Main Article Content
Abstract
This study aimed to investigate the application of safety-first approach to measure the risk behavior of wheat farmers in unreclaim land. A random sample of 105 farms in Wasit province for season 2019 were used. The analysis was divided into three stages. The first stage was to estimate the production function (Cob-Douglas) of wheat using the regression method of the Robust M-Weighted Estimator (R.M.W) to represent the functional relationship between quantity of produced wheat and the independent variables (seed, fertilizers, pesticides, number of mechanical and human).The second stage included an analysis of farmers' behavior towards risk based on safety-first standards. It was found that the number of farmers affording high, medium and natural risks were 46, 24 and 33, respectively, representing 43.8%, 24.76%, 31.34% of the total farmers, respectively. Third stage analyzed the factors affecting the farmers' behavior towards risk, using a multiple logistic regression model. The results indicated that farmers having normal or medium salinity soil, long experience (more than 25 years) and those owning their agricultural lands bear the risks more than their counterparts with high salinity soils, shorter experience and tenants of agricultural lands. Therefore, the study recommends conducting maintenance operations on the main and secondary drainage networks to ensure low salinity levels to obtain high productivity.
Keywords
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
- Abbas, A. K. (2012). Using logistic regression model to predict the functions with economic categorical dependent variable. Kirkuk University Journal Administrative and Economic Sciences, 2, 234-2563.https://www.iasj.net/iasj/download/02385e57f0f237af
- Al-Hussine, H. D., & Alyousuf, A. A. (2021). Responses of local wheat varieties to greenbug Schizaphus graminum and bird-cherry oat aphid Rhopalosiphum padi infestation. Basrah Journal Agricultural Sciences, 34, 124-138. https://doi.org/10.37077/25200860.2021.34.1.11
- Ali, K. A., & Mahmood, Z. H. (2018). Estimating profit, cost function and technical efficiencies of rice production in Nejaf (sic) for season 2016. Iraq Journal of Agricultural Sciences, 50, 1237-1246. https://doi.org/10.36103/ijas.v50i5.789
- Ali, S. S., Mubeen, M., Lal, I., & Hussain, A. (2018). Prediction of stock performance by using logistic regression model: evidence from Pakistan Stock Exchange (PSX). Asian Journal of Empirical Research, 8, 247-258. https://doi.org/10.18488/journal.1007/2018.8.7/1007.7.247.258
- Al-Mashadani, A. K., & Mahmood, Z. H. (2019). Estimation of production function of rice in Najaf province for season 2016. Journal of Plant Archives, 19, 1457-1463.
- Al-Obeidi, E. A. (2020). Economic analysis of production risks for fish farming projects in Iraq Diyala governorate as a model. M. Sc. Thesis. University of Baghdad, 78pp.
- Al-Shafi'i, M. A. (2005). Modernization in the Economics of Production and Analysis of Competencies between Theory and Practice, Al-Muraqqab University, Libya, 315 pp. (In Arabic).
- Al-Younes, A. H. (1993). Production and Enhancing Field Crops. Baghdad University, Baghdad. 218pp. (In Arabic).
- Andrews, D. W. (1988). `Chi-Square diagnostic tests for econometric models. Journal of Econometrics, 37, 135-156. https://doi.org/10.1016/0304-4076(88)90079-6.
- Audibert, J. Y., & Catoni O. (2011). Robust linear least squares regression. Annals of Statistics, 39, 2766–2794.
- Dadzie, S. K. N., & Acquah, H. D. (2015). Attitudes toward risk and coping responses: the case of food crop farmers at Agona Duakwa in Agona East District of Ghana. International Journal of Agriculture and Forestry, 2, 29-37. https://doi.org/10.5923/j.ijaf.20120202.06
- Debertin, D. (1986). Agricultural Production Economics. MacMillan Publishing Company, New York, 366pp.
