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Article

Evolution of the Innovation Process Models

1Immanuel Kant Baltic Federal University, Kaliningrad, Russia


International Journal of Econometrics and Financial Management. 2014, 2(4), 119-123
DOI: 10.12691/ijefm-2-4-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Mikhaylova Anna Alekseevna. Evolution of the Innovation Process Models. International Journal of Econometrics and Financial Management. 2014; 2(4):119-123. doi: 10.12691/ijefm-2-4-1.

Correspondence to: Mikhaylova  Anna Alekseevna, Immanuel Kant Baltic Federal University, Kaliningrad, Russia. Email: tikhonova.1989@mail.ru

Abstract

The article provides a review of the evolution of scientific concepts on the innovation process. Two main approaches to the innovation process are presented: linear and non-linear, and their distinctive features are defined. Within each approach the main types of models of the innovation process are considered. The stages of formation and development of a linear model of the innovation process are reviewed. Analyzed the influence of various factors on the occurrence of non-linear models of the innovation process. Highlighted the advantages and disadvantages of linear and non-linear approaches to the development of models of the innovation process. The effect of trends in the localization of the innovation process in the current models of the innovation process are studied. The modeling of the innovation process at the present stage is proposed to be considered as a complex, interactive, nonlinear localized learning process.

Keywords

References

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Article

Cluster Approach in Implementing the Socio-economic Development Strategy of the Region

1Department of Political Economy, Dagestan State University, Makhachkala, Russian Federation


International Journal of Econometrics and Financial Management. 2014, 2(4), 124-129
DOI: 10.12691/ijefm-2-4-2
Copyright © 2014 Science and Education Publishing

Cite this paper:
Askerov N.S.. Cluster Approach in Implementing the Socio-economic Development Strategy of the Region. International Journal of Econometrics and Financial Management. 2014; 2(4):124-129. doi: 10.12691/ijefm-2-4-2.

Correspondence to: Askerov  N.S., Department of Political Economy, Dagestan State University, Makhachkala, Russian Federation. Email: n.s.askerov@mail.ru

Abstract

The article describes the features of the cluster methodology and cluster systems. The Russian practice in implementation of the cluster approach and the experience on the use of the cluster approach in the implementation of socio-economic development strategy of the region. The study uses an example of the Republic of Dagestan (Russian Federation). The main focus is made on clusters “Caspian HUB” (transport-trade-logistics cluster) and “People’s House” (a unique cluster, aimed at stimulating the development of human capital) being nodal in the regions’ strategy. Aspects of the innovation potential of the region and the main directions of innovative activities of major enterprises of the industrial cluster of Republic of Dagestan (‘Aviaagregat’, ‘Hajiyev Plant’, ‘Research Institute ‘Sapphire’, ‘Dagfos’, etc.) are disclosed. Research results enabled to identify the main directions of the republic's economy required to stimulate clustering. The proposed initiatives are based on the improvement of mechanisms of state support for innovation at the regional level and on encouragement of the inflow of financial capital in the regional innovation system. The major objectives of the innovation potential of the Republic of Dagestan are defined.

Keywords

References

[1]  Askerov, N.S., “Institutional and theoretical foundations of the development strategy of the crisis territory”, Regional economy: theory and practice, 2013. 47 (326). 19-24. 2013.
 
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[3]  Askerov, N.S., Abakarov, M.I., Talibov, А.О., “Public-private partnership in the economy of the Republic of Dagestan”, Regional economy: theory and practice, 18 (297). 26-33. 2013.
 
[4]  Askerov, N.S., Alikerimova, T.D., “Methods of stimulating the subjects of innovative entrepreneurship” [metodi stimulirovania subjectov innovatsionnogo predprinimatelstva]. Problems of regional agribusiness. 2 (14). 69-73. 2013.
 
[5]  Cluster mechanism of economic modernization: Monograph. Eds. Askerov N.S., Dgavatova D.K. Nauka – Dagestan. Mahachkala. 2013.
 
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[6]  Guidelines for implementing cluster policies in the northern regions of the Russian Federation [Online]. Available: http://www.tpprf.ru [Accessed Jul. 13, 2014].
 
