• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.352-361
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• 2013

The purpose of this study is to analyse the impact of macroeconomic and non-macroeconomic forces on the management performance of the air transport firms and offer the useful information to the managers. To conduct the regression analysis, eight macroeconomic and non-macroeconomic variables were selected individually as an independent variable. Macroeconomic variables were the return of corporate bond, West Texas Intermediate, the unemployment rate, the money supply, the trade balance, the won to USD exchange rate, the consumer price index and the index of industrial production. And non-macroeconomic variables were Taiwan earthquake, the Asian economic crisis, the 911 terrorist attacks in the US, the Iraq war, Beijing Olympic, the outbreak of a swine flu epidemic, the 1st presidential election and the 2nd presidential election. And ROA was selected as a dependent variable. As the result of analysis, it was found that the changing rates of won to USD exchange rate and consumer price index affected the changing rate of ROA significantly. And also as the result of analysing the impact of two significant macroeconomic variables and eight non-macroeconomic variables on the changing rate of ROA, it was found that the Asian economic crisis and the outbreak of a swine flu epidemic had a negative impact on it. Therefore managers should take note of a change in macroeconomic and non-macroeconomic variables carefully to improve the management performance.

• Journal of Distribution Science
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• v.22 no.6
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• pp.1-10
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• 2024

Purpose: This study's objective is to examine the impact of firm-specific and macroeconomic factors on the business performance of non-cyclical and cyclical sectors in Indonesian listed firms. The evaluation of business performance holds paramount importance for the achievement and long-term viability of a company. Research Design Data and Methodology: The data for 61 non-cyclicals sector companies and 57 cyclicals sector companies was gathered over a 4-year period from 2018-2021. The model integrates firm size, leverage, and sales growth as firm-specific factors, with real GDP growth and inflation rate as macroeconomic variables. ROA and ROE are indicators of a firm's business performance. The regression models are estimated using the distribution of a dynamic approach with Arellano-Bond Panel Generalized Method of Moments (GMM) estimation. Results: The results of the pooled sample indicate that the historical ROA and ROE have a positive relationship with the business performance of all sectors, including both non-cyclical and cyclical industries. The ROE of non-cyclical enterprises is primarily influenced by firm-specific characteristics and macroeconomic influences. Conclusion: To ensure the successful implementation of the distribution of a dynamic approach towards enhancing corporate business performance, organizations need to take into account a combination of firm-specific factors and macroeconomic factors.

• Korean Journal of Social Welfare
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• v.58 no.3
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• pp.245-268
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• 2006

The purpose of this study is to investigate the empirical relation between economic growth and poverty in Korea. Especially, the focus is put on exploring if there are any changes in the relation of economic growth and poverty. From 1982-2004 Korea Urban Household Survey, I constructed the annual data of poverty rate. I also obtained the annual data of the real GDP and the unemployment rate from the National Statistical Office. Using these annal data of the poverty rate and the macroeconomic performance, I analyzed the relation of them. As the result, I found that the macroeconomic growth have played very important role in reducing the poverty rate in Korea. Since 2000, the macroeconomic growth have still worked as an effective instrument for poverty reduction. However, there have been poverty increase that has not been explained by the macroeconomic growth since 2000. Based on these results, this paper suggests that the anti-poverty strategy in Korea should be changed from the old strategy emphasizing only economic growth to the new strategy pursuing both economic growth and social security simultaneously.

• Korean Journal of Construction Engineering and Management
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• v.25 no.4
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• pp.53-65
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• 2024

During COVID-19 the housing market in Korea experienced the soaring prices, despite the decrease in the economic growth rate. This paper aims to analyze macroeconomic determinants affecting housing prices in Korea during the pandemic and find an appropriate statistic model to forecast the changes in housing prices in Korea. First, an appropriate lag for the model using Akaike information criterion was found. After the macroeconomic factors were checked if they possess the unit root, the dependencies in the model were analyzed using vector autoregression (VAR) model. As for the prediction, the VAR model was used and, besides, compared afterwards with the long short-term memory (LSTM) model. CPI, mortgage rate, IIP at lag 1 and federal funds effective rate at lag 1 and 2 were found to be significant for housing prices. In addition, the prediction performance of the LSTM model appeared to be more accurate in comparison with the VAR model. The results of the analysis play an essential role in policymaker perception when making decisions related to managing potential housing risks arose during crises. It is essential to take into considerations macroeconomic factors besides the taxes and housing policy amendments and use an appropriate model for prices forecast.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.181-193
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• 2022