- Doll, J. P., & Orazem F. (1984). Production Economics Theory with Application. 2nd edition, John Wiley and Sons, New York, 117pp. https://www.worldcat.org/title/production-economics-theory-with-applications/oclc/10018291
- Dutta, A., & Bandopadhyay, G. (2012). Performance in the Indian stock market using logistic regression. The International Journal of Business and Information, 7, 105-136. https://doi.org/10.18488/journal.1007/2018.8.7/1007.7.247.258
- de Menezes, D. Q. F., Prata, D. M., Secchi, A. R., & Pinto, J. C. (2021). A review on robust M-estimators for regression analysis. Computers and Chemical Engineering, 147, 107254. https://doi.org/10.1016/j.compchemeng.2021.107254
- Faisal, N. F. (2016). Logistic regression dual response technique to determine the variables affecting the monthly income adequacy for the Iraqi family. Journal of Baghdad College of Economic Sciences University, 47, 131-148. https://www.iasj.net/iasj/article/109027
- Fakayode, S. A., Rahji, M. A. Y., & Adeniyi, S. T. (2014). The application of logistic regression analysis to the cumulative grade point average of graduating students: a case study of students of applied science, federal polytechnic, Ilaro. Developing Country Studies, 4, 26-30.
- Farhan, M. O., Ali, S. H., & M. H. Ali, M. H. (2013). Study of the economics of wheat crop production in Wasit province for the year (2008-2009). Journal of Administration and Economics, 94, 1-10.
- Gujarati, D. N. (2004). Basic Econometrics. 4th edition, McGraw-Hill Book Co. New York, 1032pp. https://www.amazon.com/Basic-Econometrics-4th-Damodar-Gujarati/dp/0070597936
- Hosmer, D. W., & Lemesbow, S. (1980). Goodness-of-fit test for the multiple logistic regression model. Communications in Statistics, 9(10), 1043-1069. https://www.tandfonline.com/doi/abs/10.1080/03610928008827941?journalCode=lsta20
- Hosmer, D. W., Lemeshow, S. A., & Sturdivant, R. X. (2013). Applied Logistic Regression. Hoboken, N. J: John Wiley & Sons, 528pp.
- King, J. E. (2002). Logistic Regression: Going Beyond Point-and-Click. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, L. A.
- Ministry of Planning and Development Cooperation (2019). Central Organization for Statistics, Agricultural Statistics. Statistical publications for years (1990-2019), 87pp.
- Ministry of Agriculture (2019). Planning and Follow-up Department - Agricultural Statistics Records for the period 1990-2019, 114pp.
- Mohsin, O. M., Kathem, H. H., & Karee, Z. I. (2019). Using logistic regression to study the most important determinants of the adequacy of family income. Scientific Journal of Jihan University, 3, 282-292. https://doi.org/10.29304/jqcm.2018.10.2.374
- Monjezi, N. (2021). Energy prediction of wheat production using data mining technique in iran. Basrah Journal Agricultural Sciences, 34, 14-27. https://doi.org/10.37077/25200860.2021.34.1.02
- Moscardi, E. A., & de Janvry, A. (1977). Attitude toward risk among peasants: an econometric application approach. American Journal of Agricultural Economics, 59, 710-721. https://doi.org/10.2307/1239398
- Najm, A. K., & Saleh, M. A. (2011). The use of logistic regression in studying the causes of death in preterm babies in Babylon. Journal of Karbala University, 16, 52-64. https://kj.uokerbala.edu.iq/article_153409.html
- Nto, P. O. O., Mbanasor, J. A., & Nwaru, J. C. (2011). Analysis of risk among agribusiness enterprises investment in Abia State, Nigeria. Journal Economics and International Finance, 3, 187-194.
- Obaid, R. I. (2011). Analytical study for economics of producing rice in Najaf governorate during 2009 season. Journal of Al-Rafidain University College for Sciences, 28, 130-149.