[7]  Dagstat. [Online]. Available: http://dagstat.gks.ru.
 
[8]  Jurgens, I., Creation of a new economy requires clusters [Dlia sozdaniya novoy ekonomiki nuzgni klasteru]. [E-book] Available: http://www.allmedia.ru
 
[9]  Porter, M., Competitive Advantage of Nations. FreePress, NewYork, 1990.
 
[10]  Rudneva, P.S., The experience of creating structural clusters in developed countries. Economy of the region. 18 (2). dec. 2002. [Online]. Available: http://journal.vlsu.ru.
 
[11]  Skoch, A., International experience of cluster formation [E-book] Available: http://www.intelros.ru [Accessed Jul. 10, 2014].
 
[12]  Strategy for Socio-Economic Development of the Republic of Dagestan to 2025. [Online]. Available: http://www.minec-rd.ru.
 
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Article

Development of Agro-industrial Clusters in Russia: Synergetic Approach

1All-Russia Research Institute of Economics, Labor and Management in Agriculture, Moscow, Russian Federation


International Journal of Econometrics and Financial Management. 2014, 2(4), 130-135
DOI: 10.12691/ijefm-2-4-3
Copyright © 2014 Science and Education Publishing

Cite this paper:
Huhrin A.S., Bundina О.I., Аgnaeva I.Yu., Тolmacheva N.P.. Development of Agro-industrial Clusters in Russia: Synergetic Approach. International Journal of Econometrics and Financial Management. 2014; 2(4):130-135. doi: 10.12691/ijefm-2-4-3.

Correspondence to: Huhrin  A.S., All-Russia Research Institute of Economics, Labor and Management in Agriculture, Moscow, Russian Federation. Email: a-huhrin@bk.ru

Abstract

Based on the analysis of objective statistical data authors identified a global megatrend of the XXI century and the related growth of knowledge-intensive clustering, which provides high efficiency and competitiveness of the world economy. Based on the study of synergy, the self-organization theory and the eastern philosophy on original principles of synergy, the synergetic approach to the cluster development is elaborated. Article shows an artificial and rapid creation and development of clusters that uses the achievements of synergy, in particular ultrafast processes of the hyperbolic growth. The proposed model of clustering considers these processes.

Keywords

References

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[5]  Knyazev, E.N., Kurdyumov, S.P., Basics of synergy. Synergistic vision of the world. KomKniga. Moscow. 2005.
 
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[6]  Lysenko, E.T., Kopacz, K.V. Huhrin, A.S. LPH: organizational and economic conditions in the system integration of a mixed economy. Sunrise-A. Moscow. 2006.
 
[7]  Lysenko, ET, Kopacz, K.V., Huhrin A.S., Sustainability LPH: Conceptual framework for strategic management. Russian Agricultural Academy, Moscow, 2006.
 
[8]  Maljavin, V.V., Chinese military strategy. AST in Astrel, Moscow. 2004.
 
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[11]  Huhrin, A.S., “The concept of cluster policy in the agriculture of the Russian Federation”, Economics of agricultural and processing enterprises. 6. 53-59. 2011.
 
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Article

Investigation of Early Markers of Clustering: Experience in Applying Nonparametric Technique of Examination

1Departmentof Economics and Management, Volgograd State Medical University, Volgograd, Russia

2Department of Information Systems in the economy, Volgograd State Technical University, Volgograd, Russia


International Journal of Econometrics and Financial Management. 2014, 2(4), 136-140
DOI: 10.12691/ijefm-2-4-4
Copyright © 2014 Science and Education Publishing

Cite this paper:
Soboleva S.Yu., Tereliansky P.V.. Investigation of Early Markers of Clustering: Experience in Applying Nonparametric Technique of Examination. International Journal of Econometrics and Financial Management. 2014; 2(4):136-140. doi: 10.12691/ijefm-2-4-4.

