ISSN: 2056-3736 (Online Version) | 2056-3728 (Print Version)
Hiroaki Sakurai
Correspondence: Hiroaki Sakurai, hiroaki.sakurai@gakushuin.ac.jp
Faculty of Intercultural Studies, Gakushuin Women’s College
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1019
This study examines the relationship between foreign aid and investment in Thailand in two ways to see whether foreign aid contributes to Thai economy through encouraging investment in Thailand. The estimation results are summarized as follows. First, the relationship between foreign aid and investment adding to trade, savings, and growth from 1975 to 2020 is shown as positive relationships by using OLS but not by using VAR model. Second, positive relationship between the accumulated foreign aid and foreign direct investment from 1970 to 2020 is shown by using the VAR model, the Granger causality test, and the Impulse response test. Based on the estimation results, we infer that in Thailand foreign aid mainly arranged for social infrastructure since the 1980s guided investments to an extent since foreign aid and investment in Thailand has positive relationship under some restrictions.
Foreign Aid, Vanguard, Foreign Direct Investment, Thailand.
Arndt, C., Jones, S., and Tarp, F. (2016). What is the aggregate economic rate of return to foreign aid? The World Bank Economic Review, 30(3), 446-474.Besley, T., and Burgess, R. (2003). Halving global poverty. Journal of Economic Perspectives, 17(3), 3-22.Borensztein, E. J., De Gregorio, J., and Lee, J-W. (1998). How does foreign direct investment affect economic growth? Journal of International Economics, 45, 115-135.Burnside, C., and Dollar, D. (2000). Aid, policies and growth. American Economic Review, 90(4), 847-868.Dollar, D., and Kraay, A. (2002). Growth is good for the poor. Journal of Economic Growth, 7, 195-225.Easterly, W., Levine, R., and Roodman, D. (2004) Aid, policies, and growth: comment. American Economic Review, 94(3), 774-780.Hansen, H. and Tarp, F. (2000). Aid effectiveness disputed. Journal of International Development, 12(3), 375-398.Hsiao, F. S. T., and Hsiao, MC. W. (2006). FDI, exports, and GDP in East and Southeast Asia – panel data versus time series causality analysis, World Development, 69, 31-43.Kimura, H, and Todo, Y., (2010). Foreign aid a vanguard of foreign direct investment? A gravity-equation approach, World Development, 38(4), 482-497.Nowak-Lehmann, F., Dreher, A., Herzer, D., Klasen, S. and Martinez-Zarzoso, I. (2012). Does foreign aid really raise per capita income? A time series perspective. Canadian Journal of Economics, 45(1), 288-313.Nowak-Lehmann, F., and Gross, E. (2021). Aid effectiveness: when aid spurs investment, Applied Economic Analysis, 29(87), 189-207.Ravallian, M. (2001). Growth, inequality and poverty: looking beyond averages. World Development, 29(11), 1803-1815.Rajan, R.G. and Subramanian, A. (2008). Aid and growth: what does the cross-country evidence really show? Review of Economics and Statistics XC. 90(4), 643-665.Sakurai, H. (2021). Effects of foreign aid: Evidence from Thailand. Springer, New Frontiers in Regional Science: Asian Perspectives.
Hiroaki Sakurai
Correspondence: Hiroaki Sakurai, hiroaki.sakurai@gakushuin.ac.jp
Faculty of Intercultural Studies, Gakushuin Women’s College
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1018a
This study examines the relationship between foreign aid and total factor productivity (TFP) in Thailand from 1972 to 2013 using the VAR model and Granger causality. While discussing the role of foreign aid in the economy of recipient countries, it is important to examine whether foreign aid contributes to the productivity of the recipient country. Estimation results do not show any evidence of a relationship between foreign aid and the TFP in Thailand, indicating that foreign aid does not necessarily directly affect productivity. This result is also considered to be suitable for previous studies.
Foreign Aid, Total Factor Productivity, Thailand.
Aschauer, D. A. (1989) Is Public Expenditure Productive? Journal of Monetary Economics, 23, 177-200.Benhabib, J., and Spiegel, M. M. (1994) The Role of Human Capital in Economic Development Evidence from Aggregate Cross-country Data, Journal of Monetary Economics, 34, 143-173.Burnside, C., and Dollar, D. (2000) "Aid, Policies, and Growth," American Economic Review, 90(4), 847-868.Chuenchoksan, S., and Nakornthab, D. (2008) Past, Present, and Prospects for Thailand's Growth: A Labor Market Perspective, Bank of Thailand Discussion Paper Working Papers, 2008(7), Monetary Policy Group, Bank of Thailand.Easterly, W., Levine, R., and Roodman, D. (2004) New Data, New Doubts: Comment on 'Aid, Policies and Growth (2000)' by Burnside and Dollar, American Economic Review, 94(3), 774-780.Easterly, W. (2006) The White Man's Burden: Why the West's Efforts to Aid the Rest Have Done So Much Ill and So Little Good, New York: Penguin Press.Easterly, W. (2007) Was Development Assistance a Mistake? American Economic Review, 97(2), 328-332.Groß, E., and Nowak-Lehmann Danzinger, F. (2022) What effect does development aid have on productivity in recipient countries? Review of Development Economics, 26, 1438-1465.Jones, C. I., and Williams, J. C. (1998) Measuring the Social Return to R&D, Quarterly Journal of Economics, 113(4), 1119-1135.Krugman P. (1994) The myth of Asia's miracle, Foreign Affairs, 73(6), 62-79.Lucas, R. E. (1988) On the Mechanics of Economic Development. Journal of Monetary Economics, 22, 3-42.Nakornthab, D. (2013) Revisiting Thailand's Potential Growth Rate, TDRI Quarterly Review, 28(4), 3-6.Romer, P. M. (1990) The Problem of Development: A Conference of the Institute for the Study of Free Enterprise Systems, Journal of Political Economy, 98(5), S71-S102.Sakurai, H. (2021) Effects of foreign aid: Evidence from Thailand. Springer, New Frontiers in Regional Science: Asian Perspectives.Stokey, N. L. (2015) Catching up and falling behind, Journal of Economic Growth, 20(1), 1-36.Tinakorn, P., and Sussangkarn, C. (1996) Productivity Growth in Thailand, Thailand Development Research Institute, Research Monograph, 15.
Fahmida Mostafiz and Jianqiang Sun
Correspondence: Fahmida Mostafiz, fahmida@du.ac.bd
Department of International Business, Faculty of Business Studies, University of Dhaka, Dhaka, Bangladesh. School of Economics and Finance, South China University of Technology, Guangzhou, China.
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1017
This paper examines the effects of industrial policies series taken since 2005 on the ready-made garments in Bangladesh, including formation of export processing zones, taxation facility, flat-rate duty drawback facility, FDI with equity participation and so on. Difference in Differences technique is employed and a panel dataset of industrial policy and export data of 75 companies from 1991 to 2020 are used to evaluate the quantitative effects. Empirical findings show that the industrial policies have had a significant positive impact on the RMG export, and that RMG exports increase on an average 10.68% after industry policy 2005 introduced. This paper contributes by providing empirical evidence for the industrial policies effect on Bangladesh exportation.
Industrial Policy, RMG industry, MFA phase out, DID.
Adhikari, R., & Weeratunge, C. (2007). Textiles and Clothing in South Asia. South Asia Economic Journal, 8(2), 171-203.
Ahmed, N. (2009). Sustaining Ready-made Garment Exports from Bangladesh. Journal of Contemporary Asia, 39(4), 597-618.
