• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.566-576
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• 2016

It is known that the Real Estate Sales Market and Auction Market are closely interrelated with each other in a variety of respects and the media often mention the real estate auction market as a leading indicator of the real estate market. The purpose of this paper is to analyze the relationships between the housing market and auction market before and after macroeconomic fluctuations using VECM. The period from January 2002 to December 2008, which was before the financial crisis, was set as Model 1 and the period from January 2009 to November 2015, which was after the financial crisis, was set as Model 2. The results are as follows. First, the housing auction market is less sensitive to changes in the housing market than it is to fluctuations in the auction market. This means that changes in the auction market precede fluctuations in the housing market, which shows that the auction market as a trading market is activated. In this respect, public institutions need to realize the importance of the housing auction market and check trends in the housing contract price in the auction market. Also, investors need to ensure that they have expertise in the auction market.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.116-124
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• 2016

In the past, once apartments were built by housing construction companies, their presale went smoothly. Therefore, the developer and construction companies in Korea were extremely competitive in the housing market. However, when the 1997 foreign exchange crisis and 2008 global financial crisis occurred, the quantity of unsold new housing stocks rapidly increased, which caused construction companies to experience a serious liquidity crisis. This paper aims at analyzing the influence of Liquidity on the Housing Market before and after Macroeconomic Fluctuations using VECM. The periods from September 2001 to September 2008 and from October 2008 to October 2015, which were before and after the Subprime financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, it is important to develop a long-term policy for the housing transaction market to improve household incomes. Second, due to the shortage in the supply of jeonse housing, structural changes in the housing market have appeared. Thus, it is necessary to seek political measures to minimize the impact of transitional changes on the market.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.43-51
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• 2018

We study the impact of economic policy uncertainty (EPU) of Asian four countries such as Korea, Japan, Hong Kong, and China on housing market returns in Korea. Also, we document the relationship between the EPU index of those four countries and the housing market including macroeconomic indicators in Korea. The EPU index of those four countries has significantly a negative effect on the housing purchase price index, housing lease price index in Korea. The EPU index in Korea and Japan has significantly a negative effect on the CPI. The EPU index in only Japan has significantly a negative effect on the PPI. The EPU index in Hong Kong and Korea has significantly a negative effect but the EPU index in China significantly has a positive effect on the stock price index in construction industry. The EPU index in only Korea has significantly a negative effect the stock price index in banking industry. This study shows the EPU index of the Korea has the negative relationships on the housing market economy rather than other countries by VECM. And this study has an important evidence of the spillover of several macroeconomic indicators in Korea for the EPU index of the Asian four countries.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.1-9
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• 2018

Recently, the rapid development of artificial intelligence industry has resulted in a great change in our modern society. Due to this background, this paper takes the United Kingdom as an example to explore the determinants of artificial intelligence industry in terms of United Kingdom's macroeconomics. The quarterly time series from the first quarter of 2010 to the fourth quarter of 2017 will be employed to conduct an empirical analysis under the vector error correction model. In this paper, the real GDP, the employment figure, the real income, the foreign direct investment, the government budget and the inflation will be regarded as independent variables. The input of artificial intelligence industry will be regarded as a dependent variable. These macroeconomic variables will be applied to perform an empirical analysis so as to explore how the macroeconomic variables affect the artificial intelligence industry. The findings show that the real GDP, the real income, the foreign direct investment and the government budget are the driving determinants to promote the development of artificial intelligence industry. Conversely, the employment figure and the inflation is the obstructive determinants to hamper the development of artificial intelligence industry.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.15-25
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• 2020

This empirical research aims to identify the relationship between fiscal and financial macroeconomic fundamentals and the volatility of government bonds' borrowing cost in an emerging country - Vietnam. The study covers the period from July 2006 to December 2019 and it is based on a sample of 1-year, 3-year, and 5-year government bonds, which represent short-term, medium-term and long-term sovereign bonds in Vietnam, respectively. The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model and its derivatives such as EGARCH and TGARCH are applied on monthly dataset to examine and suggest a significant effect of fiscal and financial determinants of bond yield volatility. The findings of this study indicate that the variation of Vietnam government bond yields is in compliance with the theories of term structure of interest rate. The results also show that a proportion of the variation in the yields on Vietnam government bonds is attributed to the interest rate itself in the previous period, base rate, foreign interest rate, return of the stock market, fiscal deficit, public debt, and current account balance. Our results could be helpful in the macroeconomic policy formulation for policy-makers and in the investment practice for investors regarding the prediction of bond yield volatility.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.19-43
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• 2004

This study was motivated by a practical need for estimating the macroeconomic effect of government IT Promotion investment, specifically for micro and small firms. Small firms have been in a disadvantageous position to adopt and utilize new IT compared with medium or large-sized firms. Small firms don't have enough resource to acquire IT in general, therefore private IT companies don't have much incentive to develop IT services and products for small firms. Lack of feasible IT solutions for small firms again restricted active IT adoption of small firms. Government recognized the vicious cycle, therefore decided to promote private IT companies to develop IT services and products for small firms's. Our main concern was to identify a relevant government supporting Policy, especially in the amount and the period. To do this, we first constructed a system dynamics simulation model to Investigate important factors and causal relationships among them. Simulation results showed 2.19% of GDP contribution and 0.16% of employment contribution in max from small firms' IT adoption. Also we could find that investing proper amount for a short period would be for better than maintaining Investing small amount for a long period.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.203-212
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• 2021

Theoretically, economic growth necessitates financial liberalization. Thus, the current research examines the effect of financial liberalization on economic growth in emerging nations, with a particular focus on Egypt and Saudi Arabia. To determine this effect, the study employs a model that uses Gross Domestic Product growth as the dependent variable and the following macroeconomic variables as financial liberalization indices: Broad money as a percentage of GDP, Domestic bank credit to the private sector as a percentage of GDP, Monetary sector credit to the private sector as a percentage of GDP, Net inflows of foreign direct investment as a percentage of GDP. All data is annual data of Egypt and the Kingdom of Saudi Arabia for the period 1970-2018 obtained from the World Bank open data website. The empirical investigation employs the Autoregressive Distributed Lag (ARDL) approach. The findings indicate that, after more than three decades of implementation, both countries' financial and external liberalization policies do not have a favorable effect on their economies' growth rates. Additionally, this study has led us to conclude that any financial liberalization policy in both countries must be preceded by the strengthening of these countries' financial development and institutional frameworks, as well as the achievement of macroeconomic stability.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.1
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• pp.181-187
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• 2023

The study aimed to study the effect of the inflation rate, the real domestic product, the interbank lending interest rate, and the total deposits on credit facilities in Jordan for 2012-2021 through quarterly data. The study adopted the ARDL model. The study used the time series analysis method, as the study tests the stationarity of the time series. The results showed that the impact of inflation on the total credit facilities was negative. In contrast, the impact of each of the total deposits, real GDP, and the interest rate of interbank loans on the total credit facilities was positive and significant. The study recommended the need for the banking sector in Jordan to develop risk management mechanisms in a way that allows it to adapt to economic cycles and crises by conducting stress tests and developing scenarios that ensure the formation of sufficient provisions to meet emergencies. The study also recommended that the macroeconomic policy should be based on creating a stable macroeconomic environment that allows the efficient employment of resources in all economic sectors in a way that achieves high economic growth rates, which contributes to the promotion of economic recovery and is reflected in income. Hence, individuals have a greater ability to repay loans.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.