Correspondence to: Soboleva  S.Yu., Departmentof Economics and Management, Volgograd State Medical University, Volgograd, Russia. Email: svetlaso@mail.ru

Abstract

Article is devoted to the issue on early markers of formation of economic clusters, which are the specific regional conditions. In contemporary Russian economic reality, when the state implements the initiation of cluster projects in different geographical regions and economic sectors, particularly relevant is the task to analyze and identify the regional environment conducive to the successful cluster formation. In order to complete the task, authors propose to use non-parametric methodology of examination, allowing to analyze objects with a complex quality structure. Paper describes this technique, and tests it in an example of the emerging pharmaceutical cluster in the Volgograd region. Following the results of the study, a conclusion on the feasibility of establishing a cluster in the area, and the main insufficient conditions are identifies, the improvement of which will have a positive impact on the process of formation of the Volgograd pharmaceutical cluster.

Keywords

References

[1]  Adzhienko, V.L., Sobolev. A.V., “Institutional Premises of Formation and Factors of Success of Regional Pharmaceutical Clusters (on base of Volgograd region)”, Volgograd University Bulletin, Series 3. Economics. Ecology, 1 (20). 131-138. 2012.
 
[2]  Lomovtseva, O.A., “Problemi transfera innovatsionnih tehnologiy I productov v vuzah Rosii [Problems of Transfer of Innovative Technologies and Products in Russian Universities]” in Innowacynosc I przedsiebiorczsc wwarunkach kryzysu: Wydawnictwo KUL, Lublin (Poland). 2013, 150-155.
 
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[5]  Sobolev, A.V. “Basic Characteristics, Peculiarity of Formation and Administration of Pharmaceutical Clusters”,Belgorod State University Scientific Bulletin. History. Political Science. Economics. Information Tecnologies, 19 (138), 24/1. 65-70. 2012.
 
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[6]  Soboleva, S.Y., “Cluster Integration of Pharmaceutical Enterprises of Southern Federal Region”, Regional Economy. South of Russia, 1 (3), 222-226. 2014.
 
[7]  Terelyansky, P.V., “Approximation of Price-Approximatsiya zavisimosty tsena-kachestvo na osnove statisticheskoy obrabotki expertnoy informatsii” [Quality Dependence Based on Statistic Elaboration of Expert Information], Modern Economics Problems, 1. 560-565. 2009.
 
[8]  Terelyansky, P.V., Neparametricheskaya expertisa obyectov slozhnoy structure: monografiya [Non-parametric Expertise of the Objects Having Complicated Quality Structure: monograph] Dashkov and K, Moscow, 2009.
 
[9]  Terelyansky, P.V., Soboleva S.Y., Sobolev, A.V., “Evaluation of the Factors of Formation of Pharmaceutical Cluster by Using Non-parametric Expertise Method”, Belgorod State University Scientific Bulletin. History. Political Science. Economics. Information Tecnologies. 15 (158), 27/1. 46-53. 2013.
 
[10]  Terelyansky, P.V.. “Price-Postroueniey funktsii tsena-kachestvo na osnove anketnih oprosov expertov” [Quality Function Construction Based on Expert Poll], Volgograd State Pedagogical Bulletin, Series Socio-Economic Sciences and Art, 3. 92-96. 2009.
 
[11]  Terelyansky, P.V., “Prognozirovaniye zavisimosti tsena-kechestvo na osnove extrapolyatsii expertnih otsenok” [Price-Quality Dependence Prognosis Based on Exprapolation of Expert Evaluation], Economic Analysis: Theory and Practice, 9, 61-68. 2009.
 
[12]  Terelyansky, P.V., Svidetelstvo o gos. Registratsii program dlya EVM 2009611491. Sistema podderzhki prinyatiya resheniy y prognozirovaniya expertnih predpochteniy na osnove metoda protsentnih otsenok. [Certificate on State Registration of Computer Program № 2009611491. System of Decision Making Support and Expert Preference Forecast Based on Percentage Assessment Method], ROSPATENT. Moscow. 2009.
 
