• Journal of Construction Engineering and Project Management
• /
• 제1권3호
• /
• pp.1-8
• /
• 2011

Available data on the recent global financial crisis (GFC) show that it lasted between the second quarter (Q2) of 2007 and the fourth quarter (Q4) of 2009. Australia is one of the first economies to fully recover from this crisis. This study explorles the role played by the Australian construction industry in stimulating economic growth during the recession. In order to investigate the macro-variability trend during the financial crisis, data were collected and analysed relating to the quarterly GDP of Australia and selected countries between Q1 2000 and Q4 2009. Specifically, changes in the construction industry's GDP were compared with aggregate GDP changes in Australian economy and similar indices in the 'Group of 7' (G7) countries and Organisation for Economic Co-operation and Development (OECD) countries. Moreover, specific attention was focused on Germany, France, Japan, United States of America (USA) and United Kingdom (UK). Graphical and Pearson's correlation methods were used to analyse the relationships between changes in construction GDP and Australia's overall economic growth during the recession. In addition, an attempt was made to develop a regression model for predicting economic growth during the recent recession using changes in gross fixed capital formation (GFCF), changes in construction GDP and the impact of these changes on national economy. Analysis shows a slight contraction in construction activities during the crisis; however construction triggered significant growth in the economy during the crisis period and afterwards. This appears to be the major difference between Australia and other major economies that have experienced a longer recession.

• 무역학회지
• /
• 제44권1호
• /
• pp.17-30
• /
• 2019

This study is to investigate the effect of real exchange rate on bilateral trade balance between Korea and ASEAN 10 countries. Using quarterly data from 1991 to 2017 the paper analyzes whether or not the real depreciation of Korea's won could improve the trade balance in the short and long term. Based on Autoregressive Distributed Lag(ARDL) model, the empirical results show that trade balance, GDP, and real exchange rate are all cointegrated, representing the long-run relationship among variables. In the consideration of long-run relationship, the increases in ASEAN countries' GDP could have a negative impact and Korea's GDP positive impact on trade balance between Korea and ASEAN countries unexpectedly. For the main variable, the paper did not find the long-term effect of real exchange rate on the trade balance, for the short-term effect of the real exchange rate it was found that there exists the J-curve effect only in the case of Vietnam and Brunei. Therefore, these results imply that the intended policy concerning the exchange rate in the free-floating exchange rate system could be limited to improve the trade balance between Korea and ASEAN countries.

• Journal of Korea Trade
• /
• 제27권2호
• /
• pp.96-114
• /
• 2023

Purpose - This paper elucidates a nexus between the occurrence of rare disaster events and the volatility of economic growth by distinguishing the likelihood of rare events from stochastic volatility. We provide new empirical facts based on a quarterly time series. In particular, we focus on the role of financial liberalization in spreading the economic crisis in developing countries. Design/methodology - We use quarterly data on consumption expenditure (real per capita consumption) from 44 countries, including advanced and developing countries, ending in the fourth quarter of 2020. We estimate the likelihood of rare event occurrences and stochastic volatility for countries using the Bayesian Markov chain Monte Carlo (MCMC) method developed by Barro and Jin (2021). We present our estimation results for the relationship between rare disaster events, stochastic volatility, and growth volatility. Findings - We find the global common disaster event, the COVID-19 pandemic, and thirteen country-specific disaster events. Consumption falls by about 7% on average in the first quarter of a disaster and by 4% in the long run. The occurrence of rare disaster events and the volatility of gross domestic product (GDP) growth are positively correlated (4.8%), whereas the rare events and GDP growth rate are negatively correlated (-12.1%). In particular, financial liberalization has played an important role in exacerbating the adverse impact of both rare disasters and financial market instability on growth volatility. Several case studies, including the case of South Korea, provide insights into the cause of major financial crises in small open developing countries, including the Asian currency crisis of 1998. Originality/value - This paper presents new empirical facts on the relationship between the occurrence of rare disaster events (or stochastic volatility) and growth volatility. Increasing data frequency allows for greater accuracy in assessing a country's specific risk. Our findings suggest that financial market and institutional stability can be vital for buffering against rare disaster shocks. It is necessary to preemptively strengthen the foundation for financial stability in developing countries and increase the quality of the information provided to markets.

