Skip to main content

Advertisement

SpringerLink
Log in

How disaggregated should information be for a sound food security policy?

  • Original Paper
  • Published:
Food Security Aims and scope Submit manuscript

Abstract

This study aimed to answer the question whether disaggregating micro data on food security conditions yielded sufficient new information to improve food security policies. To answer this question, we proposed and implemented a conceptual model that comprised three successive levels of disaggregation. The model was implemented for the Punjab province of Pakistan for which primary data was collected from 1,152 rural households. To measure the food security status of households, the Dietary Intake Assessment (DIA) method was used. Furthermore, the determinants of food security were identified using a Logit Regression model. Comparing the results of this model suggested that disaggregation yields sufficient new information to warrant the extra effort. We found that food security of different household categories and micro-regions were statistically different from each other; moreover, household categories differed in their food security status even within regions. Basing potential policies on analysis of too aggregated data a level can lead to biased conclusions. An implication is that a blanket policy for ensuring rural household food security, as currently implemented in Pakistan, is not an efficient approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. See Annex-IV for medians of policy variables

  2. For education the formula is: Odds ratio = exp((β i/y) ∗ (ς i/m)), where; y = the numbers of years (e.g. 5 for primary, 8 for middle, 11 for up to intermediate, etc.)

References

  • Abadir, K., & Talmain, G. (2002). Aggregation, persistence and volatility in a macro model. Review of Economic Studies, 69, 749–779.

    Article  Google Scholar 

  • AIOU. (2001). Food composition table for Pakistan. Islamabad: Allama Iqbal Open University.

    Google Scholar 

  • Akpan, E. O. (2009). Oil resource management and food insecurity in Nigeria. Paper presented at the European Report on Development (ERD) Conference in Accra, Ghana.

  • Babatunde, R. O., Omotesho, O. A., & Sholotan, O. S. (2007). Socio-economic characteristics and food security status of farming households in Kwara State, North-Central Nigeria. Pakistan Journal of Nutrition, 6, 49–58.

    Google Scholar 

  • Barnes, S. T. (1999). Food security and food self-sufficiency in Africa II. Food Security Situation and Related Constraints. African Studies Center at the University of Pennsylvania, Philadelphia.

  • Bashir, M. K., & Schilizzi, S. (2012). Have policies in Pakistan been effective for improving food security? Wanted: disaggregated policy assessment! World Applied Sciences Journal, 17(9), 1182–1191.

    Google Scholar 

  • Bashir, M. K., Schilizzi, S. & Pandit, R. (2012a). The determinants of rural household food security in the Punjab, Pakistan: an econometric analysis, Working Paper 1203, School of Agricultural and Resource Economics, University of Western Australia, Crawley, Australia, Online available at http://ageconsearch.umn.edu/bitstream/122526/2/working%20paper%201203.pdf accessed on 29/01/2013.

  • Bashir, M. K., Schilizzi, S. & Pandit, R. (2012b). Livestock and rural household food security: the case of small farmers of the Punjab, Pakistan, Working Paper 1207, School of Agricultural and Resource Economics, University of Western Australia, Crawley, Australia, Online available at http://ageconsearch.umn.edu/bitstream/126034/2/WP120007.pdf accessed on 29/01/2013.

  • Bashir, M. K., Schilizzi, S., & Pandit, R. (2012c). Are the determinants of food insecurity for landless households different from that of other rural households? Pakistan Journal of Agricultural Sciences, 49(3), 363–370.

    Google Scholar 

  • Bashir, M. K., Schilizzi, S. & Pandit, R. (2012d). Food security and its determinants at the crossroads in Punjab, Pakistan, Working Paper 1206, School of Agricultural and Resource Economics, University of Western Australia, Crawley, Australia, Online available at http://ageconsearch.umn.edu/bitstream/126033/2/WP120006.pdf accessed on 29/01/2013.

  • Chaudhry, S. M., & Kamal, S. (1997). Introduction to statistical theory Part II. Urdu Bazar Lahore: Ilmi Kitab Khana.

    Google Scholar 

  • FAO. (2004). FAO statistics. Food and Agriculture Organization of the United Nations, Statistic Division, Socio-Economic Statistics and Analysis Service.

  • FAO. (2012). The state of food insecurity in the world: economic growth is is necessary but not sufficient to accelerate reduction of hunger and malnutrition. Food and Agriculture Organization of the United Nations, Rome, online available at http://www.fao.org/docrep/016/i3027e/i3027e.pdf accessed on 22/01/2013.

  • Fayeye, T. R., & Ola, D. J. (2007). Strategies for Food Security and Health Improvement in the Sub-Saharan Africa. World Journal of Agricultural Sciences, 3, 808–814.

    Google Scholar 

  • Firth, D. (1998). Annotated bibliography: relative importance of explanatory variables. Oxford: Nuffield College. www.nuff.ox.ac.uk/sociology/alcd/relimp.pdf (accessed on 02/10/2012).

  • Forni, M., & Lippi, M. (1999). Aggregation of linear dynamic microeconomics models. Journal of Mathematical Economics, 31, 131–158.

    Article  Google Scholar 

  • Frick, R. W. (1999). Defending the statistical status quo. Theory and Psychology, 9, 183–189.

    Article  Google Scholar 

  • Garrett, T. A. (2002). Aggregated vs. disaggregated data in regression analysis: implications for inference. Working Paper 2002-024B, Research Division, Federal Reserve Bank of St. Louis. Online available at http://research.stlouisfed.org/wp/2002/2002-024.pdf accessed on 02/10/2012.

  • GOP. (1998). Population census of Pakistan. Population Census Organization, Statistics Division, Government of Pakistan.

