Social Indicators Research

, Volume 135, Issue 1, pp 215–231 | Cite as

Income Dependency on Non-timber Forest Products: An Empirical Evidence of the Indigenous People in Peninsular Malaysia

  • Md. Khaled Saifullah
  • Fatimah Binti Kari
  • Azmah Othman


The indigenous people have been identified to be among the poorest and the most socioeconomically and culturally marginalized people all over the world. The main purpose of the paper is to explore the socioeconomic and demographic factors of indigenous people in Peninsular Malaysia in context of poverty and the role of income dependency of non-timber forest products (NTFP). The data were collected in 2014 and 2015 through primary and secondary sources. Partial least squares (PLS) method was used to analysis the data. PLS is a modeling technique that features multiple regression and principal component analysis. The study shows that still a large number of indigenous households is involved in the NTFP activities. But the communities are moving away from NTFP based income to cash-crop based income because of poor sustainable forest management and lack of forest property rights. However, NTFP have a significant role in the household income and contribute 24% of the average income. Moreover, the analysis shows that location is significant to the poverty. There should be a suitable sustainable forest management system which can teach these indigenous communities about proper way of NTFP gathering and given proper rights to forest land. Furthermore, education is not significant to indigenous people and there is a high rate of school dropout among them. The government should introduce a different education system for indigenous communities which will emphasize the importance of education to them.


Non-timber forest products (NTFP) Indigenous people Orang Asli Indigenous communities Peninsular Malaysia Poverty Socioeconomic factor Demographic factor 



The authors would like to acknowledge the University of Malaya, Kuala Lumpur for funding of this work under the grant Marketing Survey Strategy Compounds (FL001G-13BIO), PPP Grant (PG234-2015A) and Ministry of Education, Malaysia.