Alam, M. S., & Natsuda, K. (2016). The competitive factors of the Bangladeshi garment industry in the post-MFA era. Canadian Journal of Development Studies, 37(3), 316-336.
Alam, M. S., Selvanathan, E. A., & Selvanathan, S. (2017). Determinants of the Bangladesh garment exports in the post-MFA environment. Journal of the Asia Pacific Economy, 22(2), 330-352.
Ali, M. R., Grava, L., & Reaz, M. M. (2019). Agile Regulatory Delivery For Improved Investment Competitiveness In Bangladesh: Current State And Policy Options. Working paper of International Finance Corporation, Washington D.C.
Anner, M. (2020). Squeezing workers’ rights in global supply chains: purchasing practices in the Bangladesh garment export sector in comparative perspective. Review of International Political Economy, 27(2), 320-347.
Bank, B. (2020). Foreign Direct Investment (FDI) in Bangladesh. Survey Report, 2019.
BEPB. (2021). Export Data and Factories data. Bangladesh Export Promotion Bureau. doi:http://www.epb.gov.bd/site/office/dae634b2-937d-4f49-8eb7-ceae107e6736/Export-Promotion-Bureau
BGMEA. (2021). Trade Information doi:https://www.bgmea.com.bd/page/Export_Performance
Chang, Z., & Li, X. (2021). How regulation on environmental information disclosure affects brownfield prices in China: a difference-in-differences (DID) analysis. Journal of Environmental Planning and Management, 64(2), 308-333.
Eusuf, M. A., Shams, M. N. A., & Sharmin, S. (2007). RMG Export Performance: Two Years after the MFA Phase-out. Society & Change, 1(4),21-29.
Haider, M. Z. (2007). Competitiveness of the Bangladesh Ready-made Garment Industry in Major International Markets. Asia Pacific Trade and Investment Review, 3(1), 3-26.
Hossain, S. M., & Hosoe, N. (2017). Foreign Direct Investment in the Ready-Made Garments Sector of Bangladesh : Macro and Distributional Implications. GRIPS Discussion Papers 17-10, National Graduate Institute for Policy Studies.
IP. (2005). Industrial Policy 2005. Dhaka: Government of the People’s Republic of Bangladesh
IP. (2010). Industrial Policy 2010. Dhaka: Government of the People’s Republic of Bangladesh
IP. (2016). Industrial Policy 2016. Dhaka: Government of the People’s Republic of Bangladesh
Islam, M. S. (2021). Ready-made garments exports earning and its contribution to economic growth in Bangladesh. GeoJournal, 86(3), 1301-1309.
Giang, L. T., Nguyen, V. T., & Nguyen, T. D. (2021). Child labor in Vietnam: Issues and policy implications. Children and Youth Services Review, 130, 106-222.
Khan, S. R., Dhar, D., Navaid, M., Pradhananga, M., Siddique, F., Singh, A., & Yanthrawaduge, S. (2009). The Readymade Garment Sector in Bangladesh. In Export Success and Industrial Linkages: The Case of Readymade Garments in South Asia (pp. 43-56). New York: Palgrave Macmillan US.
Kiel, K., & Katherine, M. (1995). House Prices during Siting Decision Stages: The Case of an Incinerator from Rumor through Operation. Journal of Environmental Economics and Management, 28(2), 241-255.
Majmudar, M. (1996). Trade Liberalisation in Clothing: the MFA Phase-Out and theDeveloping Countries. Development Policy Review 14, 5-36.
Majumdar, A., Garg, H., & Jain, R. (2021). Managing the barriers of Industry 4.0 adoption and implementation in textile and clothing industry: Interpretive structural model and triple helix framework. Computers in Industry, 125, 103-372.
Miles, W. (2008). Exchange rates, inflation and growth in small, open economies: a difference-in-differences approach. Applied Economics, 40(3), 341-348.
Mlachila, M., & Yang, Y. (2004). The End of Textiles Quotas: A Case Study of theImpact on Bangladesh. IMF Working Paper (WP/04/108).
Nayak, R., Akbari, M., & Maleki Far, S. (2019). Recent sustainable trends in Vietnam's fashion supply chain. Journal of Cleaner Production, 225, 291-303
Neureiter, M. (2019). Evaluating the effects of immigrant integration policies in Western Europe using a difference-in-differences approach. Journal of Ethnic and Migration Studies, 45(15), 2779-2800.
Nordås, & Kyvik, H. (2004). The global textile and clothing industry post the agreement on textiles and clothing. Paper presented at the WTO Discussion Papers 5, World Trade Organization (WTO), Economic Research and Statistics Division.
Papon, A. I., Nabi, M. N., & Parvin, M. (2017). Impacts of Political Instability on Garments Productions & Productivity: A Study on a group of Textile industries in Bangladesh. International Journal of Scientific & Engineering Research, 8(4),535-551.
Pedraja-Chaparro, F., Santín, D., & Simancas, R. (2016). The impact of immigrant concentration in schools on grade retention in Spain: a difference-in-differences approach. Applied Economics, 48(21), 1978-1990.
Razzaque, A. (2005). Sustaining RMG growth after MFA phase out: An analysis of relevant issues with refrence to trade and human development ILO, UNDP Project No: BGD/85/153.
Roy, D. K. (2006). Governance, Competitiveness and Growth: The Challenges for Bangladesh ADB Institute Discussion Paper No. 53.
Slaughter, M. J. (2001). Trade liberalization and per capita income convergence: a difference-difference analysis. Journal of International Economics, 55,203-228.
WB (2020). Worldwide Governance Indicators (WGI) Project. The World Bank, Washington DC, USA
Wooldridge, J. M. (2013). Introductory econometrics: A modern approach (5 ed.). Mason, OH: South-Western, Cengage Learning.
Miguel D. Ramirez
Correspondence: Miguel D. Ramirez, Miguel.Ramirez@trincoll.edu
Trinity College, Hartford, CT, USA.
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1016
This paper investigates the impact of remittance flows on economic output and labor productivity for Mexico during the 1970-2017 period. The findings suggest that remittance flows to Mexico have a positive and significant effect on economic output and labor productivity. The paper is organized as follows: First, it gives an overview of remittance flows in absolute terms, relative to GDP, in comparison to FDI inflows, and in terms of their regional destination. Next, the paper reviews the growing literature that assesses the impact of remittances on investment spending and economic growth. Third, to motivate the discussion of the empirical results, the paper presents a simple endogenous growth model that explicitly incorporates the potential impact of remittance flows on economic output and labor productivity. Fourth, it presents a modified empirical counterpart to the simple model that tests for unit roots and performs both a Johansen cointegration test and a Gregory and Hansen cointegration test with an endogenously determined regime shift. FMOLS and DOLS long-run estimates for the period in question suggest that remittance flows to Mexico have a positive and significant effect, albeit small, on both the levels of economic output and labor productivity. The concluding section summarizes the major results and discusses potential avenues for future research on this important topic.
ADF unit root test, DOLS, FDI inflows, FMOLS, Gregory-Hansen cointegration single-break test, Gross fixed capital formation, Johansen Cointegration test, KPSS no unit root test, labor productivity, and remittance flows.
