• 제목/요약/키워드: Cointegrating Regression

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Estimating the Nature of Relationship of Entrepreneurship and Business Confidence on Youth Unemployment in the Philippines

  • CAMBA, Aileen L.
    • The Journal of Asian Finance, Economics and Business
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    • 제7권8호
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    • pp.533-542
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    • 2020
  • This study estimates the nature of the relationship of entrepreneurship and business confidence on youth unemployment in the Philippines over the 2001-2017 period. The paper employed a range of cointegrating regression models, namely, autoregressive distributed lag (ARDL) bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models, dynamic OLS, fully modified OLS, and canonical cointegrating regression (CCR) estimation techniques. The Granger causality based on error correction model (ECM) was also performed to determine the causal link of entrepreneurship and business confidence on youth unemployment. The ARDL bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models confirmed the existence of long-run equilibrium relationship of entrepreneurship and business confidence on youth unemployment. The long-run coefficients from JJ and dynamic OLS show significant long-run and positive relationship of entrepreneurship and business confidence on youth unemployment. While results of the long-run coefficients from fully modified OLS and canonical cointegrating regression (CCR) found that only entrepreneurship has significant and positive relationship with youth unemployment in the long-run. The Granger causality based on error correction model (ECM) estimates show evidence of long-run causal relationship of entrepreneurship and business confidence on youth unemployment. In the short-run, increases in entrepreneurship and business confidence causes youth unemployment to decrease.

Spillover Effects of Foreign Direct Investment Inflows and Exchange Rates on the Banking Industry in China

  • Lee, Jung Wan;Wang, Zhen
    • The Journal of Asian Finance, Economics and Business
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    • 제5권2호
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    • pp.15-24
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    • 2018
  • The study examines the magnitude of economic spillover and the impact of foreign direct investment (FDI) inflows on the efficiency of the bank industry in China. This study employs unit root tests, cointegration tests and cointegrating regression analysis, including fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR) and dynamic OLS (DOLS) to test the proposed hypotheses. The sample is restricted to the period of time in which monthly data is available and comparable among variables for the period from January 2002 to October 2013 (142 observations). All of the time series data was collected and retrieved from the People's Bank of China, China Monthly Statistics from the National Bureau of Statistics of China, and International Financial Statistics database from International Monetary Fund. The results of the Johansen cointegration test suggest that there is a long-run equilibrium relationship between FDI inflows, foreign exchange rate and banks performance in China. The results of cointegrating regression analysis using FMOLS, CCR and DOLS suggest that M2 supply and FDI inflows are significant at the 0.01 level. The results confirm that FDI inflows in the banking sector are positively related to the increase of banks productivity and performance and short-term loans in China. However, the results suggest that Chinese Yuan currency exchange rate to U.S. dollar is not significant in the banking and financial industry of China.

Joint Test for Seasonal Cointegrating Ranks

  • Seong, Byeong-Chan;Yi, Yoon-Ju
    • Communications for Statistical Applications and Methods
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    • 제15권5호
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    • pp.719-726
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    • 2008
  • In this paper we consider a joint test for seasonal cointegrating(CI) ranks that enables us to simultaneously model cointegrated structures across seasonal unit roots in seasonal cointegration. A CI rank test for a single seasonal unit root is constructed and extended to a joint test for multiple seasonal unit roots. Their asymptotic distributions and selected critical values for the joint test are obtained. Through a small Monte Carlo simulation study, we evaluate performances of the tests.

공적분벡터의 안정성에 대한 실증연구 (Statistical Tests and Applications for the Stability of an Estimated Cointegrating Vector)

  • 김태호;황성혜;김미연
    • 응용통계연구
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    • 제18권3호
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    • pp.503-519
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    • 2005
  • 공적분검정은 변수들간의 장기적 균형관계에 따른 공적분벡터가 표본기간 동안 일정하다는 가정하에서 실시된다. 따라서 기존의 연구들은 변수들 사이의 공적분관계를 안정적 장기균형관계로 해석해왔으나 장기균형관계가 존재해도 유일하지 않을 수 있으며, 표본기간 중 중요한 사건이 발생하는 경우 이러한 관계에 영향을 미처 안정성이 반드시 성립될 수 없다는 사실은 간과해왔다. 본 연구에서는 추정된 공적분벡터가 안정성을 유지하는가를 확인하기 위해 추가로 통계적 검정을 실시하였다. 공적분회귀모형 모수의 안정성을 검정하는 방식을 세분${\cdot}$체계화하여 공적분백터의 안정성 및 변동형태를 검색하는 실증분석에 적용시켜 보았다.

On the Cointegrating Relationship between Stock Prices and Earnings

  • Nam, Doo-Woo
    • 산학경영연구
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    • 제20권2호
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    • pp.1-13
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    • 2007
  • The purpose of this study is to investigate a simple present value model Involving earnings (i.e., the earnings discount model) that presumes a relationship between stock prices and earnings. The model suggests a simple linear equilibrium relationship between stock prices and earnings. The tests for cointegration render strong support for the cointegration hypothesis between stock prices (Pt) and earnings (Xt) even at the one-percent significance level. The tests are based on residuals from a cointegrating regression of Pt on Pt+l + Xt. This suggests that there is a stable long-nu equilibrium relationship between stock prices and earnings. The results of the tests lead to the acceptance of the present value model of stock prices involving earnings.