  • GOP. (2003). Economic survey of Pakistan, 2002–03. Ministry of Food and Agriculture. Finance Division, Economic Advisor’s Wing, Islamabad, Pakistan.

  • GOP. (2010). Economic survey of Pakistan, 2009–10. Ministry of Food and Agriculture. Finance Division, Economic Advisor’s Wing, Islamabad, Pakistan.

  • Gubert, M. B., Benicio, M. H. D., Silva, J. P., Rosa, T. E. C., Santos, S. M., & Santos, L. M. P. (2010). Use of a predictive model for food insecurity estimates in Brazil. Archivos Latino Americanos De Nutricion, 60, 119–125.

    Google Scholar 

  • Hailu, A., & Nigatu, R. (2007). Correlates of household food security in densely populated areas of southern Ethiopia: does the household structure matter? Studies on Home and Community Science, 1, 85–91.

    Google Scholar 

  • Hosmer, D .W., & Lemeshow, S. (2000). Applied logistic regression. New York: John Wiley and Sons.

  • Hsiao, C., Shen, Y. & Fujiki, H. (2004). Aggregate vs disaggregate data analysis - a paradox in the estimation of a money demand function of Japan under the low interest rate policy. IEPR Working Paper No. 04.1, Institute for Economic Policy Research, University of Southern California (USC).

  • Lashgarara, F., Mirdamadi, S. M., & Hosseini, S. J. F. (2010). Determining the causal model role of ICT in improving food availability of Iranian rural households. International Journal of Advanced Science and Technology, 24, 27–40.

    Google Scholar 

  • Lewbel, A. (1994). Aggregation and simple dynamics. American Economic Review, 84, 905–918.

    Google Scholar 

  • Maxwell, S., & Frankenberger, T. (1992). Household food security: concepts, indicators, measurements: a technical review. Rome: IFAD/UNICEF.

    Google Scholar 

  • Menard, S. (2000). Coefficients of determination for multiple logistic regression analysis. The Americani Statistician, 54, 17–24.

    Google Scholar 

  • Menard, S. (2004). Six approaches to calculating standardized logistic regression coefficients. The American Statistician, 58(3), 218–223.

    Article  Google Scholar 

  • Mengistu, E., Regassa, N. & Yusufe, A. (2009). The levels, determinants and coping mechanisms of food insecure households in southern Ethiopia: case study of Sidama, Wolaita and Guraghe Zones. DCG Report No. 55, the Drylands Coordination Group.

  • Misselhorn, A. A. (2005). What drives food insecurity in Southern Africa? A meta-analysis of household economy studies. Global Environmental Change, 15, 33–43.

    Google Scholar 

  • Mittal, S. & Seethi, D. (2009). Food security in South Asia: issues and opportunities. Working Paper No. 240, Indian Council for Research on International Economic Relations.

  • Molnar, J. J. (1999). Sound policies for food security: the role of culture and social organization. Review of Agricultural Economics, 21, 489–498.

    Google Scholar 

  • NSSO. (1995). Measurement of poverty in Sri Lanka. National Sample Survey Organization of India.

  • Omotesho, O. A., Adewumi, M. O. & Fadimula, K. S. (2007). Food security and poverty of the rural households in Kwarwa State, Nigeria. AAAE Conf Proceedings: 571–575.

  • Oriola, E. O. (2009). A framework for food security and poverty reduction in Nigeria. European Journal of Social Sciences, 8, 132–139.

    Google Scholar 

  • Pérez-Escamilla, R., & Segall-Corrêa, A. M. (2008). Food insecurity measurement and indicators. Review of Nutrition, Campinas, 21(suplemento), 15s–26s.

    Google Scholar 

  • Pesaran, M. H. (2003). On aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation. Economic Modeling, 20, 227–435.

    Article  Google Scholar 

  • Riely, F., Mock, N., Bailey, L., & Kenefick, E. (1999). Food security indicators and framework for use in the monitoring and evaluation of food aid programmes. Washington D.C: Food Aid Management (FAM).

    Google Scholar 

  • Romanoff, S., & Commentary, L. J. (1992). Cassava and African food security: some ethnographic examples. Ecology of Food and Nutrition, 27, 29–41.

    Article  Google Scholar 

  • Thompson, D. (2009). Ranking predictors in logistic regression. Paper D10-2009, Assurant Health, West Michigan.

Download references

Author information

Authors and Affiliations

  1. Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, Crawley, Perth, Western Australia, 6009

    Muhammad Khalid Bashir & Steven Schilizzi

  2. School of Agricultural and Resource Economics, The University of Western Australia, 35 Stirling Highway, Crawley, Perth, Western Australia, 6009

    Muhammad Khalid Bashir & Steven Schilizzi

  3. Institute of Agricultural and Resource Economics, University of Agriculture, Faisalabad, Pakistan

    Muhammad Khalid Bashir

Authors
  1. Muhammad Khalid Bashir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Steven Schilizzi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muhammad Khalid Bashir.

Appendices

Annex-I

Table 5 Descriptive analysis for L1 and L2
Full size table
Table 6 Descriptive analysis for L3
Full size table

Annex-II

Table 7 Comparison of the results of binary logistic regression models of L1 and L2
Full size table

Annex-III

Table 8 Comparison of the results of binary logistic regression models of L3
Full size table

Annex-IV

Table 9 Medians of the variables that can be targeted by policy makers
Full size table
Table 10 ᅟ
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bashir, M.K., Schilizzi, S. How disaggregated should information be for a sound food security policy?. Food Sec. 5, 551–563 (2013). https://doi.org/10.1007/s12571-013-0271-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12571-013-0271-y

Keywords

Search

Navigation