Acosta, Pablo A. et al. 2008. “Remittances and the Dutch Disease.” Federal Reserve Bank of Atlanta, Working Paper2007-8a (August), 1-22.Aitymbetov, S. 2006. “Emigrant remittances: Impact on economic development of Kyrgyzstan.” ICEG Working Paper (June), 1-20.Bahamani-Oskoee, M. 1996. “Decline of the Iranian Rial during the post-revolutionary period: A Productivity Approach,” Journal of Developing Areas, 30, 479-92.Barajas, Adolfo et al. 2009. “Do Workers Remittances Promote Economic Growth?” IMF Working Paper, No. 153 (July), 1-22.Barro, R.J. 1990. “Government Spending in a Simple Model of Endogenous Growth,” Journal of Political Economy, 98, 5, 103-125.Bloomstrom, M. and E. Wolff. Multinational Corporations and Productivity Convergence in Mexico. 1994. In Convergence of Productivity: Cross-National Studies Historical Evidence, edited by W. Baumol, R. Nelson, and E. Wolff. Oxford: Oxford University Press.Canas, J., Coronado, R., & Orrenius, P. 2007. Explaining the increase in remittances to Mexico. The Southwest Economy, Federal Reserve Bank of Dallas, July/August.Chami, R., Fullenkamp, C., & Jahjah, S. 2005. “Are immigrant remittance flows a source of capital for development?” IMF Staff Papers, 53 (1), 57-70.Chami, R., Barajas, A., Montiel, P., & Hakura, D. 2010. “Workers' remittances and the equilibrium real exchange rate: Theory and evidence,” IMF Working Papers, 10 (287), 1. https://doi.org/10.5089/9781455210947.001 Charemza, W.W. and D.F. Deadman. 1997. New Directions in Econometric Practice: General to Specific Modelling, Cointegration and Vector Autoregression. Cheltenham: Edward Elgar Publishers.Cypher, J.M. 2014. The Process of Economic Development, 4th ed. New York: Routledge.De Mello, Jr. Luiz R. 1997. “Foreign Direct Investment in Developing Countries and Growth: A Selective Survey.” Journal of Development Studies, 34, 1 (October), 1-34.De Vita, G. and K. Lawler. 2004. “Foreign Direct Investment and its Determinants: A Look to the Past, A View to the Future." In Foreign Investment in Developing Nations, edited by H.S. Kehal. New York: Palgrave Macmillan, Ltd.Dickey, D., and W. Fuller, 1979. “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root.” Econometrica, 49 (June), 1057-1072.Doldado, J., T. Jenkinson, and S. Sosvilla-Rivero, 1990. “Cointegration and Unit Roots,” Journal of Economic Surveys, 4: 249-73.ECLAC. 2006-2021. Foreign Investment in Latin America and the Caribbean, Various Reports.Ellerman, D. 2003. “Policy Research on Migration and Development,” World Bank Policy Research Working Paper, No. 3117. Washington, D.C.: The World Bank.Engle, R.F. and C.W.J. Granger. 1987. “Cointegration and Error Correction: Representation, Estimation, and Testing.” Econometrica 55 (March), 251-76.Fayissa, B. and C. Nsiah, 2012. “Financial Development and Remittances in Africa and the Americas: A Panel-Unit Root Tests and Panel Cointegration Analysis.” Department of Economics and Finance Working Paper Series, Middle Tennessee State University, March: 1-22.Guiliano, P. and Ruiz-Arranz, M. 2006. “Remittances, Financial Development, and Growth.” IMF Working Papers, No. 05-234.Gregory, A.W. and B.E. Hansen. 1996. “Tests for Cointegration in Models with Regime and Trend shifts.” Journal of Econometrics 70, 1, 99-126.Hakkio, C. S., and M. Rush. 1991. “Cointegration: How Short is the Long- run? Journal of International Money and Finance, 10, 571-81.Johansen, Soren and K. Juselius. 1990. “Maximum Likelihood Estimation and Inference on Cointegration with Applications to the Demand for Money.” Oxford Bulletin of Economics and Statistics, 52 (May), 169-210.Kao, C. and Chiang, M.H. 2000. “On the Estimation and Inference of a Cointegrated Regression in Panel Data.” In: Baltagi, B., Ed., Nonstationary Panels, Panel Cointegration, and Dynamic Panels, JAI Press, Amsterdam, 161-178Kumar, R. R. 2013. “Remittances and economic growth: A study of Guyana.” Economic Systems, 37(3), 462–472. https://doi.org/10.1016/j.ecosys.2013.01.001Kwaitkowski, D., Phillips, P.C.B., Schmidt, P., and Shin, Y., 1992. “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root,” Journal of Econometrics, 54, 159-78.Lee, J. and M.C. Strazicich. 2003. “Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks,” The Review of Economics and Statistics, 85 (4), 1082-1089.Meyer, D. and A. Shera, 2017. “The Impact of Remittances on Economic Growth: An Econometric Model,” EconomiA, 18, 2, 147-155.Mohapatra, D., D. Ratha, and A. Silwal. 2011. “Outlook for Remittance Flows 2011-13,” Migration and Development Brief, No. 16. Washington, D.C.: The World Bank, May.Mundaca, G. (2005). Can remittances enhance economic growth? the role of financial market development SSRN. Retrieved from http://ssrn.com/paper=799484Nacional Financiera, S.A. La Economia Mexicana en Cifras. Mexico, D.F.: Nafinsa, various issues.Orozco, M. 2004. “Mexican Hometown Associations and Development Opportunities,” Journal of International Affairs, 57, 2, 1-20.Perron, P. 1989. “The Great Crash, the Oil Price Shock and the Unit Root Hypothesis,” Econometrica, 57, 1361-1401.Ramanarayanan, A. 2009. “Ties that Bind: Bilateral Trade’s Role in Synchronizing Business Cycles” Economic Letter, 4, 1, January, pp. 1-8. Federal Reserve Bank of Dallas.Ram, R., and Zhang, K. H. 2002. “Foreign Direct Investment and Economic Growth: Evidence from Cross-Country Data for the 1990s,” Economic Development and Cultural Change, 51, 205-215.Ratha, D. 2003. “Workers’ Remittances: An important and Stable Source of External Development Finance.” Global Development Finance. Washington, D.C.: The World Bank.Saikkonen, P. 1991. “Asymptotically Efficient Estimation of Cointegration Regressions. Econometric Theory,” 7, 1-21. http://dx.doi.org/10.1017/S0266466600004217Salahuddin, M. and Gow, J. 2015. “The Relationship between Economic Growth and Remittances in the Presence of Cross-Sectional Dependence,” The Journal of Developing Areas, 49, 207-221. https://doi.org/10.1353/jda.2015.0007Sharma, H. and M.D. Ramirez. 2009. “Remittances and Growth in Latin America: A Panel Unit Root and Panel Cointegration Analysis,” Estudios Economicos de Desarrollo Internacional, 9 (1), 5-32.Solimano, A. 2003. “Remittances by Emigrants: Issues and Evidence.” Macroeconomias del Desarrollo, 26, Economic Development Division. Santiago: Chile, October.The World Bank. 2010-2022. Migration and Development Brief, Various Issues. Washington, D.C.: Migration and Remittances Unit.United Nations. 2021-2022. World Investment Reports 2021-2022: Trends and Determinants. Switzerland: United Nations.Woodruff, C., 2006. Mexican microenterprise investment and employment: Role of remittances. INTAL-ITD Working Paper 26.
