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The Impact of GDP on Cross-Country Efficiency in Wealth Maximization: a Joint Analysis Through the Stochastic Frontier and Generalized Method of Moments

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  • Md Harun Or Rosid
  • Zhao Xuefeng
  • Sk Alamgir Hossain
  • Mohammad Raihanul Hasan
  • Md Reza Sultanuzzaman

Abstract

Wealth maximization is still the principal objective of a corporation and income plays a pivotal role in this regard. Taking this to the country context, wealth maximization can be a more refined objective alongside GDP growth. Considering GDP as the key wealth maximizer for a nation, the present work was undertaken to determine cross-country wealth efficiency and its determinants based on GDP covariates. The relationship between aggregate net wealth and GDP of 106 different countries for a period of 2009 to 2018 were analyzed to estimate annual incremental wealth efficiency based on their GDP covariates using input-output stochastic frontier analysis (SFA). Further, the determinants of incremental wealth efficiency were identified using multiple regression models. The SFA analysis shows significant negative impact of GDP on wealth maximization efficiency, like the law of diminishing marginal return to scales advocates. With the increase of GDP of a country, its marginal efficiency in wealth maximization decreases though aggregate wealth increases. The robust regression models show that imports, broad money and exchange rate undermine the wealth efficiency of a country and country’s past efficiency positively influences the subsequent year’s efficiency. These findings are expected to open new horizons for policymakers in policy analyses.JEL classification numbers: E1, E2, F4Keywords: Wealth Maximization, GDP, SFA, Technical Efficiency, GMM, Driscoll Kraay.