[13]  Terelyansky, P.V. Svidetelstvo o gos. Registratsii program dlya EVM 2009611495. Raschet vektora prioritetov na osnove priblizhennogo rascheta pravogo sobstvennogo vectora kvadratnoy obratnosimmetrichnoy matritsi [Certificate on State Registration of Computer Program № 2009611495. Calculation of Priority Vector Based on Approached Calculation of the Right Own Vector of Square Reversesymmetric Matrix] ROSPATENT. Moscow. 2009.
 
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Article

Analysis of Potential of International Inter-Cluster Cooperation in High-Tech Industries

1Department of Economic Theory, Sumy State University, Sumy, Ukraine


International Journal of Econometrics and Financial Management. 2014, 2(4), 141-147
DOI: 10.12691/ijefm-2-4-5
Copyright © 2014 Science and Education Publishing

Cite this paper:
Omelyanenko V.A.. Analysis of Potential of International Inter-Cluster Cooperation in High-Tech Industries. International Journal of Econometrics and Financial Management. 2014; 2(4):141-147. doi: 10.12691/ijefm-2-4-5.

Correspondence to: Omelyanenko  V.A., Department of Economic Theory, Sumy State University, Sumy, Ukraine. Email: sumyvit@ya.ru

Abstract

The article deals with the background and benefits of international inter-cluster interactions. Research shows that the cluster is the most effective form of innovative development based on the concept of innovation ecosystem, and intercluster international partnership is the most appropriate form of organization for the development of high-tech-based inter-sectoral cooperation and implementation of international projects. It is shown that the consideration of high-tech industry in the framework of the structural model as mega cluster means that the synergistic advantage can be seen only with a clear organizational structure and coordinated interaction of clusters. Analysis of necessity of inter-cluster interaction is considered on example of space industry. We propose tools for serching partners and assess the effectiveness of the scheme on the basis of inter-cluster interaction network approach and the results for the regional economy.

Keywords

References

[1]  Boosting Innovation: The Cluster Approach. OECD. Paris. 1999.
 
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[3]  Clusters and Cooperation for Regional Development in Central Europe. [Online]. Available: http://www.central2013.eu/fileadmin/user_upload/Downloads/outputlib/Tourism_Strategic_Plan.pdf [Accessed Jul. 30, 2014].
 
[4]  Franzuzov, А. Yu., “Razrabotka sistemyi pokazateley effektivnosti mezhklasternogo informatsionnogo vzaimodeystviya hozyaystvuyuschih subektov” [Develop a system of performance indicators intercluster information interaction of economic agents], Transportnoe delo Rossii [Transportation business in Russia]. No 1. 2008. [Online]. Available: http://www.morvesti.ru/archive/tdr/element.php?IBLOCK_ID=66&SECTION_ID=1350&ELEMENT_ID=2915
 
[5]  Handbook on Cluster Internationalisation. TACTICS. 2012.
 
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[8]  Omelyanenko, V.A. Analiz razvitiya otrasley, orientirovannyih na mezhdunarodnoe sotrudnichestvo (na primere kosmicheskogo priborostroeniya) [Analysis of the development-oriented industries on international cooperation (for example, Space Instrument)]. in 86th International Research and Practice Conference The power and freedom in the structure of global trends of development of economical and legal systems and management techniques. GISAP, London. 2014. [Online]. Available: http://gisap.eu/ru/node/52463
 
[9]  Omelyanenko, V.A. Strategiya razvitiya mezhotraslevogo vzaimodeystviya na osnove klasterov [The development strategy of inter-sectoral collaboration on the basis of clusters]. in Innovacii v tehnologijah i obrazovanii [Innovations in technologies and education]: Digest of Sci. Art. participants of the VII International Scientific and Practical Conference, Veliko Tarnovo, Bulgaria. 2. 234-237. 2014.
 
[10]  Prokopenko, O., Eremenko, Yu., Omelyanenko, V., “Role of international factor in innovation ecosystem formation”, Economic Annals-XXI. 3-4 (2). 4-7. 2014.
 
[11]  Record, S.I. Razvitie promyishlenno-innovatsionnyih klasterov v Evrope: evolyutsiya i sovremennaya diskussiya [Development of industrial and innovation clusters in Europe: evolution and the modern debate]. SPb. 2010.
 