• 응용통계연구
• /
• 제37권2호
• /
• pp.119-138
• /
• 2024

본 연구는 노이즈 필터링과 차원축소 등의 방법을 이용하여 텍스트 지표의 정상화에 대해 검토하고 실증 분석을 통해 동 지표의 활용가능성을 제고할 수 있는 후처리 과정을 탐색하고자 하였다. 실증분석에 대한 예측 목표 변수로 월별 선행지수 순환 변동치, BSI 전산업 매출실적, BSI 전산업 매출전망 그리고 분기별 실질 GDP SA전기비와 실질 GDP 원계열 전년동기비를 상정하고 계량경제학에서 널리 활용되는 Hodrick and Prescott 필터와 비모수 차원축소 방법론인 충분차원축소를 비정형 텍스트 데이터와 결합하여 분석하였다. 분석 결과 월별과 분기별 변수 모두에서 자료의 수가 많은 경우 텍스트 지표의 노이즈 필터링이 예측 정확도를 높이고, 차원 축소를 적용함에 따라 보다 높은 예측력을 확보할 수 있음을 확인하였다. 분석 결과가 시사하는 바는 텍스트 지표의 활용도 제고를 위해서는 노이즈 필터링과 차원 축소 등의 후처리 과정이 중요하며 이를 통해 경기 예측의 정도를 높일 수 있다는 것이다.

• KDI Journal of Economic Policy
• /
• 제28권2호
• /
• pp.51-96
• /
• 2006

재정이 경기조절 역할을 수행하기 위해서는 정책의 시점이 적절해야 하고, 정책의 효과가 유의미해야 한다. 본 연구는 재정정책기조와 경기환경의 상관관계를 고찰함으로써 위의 첫 번째 조건인 정책시점의 적절성을 평가한다. 이를 위해 본 연구는 한국은행 "조사통계월보"의 분기별 재정수지 자료와 추정된 잠재 GDP를 바탕으로 재정충격지수(Fiscal Impulse: FI)를 계산하였다. 이를 이용하여, 첫째 재정충격지수가 GDP 갭으로 대변되는 경기상황에 어떻게 대응하는지를 회귀식을 통하여 분석하고, 둘째 통계청의 경기순환주기에 따라 이 지표의 평균값을 비교하며, 셋째 각 연도의 예산제안서를 검토하여 재정당국의 경기 판단의 적절성과 정책의도의 실현을 평가하였다. 회귀분석 결과는 재정정책, 특히 지출측면이 경기 대응적(counter-cyclical)이었음을 보여주나, 경기순환주기에 따른 지표의 평균값은 경기 상승기와 하강기에 유의미한 차이를 보여주지 못하여, 전체적으로 재정정책이 경기 대응적인 모습을 보였는지에 대한 확정적인 결론을 내리기는 힘들다. 예산제안서를 검토한 결과, 재정의 경기 대응도는 정부의 경기 인식 및 정책의도와 사뭇 다르게 나타날 때도 있어 재정정책을 경기조절을 위하여 적극적으로 사용하기가 어려움을 보여준다.

• 통상정보연구
• /
• 제14권4호
• /
• pp.27-47
• /
• 2012

2006년의 미국의 금융위기 및 현재 유럽의 재정위기로 인하여 세계경제는 침체의 위기에 서 있으며 저성장 고실업율의 문제를 해결하기 위하여 여러 가지 방법을 강구하고 있다. 따라서 경제성장에 원인이 되는 요인이 무엇인지에 대한 연구는 끊임없이 되어오고 있다. 이에 본 연구는 수출, 수입, 외국인 직접투자 및 해외직접투자 등이 경제성장에 미치는 영향과 변수들간 상호 어떠한 영향을 미칠 것인가에 대한 분석을 하는 것과 IMF를 전후로 하여 분석을 실시하여 국내경제의 변화가 실질적으로 변수들 간에 영향을 어떻게 미친 것인가에 대하여 알아보는 것에 그 목적이 있다고 할 수 있다. 따라서 위와 같은 연구를 바탕으로 아래와 같은 결론을 낼 수가 있었다. 1997년을 중심으로 변수들간의 인과관계에 대한 많은 변화가 있었다는 것이다. IMF기간이전에서는 보이지 않던 GDP와 해외직접투자 및 외국인 직접투자의 인과관계가 확인됨으로서, IMF 구제금융 이후 한국의 자본시장의 개방이 외국인직접투자 및 해외직접투자에 영향을 끼쳤음을 알 수가 있었다. 또한 외국인직접투자와 해외직접투자의 연관성 역시 한국의 자본시장 개방과 관련성으로 판단지어 볼 수가 있었다. 결론적으로 말해서, 수출입 등의 실물시장보다는 급증하고 있는 자본시장의 영향이 거시경제변수들간에 인과관계를 좀 더 잘 설명하고 있는 예가 아닐까 생각된다.