Tito Nestor TIEHI
Correspondence: Tito Nestor TIEHI, tito.tiehi@cierea-ptci.com
University of Cocody-Abidjan, Côte d’Ivoire
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1015
The purpose of this study is to estimate the impact of HIV and Covid19 on the efficiency of the public health system in Côte d'Ivoire. To this end, we use non-parametric data envelopment analysis (DEA) and double bootstrap procedures to analyze the data. The analyze reveals that district hospitals are not technically efficient. These estimates show that in 2019, TB-HIV co-infection and geographic accessibility increases technical efficiency, while respiratory diseases reduce it. In contrast, in 2020, the advent of the Covid-19 pandemic blunted the positive impact of TB-HIV co-infection and geographical accessibility on the technical efficiency of the Ivorian health system observed in 2019. This result, due to the reorientation of resources allocated to the health sector to deal with the Covid-19 pandemic, is similar to the crowding out of the HIV pandemic by that of Covid-19.
Double Bootstrap, Tuberculosis/HIV, Covid-19.
Aldieri, L., Brahmi, M., Chen, X. and Vinci, C.P. (2021). “Knowledge spillovers and technical efficiency for cleaner production: An economic analysis from agriculture innovation”, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2021.128830.Anang, B. T., Alhassan, H., and Danso-Abbeam, G. (2020). “Technology adoption and technical efficiency of smallholder farmers in Tolon district of Ghana: double bootstrap DEA approach”, Agricultural Economics and Policy. https://doi.org/10.21203/rs.3.rs-17237/v1.Battese, G. and Corra, G. (-1977). “Estimation of a production frontier model with application to the pastoral zone of Eastern Australia” Aust. J. Agric. Resour. Econ. 21, 167–179Blank, J.L.T. and Valdmanis, V.G. (2010). “Environmental factors and productivity on Dutch hospitals: a semi-parametric approach” Health Care Management Science 13, 27-34.Chilingerian, J. A. (1995). “Evaluating physician efficiency of decision-making units” European Journal of Operational Research 80, 548-574.Coelli, T. (1998). “A multi-stage methodology for the solution of orientated DEA models” Operations Research Letters 23, 3-5 143-149.Farrell, M. J. (1957). “The Measurement of Productive Efficiency” Journal of the Royal Statistical Society, A 120, 253-290.Halkos, G. E. and Tzeremes, N. G. (2011).“A conditional nonparametric analysis for measuring the efficiency of regional public healthcare delivery: An application to Greek prefectures”. Health policy, 103(1), 73-82.Kirjavaïnen, T. and Loikkanen, H. A. (1998). “Efficiency differences of Finnish senior secondary schools: an application of DEA and Tobit analysis” Economics of Education Review. 17,4, 377-394.Leleu, H. and Derveaux, B. (1997). “Comparaison des différentes mesures d’efficacité technique: application aux centres hospitaliers français” Economie et Prévision, 129-130, 3/4.Romley, J.A. and Goldman, D.P. (2011). “How Costly is Hospital Quality? A Revealed‐Preference Approach” The Journal of Industrial Economics 59, 4, 578-608.Scheraga, D. J. (2004). Operational efficiency versus financial mobility in the global airline industry: A Data Envelopment and Tobit analysis. Transportation Research. part A. 38, 383-404.Simar, L. and Wilson, P.W. (2007). “Estimation and Inference in Two-Stage. Semi-Parametric Models of Production Processes” Journal of Econometrics,136, 31-64.Steinmann, L. Zweifel (2003). “On the Inefficiency of Swiss hospital”, Applied Economics vol 35, n°3, pp 361-370.Tiehi, T.N. (2020). “Technical Inefficiency of District Hospitals in Côte d'Ivoire: Measurement, Causes and Consequences, International” Journal of Economics and Finance, 12,9, 35-45.UNAIDS (2020). “2020 Global AIDS Update -Seizing the moment-Tackling entrenched inequalities to end epidemics”, UNAIDS report on the global AIDS epidemic, retrieved from:https://www.unaids.org/sites/default/files/media_asset/2020_global-aids-report_en.pdf.Valdmanis, V., Kumanarayake, L. and Lertiendumrong, J. (2004). “Capacity in Thai Public Hospitals and the Production of Care for Poor and Nonpoor Patients”, Health Service Research Volume39, Issue6p2 Pages 2117-2134.Ventura, J., Gonzalez, E. and Carcaba, A. (2004). Efficiency and program-contract bargaining in Spanish public hospital, Annals of public and cooperatives Economics, vol 75, n°4, pp 549-573.WHO (2021). “World health statistics 2021: monitoring health for the SDGs, sustainable development goals”. World Health Organization. https://apps.who.int/iris/handle/10665/342703. Licence: CC BY-NC-SA 3.0 IGO
Abdullaev Elbek Erkin Ugli
Correspondence: Abdullaev Elbek Erkin Ugli, eeabdullaev@gmail.com
Graduate School of Humanities and Social Sciences, Saitama University, Saitama, Japan.
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1014a
Post-Soviet countries have never been analysed in the global value chain (GVC) context. Therefore, in this study, we evaluate the degree of backward participation of GVCs in the manufacturing sector of post-Soviet countries. We also examine the quantitative linkage between GVCs and host countries’ logistics performance as a service-link component. We used the UNCTAD-Eora GVC database and employed a structural gravity trade model. The results illustrate a positive correlation between GVC backward participation in manufacturing and income levels in the post-Soviet economies. The empirical estimation using the structural gravity trade model demonstrates a quantitative linkage between GVC backward participation and the logistics performance of the host country. The level of logistics performance accounts for 70–80 percent of the degree of GVC backward participation. Our findings’ major policy implication is that post-Soviet economies’ logistics performance should be improved by erasing the Soviet era’s negative legacy.
Global value chains, Logistics performance, Post-Soviet countries, Manufacturing, Structural gravity trade model.
Kaldor, N. (1967). Strategic Factor in Economic Development. Ithaca, Cornell University.Rodrik, D. (2013). Unconditional convergence in manufacturing. Q J Econ, 128(1), 165–204.UNCTAD (2013). World investment report—global value chains: Investment and trade for development. New York and Geneva, The United Nations.Kimura, F. (2006). International production and distribution networks in East Asia: Eighteen facts, mechanics, and policy implications. Asian Econ Policy Rev, 1(2), 326–344.Kimura, F., Takahashi and Y., Hayakawa, K. (2007). Fragmentation and parts and components trade: Comparison between East Asia and Europe. N Am J Econ Finance, 18(1), 23–40.World Bank (2020). World development report 2020: Trading for development in the age of global value chains. Washington, The World Bank.Hummels, D., Ishii, J. and Yi, K.M. (2001). The nature and growth of vertical specialization in world trade. J Int Econ, 5, 75–96.Koopman, R., Powers, W., Wang, Z. and Wei, S.J. (2010). Give credit where credit is due: Tracing value added in global production chains. NBER Working Paper, No. 16426.Koopman, R., Wang, Z. and Wei, S.J. (2014). Tracing value-added and double counting in gross exports. Am Econ Rev, 104, 459–494.Jones, R.W. and Kierzkowski, H. (1990). The role of services in production and international trade: A theoretical framework, In: Jones, R.W. and Krueger, A. (eds.), The Political Economy of International Trade: Essays in Honor of Robert E. Baldwin. Oxford, Blackwell.Jones, R.W. and Kierzkowski, H. (2005). International trade and agglomeration: an alternative framework. J Econ, 10, 1–16.Deardorff, A.V. (2001). Fragmentation in simple trade models. N Am J Econ Finance, 12, 121–137.Gereffi, G. (2018). Global Value Chains and Development: Redefining the Contours of 21st Century Capitalism. Cambridge, Cambridge University Press.Taguchi, H. and Thet, M.S. (2021). Quantitative linkage between global value chains’ backward participation and logistics performance in the host country: a structural gravity model analysis of emerging ASEAN economies. Asia-Pacific Journal of Regional Science, 5, 453–475.Piermartini, R. and Yotov, Y.V. (2016). Estimating trade policy effects with structural gravity. WTO Staff Working Papers, ERSD-2016-10.Taguchi, H. and Amirjon, A. (2021). Manufacturing exports and institutional qualities in Central Asian countries. Asia-Pacific Journal of Accounting & Economics Online. https://doi.org/10.1080/16081625.2021.2012703World Bank (2016). Making global value chains work for development. Washington: The World Bank.Casella B, Bolwijn R, Moran D, Kanemoto K (2019). Improving the analysis of global value chains: The UNCTAD-Eora Database. Transnatl Corp, 26(3), 115–142.Aslam, A., Novta, N. and Rodrigues-Bastos, F. (2017). Calculating Trade in Value Added. IMF Working Paper, No. 17/178.Levin, A., Lin, C.F. and Chu, C. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. J Econom, 108, 1–24.Choi, I. (2001). Unit root tests for panel data. J Int Money Finance, 20, 249–272.Maddala, G.S. and Wu, S.A. (1999). Comparative study of unit root tests with panel data and a new simple test. Oxf Bull Econ Stat, 61, 631–652.Im, K.S., Pesaran, M.H. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. J Econom, 115, 53–74.Taguchi, H. and Zhao, J. (2022). China's global value chain linkage and logistics performances in emerging ASEAN economies. International Studies of Economics, 17, 126–155.