[12]  Zvjagina, Е.М., “Tipologiya klasterov i osobennosti klasterizatsii ekonomiki regionov Rossii” [Typology of clusters and clustering features of the economy of regions of Russia]. Sovremennye problemy nauki i obrazovanija [Modern Problems of Science and Education]. 2. 2014. [Online]. Available: www.science-education.ru/116-12696.
 
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Article

Supporting Rationale of Regional Clusterization Effectiveness: Methodological Approach

1Economics and Management Department, Nizhnekamsk Institute of Chemical Engineering (Branch), Kazan National Research Technological University, Nizhnekamsk, Russian Federation


International Journal of Econometrics and Financial Management. 2014, 2(4), 148-152
DOI: 10.12691/ijefm-2-4-6
Copyright © 2014 Science and Education Publishing

Cite this paper:
Dyrdonova A.N., Fomin N.Y.. Supporting Rationale of Regional Clusterization Effectiveness: Methodological Approach. International Journal of Econometrics and Financial Management. 2014; 2(4):148-152. doi: 10.12691/ijefm-2-4-6.

Correspondence to: Dyrdonova  A.N., Economics and Management Department, Nizhnekamsk Institute of Chemical Engineering (Branch), Kazan National Research Technological University, Nizhnekamsk, Russian Federation. Email: Danauka@lenta.ru

Abstract

The paper deals with a study of cluster-type development of regional economic systems. Positive influence on the social and economic growth of a number of regions in the Russian Federation has been evaluated owing to generation of territorial cluster-type formations. The paper includes findings of an investigation into theoretical nature of «cluster» as an economic category. As an example of positive influence of the clusterization strategy, the project of formation and development of the regional cluster of Nizhnekamsk Municipal District of the Republic of Tatarstan has been offered and validated from economic effectiveness point of view. For the purpose of the project feasibility validation, a methodological approach has been specifically designed for evaluation of economic potential of the city-forming enterprises. During approbation, the above mentioned approach brought to the front a number of intensive growth prospects for the enterprises in question in the course of integration, and, consequently, viability of the regional cluster became worthy of notice. At the same time, the project in question was rationalized from economic effectiveness perspective. For this line of the investigation a special methodological approach has been developed so as to allow predicting a level of synergetic effect of the clusterization.

Keywords

References

[1]  Boosting Innovation: The Cluster Approach, OECD Proceedings. OECD Publishing. Paris, 2012.
 
[2]  Dyrdonova, A.N., "Clustering petrochemical industry of the Republic of Tatarstan", Bulletin of the Kazan Technological University, 16 (12). 221-224. 2013.
 
[3]  Dyrdonova, A.N., "Formation and development of elements of innovation infrastructure in the region", Management of economic systems: electronic scientific journal, 12 (60). 2014. [Online].
 
[4]  Dyrdonova, A.N., "Methodical bases of potential clustering of regional economic systems", Business. Education. Law. Bulletin of the Volgograd Business Institute. 1 (26). 252-262. 2014.
 
[5]  Isbasoiu, G.M., Industrial Clusters and Regional Development. The Case of Timisoara and Montebelluna. MPRA Paper No. 5037. 2012. [Online].
 
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[6]  Ketels, С., Cluster Initiatives in Developing and Transition Economies. Center for Strategy and Competitiveness. Stockholm, 2012.
 
[7]  OECD Reviews of Regional Innovation: Competitive Regional Clusters: National Policy Approaches. OECD Publishing, Paris, 2013.
 
[8]  Porter, M.E., The Competitive Advantage of Nations. New York: Free Press, 2010.
 
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Article

Identification of the Educational Clusters in the Regional Economy: Theory, Methodology and Research Results (in Example of Perm Krai)

1Department of Worldand Regional Economics, Economic Theory, Perm State University, Perm, Russia


International Journal of Econometrics and Financial Management. 2014, 2(4), 153-162
DOI: 10.12691/ijefm-2-4-7
Copyright © 2014 Science and Education Publishing

Cite this paper:
Kovaleva T.Yu., Baleevskih V.G.. Identification of the Educational Clusters in the Regional Economy: Theory, Methodology and Research Results (in Example of Perm Krai). International Journal of Econometrics and Financial Management. 2014; 2(4):153-162. doi: 10.12691/ijefm-2-4-7.