- Olarinde, L.E., Manyony, V. M. & Akintola, J. O. (2007). Attitudes towards risk among maize farmers in the dry savanna zone of Nigeria: Some prospective policies for improving food production. African Journal of Agricultural Research, 2, 399-408. https://doi.org/10.5897/AJAR.9000078
- Rijib, M. Z., & Nasir, S. A. (2019). Economic analysis of the effect soil salinity levels on wheat production in the irrigated area (Wasit governorate: A case study). Plant Archives, 19, 118-122. https://doi.org/10.36103/ijas.v47i4.534
- Sadiq, M. S. (2018). Application of safety-first approach to measure risk behaviour of Yam farmers in Benue state, Nigeria. Journal of Scientific Agriculture, 2, 52-61. https://doi.org/10.25081/jsa.2018.v2.890
- Salimonu, K. K., & Falusi, A. O. (2009). Sources of risk and management strategies among food crop farmers in Osun State, Nigeria. African Journal Food, Agriculture, Nutrition and Development, 9, 1592-1605. https://doi.org/10.4314/ajfand.v9i7.47687
- Teweldemedhin, M. Y. (2012). Factors influencing enterprise diversification as a risk strategy management in Namibia: a case study of communal farmers from the Kunene region. International Journal of Agricultural Sciences, 2, 845-853.https://agris.fao.org/agris-search/search.do?recordID=DJ2012079950
References
Abbas, A. K. (2012). Using logistic regression model to predict the functions with economic categorical dependent variable. Kirkuk University Journal Administrative and Economic Sciences, 2, 234-2563.https://www.iasj.net/iasj/download/02385e57f0f237af
Al-Hussine, H. D., & Alyousuf, A. A. (2021). Responses of local wheat varieties to greenbug Schizaphus graminum and bird-cherry oat aphid Rhopalosiphum padi infestation. Basrah Journal Agricultural Sciences, 34, 124-138. https://doi.org/10.37077/25200860.2021.34.1.11
Ali, K. A., & Mahmood, Z. H. (2018). Estimating profit, cost function and technical efficiencies of rice production in Nejaf (sic) for season 2016. Iraq Journal of Agricultural Sciences, 50, 1237-1246. https://doi.org/10.36103/ijas.v50i5.789
Ali, S. S., Mubeen, M., Lal, I., & Hussain, A. (2018). Prediction of stock performance by using logistic regression model: evidence from Pakistan Stock Exchange (PSX). Asian Journal of Empirical Research, 8, 247-258. https://doi.org/10.18488/journal.1007/2018.8.7/1007.7.247.258
Al-Mashadani, A. K., & Mahmood, Z. H. (2019). Estimation of production function of rice in Najaf province for season 2016. Journal of Plant Archives, 19, 1457-1463.
Al-Obeidi, E. A. (2020). Economic analysis of production risks for fish farming projects in Iraq Diyala governorate as a model. M. Sc. Thesis. University of Baghdad, 78pp.
Al-Shafi'i, M. A. (2005). Modernization in the Economics of Production and Analysis of Competencies between Theory and Practice, Al-Muraqqab University, Libya, 315 pp. (In Arabic).
Al-Younes, A. H. (1993). Production and Enhancing Field Crops. Baghdad University, Baghdad. 218pp. (In Arabic).
Andrews, D. W. (1988). `Chi-Square diagnostic tests for econometric models. Journal of Econometrics, 37, 135-156. https://doi.org/10.1016/0304-4076(88)90079-6.
Audibert, J. Y., & Catoni O. (2011). Robust linear least squares regression. Annals of Statistics, 39, 2766–2794.
Dadzie, S. K. N., & Acquah, H. D. (2015). Attitudes toward risk and coping responses: the case of food crop farmers at Agona Duakwa in Agona East District of Ghana. International Journal of Agriculture and Forestry, 2, 29-37. https://doi.org/10.5923/j.ijaf.20120202.06
Debertin, D. (1986). Agricultural Production Economics. MacMillan Publishing Company, New York, 366pp.
Doll, J. P., & Orazem F. (1984). Production Economics Theory with Application. 2nd edition, John Wiley and Sons, New York, 117pp. https://www.worldcat.org/title/production-economics-theory-with-applications/oclc/10018291
Dutta, A., & Bandopadhyay, G. (2012). Performance in the Indian stock market using logistic regression. The International Journal of Business and Information, 7, 105-136. https://doi.org/10.18488/journal.1007/2018.8.7/1007.7.247.258
de Menezes, D. Q. F., Prata, D. M., Secchi, A. R., & Pinto, J. C. (2021). A review on robust M-estimators for regression analysis. Computers and Chemical Engineering, 147, 107254. https://doi.org/10.1016/j.compchemeng.2021.107254
Faisal, N. F. (2016). Logistic regression dual response technique to determine the variables affecting the monthly income adequacy for the Iraqi family. Journal of Baghdad College of Economic Sciences University, 47, 131-148. https://www.iasj.net/iasj/article/109027
Fakayode, S. A., Rahji, M. A. Y., & Adeniyi, S. T. (2014). The application of logistic regression analysis to the cumulative grade point average of graduating students: a case study of students of applied science, federal polytechnic, Ilaro. Developing Country Studies, 4, 26-30.
