용한 분기단위 단기수요예측모델을 개발하고, 브랜드별 예측모델을 통해 산출된 t+1분기 시점의 예측값과 실제 판매된 판매대수를 대상기간을 1분기씩 달리하여 비교평가 하였다. 그 결과 엑센트와 아반떼의 RMSE %는 각각 4.3%와 20.0%로 났으며, 일평균 판매량을 기준으로 보았을 때 엑센트는 3.9일에 해당하고 아반떼는 18.4일에 해당하는 물량임을 알 수 있었다. 따라서 본 연구의 단기수출수요예측모델은 예측력과 검정시점별 일관성 측면에서 활용성이 높은 것으로 평가할 수 있었다.

• 가정과삶의질연구
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• 제20권1호
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• pp.45-56
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• 2002

The main purposes of this article are to introduce the theoretical backgrounds and empirical application methods of two different Models for the function of expenditure, and to compare the goodness-o(-fit of the two models: a single-equation model and a complete-system-of-demand-equation model. For the empirical analysis of the single-equation model, a linear formula and a double-leg formula were employed. In order to test the complete-system-of-demand-equation model empirically, the \"Linear Approximation/Almost Ideal Demand System (LA/AIDS)" was used. The independent variables were the total living expense and expenditure categories Price index. The data used in this study were obtained from the quarterly statistics of "The Annual Report on the Urban Family Income and Expenditure Survey (Dosigagyeyonbo)" and "The Annual Report on the Consumer Price Index (Sobijamulgajaryo)," for the years 1994 to 1997. The goodness-of-fit (R-square) was higher with the complete-system-of-demand-equation model than with the single-equation model for the budget share on food (excluding eating-out expenses) and for the share on cultural and recreational activities. However, there was no difference between the two models in terms of the proportion of the expenditure on automobile fuel.fuel.

• The Journal of Asian Finance, Economics and Business
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• 제3권2호
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• pp.33-39
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• 2016

This study empirically evaluates the impact of exchange rate volatility, foreign direct investment, terms of trade, inflation, and industrial production and foreign exchange reserves on Pakistani trade volume over the period of 1975-2010 using quarterly data set. The study employs financial econometrics methods such as Augmented Dickey Fuller (ADF) test GARCH (1, 1) technique and Almon Polynomial Distributed Lag (APDL) models to estimate the relationship of variables. Findings of the study are in accordance with theoretical relationships presented by Clark, Tamirisa, Wei, Sadikov, & Zeng (2004), McKenzie (1999), Dellas & Zilberfarb (1993) and Côté (1994). These findings are also in accordance with the empirical studies which support positive relationship of exchange rate volatility and exports presented by Hsu & Chiang (2011), Chit (2008), Feenstra & Kendall (1991), Esquivel & Larraín (2002) and Onafowora & Owoye (2008). Findings of the study in terms of imports are supported by the studies such as Lee (1999), Alam & Ahmad (2011) and Arize (1998). The study also recommends some very important policy prescriptions.

• The Journal of Asian Finance, Economics and Business
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• 제1권3호
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• pp.17-28
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• 2014

The paper deals with the impact of the product distribution and information technology sectors on energy resource use, carbon emissions and economic growth by examining the long-run equilibrium relationships and Granger causal relationships among these variables in South Korea. The quarterly time series data from the first quarter of 1970 to the third quarter of 2010 (163 observations) are collected and retrieved from the Bank of Korea database. The paper examines the long-run equilibrium relationships using cointegration techniques and Granger causality using vector error correction models. Test results indicate a long-run equilibrium relationship exists among these variables. In testing directional causality, both the product distribution and the information technology sectors show direct effects on economic growth but only marginal effects on carbon emissions.

• 통합자연과학논문집
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• 제1권2호
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• pp.127-132
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• 2008

This project follows the heterogeneous agent market segmented model of Landon-Lane and Occhino (2007) with using Korean data, M1 and GDP deflator from 1882:I to 2007:II. This paper estimates parameters with Monte Carlo Markov Chain. The fraction of traders, ${\lambda}$, in Korea is 15.64%. The quarterly preferences discount factor's, ${\beta}$, posterior mean is 0.9922. The posterior mean of the inverse of the elasticity of the labor supply to the real wage, ${\varphi}$, is 0.0316. The elasticity of the labor supply to the real wage has a very large value. By Hansen (1985) and Christiano and Eichenbaum (1992) and Cooley and Hansen (1989), models having large elasticity of the aggregate labor supply better match macroeconomic data.

• 유통과학연구
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• 제10권6호
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• pp.7-15
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• 2012

The paper deals with the impact of information and communications technology on carbon emissions and economic growth in South Korea. The quarterly time series data from the first quarter of 1970 to the third quarter of 2010 (163 observations) are collected and retrieved from the Bank of Korea database. The paper examines long-run equilibrium relationships using cointegration techniques and Granger causality with vector error correction models. In directional causality tests, information and communications technology shows highly significant positive effects on economic growth and marginal effect on carbon emissions. Carbon emissions and economic growth exhibit an inverse relationship with each other; that is, carbon emissions have an inverse relation to economic growth and economic growth does not significantly affect carbon emissions in South Korea. We also note possible implications regarding growth policies and the information communications technology and "green" technology sectors for economies in the range represented by Korea's 1970 - 2010 data.

• 대한안전경영과학회지
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• 제19권4호
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• pp.87-94
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• 2017

The purpose of this study is to provide basic data to help ensure the safety and enhance industrial competitiveness of plant construction projects by analyzing the safety management status of, mainly, chemical engineering plant construction projects, and proposing specific measures and models to reduce human/educational, technical/systemic, institutional disasters. This study was done using literature research and case study/empirical study methods. The results of this study are summarized as follows. First, we classified the major disasters from the quarterly released 'major diaster cases in construction business' from Korea Occupational Safety and Health Agency according to the type of construction and presented the causes and prevention measures.

• 시큐리티연구
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• 제30호
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• pp.139-169
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• 2012

본 연구는 살인, 강도, 강간, 절도, 폭력 등 주요 범죄를 예측할 수 있는 시계열 모형을 도출하고 이를 이용한 주요 범죄의 발생 전망을 파악하여 범죄 발생에 대한 과학적인 치안정책 수립에 기여하는데 그 목적이 있다. 이와 같은 목적을 달성하기 위하여 2002년부터 2010년까지의 살인, 강도, 강간, 절도, 폭력 등 주요범죄에 대한 월별 발생건수를 IBM PASW(SPSS) 19.0을 사용하여 주요 범죄의 시계열 예측모형을 규명하기 위한 시계열 모형생성(C), 주요 범죄의 시계열 예측모형에 대한 정확도 규명을 위한 시계열 모형생성(C) 및 시계열 순차도표(N)를 실시하였다. 이와 같은 연구목적과 연구방법을 통하여 도출한 연구결과는 다음과 같다. 첫째, 살인, 강도, 강간, 절도, 폭력 등 주요 범죄에 대한 시계열 예측모형은 각각 단순계절, Winters 승법, ARIMA(0,1,1)(0,1,1), ARIMA(1,1,0)(0,1,1), 단순계절로 나타났다. 둘째, 살인, 강도, 강간, 절도, 폭력 등 주요 범죄에 대하여 시계열 예측모형을 이용한 주요 범죄에 대한 단기적 발생 전망이 가능한 것으로 나타났다. 이러한 연구결과를 토대로 범죄 발생에 대한 지속적인 시계열 예측모형 제시, 분기별, 연도별 범죄 발생건수를 기초로 하는 중 장기 시계열 예측모형에 대한 관심이 요구된다.