  1. Abdi, H. (2010). Partial least squares regression and projection on latent structure regression (PLS regression). Wiley Interdisciplinary Reviews: Computational Statistics, 2(1), 97–106.CrossRefGoogle Scholar
  2. Adhikari, M., Nagata, S., & Adhikari, M. (2004). Rural house and forest: An evaluation of household’s dependency on community forest in Nepal. Journal of Forest Research, 9(1), 33–44.CrossRefGoogle Scholar
  3. Altman, J. C. (2007). Alleviating poverty in remote indigenous Australia: The role of the hybrid economy. Canberra: Australian National University, Centre for Aboriginal Economic Policy Research.Google Scholar
  4. Anderson, J., Ball, J., Bourke, I. J., Braatz, S., Clément, J., Dembner, S. A., et al. (1999). Non-wood forest products and income generation (p. 198). Rome: Unasylva, FAO.Google Scholar
  5. Angelsen, A., & Wunder, S. (2003). Exploring the forestpoverty link: Key concepts, issues and research implication. Occasional paper No. 40. Center for International Forestry Research, Jakarta, Indonesia.Google Scholar
  6. Arnold, J. E. M., & Pérez, M. R. (2001). Can non-timber forest products match tropical forest conservation and development objectives? Ecological Economics, 39(3), 437–447.CrossRefGoogle Scholar
  7. Arnold, M., & Townson, J. (1998). Assessing the potential of forest product activities to contribute to rural incomes in Africa. London: Overseas Development Institute.Google Scholar
  8. Cavendish, W. (2000). Empirical regularities in the poverty-environment relationship of rural households: Evidence from Zimbabwe. World Development, 28(11), 1979–2003.CrossRefGoogle Scholar
  9. Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: Relative importance of beliefs. ACM SigMIS Database, 26(2–3), 42–64.CrossRefGoogle Scholar
  10. Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. Statistical Strategies for Small Sample Research, 2, 307–342.Google Scholar
  11. Colchester, M., MacKay, F., Griffiths, T., & Nelson, J. (2001). A survey of indigenous land tenure. Rome: Food and Agriculture Organization (FAO).Google Scholar
  12. Deaton, A. (2008). Income, health, and well-being around the world: Evidence from the Gallup World Poll. Journal of Economic Perspectives, 22(2), 53–72.CrossRefGoogle Scholar
  13. Don, A. G. B. (2014). Masyarakat Orang Asli Muslim Malaysia Senario dan Realiti Kefahaman dan Penghayatan Islam. International Seminar: Da’wah & Ethnicity: Multidisciplinary Perspective.Google Scholar
  14. EPU. (2009). Malaysia: Measuring and monitoring poverty and inequality. Putrajaya: The Economic Planning Unit, Ministry of Development.Google Scholar
  15. FAO. (2010). Global forest resources assessment. Rome: The Food and Agriculture Organization of the United Nations (FAO).Google Scholar
  16. Fornell, C., & Larcker, D. F. (1981). Two structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.CrossRefGoogle Scholar
  17. Geladi, P., & Kowalski, B. R. (1986). Partial least-squares regression: A tutorial. Analytica Chimica Acta, 185, 1–17.CrossRefGoogle Scholar
  18. Greene, S. M., Hammett, A. L., & Kant, S. (2000). Non-timber forest products marking system and market players in southwest Virginia: Crafts, medicinal and herbal and specialty wood products. Journal of Sustainable Forestry, 11(3), 19–39.CrossRefGoogle Scholar
  19. Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.CrossRefGoogle Scholar
  20. Hall, G. H., & Patrinos, H. A. (2012). Indigenous peoples, poverty, and development. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  21. Hamilton, E. (2012). Non-timer forest products in British Columbia: Policies, practices, opportunities and recommendations. Journal of Ecosystems and Management, 13(2), 1–24.Google Scholar
  22. Homma, A. K. (1992). The dynamics of extraction in Amazonia: A historical perspective. Advances in Economic Botany, 9, 23.Google Scholar
  23. Howell, C. J., Schwabe, K. A., & Samah, A. H. A. (2010). Non-timber forest product dependence among the Jah Hut subgroup of Peninsular Malaysia’s Orang Asli. Environment, Development and Sustainability, 12(1), 1–18.CrossRefGoogle Scholar
  24. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204.CrossRefGoogle Scholar
  25. Huyser, K. R., Takei, I., & Sakamoto, A. (2014). Demographic factors associated with poverty among American Indians and Alaska Natives. Race and Social Problems, 6(2), 120–134.CrossRefGoogle Scholar
  26. Ismartini, P., Sunaryo, S., & Setiawan, S. (2010). The jackknife interval estimation of parameters in partial least squares regression model for poverty data analysis. IPTEK The Journal for Technology and Science, 21(3), 118–123.CrossRefGoogle Scholar
  27. JAKOA. (2011). Pelan Strategik Kemajuan Orang Asli 2011–2015. Kuala Lumpur: Jabatan Kemajuan Orang Asli Malaysia.Google Scholar
  28. JHEOA (2008). Data maklumat asas Jabatan Hal Ehwal Orang Asli. Kuala Lumpur: Bahagian Perancangan dan Penyelidikan. Jabatan Hal Ehwal Orang Asli (JHEOA).
  29. Jones, E. T. (2000). Non timber forest products: Considerations for tribal forestry. Proceedings of the Intertribal Timber Council Meeting. Lewiston, Idaho, June.Google Scholar
  30. Kalt, J. P. (2007). The state of the native nations: Conditions under U.S. policies of self-determination. Oxford: Oxford University Press.Google Scholar
  31. Kardooni, R., Kari, B. F., Yahaya, S. R., & Yusuf, S. H. (2014). Traditional knowledge of Orang Asli on forests in peninsular Malaysia. Indian Journal of Traditional Knowledge, 13(2), 283–291.Google Scholar
  32. Kari, F. B., Masud, M. M., Yahaya, S. R. B., & Saifullah, M. K. (2016). Poverty within watershed and environmentally protected areas: The case of the indigenous community in Peninsular Malaysia. Environmental Monitoring and Assessment, 188(3), 1–14.CrossRefGoogle Scholar
  33. Krishnakumar, J., Yanagida, J. F., Anitha, V., Balakrishnan, R., & Radovich, T. J. (2015). Non-timber forest products certification and management: A socioeconomic study among the Kadars in Kerala, India. Environment, Development and Sustainability, 17(4), 837–858.CrossRefGoogle Scholar
  34. Mahapatra, A. K., Albers, H. J., & Robinson, E. J. (2005). The impact of NTFP sales on rural households’ cash income in India’s dry deciduous forest. Environmental Management, 35(3), 258–265.CrossRefGoogle Scholar
  35. Melaku, E., Ewnetu, Z., & Teketay, D. (2014). Non-timber forest products and household incomes in Bonga forest area, southwestern Ethiopia. Journal of forestry research, 25(1), 215–223.CrossRefGoogle Scholar
  36. Mina, C. D., & Barrios, E. B. (2010). Profiling poverty with multivariate adaptive regression splines. Philippine Journal of Development, 37(2), 55.Google Scholar
  37. Noora, M. A. M. (2012). Advancing the Orang Asli through Malaysia’s clusters of excellence policy. Journal of International and Comparative Education, 1(2), 2232-1802.Google Scholar
  38. Paumgarten, F. (2005). The role of non-timber forest products as safety-nets: A review of evidence with a focus on South Africa. GeoJournal, 64(3), 189–197.CrossRefGoogle Scholar
  39. Peters, C. M. (1994). Sustainable harvest of non-timber plant resources in tropical moist forest: An ecological primer. Washington, DC: Biodiversity Support Program.Google Scholar
  40. Ringle, C. M., Götz, O., Wetzels, M., & Wilson, B. (2009). On the use of formative measurement specifications in structural equation modeling: A Monte Carlo simulation study to compare covariance-based and partial least squares model estimation methodologies. In METEOR Research Memoranda (RM/09/014), Maastricht University.Google Scholar
  41. Sabates, R., Akyeampong, K., Westbrook, J., & Hunt, F. (2011). School dropout: Patterns, causes, changes and policies. Vienna: Paper commissioned for the EFA Global Monitoring Report.Google Scholar
  42. Sawatsky, M. L., Clyde, M., & Meek, F. (2015). Partial least squares regression in the social sciences. The Quantitative Methods for Psychology, 11(2), 52–62.CrossRefGoogle Scholar
  43. Schreckenberg, K., Marshall, E., & Velde, D. W. (2006). NTFP commercialization and the rural poor: More than a safety net? Commercialization of non-timber forest products: Factors influencing success. Cambridge: UNEP World Conservation Monitoring Centre.Google Scholar
  44. Tuck Po, L. (2002). The significance of Forest to the emergence of Batek knowledge in Pahang, Malaysia. Journal of Southeast Asian Studies, 40(1), 3–22.Google Scholar
  45. Vedeld, P., Angelsen, A., Sjaastad, E., & Berg, G. K. (2004). Counting on the environment: Forest incomes and the rural Poor. Washington, DC: World Bank Environment Department, World Bank.Google Scholar
  46. Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (Eds.). (2010). Handbook of partial least squares: Concepts, methods and applications. Springer Handbooks of Computational Statistics Series. Berlin: Springer.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Md. Khaled Saifullah
    • 1
  • Fatimah Binti Kari
    • 1
  • Azmah Othman
    • 2
  1. 1.Department of Economics, Faculty of Economics and AdministrationUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Development Studies, Faculty of Economics and AdministrationUniversity of MalayaKuala LumpurMalaysia

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