Farhan, M. O., Ali, S. H., & M. H. Ali, M. H. (2013). Study of the economics of wheat crop production in Wasit province for the year (2008-2009). Journal of Administration and Economics, 94, 1-10.
Gujarati, D. N. (2004). Basic Econometrics. 4th edition, McGraw-Hill Book Co. New York, 1032pp. https://www.amazon.com/Basic-Econometrics-4th-Damodar-Gujarati/dp/0070597936
Hosmer, D. W., & Lemesbow, S. (1980). Goodness-of-fit test for the multiple logistic regression model. Communications in Statistics, 9(10), 1043-1069. https://www.tandfonline.com/doi/abs/10.1080/03610928008827941?journalCode=lsta20
Hosmer, D. W., Lemeshow, S. A., & Sturdivant, R. X. (2013). Applied Logistic Regression. Hoboken, N. J: John Wiley & Sons, 528pp.
King, J. E. (2002). Logistic Regression: Going Beyond Point-and-Click. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, L. A.
Ministry of Planning and Development Cooperation (2019). Central Organization for Statistics, Agricultural Statistics. Statistical publications for years (1990-2019), 87pp.
Ministry of Agriculture (2019). Planning and Follow-up Department - Agricultural Statistics Records for the period 1990-2019, 114pp.
Mohsin, O. M., Kathem, H. H., & Karee, Z. I. (2019). Using logistic regression to study the most important determinants of the adequacy of family income. Scientific Journal of Jihan University, 3, 282-292. https://doi.org/10.29304/jqcm.2018.10.2.374
Monjezi, N. (2021). Energy prediction of wheat production using data mining technique in iran. Basrah Journal Agricultural Sciences, 34, 14-27. https://doi.org/10.37077/25200860.2021.34.1.02
Moscardi, E. A., & de Janvry, A. (1977). Attitude toward risk among peasants: an econometric application approach. American Journal of Agricultural Economics, 59, 710-721. https://doi.org/10.2307/1239398
Najm, A. K., & Saleh, M. A. (2011). The use of logistic regression in studying the causes of death in preterm babies in Babylon. Journal of Karbala University, 16, 52-64. https://kj.uokerbala.edu.iq/article_153409.html
Nto, P. O. O., Mbanasor, J. A., & Nwaru, J. C. (2011). Analysis of risk among agribusiness enterprises investment in Abia State, Nigeria. Journal Economics and International Finance, 3, 187-194.
Obaid, R. I. (2011). Analytical study for economics of producing rice in Najaf governorate during 2009 season. Journal of Al-Rafidain University College for Sciences, 28, 130-149.
Olarinde, L.E., Manyony, V. M. & Akintola, J. O. (2007). Attitudes towards risk among maize farmers in the dry savanna zone of Nigeria: Some prospective policies for improving food production. African Journal of Agricultural Research, 2, 399-408. https://doi.org/10.5897/AJAR.9000078
Rijib, M. Z., & Nasir, S. A. (2019). Economic analysis of the effect soil salinity levels on wheat production in the irrigated area (Wasit governorate: A case study). Plant Archives, 19, 118-122. https://doi.org/10.36103/ijas.v47i4.534
Sadiq, M. S. (2018). Application of safety-first approach to measure risk behaviour of Yam farmers in Benue state, Nigeria. Journal of Scientific Agriculture, 2, 52-61. https://doi.org/10.25081/jsa.2018.v2.890
Salimonu, K. K., & Falusi, A. O. (2009). Sources of risk and management strategies among food crop farmers in Osun State, Nigeria. African Journal Food, Agriculture, Nutrition and Development, 9, 1592-1605. https://doi.org/10.4314/ajfand.v9i7.47687
Teweldemedhin, M. Y. (2012). Factors influencing enterprise diversification as a risk strategy management in Namibia: a case study of communal farmers from the Kunene region. International Journal of Agricultural Sciences, 2, 845-853.https://agris.fao.org/agris-search/search.do?recordID=DJ2012079950