Correspondence to: Baleevskih  V.G., Department of Worldand Regional Economics, Economic Theory, Perm State University, Perm, Russia. Email: kovalevatu@yandex.ru

Abstract

Article provides an algorithm and defined criteria for the identification of educational clusters in the regional economy, adapted to the Russian reality. Identification of the leading industries as promising regional educational clusters in the economy of Perm Krai conducted on the basis of quantitative Shift-Share analysis and the calculation of the localization coefficient. Statistical base of the research were materials of the central statistical database of the Federal State Statistics Service of the Russian Federation for 2007-2012 years by employment indicators. Qualitative diagnosis of educational clusters allowed to establish the shape and direction of development of strategic partnership in the educational system in the region, to identify the factors of competition. As a result, by applying a set of quantitative and qualitative methods of analysis of cluster, authors found that in the economy of Perm Krai has four potential educational clusters to be formed, the development of which should be a priority of educational policy in the region.

Keywords

References

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[18]  Zhuravleva, M.V., "Professional'naja podgotovka kadrov na osnove klasternogo podhoda" [Vocational training of shots on the basis of cluster approach], Vestnik Vysshej shkoly Alma mater” [Higher School Review. Alma mater]. 2. 50-56. 2010.
 
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Article

Identification of Tourist Clusters in the Pribaikal Region

1Department of Management and Service, Baikal State University of Economics and Law, Irkutsk, Russia


International Journal of Econometrics and Financial Management. 2014, 2(4), 163-167
DOI: 10.12691/ijefm-2-4-8
Copyright © 2014 Science and Education Publishing

Cite this paper:
Rubtsova Natalia Vladimirovna. Identification of Tourist Clusters in the Pribaikal Region. International Journal of Econometrics and Financial Management. 2014; 2(4):163-167. doi: 10.12691/ijefm-2-4-8.

Correspondence to: Rubtsova  Natalia Vladimirovna, Department of Management and Service, Baikal State University of Economics and Law, Irkutsk, Russia. Email: runatasha21@yandex.ru

Abstract

The purpose of this study was to assess the availability of tourism clusters in the regions of Pribaikal, namely the Irkutsk region and the Republic of Buryatia, using a variety of cluster identification methods. The findings suggest that the characteristics of tourism clusters are found in the Republic of Buryatia. However, in Irkutsk region they are not available, although the two regions are the object of a number of national and regional development programs of tourism clusters.

Keywords

References

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Article

Does Remittance in Nepal Cause Gross Domestic Product? An Empirical Evidence Using Vector Error Correction Model

1Central Department of Economics, Tribhuvan Univercity, Kathmandu, Nepal


International Journal of Econometrics and Financial Management. 2014, 2(5), 168-174
DOI: 10.12691/ijefm-2-5-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Kamal Raj Dhungel. Does Remittance in Nepal Cause Gross Domestic Product? An Empirical Evidence Using Vector Error Correction Model. International Journal of Econometrics and Financial Management. 2014; 2(5):168-174. doi: 10.12691/ijefm-2-5-1.

Correspondence to: Kamal  Raj Dhungel, Central Department of Economics, Tribhuvan Univercity, Kathmandu, Nepal. Email: kamal.raj.dhungel@gmail.com

Abstract

This study aims to investigate short and long run causality between the variable gross domestic product and remittance. The study is based on the estimation of vector error correction model. Testing the unit root and the co-integration is the basic requirement for the estimation of vector error correction model. Further, it also has estimated remittance elasticity using ordinary least square method. The finding reveals that the contribution of remittance in gross domestic product is only 0.07%. It means a 1% change in remittance will change the gross domestic product by only 0.07%. It indicates that the remittance what Nepal received from its migrants is being consumed, not saved and invested in the productive sector that can create gainful employment to the generation to come. Evidence has not support the hypothesis of remittance causes gross domestic product in the long run but there is strong evidence about the short run causality running from remittance to gross domestic product. But opposite is true in reverse order. Gross domestic product causes remittance in both short and long run.

