• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.143-150
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• 2007

Using a panel data of Korea for $1979{\sim}2002$, this study investigates the determinants of the service sector employment share in Korea. In order to analyze the impact of macroeconomic factors on the service sector's employment share we estimate a simple panel model which is in line with Baumol's model. The panel GMM estimation results show that: 1) The increase in the share of service-related jobs in total employment tends to rise with GDP per capita, which confirms demand-bias hypothesis proposed by Clark. 2) We find that a crucial role in this process has been played by the productivity gap. As Baumol's hypothesis or Baumolis disease, the expansion of the employment share in services relative to industry is the direct consequence of services' lower productivity performances.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.107-119
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• 2019

This paper examines the impact of financial integration on economic growth in Southeast Asia over the period 1993-2013. This paper further investigates whether the relationship depends on the level of financial and economic development, government corruption, and macroeconomic policy. These questions raise important issues both from a theoretical and a policy perspective. We employ the generalized methods of moment (GMM) in the dynamic panel estimation framework to analyse several factors, including initial income, initial schooling, financial development, inflation, trade openness, corruption, and financial crisis. The study further analyzes the data using the EGLS model to examine the consistency of the GMM model. We found that financial integration has a significant positive effect on economic growth in Southeast Asia. Our findings suggest that increasing financial integration could improve the productive capacity of the economy, including more investments and efficient allocation of capital, and thus enhancing economic growth in this region. More specifically, the results suggest that the government should work towards eliminating corruption and stabilizing macroeconomics in order to enhance financial integration and economic growth. This paper sheds new insights on a better evaluation of the past and present theorizing on the subject of financial integration and economic growth; especially, in Southeast Asia.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.165-170
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• 2021

This study analyzed the effect of housing price changes on the performance of Korean regional banks using DOLS model. The analysis shows that housing price changes does not have a statistically significant effect on the loan growth, profitability and soundness of regional banks. Among macroeconomic variables, only short-term interest rates have a significant positive effect on any model. This means that a rise in short-term interest rates significantly increases loans by regional banks, which leads to a significant increase in profitability, but has a significant negative impact on soundness. On the other hand, bank characteristics variables are found to have a significant negative effect on the loan growth, profitability and soundness of Korean regional banks.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• Economic Analysis
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• v.26 no.4
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• pp.39-64
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• 2020

Typical business cycle models have difficulties in explaining key macroeconomic labor market variables, such as employment and unemployment, as they usually consider labor hour choices only. In this paper, we introduce labor market search and matching frictions into a New Keynesian nominal rigidity model and estimate it by Bayesian methods to examine the dynamics of the key labor market variables and business cycles in Korea. The results show that unemployment rates are largely explained by technology shocks, which affect the labor demand side, as well as labor supply shocks. In addition, wage bargaining shocks originating from the bargaining process between firms and workers have non-negligible negative effects on output and employment growth, and careful measures need to be taken to limit their adverse effects.

• Asia-Pacific Journal of Business
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• v.14 no.3
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• pp.221-240
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• 2023

Purpose - This paper investigates how business cycle impacts on corporate credit spreads since global financial crisis. Furthermore, it tests how the impact changes by the phase of the cycle. Design/methodology/approach - This study collected dataset from Barclays Global Aggregate Bond Index through the Bloomberg. It conducted multi-regression analysis by projecting business cycle using Hodrick-Prescott filtering and various cyclical variables, while ran dynamic analysis of 5-variable Vector Error Correction Model to confirm the robustness of the test. Findings - First, it proves to be statistically significant that corporate credit spreads have moved countercyclicaly since the crisis. Second, It indicates that the corporate credit spread's countercyclicality to the macroeconomic changes works symmetrically by the phase of the cycle. Third, the VECM supports that business cycle's impact on the spreads maintains more sustainably than other explanatory variable does in the model. Research implications or Originality - It becomes more appealing to accurately measure the real economic impact on corporate credit spreads as the interaction between credit and business cycle deepens. The economic impact on the spreads works symmetrically by boom and bust, which implies that the market stress could impact as another negative driver during the bust. Finally, the business cycle's sustainable impact on the spreads supports the fact that the economic recovery is the key driver for the resilience of credit cycle.

• Asian Journal for Public Opinion Research
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• v.12 no.2
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• pp.75-101
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• 2024

This study investigates the variation in anxiety levels across income classes in the wake of the COVID-19 pandemic in Indonesia. The research is based on data from nationally representative surveys conducted in 2017 and 2021, and it employs a multilevel mixed-effects ordered logistic model. The unique aspect of this investigation lies in its utilization of the Cantril ladder, a commonly employed tool in public opinion research, to gauge anxiety levels. Participants are prompted to assess their present life circumstances concerning their daily worries and anxieties. The empirical findings provide evidence that individuals in provinces with higher exposures to COVID-19 reported heightened anxiety levels. Furthermore, the results highlight a consistent association between higher household income and lower levels of anxiety. Notably, individuals from the highest income group experienced a substantial decline in anxiety levels during the pandemic. When examining specific income classes, the study reveals heightened anxiety among women in higher-income brackets and among lower-income households residing in urban areas. Furthermore, regarding macroeconomic circumstances, the results illustrate a positive correlation between economic prosperity and anxiety levels among members of low-income households. The study also uncovers a positive connection between income inequality and self-assessed anxiety within upper-middle and high-income brackets.

• 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.

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.1-13
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• 2009

The monetary model suggests that nominal exchange rates between two countries will be determined by important macroeconomic variables. The existence of a cointegrating relationship among these fundamental variables is the backbone of the monetary model. In a recent paper, Rapach and Wohar (2002, Journal of International Economics) advance the literature by testing for linear cointegration in the monetary model using a century of data to increase power. They find evidence of cointegration in five or six of ten countries. We extend their work to the nonlinear framework by performing threshold cointegration tests that allow for asymmetric adjustments in two regimes. Asymmetric adjustments in exchange rates can occur, for example, if transactions costs are present or if policy makers react asymmetrically to changing fundamentals. Moreover, whereas Rapach and Wohar (2002) found it necessary to exclude the relative output variable in some cases to maintain the validity of their cointegration tests, we can include this variable as a stationary covariate to increase power. Overall, using their same long-span data, we find more support for cointegration in a nonlinear framework.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.171-194
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• 2020

We revisit the impact of oil shocks on the Korean economy and examine how this impact varies depending on a business cycle. First, we estimate the probability of a recession through a logistic probability distribution, and correct the probability to match business cycles announced by the Korea National Statistical Office. We set up a STVAR model to analyze the response of macroeconomic variables to oil shocks according to business cycles. We find that oil shocks during the recession have a negative effect on GDP in the mid- and long-term, but during the expansion, GDP does not show a statistically significant response to oil shocks. We presume that this finding is associated with the factors of both the increase in demand for consumption and the increase in current account during the economic boom. Also, we find that the impact of oil shocks on the price level was also observed differently in terms of the persistence of inflation by business cycle. These results highlight the importance of an application of a regime switching model, which has been widely used in energy economics in recent years.