• 아태비즈니스연구
• /
• 제13권2호
• /
• pp.39-50
• /
• 2022

Purpose - The purpose of this study is to examine how Korea's macroeconomic factors, such as GDP, CPI, Export, Import, Unemployment rate and USD/KRW exchange rate, are affected by the oil price shocks. Design/methodology/approach - This study used monthly and quarterly time-series data of each variable for the period 1983 to 2022, consisting of two sub-periods, to employ Granger causality test and GARCH method in order to identify the role of the oil price movement in macroeconomic factors in Korea. Findings - Korea's currency rate to the US dollar is negatively correlated with the price change of crude oil while the GDP change is positively correlated with the price change of crude oil with strong relationship between Export and Import in particular. The exchange rate and GDP growth are believed to be not correlated with the oil price change for the pre-GFC period. According to the Granger causality test, the price change in crude oil has a causal impact on CPI, Export and Import while other factors are relatively slightly affected. Transmission effect from the oil price to Export is found and there also exists volatility spillover from oil price to economic variables under examination. Comparing two sub-periods, CPI and Export volatility responds negatively to shocks in the oil price for the pre-GFC period while volatility of CPI and Unemployment reacts positively to the oil price shocks for the post-GFC period. Research implications or Originality - The findings of this study could be helpful for both domestic and international investors to build their portfolio for the risk management since rising WTI price can be interpreted as a result of global economic growth and ensuing increase in the worldwide demand of the crude oil. Consequently, the national output is expected to increase and the currency is also expected to be strong in the long run.

• 응용통계연구
• /
• 제25권1호
• /
• pp.89-99
• /
• 2012

본 연구는 한국의 경제성장과 전력수요 사이의 Granger-인과성을 조사한 것이다. 실증분석을 위해 1970년 1분기부터 2009년 4분기까지의 분기별 실질 GDP와 전력소비 시계열 자료를 활용하였다. 두 시계열에 단위근이 존재하고 공적분 관계가 있음을 확인한 후 오차수정모형을 구성하였으며, Hsiao (1979)의 순차적 모형식별 과정을 적용해서 자기회귀항의 최적시차를 결정하여 모형을 추정하였다. Hsiao 방식의 Granger-인과성 분석결과, 한국의 경제성장과 전력수요는 양방향의 인과관계를 보였다. 추정된 개별 오차수정모형을 기반으로 Engle-Granger 방식의 추가적인 인과성 분석 결과로부터는 (1) 경제성장과 전력수요 사이의 단기적인 양방향성 인과관계, (2) 양방향성 강 인과관계, 그리고 (3) 장기적으로는 전력수요로부터 경제성장으로의 단방향성 인과관계를 확인할 수 있었다. 이러한 결과는 기존의 선행연구의 결과와는 상반되는 것이나, 지속적인 경제성장을 추구하는 한국의 상황에서 더 의미 있는 정책적 시사점을 줄 수 있다.

• The Journal of Asian Finance, Economics and Business
• /
• 제6권4호
• /
• pp.37-43
• /
• 2019

The research aims to study the relationship between export performance and stock return of Vietnamese fishery companies. To conduct this study, quarterly data was collected for period from 2010-2018 of 13 fishery companies listing in Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX). The export performance was measured by export intensity, export growth and export market coverage. In addition, interest rate, exchange rate, GDP, firm size, profitability, and financial leverage were considered as the control variables in the research model. Panel data analysis with Generalized Least Squares model was employed to estimate the predictive regression. The findings indicated that export intensity and export growth have a significant and positive relationship with stock returns. However, export market coverage has not a significant relationship with stock return at the 0.05 level. Profitability, financial leverage, and exchange rate have a positive relationship, while interest rate and GDP have no relation to stock return at the 0.05 significance level. The findings imply that investors should consider the export intensity instead of export growth and export market coverage as selecting stock of fishery exports firms to invest; managers should increase export intensity to increase company's stock price or firm market value.

• 한국인공지능학회지
• /
• 제6권2호
• /
• pp.1-9
• /
• 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.