[논문]Impact of Debts on Economic Growth of Bangladesh: An Application of ARDL Model

Hossain, Muhammad Amir; Shirin, Shabnam

Impact of Debts on Economic Growth of Bangladesh: An Application of ARDL Model 원문보기

Asia-Pacific journal of business = 아태비즈니스연구, v.7 no.1, 2016년, pp.1 - 10

Hossain, Muhammad Amir (Statistics Department Bangladesh Bank) , Shirin, Shabnam (Statistics Department Bangladesh Bank)

Abstract ▼ AI-Helper

This study attempts to investigate the effects of different types of debts on economic growth in Bangladesh using time series data spanning from 2000 to 2015. In this study, the RDL model has been applied to determine the long run relationship among the selected variables. The result of the ARDL model shows that there exists a long term relationship between economic growth and the debt variables. It was evident from the findings that there exists bidirectional causality between public sector external debt and economic growth. Causality between private external debt and economic growth has been found to be insignificant. However, causality between domestic debt and economic growth showed a unidirectional causality from domestic debt to economic growth and not vice versa. Causality tests suggest that impact of domestic debt on economic growth is more effective compared to external debts.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

The main objective is to specifically examine the long run and short run relationship among different types of debts and economic growth in Bangladesh during 2000-2015. In this study stationarity test was performed using ADF and PP test, which shows that the variables are integrated at different order.

제안 방법

The main objective is to specifically examine the long run and short run relationship among different types of debts and economic growth in Bangladesh during 2000-2015. In this study stationarity test was performed using ADF and PP test, which shows that the variables are integrated at different order. So ARDL model was applied to determine the long run relationship among the variables.

이론/모형

, I(2). Hence above mentioned technique is not appropriate and hence we adopt ARDL bounds testing approach for cointegration analysis in this study. The equation of the ARDL bounds testing approach is as follows:

성능/효과

The coefficient of GSED is negative at level but positive at lag 1 meaning that response of GDPR has the negative impact in the same year and positive impact at lag 1. As per findings, 1% increase of public external debt, economic growth decreased by 0.52% but 1% increase at lag 1, economic growth increased by 0.68%. However the coefficient of GSED is statistically insignificant and coefficient of GSED (-1) is significant.
This test indicates that p-value against test statistic is greater than 5% meaning that error variance are homoscedastic. By applying Cusum and Cusum squares test we found that our data set is within the limits of 5% error meaning that data of our consideration is stable. Thus we see that all post diagnostic tests suggest our applied model is statistically acceptable.
Amassoma (2011) studied the causal nexus between external debt, domestic debt and the economic growth in Nigeria between 1970 and 2009 using VEC approach. The findings revealed that there is bidirectional causality between the domestic debt and economic growth while there is a unidirectional causality from the economic growth to the external debt of Nigeria. Atique and Malik (2012) examined the impact of external debt on the economic growth of Pakistan over period of 1980 to 2010.
His paper shows that there is a positive and significant relationship between external debt and economic growth. The main findings of their study revealed that external debt has a negative impact on economic growth.
The result of table 4 suggests that unlike public sector external debt, private sector external debt has the positive impact on economic growth in the same year but has the negative impact at lag 1. The result shows that 1% increase of PSED, economic growth increased by 0.73% and 1% increase of PSED at lag 1, economic growth decreased by 0.75%. One remarkable thing is that impact of GSED on GDPR is faster than PSED.
However the coefficient of DOMD and DOMD(-1) both are statistically significant at 10% and 5% level of significance respectively. The result shows that 1% increase of domestic debt, economic growth increases by 0.20% and 1% increase of domestic debt at lag 1, GDPR decreases by 0.23%. On the other hand Wald test suggests that combined effect of DOMD and DOMD (-1) on GDPR is statistically significant at 5% level of significance.
(2003) examined that external debt affects in low income countries. The results suggest that the substantial reduction in the stock of external debt projected for highly indebted poor countries (HIPC) would directly increase per capita income growth by about 1% per annum. The empirical results of Bakar and Hasan (2008) are based on VAR estimates and it indicates that total external debts affect economic growth positively.
To determine whether error variance is homogeneous or not we applied Breusch-Pagan-Godfrey Test. This test indicates that p-value against test statistic is greater than 5% meaning that error variance are homoscedastic. By applying Cusum and Cusum squares test we found that our data set is within the limits of 5% error meaning that data of our consideration is stable.