Konstantinos Marinakos, Georgia Pistikou and Alkistis Papaioanou
Correspondence: Georgia Pistikou, gpistikou@uniwa.gr
Department of Tourism Management, University of West Attica, Greece.
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1013
This paper focused on the study and analysis of the phenomenon of tax evasion in Greek hospitality companies (hotels). Its main research objective was to investigate the degree of tax evasion of hotel companies, to examine its causes, its implications and how to deal with it. The processing of the replies given shows that a large proportion of hoteliers consider that businesses are 'over-taxed', while a common belief is that if a more favourable tax treatment were to apply it would lead to a strengthening of the overall conscience/ideological perception in favour of the institution of taxation. Finally, it is necessary to take measures to deal more rationally with tourism enterprises and to review the taxation policies of hotel companies as a tool to support them in times of crisis such as the current Covid-19 pandemic.
Tax evasion, Over- taxed, Hospitality companies, Taxation policies.
Alvarez-Martinez, M. T., Barrios, S., d’Andria, D., Gesualdo, M., Nicodème, G., & Pycroft, J. (2018). How large is the corporate tax base erosion and profit shifting? A general equilibrium approach CEPR discussion papers DP12637. Centre for Economic Policy Research.Antonakakis, N., Dragouni, M., & Filis, G. (2015). How strong is the linkage between tourism and economic growth in Europe? Economic Modelling, 44,142–155.Atuguba, R. (2006). The tax culture of Ghana: A research report prepared for the Revenue Mobilisation Support (RMS). Accra: German Development Cooperation (GTZ), Revenue Mobilisation Support (RMS), Ghana.Barrios, S., d’Andria, D. & Gesualdo, M. (2020). Reducing tax compliance costs through corporate tax base harmonization in the European Union. Journal of International Accounting, Auditing and Taxation, 41.Boadway, R., & Keen, M. (1993). Public goods, self-selection and optimal income taxation. International Economic Review, 34(3), 463–478.Chang, J. Lu, L. & Hu, S. (2011). Congestion externalities of tourism, Dutch Disease and optimal taxation: macroeconomic implications. Economic Record, 87(276), 90-108.Chuenjit, P. (2014). The Culture of Taxation: Definition and Conceptual Approaches for Tax Administration. Journal of Population and Social Studies, 22(1), 14-34.Danopoulos, C. P., & Znidaric, B. (2007). Informal economy, tax evasion, and poverty in a democratic setting: Greece. Mediterranean Quarterly, 18(2), 67-84.Forsyth, P. & Dwyer, L. (2002). Market Power and the Taxation of Domestic and Intonational Tourism. Tourism Economics, 8(4), 377-399.Jacobs, B. (2018). The marginal cost of public funds is one at the optimal tax system. International Tax and Public Finance, 25(4), 883-912.Jacquet, L., Lehmann, E., & Van der Linden, B. (2013). The optimal marginal tax rates with both intensive and extensive responses. Journal of Economic Theory, 148(5), 1770–1805.Jairaj, A. & Harriss-White, B. (2006). Social structure, tax culture and the state: The case of Tamil Nadu. Economic and Political Weekly, 41(51), 5247-5256.Haga, J., Höglund, H., & Sundvik, D. (2019). Cost behaviour around corporate tax rate cuts. Journal of International Accounting, Auditing and Taxation, 34, 1–11.Hartner, M., Rechberger, S., Kirchler, E. & Schabmann, A. (2008). Procedural fairness and tax compliance. Economic Analysis and Policy, 38(1), 137-152.Hyun, J. K. (2005). Tax compliances in Korea and Japan: Why are they different? Policy Research Institute. Ministry of Finance. Japan.Gago, A., Labandeira, X., Picos, F. &. Rodriguez, M. (2009). Specific and general taxation of tourism activities. Evidence from Spain. Tourism Management, 30, 381–392.Gahvari, F. (2014). Second-best Pigouvian taxation: A clarification. Environmental and Resource Economics, 59(4), 525-535.Gainous, J., Martinez, MD. & Craig, SC. (2010) The multiple causes of citizen ambivalence: attitudes about social welfare policy. Journal of Elections Public Opinion & Parties, 20:335–356.Karagiannis, G., Metaxas, M. & Laloumis, A. (2017). The viability of the Greek tax system from the point of view of Hospitality Enterprises. A field research in Athens, Greece. Journal of Tourism Research, 16, 311-323.Keen, M. (2007). VAT attacks! International Tax and Public Finance. 14, 365–381.Lyberaki, A., Meghir, C., & Nikolitsas, D. (2017). Beyond Austerity: Reforming the Greek Economy. England: The MIT Press Cambridge.Mateus, C. & Mateus, I.B. (2021). Does a VAT rise harm the tourism industry? Portuguese evidence. Tourism Management, 83, 104234.Μarabegias, Ν. (2017). Strategies on addressing the debt. Review of the Decentralization of Local Government and Regional Development, 87, 23Mirrlees, J. A. (1976). Optimal tax theory: A synthesis. Journal of Public Economics, 6(4), pp.327–358.Mirrlees, J. A. (1971). An exploration in the theory of optimum income taxation. Review of Economic Studies, 38(2), 175–208.Murphy, K. (2004). The role of trust in nurturing compliance: A study of accused tax avoiders. Working Paper 49. Centre for Tax System Integrity, Research School of Social Sciences, Australian National University.OECD, (2014). Taxation and tourism, in OECD Tourism Trends and Policies 2014. OECD Publishing, Paris. DOI: https://doi.org/10.1787/tour-2014-6-enOECD, (2012). Consumption Tax Trends 2012: VAT/GST and Excise Rates, Trends and Administration Issues. OECD Publishing, Paris. DOI: http://dx.doi.org/10.1787/ctt-2012-enPazarskis, M., Drogalas, G., & Koutoupis, A. (2017). Mergers, taxation and accounting performance: some evidence from Greece. Journal of Accounting and Taxation, 9(9), 119-130.Patsouratis, V., Frangouli, Z., & Anastasopoulos, G. (2005). Competition in tourism among the Mediterranean countries. Applied Economics, 37(16), 1865–1870.PricewaterhouseCoopers LLP (PwC), (2017). The Impact of Taxes on the Competitiveness of European Tourism- Final Report. Luxembourg: Publications Office of the European Union. Available at: file:///C:/Users/Administrator/Downloads/Final%20Report%20-%20The%20Impact%20of%20Taxes%20on%20the%20Competitiveness%20of%20European%20Tourism%20(2017).docx.pdfRiedel, N. (2018). Quantifying international tax avoidance: A review of the academic literature. Review of Economics, 69(2), 169–181.Saez, E., Matsaganis, M., & Tsakloglou, P. (2012). Earnings determination and taxes: Evidence from a cohort-based payroll tax reform in Greece. The Quarterly Journal of Economics, 127(1), 493-533.Salanie, B. (2011). The Economics of Taxation. England: The MIT Press Cambridge, 2nd Edition.SETE, (2018). Over-taxation affects the competitiveness of Greek tourism companies. Available at: https://sete.gr/media/12233/yperforologisi-gr.pdf (in Greek)Stamatopoulos, I., Hadjidema, S., & Eleftheriou, K. (2017). Corporate income tax compliance costs and their determinants: Evidence from Greece. Advances in Taxation, 24, 233-270.Sinkuniene, K. (2005). Taxation principles in tax