This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.297-303
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• 2021

The performance of the retail industry in a country, which simultaneously reflects the demand for retail space, is significantly influenced by the macroeconomic environment of said country. However, in the case of Malaysia, studies regarding this issue are limited. Therefore, this paper aims to identify the macroeconomic determinants of the demand for retail space in shopping centers in Malaysia through the study of six variables: per capita income, private expenditure, inflation rate, interest rate, total population, and the number of tourists arrival. The nexus between these variables and the demand for retail space in shopping centers were examined by cointegration and causality tests, and regression analysis using quarterly data for the period 1993Q1 to 2016Q4. The results from bivariate cointegration tests indicate that inflation rate, interest rates, population size, and the number of tourists arrival have significant long-run relationships with the demand for retail space of Malaysian shopping centers. Meanwhile, the Granger causality tests show that only population size can cause the demand for shopping centers' retail space. Finally, the results from the regression analysis revealed that income per capita, private expenditure, interest rates, and population are the variables that significantly influence the demand for the retail space of the Malaysian shopping centers.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.129-140
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• 2020

In the future, the global container handling market will be reorganized into larger ships and shipping alliances, and the bargaining power of shipping companies will be further strengthened. Therefore, the global terminal operator (GTO), which has a global network, vast experience, and operational know-how, is expected to strengthen its competitiveness. In Korea, the central government promoted the development of GTOs in the mid-2000s, but it failed, mainly due to disagreements between port stakeholders. In this study, the macroeconomic indicators that have the same effect in all regions were used to analyze GTO management performance. In the short term, it could be used to establish the business strategy of domestic terminal operators based on changes in macroeconomic indicators. In the long term, it would be used to establish a promotion strategy for GTOs in Korea. The results of analyzing the impact of macroeconomic indicators on the GTO's profit show that the GTO's profit is significantly affected by cargo handling capacity, the consumer price index of the United States, the Shanghai Composite Index, the Crude Oil Price, and the London Inter-bank Offered Rate (LIBOR). However, the scale of impact was not significantly different between public and private GTOs.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.431-444
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• 2014

We introduce the empirical model decomposition (EMD) to decompose a time series into a set of components in the time-frequency domain. By using EMD, we also extract cycle and trend components from major Korean macroeconomic indices and forecast the indices with the components combined. In order to evaluate their efficiencies, we investigate volatility, autocorrelation, persistence, Granger causality, nonstationarity, and forecasting performance. They are then compared with those by Hodrick-Prescott filter which is the most commonly used method.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1093-1102
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• 2012

In this paper, we predicted the interest spread using the VAR (vector autoregressive) model. Variables used in the VAR model were selected among 56 domestic and foreign macroeconomic time series through crosscorrelation and Granger causality test. The performance of the VAR model was compared with the univariate time series model, AR (autoregressive) model, in view of MAPE (mean absolute percentage error) and RMSE (root mean square error) of forecasts for the last twelve months.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.150-153
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• 2015

The construction industry is an integral part of any nation's economy, whether measured by dollar volume or workforce size. In spite of its strong influence, there has been very little specifically aimed at evaluating the current industry performance. This research investigates the macroeconomic performance of the construction industry by accounting for crucial performance affecting factors such as labor productivity and gross margin. A clustering analysis, followed by a series of statistical analyses, yielded a notable finding that labor productivity is the most important factor that affects industry's profitability. The results of the analysis also revealed that the states with the strongest labor productivity show the highest level of profitability in terms of gross margin. This study should be of value to decision-makers when plotting a roadmap for future growth and rendering a strategic business decision.