Keywords

References

[1]  Ang, Alvin P. (2007), “Workers’ Remittances and Economic Growth in the Philippines”, Social Research Center, University of Santo Tomas, from (http://www.degit.ifw-kiel.de/papers/degit_12/C012_029.pdf).
 
[2]  Barajas, A., Chami, R., Connel, F., Gapen, M. and Montiel, P. (2009), “Do Workers’ Remittances Promote Economic Growth?” IMF Working Paper, WP/09/153, Washington, DC: IMF.
 
[3]  CBS (2011), “Nepal Living Standard Survey, Highlights” Central Bureau of Statistics, Kathmandu.
 
[4]  Carrasco, E. & Ro, J. (2007), “Remittances and Development”, http://www.uiowa.edu
 
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[7]  Dhungel K.R.(2008), “A causal relationship between energy consumption and economic growth in Nepal” Asia-Pacific Development Journal, Vol.15, No.1, pp. 137-150.
 
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[9]  Dhungel K.R.(2012), “ On the relationship between remittance and economic growth: Evidence from Nepal”, South Asia Journal, NJ, USA, October 2012, PP. 52-67.
 
[10]  Dhungel, K. R. (2008), “Remittance: A significant Income Source”`, The Kathmandu Post, March 16, 2008.
 
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[12]  Fayissa B, Nsiah (2008). “The impact of remittances on economic growth and development in Africa”, Department of Economics and Finance, Working paper Series, February, 2008. Online available at:http://ideas.repec.org/p/mts/wpaper/200802.html
 
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[22]  Rao B, Hassan G (2009), “Are the Direct and Indirect Growth Effects of Remittances Significant?” MPRA Paper, 18641 Available at: http://mpra.ub.uni/muenchen.de/18641 /1/MPRA_ paper_18641.pdf. Remittances Promote Economic Growth?,International Monetary Fund Working Paper.
 
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Article

Parametric Bootstrap Methods for Parameter Estimation in SLR Models

1Department of Statistics, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria


International Journal of Econometrics and Financial Management. 2014, 2(5), 175-179
DOI: 10.12691/ijefm-2-5-2
Copyright © 2014 Science and Education Publishing

Cite this paper:
Chigozie Kelechi Acha. Parametric Bootstrap Methods for Parameter Estimation in SLR Models. International Journal of Econometrics and Financial Management. 2014; 2(5):175-179. doi: 10.12691/ijefm-2-5-2.

Correspondence to: Chigozie  Kelechi Acha, Department of Statistics, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria. Email: specialgozie@yahoo.com

Abstract

The purpose of this study is to investigate the performance of the bootstrap method on external sector statistics (ESS) in the Nigerian economy. It was carried out using the parametric methods and comparing them with a parametric bootstrap method in regression analysis. To achieve this, three general methods of parameter estimation: least-squares estimation (LSE) maximum likelihood estimation (MLE) and method of moments (MOM) were used in terms of their betas and standard errors. Secondary quarterly data collected from Central Bank of Nigeria statistical bulletin 2012 from 1983-2012 was analyzed using by S-PLUS softwares. Datasets on external sector statistics were used as the basis to define the population and the true standard errors. The sampling distribution of the ESS was found to be a Chi-square distribution and was confirmed using a bootstrap method. The stability of the test statistic θ was also ascertained. In addition, other parameter estimation methods like R2, R2adj, Akaike Information criterion (AIC), Schwart Bayesian Information criterion (SBIC), Hannan-Quinn Information criterion (HQIC) were used and they confirmed that when the ESS was bootstrapped it turned out to be the best model with 98.9%, 99.9%, 84.9%, 85.4% and 86.7% respectively.

Keywords

References

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[12]  Xu, K. (2008). Bootstrapping autoregression under nonstationary volatility, Econometrics Journal, 11: 1-26.
 
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