culture: Theoretical and practical aspects. Management of Organizations: Systematic Research [Organizacijø Vadyba: Sisteminiai Tyrimai], .35, 177-192.Tagkalakis, A.O. (2013). Audits and tax offenders: recent evidence from Greece. Economics Letters, 118(3), 519-522.Tatsos, N. (2012). Tax theory and tax policy. Athens: Review.Torgler, B., Demir, I.C., Macintyre, A. & Schaffner, M. (2008). Causes and consequences of tax morale: An empirical investigation. Economic Analysis and Policy, 38(2), 314-339.UNWTO, (1998). Tourism Taxation: Striking a Fair Deal. World Tourism Organization. Madrid, Spain.Varotsis, N. & Katerelos, I. (2020). Tax behavior relating to the review of a revised regional tax policy: a study in Greece. Journal of Economic Structures, 9(7), 2-16.Varvaresos, S. (2008). Economics of tourism: Conceptual, theoretical and methodological approaches from the 1st to the 21st century. Athens: Forerunner (in Greek).Williams, C.C. & Krasniqi, B. (2017). Evaluating the Individual- and Country-Level Variations in Tax Morale: Evidence from 35 Eurasian Countries. Journal of Economic Studies, 44, 816-832.World Economic Forum (WFC), (2017). The Global Competitiveness Report 2017–2018. Geneva: Word Economic Forum. Available at: http://www3.weforum.org/docs/GCR2017-2018/05FullReport/TheGlobalCompetitivenessReport2017%E2%80%932018.pdf
Hong-Wen Tsai and Hui-Chung Che
Correspondence: Hui-Chung Che, drcharlie918@yeah.net
National Taiwan University of Science and Technology
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/1012
The industry difference on patent drawings of invention publications and utility model grants over top nine non-manufacturing industry sectors in China stock market was discussed via analysis of variation (ANOVA). Regarding patent drawing count’s capability for differentiating Chinese listed company’s stock rate of return, the invention publication and the utility model grant were different. The invention publication’s drawing count showed well capability for one industry sector, fair capability for two industry sectors, partial capability for one industry sector, weak capability for two industry sectors, and ineffective capability for three industry sectors; whereas the utility model grant’s drawing count showed partial capability for four industry sectors, weak capability for three industry sectors, and ineffective capability for two industry sectors. The patent drawing count of invention publications showed superior capability to those of utility model grants and invention grants. The higher patent counts of invention publications showed fairly connection with the capability, however, the higher patent counts of utility model grants showed weak connection with the capability. The higher stock rates of return also showed weak connection with the capability for either invention publications or utility model grants. Every non-manufacturing industry sector had its particularity. The industry difference among top nine non-manufacturing industry sectors in China stock market was distinct.
Patent, Invention publications, Utility model grants, ANOVA, Stock rate of return, Drawing count, Industry difference.
Boeing, P., & Mueller, E. (2019). Measuring China's patent quality: Development and validation of ISR indices. China Economic Review, 57, 101331. https://doi.org/10.1016/J.CHIECO.2019.101331Chen, C.Y., Chu, C.L, Che, H.C., Tsai, H.W., & Bai, B. (2022). Using Patent Drawings to Differentiate Stock Rate of Return of China Listed Companies — A Study on China Patent Species of Invention Grant. Advances in Management & Applied Economics, 12(3), 71-106. https://doi.org/10.47260/amae/1234Chen, C.Y., Chu, C.L., Che, H.C., & Tsai, H.W. (2022). Using Patent Drawings to Differentiate Stock Rate of Return of China Listed Companies — A Study on China Patent Species of Utility Model Grant. Advances in Management & Applied Economics, 12(4), 1-33. https://doi.org/10.47260/amae/1241Chen, C.Y., & Chu, C.L. (2022). Exploring Industry Difference in Using Patent Drawings of Invention Grants for Differentiating Stock Rate of Return — A Study on Chinese Listed Companies in Non-Manufacturing Industries. Modern Economy, 13, 679714. https://doi.org/10.4236/me.2022.135037Chen, T.M., Wei, C.C., & Che, H.C. (2018). Contribution of Patent Indicators to China Stock Performance. In Proceedings of IEEE 7th International Congress on Advanced Applied Informatics (ICAAI2018), 793-798, Yonago, Japan. https://doi.org/10.1109/IIAI-AAI.2018.00163Chen, T.M., Wei, C.C., & Che, H.C. (2020). Exploring Contribution of Patents to Stock Price in China. International Journal of Economics and Research, 11 (i4) (ja), 01-29.Chen, Z., & Zhang, J. (2019). Types of patents and driving forces behind the patent growth in China. Economic Modelling, 80, 294-302. https://doi.org/10.1016/J.ECONMOD.2018.11.015Chiu, Y.J., Chen, K.C., & Che, H.C. (2020a). Does Patent Help to Build Investment Portfolio of China A-Shares under China-US Trade Conflict? Mathematical Problems in Engineering, 7317480. https://doi.org/10.1155/2020/7317480Chiu, Y.J., Chen, K.C., & Che, H.C. (2020b). Patent Implemented Time Series Algorithm for Building Stock Portfolios in China A-Shares. Asian Journal of Information and Communications, 12(1), 156-170.Chiu, Y.J., Chen, K.C., & Che, H.C. (2020c, December). Patent As Predictive Indicator of Investment: An Empirical Study of China A-Shares. In 2020 Chinese Society for Management of Technology Conference, Hsinchu, Taiwan.Chiu, Y.J., Chen, K.C., & Che, H.C. (2020d, November). Patent Informatics in Predicting Stock Price and Increasing Investment Performance -- An Empirical Study of China Four Stock Boards. In Proceedings of 2020 International Conference on Economics, Management and Technology (IEMT2020), Kaohsiung, Taiwan. https://doi.org/10.1145/3429395.3429414Chiu, Y.J., Chen, K.C., & Che, H.C. (2020e). Patent Informatics in Predicting Return-on-Assets (ROA) and Increasing Investment Performance in China. In 2020 International Conference on Business Administration - Fall Session (ICBA 2020 Fall), New Taipei City, Taiwan.Chiu, Y.J., Chen, K.C., & Che, H.C. (2020f). Using Patent to Predict Book-Value-Per-Share and Investment -- Evidence in China A-Shares. International Journal of Innovation in Management, 8(2), 47-64.Chiu, Y.J., Chen, K.C., & Che, H.C. (2021). Patent predictive price-to-book ratio (PB) on improving investment performance -- Evidence in China. World Patent Information, 102039. https://doi.org/10.1016/j.wpi.2021.102039Dang, J., & Motohashi, K. (2015). Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality. China Economic Review, 35 (Sep), 137-155. https://doi.org/10.1016/j.chieco.2015.03.012Hanley, A., Liu, WH., & Vaona, A. (2015). Credit depth, government intervention and innovation in China: evidence from the provincial data. Eurasian Business Review, 5, 73-98. https://doi.org/10.1007/s40821-015-0016-2He, Z.L., Tong, T.W., Zhang, Y., & He, W. (2016). Constructing a Chinese patent database of listed firms in China: Descriptions, lessons, and insights. Journal of Economics & Management Strategy, 27(3), 579-606. https://doi.org/10.1111/jems.12186Hu, A.G., & Jefferson, G.H. (2009). A great wall of patents: What is behind China's recent patent explosion? Journal of Development Economics, 90, 57-68. https://doi.org/10.1016/j.jdeveco.2008.11.004Lai, Y.H., & Che, H.C. (2009a). Modeling patent legal value by extension neural network. Expert Systems with Applications, 36(7), 10520-10528. https://doi.org/10.1016/j.eswa.2009.01.027Lai, Y.H., & Che, H.C. (2009b). Evaluating patents using damage awards of infringement lawsuits: A case study. The Journal of Engineering and Technology Management, 26, 167-180. https://doi.org/10.1016/j.jengtecman.2009.06.005Lai, Y.H., & Che, H.C. (2009c). Integrated evaluator extracted from infringement lawsuits using extension neural network accommodated to patent assessment. The International Journal of Computer Applications in Technology, 35(2/3/4), 84-96.https://doi.org/10.1504/IJCAT.2009.026585Lei, X.P., Zhao, Z.Y., Zhang, X., Chen, D.Z., Huang, M.H., & Zhao, Y.H. (2011). The inventive activities and collaboration pattern of university---industry---government in China based on patent analysis. Scientometrics, 90(1), 231-251. https://doi.org/10.1007/S11192-011-0510-YLi, X. (2012). Behind the recent surge of Chinese patenting: an institutional view. Research Policy, 41(1), 236-249. https://doi.org/10.1016/j.respol.2011.07.003Li, Z., Deng, G., & Che, H.C. (2020a, December). Patent-Based Predictive Price-to-Earnings on Increasing Investment Performance of China Stock Market. In Proceedings of 2020 International Symposium on Computational Intelligence and Design (ISCID2020), Hangzhou, China. https://doi.org/10.1109/ISCID51228.2020.00197Li, Z., Deng, G., & Che, H.C. (2020b, December). Patent-Based Predictive ROE on Increasing Investment Performance of China Stock Market. In Proceedings of 2020 IEEE International Conference on Computer and Communications (ICCC2020), Chengdu, China. https://doi.org/10.1109/ICCC51575.2020.9345204Li, Z., Deng, G., & Che, H.C. (2021, January). Patent-Based Predictive EPS on Increasing Investment Performance of China Stock Market. In Proceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA2021), Shenyang, China. https://doi.org/10.1109/ICPECA51329.2021.9362701Liu, Q., & Qiu, L. D. (2016). Intermediate input imports and innovations: Evidence from Chinese firms' patent filings. Journal of International Economics, 103, 166-183. https://doi.org/10.1016/J.JINTECO.2016.09.009Motohashi, K. (2008). Assessment of technological capability in science industry linkage in China by patent database. World Patent Information, 30(3), 225-232. https://doi.org/10.1016/J.WPI.2007.10.006Motohashi, K. (2009). Catching up or lagging behind? Assessment of technological capacity of China by patent database. China Economic Journal, 2(1), 1-24. https://doi.org/10.1080/17538960902860055Tsai, H.W., Che, H.C., & Bai, B. (2021a). Innovation Continuity as Indicator for Observing Stock Rate of Return in China Stock Market. Advances in Management and Applied Economics, 11(5), 25-49. https://doi.org/10.47260/amae/1152Tsai, H.W., Che, H.C., & Bai, B. (2021b). Exploring Patent Effects on Higher Stock Price and Stock Rate of Return—A Study in China Stock Market. Chinese Business Review, 20(5), 168-180. https://doi.org/10.17265/1537-1506/2021.05.003Tsai, H.W., Che, H.C., & Bai, B. (2021c). Patent Effects on Higher Stock Price - An Insight into China Stock Market and Four Stock Boards. International Journal of Innovation in Management, 9(2), 61-74.Tsai, H.W., Che, H.C., & Bai, B. (2021d). Exploring Technology Variety Effect on Stock Rate of Return in China Stock Market. In Proceedings of the 2021 7th International Conference on Industrial and Business Engineering (ICIBE2021), 19-206, Macao, China. https://doi.org/10.1145/3494583.3494621Tsai, H.W., Che, H.C., & Bai, B. (2021e). How Does Patent Examination Indicate Stock Performance? An Empirical Study of China Stock Market and Patents. Internal Journal of Economics and Research, 12(i5), 01-29 (so).Tsai, H.W., Che, H.C., & Bai, B. (2021f). Using Patent Backward Citation for Classifying Stock Price of China Stock Market. Economics and Management, 18(2), 12-34. https://doi.org/10.37708/em.swu.v18i2.2Tsai, H.W., Che, H.C., & Bai, B. (2022a). AI Implemented Stock Price Prediction and Stock Selection via Patent Forward Citation—A Study on China Stock Market and Patents. Theoretical Economics Letters, 12, 664687. https://doi.org/10.4236/tel.2022.123037Tsai, H.W., Che, H.C., & Bai, B. (2022b). Using Patent Forward Citation for Discriminating Stock Price in China Stock Market. Journal of Business and Management Sciences, 10(1), 1-12. https://doi.org/10.12691/jbms-10-1-1Tsai, H.W., Che, H.C., & Bai, B. (2022c). Exploring the Relationship Between Patent Forward Citation and Stock Rate of Return Using Empirical Data of China Stock Market. International Journal of Innovation in Management, 10(1), 1-16.Tsai, H.W., Che, H.C., & Bai, B. (2022d). Longer Patent Life Representing Higher Value? -- A Study on China Stock Market and China Patents. Bulletin of Applied Economics, 9 (1), 115-136. https://doi.org/10.47260/bae/918Tsai, H.W., Che, H.C. & Bai, B. (2022e). Patent Claim's Impact on Stock Rate of Return Based on China Stock Market's Empirical Study. International Journal of Business and Economic Sciences Applied Research, 15(1). https://doi.org/10.25103/ijbesar.151.03Tsai, H.W., Che, H.C., & Bai, B. (2022f). Using Patent Drawings of Invention Publications to Differentiate Stock Rate of Return - An Empirical Study on China Stock Market. Eurasian Journal of Business and Management, 10(1), 37-61. https://doi.org/10.15604/ejbm.2022.10.01.004
Mitch Kunce
Correspondence: Mitch Kunce, DouglasMitchellConsulting@protonmail.com
DouglasMitchell Econometric Consulting Laramie, WY USA
pdf (733.39 Kb) | doi: https://doi.org/10.47260/bae/101
Recent reviews of the sociological and economic-based ecological studies of suicide find cyclical unemployment to be a key suicide risk factor, though the evidence presented is mixed at best. The ambiguity of the ecological associations appear to stem from faulty statistical methodologies. Panel treatments offer advantages over conventional time-series methods by exploiting cross-section variation. However, if the added cross-section units are cointegrating (dependent) and independence is presumed, incorrect statistical inference and inconsistent coefficient estimation can result. Herein, we fully address the import of cross-sectional dependence on the ecological relationship between U.S. unemployment rates and suicide rates using an 81-year panel of the 48 contiguous states and the District of Columbia. When proper allowances are made for cross-section dependence at each step of the examination, we find no significant statistical association, short-run or long-run, running from unemployment to suicide rates in the U.S. Results of this sequential analysis highlight potential sources of the ambiguity found in the literature.