Suggested Citation

  • Md Harun Or Rosid & Zhao Xuefeng & Sk Alamgir Hossain & Mohammad Raihanul Hasan & Md Reza Sultanuzzaman, 2021. "The Impact of GDP on Cross-Country Efficiency in Wealth Maximization: a Joint Analysis Through the Stochastic Frontier and Generalized Method of Moments," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(1), pages 1-6.
  • Handle: RePEc:spt:admaec:v:11:y:2021:i:1:f:11_1_6
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    as
    1. Rodolfo E. Manuelli & Ananth Seshadri, 2014. "Human Capital and the Wealth of Nations," American Economic Review, American Economic Association, vol. 104(9), pages 2736-2762, September.
    2. Frank Cowell & Eleni Karagiannaki & Abigail Mcknight, 2018. "Accounting for Cross†Country Differences in Wealth Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 332-356, June.
    3. Michael Danquah and Bazoumana Ouattara, 2018. "Comparison of Stochastic Frontier Approaches for Estimating National Efficiency: An Application to Sub-Saharan African Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(3), pages 119-142, September.
    4. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    5. Fu, Shihe & Liao, Yu & Zhang, Junfu, 2016. "The effect of housing wealth on labor force participation: Evidence from China," Journal of Housing Economics, Elsevier, vol. 33(C), pages 59-69.
    6. Carroll, Christopher D. & Jeanne, Olivier, 2009. "A tractable model of precautionary reserves, net foreign assets, or sovereign wealth funds," CFS Working Paper Series 2009/15, Center for Financial Studies (CFS).
    7. Ahmad Baharumshah & Siew-Voon Soon, 2015. "Demand for broad money in Singapore: does wealth matter?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(3), pages 557-573, July.
    8. Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
    9. Randall Morck & David Stangeland & Bernard Yeung, 2000. "Inherited Wealth, Corporate Control, and Economic Growth The Canadian Disease?," NBER Chapters, in: Concentrated Corporate Ownership, pages 319-372, National Bureau of Economic Research, Inc.
    10. Hung‐pin Lai & Subal C. Kumbhakar, 2020. "Estimation of a dynamic stochastic frontier model using likelihood‐based approaches," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 217-247, March.
    11. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264, September.
    12. Robert Costanza & Ida Kubiszewski & Enrico Giovannini & Hunter Lovins & Jacqueline McGlade & Kate E. Pickett & Kristín Vala Ragnarsdóttir & Debra Roberts & Roberto De Vogli & Richard Wilkinson, 2014. "Development: Time to leave GDP behind," Nature, Nature, vol. 505(7483), pages 283-285, January.
    13. Baltagi, Badi H. & Heun Song, Seuck & Cheol Jung, Byoung & Koh, Won, 2007. "Testing for serial correlation, spatial autocorrelation and random effects using panel data," Journal of Econometrics, Elsevier, vol. 140(1), pages 5-51, September.
    14. Frank Cowell & Eleni Karagiannaki & Abigail McKnight, 2012. "Accounting for Cross-Country Differences in Wealth Inequality," LWS Working papers 13, LIS Cross-National Data Center in Luxembourg.
    15. Furong Chen & Yifu Zhao, 2019. "Determinants and Differences of Grain Production Efficiency Between Main and Non-Main Producing Area in China," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    16. Chieh-Wen Chang & Kun-Shan Wu & Bao-Guang Chang & Kuo-Ren Lou, 2019. "Measuring Technical Efficiency and Returns to Scale in Taiwan’s Baking Industry―A Case Study of the 85 °C Company," Sustainability, MDPI, vol. 11(5), pages 1-14, February.
    17. Rudan Wang & Bruce Morley & Javier Ordóñez, 2016. "The Taylor Rule, Wealth Effects and the Exchange Rate," Review of International Economics, Wiley Blackwell, vol. 24(2), pages 282-301, May.
    18. Nara F Monkam, 2014. "Local municipality productive efficiency and its determinants in South Africa," Development Southern Africa, Taylor & Francis Journals, vol. 31(2), pages 275-298, March.
    19. Randall K. Morck & David A. Strangeland & Bernard Yeung, 1998. "Inherited Wealth, Corporate Control and Economic Growth," William Davidson Institute Working Papers Series 209, William Davidson Institute at the University of Michigan.
    20. Baris Kaymak & CHEUK SHING LEUNG & Markus Poschke, 2018. "Accounting for the determinants of wealth concentration in the US," 2018 Meeting Papers 911, Society for Economic Dynamics.
    21. Gloria O. Dzeha & Joshua Abor & Festus Turkson & Elikplimi Agbloyor, 2018. "Technical Efficiency and Technical Change in Africa: The Role of Money from the Diasporas," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(7), pages 177-177, July.
    22. Ilke Van Beveren, 2012. "Total Factor Productivity Estimation: A Practical Review," Journal of Economic Surveys, Wiley Blackwell, vol. 26(1), pages 98-128, February.
    23. Peter Mihalyi & Iván Szelényi, 2017. "Wealth and capital: a critique of Piketty’s conceptualisation of return on capital," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 41(4), pages 1237-1247.
    24. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    25. Chen, Tain-jy & Tang, De-piao, 1987. "Comparing technical efficiency between import-substitution-oriented and export-oriented foreign firms in a developing economy," Journal of Development Economics, Elsevier, vol. 26(2), pages 277-289, August.
    26. Nazrul Islam, 2008. "Determinants of productivity across countries:an exploratory analysis," Journal of Developing Areas, Tennessee State University, College of Business, vol. 42(1), pages 201-242, September.
    27. Mollah Aminul Islam & Muhammad Asif Khan & József Popp & Wlodzimierz Sroka & Judit Oláh, 2020. "Financial Development and Foreign Direct Investment—The Moderating Role of Quality Institutions," Sustainability, MDPI, vol. 12(9), pages 1-22, April.
    28. Hayatullah Ahmadzai, 2017. "Crop Diversification and Technical Efficiency in Afghanistan: Stochastic Frontier Analysis," Discussion Papers 2017-04, University of Nottingham, CREDIT.
    29. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464, September.
    30. Schut, Frederik T. & Hassink, Wolter H. J., 2002. "Managed competition and consumer price sensitivity in social health insurance," Journal of Health Economics, Elsevier, vol. 21(6), pages 1009-1029, November.
    31. Mr. Boileau Loko & Mame Astou Diouf, 2009. "Revisiting the Determinants of Productivity Growth - What’s new?," IMF Working Papers 2009/225, International Monetary Fund.
    32. Filiz Garip, 2014. "The Impact of Migration and Remittances on Wealth Accumulation and Distribution in Rural Thailand," Demography, Springer;Population Association of America (PAA), vol. 51(2), pages 673-698, April.
    33. Donghun Kim & Dongwon Lee & Kap-Young Jeong, 2018. "A New Approach to Measuring a Multidimensional Productivity Index: An Application for 60 Selected Countries," Global Economic Review, Taylor & Francis Journals, vol. 47(3), pages 270-288, July.
    34. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    35. Lee, Lung-Fei & Tyler, William G., 1978. "The stochastic frontier production function and average efficiency : An empirical analysis," Journal of Econometrics, Elsevier, vol. 7(3), pages 385-389, April.
    36. Douglas, Paul H, 1976. "The Cobb-Douglas Production Function Once Again: Its History, Its Testing, and Some New Empirical Values," Journal of Political Economy, University of Chicago Press, vol. 84(5), pages 903-915, October.
    37. Donald Wittman, 2000. "The Wealth and Size of Nations," Journal of Conflict Resolution, Peace Science Society (International), vol. 44(6), pages 868-884, December.
    38. Fernando Gómez-Bezares & Wojciech Przychodzen & Justyna Przychodzen, 2016. "Corporate Sustainability and Shareholder Wealth—Evidence from British Companies and Lessons from the Crisis," Sustainability, MDPI, vol. 8(3), pages 1-22, March.
    39. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    wealth maximization; gdp; sfa; technical efficiency; gmm; driscoll kraay.;
    All these keywords.

    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment

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