참고문헌 (21)

Abdelhadi, S.A., (2013), "External Debt and Economic Growth: Case of Jordan (1990-2011)", Journal of Economics and Sustainable Development 4 (18), 26-32.
Amassoma, D., (2011), "External debt, Internal debt and Economic Growth Bound in Nigeria using a Causality Approach", Current Research Journal of Social Sciences 3(4): 320-325, 2011.
Atique, R., and Malik, K., (2012), "Impact of Domestic and External Debt on the Economic Growth of Pakistan", World Applied Sciences Journal 20(1), 120-129.
Audu, I., (2004), "The impact of external debt on economic growth and public investment: The case of Nigeria", African Institute for Economic Development and Planning (IDEP), Dakar.
Azam, M., Emirullah, C., Prabhakar, A.C., and Khan, A.Q., (2013), "The Role of External Debt in Economic Growth of Indonesia - A Blessing or Burden?", Middle-East Journal of Scientific Research 17 (5), 565-572.
Bakar, A.N., and Hassan, S., (2008), "Empirical Evaluation on Exter-nal Debt of Malaysia", International Business & Economics Research Journal 7 (2), 95-108.
Chowdhury, K., (1994), "A Structural Analysis of External Debt and Economic Growth: Some Evidence from Selected Countries in Asia and the Pacific", Applied Economics 26 (12), 1121-1131.

상세보기
Clements B, Bhattacharya R, Nguyen TQ (2003) "External debt, public investment and growth in low-income countries", IMF Working Paper WP/03/249, International Monetary Fund, Washington D.C.
Engle, R. F. and C. W .J. Granger, (1987), "Co-integration and error correction: Representation, estimation and testing", Econometrics 55: 251-276.

상세보기
Fosu, A.K., (1996), "The Impact of External Debt on Economic Growth in Sub-Saharan Africa", Journal of Economic Development 21 (1), 93-118.

상세보기
Hameed, A., Ashraf, H., and Chaudhary, M.A., (2008), "External Debt and Its Impact on Economic and Business Growth in Pakistan", International Research Journal of Finance and Economics 20, 132-140.
Ibi, E.E. and Alfred, A., (2015), "Impact of external debt on economic growth in Nigeria: a VAR approach", Journal of Business Management and Administration Vol. 3(1): pp. 1-5, March 2015
Johansen and Juselius, K., (1990), "Maximum Likelihood Estimation and Inference on Cointegration-with Applications to the Demand for Money", Oxford Bulletin of Economics and Statistics, Vol. 52, No. 2, pp. 169-210
Johansen, S., (1991), "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models", Econometrica, Vol. 59, No. 6, pp. 1551-1580.

상세보기
Johansen, S., (1995), "Likelihood based inference in cointegrated vector autoregressive models", Oxford University Press (New York).
Karagol, E., (2002), "The causality analysis of external debt service and GDP: The case of Turkey", Central Bank Rev. 2(1): 39-64
Pesaran, M. H. and B. Pesaran (1997), Microfit 4.0, Oxford University Press.
Rahman, M.M., Bashar, M.A., and Dey, S., (2012), "External Debt and Gross Domestic Product in Bangladesh: A Co-Integration Analysis", Management Research and Practice 4 (4), 28-36.
Shah, M.H., and Pervin, S., (2012), "External Public Debt and Economic Growth: Empirical Evidence from Bangladesh", 1974 to 2010, Academic Research International 3 (2), 508-515.
Tehereni, B.H.M., Sekhampu, T.J., and Ndovi, R.F., (2013), "The Impact of Foreign Debt on Economic Growth in Malawi", African Development Review 25 (1), 85-90.

상세보기
Uzun, A., Karakoy, C., Kabadayi, B., and Emsen, O.S., (2012), "The Impacts of External Debt on Economic Growth in Transition Economies", Chinese Business Review 11 (5), 491-499.

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

Impact of Debts on Economic Growth of Bangladesh: An Application of ARDL Model 원문보기

Abstract ▼ AI-Helper

주제어

AI 본문요약
AI-Helper

문제 정의

제안 방법

이론/모형

성능/효과

참고문헌 (21)

이 논문을 인용한 문헌

관련 콘텐츠

원문 보기

원문 URL 링크

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

연합인증

Impact of Debts on Economic Growth of Bangladesh: An Application of ARDL Model 원문보기

Abstract ▼ AI-Helper

주제어

AI 본문요약 엑셀 다운로드 AI-Helper

문제 정의

제안 방법

이론/모형

성능/효과

참고문헌 (21)

이 논문을 인용한 문헌

관련 콘텐츠

원문 보기

원문 URL 링크

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

AI 본문요약
AI-Helper