Suicide rates, Cointegration, Cross-section dependence.
Bai, J. and Ng, S. (2002). Determining the number of factors in approximate factor models. Econometrica 70(1), pp. 191-221.Bai, J. and Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica 72(4), pp. 1127-1177.Bai, J. and Ng, S. (2010). Panel unit root tests with cross-section dependence: A further investigation. Econometric Theory 26, pp. 1088–1114.Bailey, N., Kapetanios, G. and Pesaran, M. (2016). Exponent of cross-sectional dependence: estimation and inference. Journal of Applied Econometrics 31(6), pp. 929-960.Baltagi, B. (2021). Econometric Analysis of Panel Data. Sixth Edition. Chapter 12. Springer: Switzerland.Banerjee, A., and Carrion-i-Silvestre, J.L. (2015). Cointegration in panel data with breaks and cross- section dependence. Journal of Applied Econometrics 30, pp. 1-23.Beck, N. and Katz, J. (1995). What to do (and not to do) with time-series cross-section data. American Political Science Review 89(3), pp. 634-647.Beenstock, M. and Felsenstein, D. (2019). The Econometric Analysis of Non-Stationary Panel Data. Springer: Switzerland.Chang, T. and Chen, W. (2017). Revisiting the relationship between suicide and unemployment: evidence from linear and non-linear cointegration. Economic Systems 41(2), pp. 266-278.Cheng, K., Durmaz, N., Kim, H. and Stern, M. (2012). Hysteresis vs. the natural rate of US unemployment. Economic Modeling 29(2), pp. 428-434.Chudik, A. and Pesaran, M. (2015). Common correlated effects estimation of hetergeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics 188, pp. 393-420.Curtin, S., Garnett, M. and Ahmad, F. (2022). Provisional numbers and rates of suicide by month and demographic characteristics: United States, 2021. Vital Statistics Rapid Release Number 24, Report 120830.Curtin, S. and Hedegaard, H. (2019). Suicide rates for females and males by race and ethnicity: United States, 1999 and 2017. National Center for Health Statistics, Health E-Stat, June edition.Douglas, J. (1967). The Social Meaning of Suicide. Princeton, NJ: Princeton University Press.Durkheim, E. (1897/1951). Suicide. Translated by Spaulding, J. and Simpson, G. Glencoe, IL: Free Press.Dickey, D. and Fuller, W. (1979). Distribution of the estimators for autoregressive time-series with a unit root. Journal of the American Statistical Association 74, pp. 427-431.Dickey, D. and Fuller, W. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49, pp. 1057-1072.Engle, R. and Granger, C. (1987). Co-integration and error correction: representation, estimation and testing. Econometrica 55, pp. 251-276.Fedden, H. (1938). Suicide: A Social and Historical Study. London: Peter Davies.Feng, S. and Hu, Y. (2013). Misclassification errors and the underestimation of the U.S. unemployment rate. American Economic Review 103(2), pp. 1054-1070.Granger, C. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, pp. 424-438.Hamermesh, D. and Soss, N. (1974). An economic theory of suicide. Journal of Political Economy 82(1), pp. 83-98.Hatzius, J. and Stehn, S. (2012). Comment on: The ins and outs of forecasting unemployment: using labor force flows to forecast the labor market, by Barnichon, R. and Nekarda, C. Brookings Papers on Economic Activity 45(2), pp. 118-123.Hausman, J. (1978). Specification tests in econometrics. Econometrica 46(6), pp. 1251-1271.Henry, A. and Short, J. (1954). Suicide and Homicide. Glencoe, IL: Free Press.Holderness, C. (2016). Problems using aggregate data to infer individual behavior: Evidence from law, finance, and ownership concentration. Critical Finance Review 5(1), pp. 1-40.Im, K., Pesaran, M. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, pp. 53-74.Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics 90, pp. 1–44.Laanani, M., Ghosn, W., Jougla, E. and Rey, G. (2015). Impact of unemployment variations on suicide mortality in Western European countries (2000-2010). Journal of Epidemiology and Community Health 69, pp. 103-109.Levin, A., Lin, CF., and Chu, CS. (2002). Unit root tests in panel data: asymptotic and finite - sample properties. Journal of Econometrics 108(1), pp. 1-24.Lin, Y.H. and Chen, W.Y. (2018). Does unemployment have asymmetric effects on suicide rates? Evidence from the United States: 1928-2013. Economic Research - Ekonomska Istraživanja 31(1). pp. 1404-1417.Milner, A., Page, A. and LaMontague, A. (2014). Cause and effect in studies on unemployment, mental health and suicide: a meta-analytic and conceptual review. Psychological Medicine 44, pp. 909-917.Newey, W. and West, K. (1987). A simple positive semi-definite heteroscedasticity and autocorrelation consistent covariance matrix. Econometrica 55, pp. 150-161.O'Connell, P. (1998). The overvaluation of purchasing power parity. Journal of International Economics 44, pp. 1-19.Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics 61, pp. 653–670.Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory 20, pp. 597–625.Pesaran, M. (2004). General diagnostic tests for cross section dependence in panels. University of Cambridge Working Papers in Economics No. 0435.Pesaran, M. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics 22, pp. 265-312.Pesaran, M. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews 34, pp. 1089-1117.Pesaran, M. and Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics 68, pp. 79-113.Pesaran, M., Shin, Y. and Smith, R. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association 94(446), pp. 621-634.Phillips, P. (1987). Time series regression with a unit root. Econometrica 55(2), pp 277-301.Phillips, P. and Moon, H. (1999). Linear regression limit theory for nonstationary panel data. Econometrica 67, pp. 1057-1111.Phillips, P. and Ouliaris, S. (1990). Asymptotic properties of residual based tests for cointegration. Econometrica 58, pp. 165–193.Phillips, P. and Perron, P. (1988). Testing for a unit root in time series regressions. Biometrika 75, pp. 335–346.Stock, J. and Watson, M. (1988). Testing for common trends. Journal of the American Statistical Association 83, pp. 1097-1107.Vandoros, S. and Kawachi, I. (2021). Economic uncertainty and suicide in the United States. European Journal of Epidemiology 36, pp. 641-647.Warshauer, M. and Monk, M. (1978). Problems with suicide statistics for whites and blacks. American Journal of Public Health 68(4), pp. 383-388.Westerlund, J. and Breitung, J. (2013). Lessons from a decade of IPS and LLC. Econometric Review 32, pp. 547-591.