• The Korean Journal of Applied Statistics
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• v.25 no.4
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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.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.255-263
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• 2024

GDP represents the total market value of goods and services produced by all economic entities, including households, businesses, and governments in a country, during a specific time period. It is a representative economic indicator that helps identify the size of a country's economy and influences government policies, so various studies are being conducted on it. This paper presents a GDP growth rate forecasting model based on a dynamic factor model using key macroeconomic indicators of G20 countries. The extracted factors are combined with various regression analysis methodologies to compare results. Additionally, traditional time series forecasting methods such as the ARIMA model and forecasting using common components are also evaluated. Considering the significant volatility of indicators following the COVID-19 pandemic, the forecast period is divided into pre-COVID and post-COVID periods. The findings reveal that the dynamic factor model, incorporating ridge regression and lasso regression, demonstrates the best performance both before and after COVID.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.387-396
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• 2014

The GDP gap (also called the output gap) is the difference between potential GDP and actual GDP. Potential GDP is the maximum sustainable output that is achieved when the resources (labor and capital) are used to capacity. Central banks pursuing price and employment stability consider the output gap as an informative variable for monetary policy since the output gap could be regarded as a proxy of demand-supply imbalances. In this paper, the GDP gap of Korea is decomposed following the filtering method in the previous research, and major factors that affect the variation of GDP gap are investigated based on the decomposed series. The analysis results by the Super Smoother algorithm used in Fox et al. (2003)and Fox and Zurlinden (2006) are found consistent with theory. Much of the variation of nominal GDP gap is explained by Total Factor Productivity(TFP) gap, which is the change of productivity due to recent technological innovation and environmental change. It is also found that variation of terms of trade significantly affects the GDP gap of Korea due to its high dependency on international trade; however, the effect of the domestic price is not negligible like other countries.

• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Knowledge Management Research
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• v.22 no.4
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• pp.103-118
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• 2021

Gross Domestic Product(GDP) is affected by the economic power of each industry. Therefore, using statistical data related to the food and drug industry, we tried to determine the proportion of GDP and analyzed the impact of the food, medical & drug industry on the domestic economy through comparison with other industries. The food, medical & drug industry has a wide range of industries among domestic industries and is closely related to the lives of the people. In addition, human lifespan is increasing, and recently, due to the spread of an infectious disease called COVID-19, the bio sector belonging to the food, medical & drug industry is in the spotlight. Attention is needed to the industry as the competitiveness of the food, medical & drug industry is expected to increase. The Ministry of Food and Drug Safety provides statistics on the food, medical & drug industry, but does not provide a systematic share of GDP. Since it is difficult to determine how influential the industry is compared to other industries, this study attempts to obtain the share of GDP in the food, medical & drug industry and compare it with other industries. In the process of obtaining GDP in the food, medical & drug industry sector, there was a difficulty in that the figures in statistical data were not unified by time point. In order to overcome the limitations, statistical data as a standard are determined. The GDP of the Food, Medical & Drug Industry was estimated using total added value, production, sales, and added value by industry. Compared to other industries, the Food, Medical & Drug Industry's GDP ranked second after the GDP of the manufacturing industry. As a result, it suggests that the food, medical & drug industry has a great influence on the national economic power among domestic industries.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.877-887
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• 2012

The Bank of Korea changed its method of GDP estimation from a fixed-weighted to a chain-weighted measure in 2009. The fixed-weighted method had had problems such as substitution bias and the rewriting of economic history. As a result of the change, annual growth rates calculated using the chain-weighted method from 1970 through 2008 turned out to be 0.8%p higher on average than the existing rates. The quarterly average chain-weighted growth rates were 0.19%p higher than the fixed-weighted ones, but they changed in the same directions. In this paper we analyze whether the differences in rates between the two calculation methods would bring about a difference in the cyclical characteristics of GDP. We conclude that although there were differences in growth rates after introduction of the chain-weighted method, there was no difference in the cyclical fluctuation.

• Journal of Korea Port Economic Association
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• v.22 no.3
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• pp.79-96
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• 2006

In this paper, using the gravity model, I examined that the port traffic in the port of Pusan have been influenced by GDP of South Korea, GDP of trading countries, an agreement on maritime transport, maritime transport charge and the local economic integration, etc. In view of the policy implication based on the result of analysis by the gravity model, the port traffic and the transshipment in the port of Pusan is positively influenced by GDP of South Korea, GDP of trading countries and countries on the way of main sea route(LINE). But it is negatively influenced by maritime transport charge. Especially, when a maritime transport charge goes up 1 percentage point, it is estimated that a transshipment decreases about 0.586-0.895 percentage point. So, a maritime transport charge was found to have more effect on a transshipment than a port traffic(except transshipment).

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.11-22
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• 2007

In this study, we have proposed the new statistical methods to convert the statistics based of workplace units into the statistics based of industrial units using the industrial survey data published by National Statistical Once in 2001. It could help to apprehend the weight of service sectors of korea small business in terms of the Gross Domestic Product (GDP).

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.397-404
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• 1999

1997년말 발생한 외환위기 이후 불확실성의 증대로 시계열모형을 이용한 경제예측에 한계가 노정되고 있다. 이를 극복하기 위하여 경제주체의 기대(expectation)를 파악할수 있는 기업경기실사지수를 경제예측에 도입할 필요가 있다. 본고에서는 기업경기실사지수를 이용한 모형과 시계열모형을 추정하고 이들을 예측력 측면에서 비교, 분석해보았다. 분석결과 불확실성이 높았던 외환위기이후 기간에는 기업경기실사지수를 이용한 모형이 시계열모형보다 예측력면에서 우수한 것으로 나타났다.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.75-88
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• 2009

Gross Regional Domestic Product (GRDP) is regarded as an essential information to understand regional economy. However, GRDP is hardly used for establishment of regional economic plan and related statistical research due to its late and yearly publication. Therefore, it is necessary to estimate quarterly GRDP to grasp the current regional economy faster In this study, considering the comovement between GDP and GRDP for the same industry, reference series are made. Quarterly GRDP is estimated the following two steps; First, preliminary quarterly GRDP is estimated using Chow-Lin's method based on the reference series to eliminate temporal discrepancies. Second, preliminary quarterly GRDP is adjusted using Denton's multivariate method to eliminate contemporaneous discrepancies.