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A Study on the Impact of Artificial Intelligence Industry on Macroeconomy: Evidence from United States of America

  • He, Yugang
    • Asian Journal of Business Environment
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    • 제8권4호
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    • pp.37-44
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    • 2018
  • Purpose - The artificial intelligence industry plays an increasingly significant role in stimulating the development of United States of America's economy. On account of this background, this paper attempts to explore the impact of artificial intelligence industry on United States of America's macroeconomy. Research design, data, and methodology - This paper mainly focuses on the impact of artificial intelligence industry on GDP, employment, real income, import, export and foreign direct investment. Furthermore, the Phillips-Perron test and Canonical cointegrating regression will be employed to examine the impact of artificial intelligence industry on United States of America's macroeconomy with a sample form 2010-Q1 to 2017-Q4. Results - Via the empirical analysis, the results reveal that the artificial intelligence industry has a positive effect on United States of America's GDP, employment, real income, export and foreign direct investment. Conversely, the artificial intelligence industry has a negative effect on United States of America's import. Conclusions - In summary, the impact of artificial intelligence industry on United States of America's macroeconomy is positive and significant in statistics. Therefore, the government of United States of America should put more input into artificial intelligence industry.

Economic and Environmental Impacts of Mass Tourism on Regional Tourism Destinations in Indonesia

  • Lee, Jung Wan;Syah, Ahmad Mujafar
    • The Journal of Asian Finance, Economics and Business
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    • 제5권3호
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    • pp.31-41
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    • 2018
  • The study examines economic and environmental impacts of mass tourism on regional tourism destinations, particularly the establishment of "Ten New Bali", in Indonesia. The sample is restricted to the period of time in which annual data is available and comparable among variables from 1980 to 2015 (36 observations). All of the time series data was collected and retrieved from the World Development Indicator database published by the World Bank. This study applies cointegrating regression analysis using the fully modified OLS, canonical cointegrating regression, and dynamic OLS. The results of the study suggest that 1) there is a long-run equilibrium relationship between tourism receipts, environmental degradation and economic growth in Indonesia, 2) tourism growth and agriculture land growth are positively related to an increase of total output in the short-run in Indonesia, and 3) arable land is significant at the 0.01 level, but forest rents and CO2 from transport are not significant in the short-run in Indonesia. The results confirm that arable land is negatively related to an increase of total output in Indonesia. That is, when tourism growth in the economy is getting realized it shows that the environmental degradation increases greatly in inverse in the model, eventually negative impacts to the environment.

제주지역 호텔이용률에 영향을 미치는 결정요인 분석 (Analysis on the Determinants of Hotel Occupancy Rate in Jeju Island)

  • 류강민;송기욱
    • 토지주택연구
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    • 제9권4호
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    • pp.10-18
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    • 2018
  • As the volatility increasement of the number of tourist, there was been controversy over supply-demand imbalance in hotel market. The purpose of this study is to analysis on determinants of hotel occupancy rate in Jeju Island. The quantitative method is based on cointegrating regression, using an empirical dataset with hotel from 2000 to 2017. The primary results of research is briefly summarized as follows; First, there are high relationship between total hotel occupancy rate and hotel occupancy of foreign tourist. The volatility of hotel occupancy is caused by foreigner user than local tourists though local tourist high propotion of hotel occupancy in Jeju Island. Second, hotel occupancy of local tourist has not relationship with demand and supply variables. Because some hotel users are not local tourists but local resident, and effects to other variables of hotel consumer trend, accommodation such as Guest house, Airbnb. Third, there are high relationship between foreign hotel occupancy rate and demand-supply variables. These research imply that total management of supply-demand is very important to seek stability of hotel occupancy rate in Jeju Island. Also it can provide a useful solution regarding mismatch problem between supply-demand as well as development the systematic forecasting model for hotel market participants.

Effects of Technology and Innovation Management and Total Factor Productivity on the Economic Growth of China

  • LEE, Jung Wan;XUAN, Ye
    • The Journal of Asian Finance, Economics and Business
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    • 제6권2호
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    • pp.63-73
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    • 2019
  • The paper aims to investigate relationships between technology and innovation management, total factor productivity and economic growth in China. By comparing the trends in total factor productivity growth of industrialized economies (i.e. OECD), this study intends to showcase the importance of total factor productivity progress in the Chinese economy. The study employs time series data of an annual basis for the period from 1977 to 2016 retrieved from the World Development Indicator. The study employs unit root test, cointegration test, fully modified least squares estimation method, canonical cointegrating regression and dynamic least squares estimation method to test the hypotheses. The results of the cointegrating regression analysis show that manufacturing growth leads to an increase of total factor productivity in the short-run in China. The findings of the study suggest that manufacturing (i.e. technology and product innovation) is positively related to the increase of total factor productivity in the short-run and total output growth in the long-run. The findings suggest that promoting technology and innovation management and supporting R&D subsidies may reduce the marginal cost of conducting R&D and increase the rate of technology and innovation management and R&D activity and therefore, the total factor productivity growth rate.

Structural Change in the Price-Dividend Ratio and Implications on Stock Return Prediction Regression

  • Lee, Ho-Jin
    • 재무관리연구
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    • 제24권2호
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    • pp.183-206
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    • 2007
  • The price-dividend ratio is one of the most frequently used financial variables to predict long-horizon stock return. However, the persistency of the price-dividend ratio is found to cause the spuriousness of the stock return prediction regression. The stable relationship between the stock price and the dividend, however, seems to weaken after World War II and to experience structural break. In this paper, we identify a structural change in the cointegrating relationship between the log of the stock price and the log of the dividend. Confirming a structural break in 1962, we subdivide the sample and apply the fully modified estimator to correct for the nonstationarity of the regressor. With the subdivided sample, we exercise the nonparametric bootstrap procedure to derive the empirical distribution of the test statistics and fail to find return predictability in each subsample period.

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