• 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.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.61-66
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• 2017

Environmental awareness and its relation to the development of economy has garnered increased attention in recent years. Researchers, over the years, have argued that sustainable development warrants for minimizing environmental degradation since one depends on the other. This study analyzes the relationship between environmental degradation (carbon emission taken as proxy for degradation), economic growth, total energy consumption and industrial production index growth in Bangladesh from year 1998 to 2013. This study uses Vector Autoregression (VAR) Model and variance decomposition of VAR to analyze the effect of these variables on carbon emission and vice-versa. The findings of VAR model suggest that industrial production and GDP per capita has significant relationship with carbon emission. Further analysis through variance decomposition shows carbon emission has consistent impact on industrial production over time, whereas, industrial production has high impact on emission in the short run which fades in the long run which is consistent with Environmental Kuznets Curve (EKC) hypothesis. Carbon emission rising along with GDP per capita and at the same time having low impact in the long run on industrial index indicates there may be other sources of pollution introduced with the rise in income of the economy over time.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.543-553
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• 2020

This paper examines the effect of COVID-19 pandemic on the Philippine stock exchange, peso-dollar rate and retail price of diesel using robust least squares regression and vector autoregression (VAR). The robust least squares regression using MM-estimation method concluded that COVID-19 daily infection has negative and statistically significant effect on the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. This is consistent with the results of correlation diagnostics. As for the VAR model, the lag values of the independent variable disclose significance in explaining the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. Moreover, in the short run, the impulse response function confirmed relative effect of COVID-19 daily infections and the variance decomposition divulge that COVID-19 daily infections have accounted for only minor portion in explaining fluctuations of the Philippine stock exchange index, peso-dollar exchange and retail pump price of diesel. In the long term, the influence levels off. The Granger causality test suggests that COVID-19 daily infections cause changes in the Philippine stock exchange index and peso-dollar exchange rate in the short run. However, COVID-19 infection has no causal link with retail pump price of diesel.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.63-76
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• 2016

Most previous studies found a positive relationship between the value of a firm and its R&D investments. This research measures the impact of the timescale of the R&D investment of a firm on its value using panel vector autoregression. By measuring the time required for R&D to impact the value of a firm, this study demonstrates that the lead time is an essential factor in the analysis of the effect of R&D investment on a firm's value. Our study finds that the length of the lead time varies according to the firm's size, industry concentration, and book to market ratio. Firms with a higher industry concentration show a shorter lead time. Also, firms with a larger size and higher book to market ratio generally show a shorter lead time.

• East Asian Economic Review
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• v.23 no.2
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• pp.203-223
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• 2019

This paper examines the interactions between financial conditions and business cycles in Mongolia, a small open economy, heavily depending on commodity exports. We construct two financial conditions indexes based on the reduced form IS model and the vector autoregression (VAR) model as surveillance tools to quantify the degree of the financial conditions. We find that real short-term interest rate and real effective exchange rate gap get a higher weight in the FCIs. Both business and financial cycles are often more pronounced in Mongolia, and financial condition is dependent of the financial and monetary policies in place. The analysis of the predictive power of the FCIs for business cycles shows that they have predictive information for the near-term economic activities. FCIs are also helpful in signaling inflation turning points.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.111-118
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• 2021

The purpose of this paper is to study the impact of trade openness on foreign direct investment (FDI) inflows into Vietnam, an emerging country with relatively high trade openness in recent years. The study used the vector autoregression (VAR) model to examine the impact of trade openness on FDI in Vietnam, in the period from 2005 to 2019. The research data are time-series data, with quarterly frequency, from 2005:Q4 to 2019:Q3. The FDI data were collected by International Financial Statistics. The data of trade openness were calculated based on Vietnam's export, import, and GDP data collected by the General Statistics Office of Vietnam. The estimated result shows that the trade openness has a positive effect on FDI. The current FDI is heavily influenced by FDI in the past with an average explanation of 74%. The main findings indicate that trade openness has a positive effect on FDI inflows into Vietnam. The findings also show that FDI in Vietnam is significantly affected by the shocks of the FDI itself in the past. The findings of the study suggest the Vietnamese Government improves the quality of trade openness and FDI, continues and maintains economic relations with other countries to increase trade openness.

• Knowledge Management Research
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• v.19 no.2
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• pp.1-19
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• 2018

This study aims to identify the causal relationship among public technology transfer, technological performance, and research and development (R&D) productivity. Using the impulse-response function(IRF) of a panel vector autoregressive model (panel VAR), this study suggests the results of how long the factors such as technological performance (patent), public technology transfer, and R&D productivity takes and lasts if a one-unit shock of standard deviation occurs. As a result, first, the increase of public technology transfer activities has no power to increase the technology performance but improve the R&D productivity. If the public institute increases its technology transfer activities by one unit, the R&D productivity will increase within five years. Second, the impact of increasing technological performance on improvement of public technology transfer and R&D productivity is an insignificant. Third, the effect of R&D productivity on the public technology transfer creates a substantial reaction after a current time. Considering the structural relationships among public technology transfer, technological performance, and R&D productivity, if policy makers intend to construct the active R&D circumstance, technology suppliers should be motivated to run the active R&D mechanism because they achieve gains.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.127-135
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• 2020

This study aims to measure the effects of real interest rate (RIR), gross domestic savings (GDS), and net exports (EN) shocks on Indonesia's economic growth (EG). The focus on Indonesia is unique due to the abundant resources available in the nation, but they are unsuccessful in boosting economic growth. This study applied a quantitative method to comprehensively analyze the correlation between variables by employing Vector Autoregression Model (VAR) combined with Vector Error Correction Model (VECM). Various procedures are preformed: Augmented Dickey-Fuller test (ADF), Optimum Lag Test, Johansen Cointegration Test, Granger Causality Test, as well as Impulse Response Function (IRF) and Error Variance Decomposition Analysis (FEVD). The data were collected from the World Bank and the Asian Development Bank from 1986 to 2017. The findings of the study indicated that economic growth responded positively to real interest rate shocks, which implies that when the real interest rate experiences a shock (increase), the economy will be inclined to growth. While, economic growth responded negatively to gross domestic savings and net export shocks. Policymakers are expected to consider several matters, particularly the economic conditions at the time of formulating policy, so that the prediction effectiveness of a policy can be appropriately assessed.

• Information Systems Review
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• v.16 no.2
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• pp.77-95
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• 2014

From the success of TDX and CDMA to today's social media boom, Korea's ICT has achieved an amazing growth for the last couple of decades. However, in spite of ICT's role as an engine of growth in Korea, there have been concerns that ICT growth would negatively affect national employment due to the labor substitution effect. While some scholars insist that ICT would positively affect employment because it will enlarge the size of industry itself, many people blame ICT as a main culprit of rising unemployment rates. In this study, we try to empirically find the true effect of ICT growth on employment in Korea. We use the data of ICT productions, ICT investments, and various industries employments from 1995 to 2011. The methodologies we adopted for this study is Granger causality tests and impulse response functions based on vector autoregression (VAR) model. We find that ICT has negative impact on service industries, while it has positive impact on manufacturing industries. Meanwhile, ICT has no statistically significant impact on ICT industry itself. Since the impacts of ICT on employment are mixed, we can argue that ICT should not be blamed for the main cause of low employment. We suggest a direction of future policies to utilize ICT for vitalizing employments in Korea.