Investigando as principais formas de impulsionar a agricultura orgânica: uma análise de sobrevivência

Akram, Muhammad Waqar; Akram, Nida; hongshu, Wang; Andleeb, Shahla; Rehman, Khalil ur; Hassan, Farhaan

RESUMO:

O objetivo do presente estudo é avaliar as decisões dos agricultores de adotar a agricultura orgânica. Foi introduzido pela primeira vez por países desenvolvidos para minimizar os impactos ambientais originados pelo uso intensivo de fertilizantes sintéticos e pesticidas para aumentar o rendimento da produção. Embora a agricultura orgânica ofereça metodologias ambientalmente corretas para a produção agrícola, os agricultores asiáticos relutam em adotar a agricultura orgânica. Neste estudo, uma análise de sobrevivência (SA) foi empregada para determinar os motivos e o tempo que os agricultores levam para adotar a agricultura orgânica. Esta pesquisa estudou os objetivos dos agricultores, as políticas agrícolas e a atitude em relação ao risco, como covariáveis na análise de sobrevivência. Um método de tomada de decisão de múltiplos critérios com base no Processo de Hierarquia Analítica foi usado para avaliar os objetivos dos agricultores. Os dados foram coletados em fazendas agrícolas localizadas em três distritos de Punjab, Paquistão. Um questionário foi usado para coletar evidências empíricas. Este estudo descobriu que os objetivos dos agricultores eram cruciais para aceitação da agricultura orgânica; além disso, jovens agricultores e agricultores com atitudes inclinadas ao risco eram mais propensos a adotar a agricultura orgânica. O estudo também determinou que a mudança na política e a introdução de um pacote especial para a agricultura orgânica podem estimular a adoção de métodos orgânicos.

Palavras-chave:
método de cultivo; agricultura orgânica; produção; atitude do agricultor; análise de sobrevivência

[1] E-mail: waqar.akram13@yahoo.com. ^*Corresponding author.

Method of Analysis	Sample Size	Region	Study
Bayesian Logistic Growth Model	16	The Netherlands	Gardebroek and Jongeneel (2004GARDEBROEK, C.; JONGENEEL, R. The growth in organic agriculture: temporary shift or structural change. Paper presented at the Annual Meeting of the American Agricultural Economics Association, Denver, USA, 2004.)
Bayesian Spatial Durbin Probit Model	600	Ireland	Läpple and Kelley (2014LÄPPLE, D.; KELLEY, H. (2014). Spatial dependence in the adoption of organic drystock farming in Ireland. European Review of Agricultural Economics, 42(2), 315-337, 2014.)
Binary Choice Model	CF=388 OF=143	Czech Republic	Mala and Maly (2013MALA, Z.; MALY, M. The determinants of adopting organic farming practices: a case study in the Czech Republic. Agricultural Economics/Zemedelska Ekonomika, 59(1), 2013.)
Binary Logistic Regression	100	Pakistan	Ullah et al. (2015ULLAH, A. et al. Factors affecting the adoption of organic farming in Peshawar-Pakistan. Agricultural Sciences, 6(06), 587, 2015.)
Decision Tree Modeling	CF=12 OF=9	Austria	Darnhofer et al. (2005DARNHOFER, I. et al. Converting or not converting to organic farming in Austria: Farmer types and their rationale. Agriculture and human values, 22(1), 39-52, 2005.)
Dynamic Linear Programming		Denmark	Acs et al. (2007ACS, S. et al. Conversion to organic arable farming in The Netherlands: A dynamic linear programming analysis. Agricultural Systems, 94(2), 405-415, 2007.)
Endogenous Switching Regression Model	386	Ghana	Kleemann et al. (2014KLEEMANN, L. et al. Certification and access to export markets: Adoption and return on investment of organic-certified pineapple farming in Ghana. World Development, 64, 79-92, 2014.)
Empirical Switching Regression Model	247	USA	Kuminoff and Wossink (2010KUMINOFF, N. V.; WOSSINK, A. Why isn’t more US farmland organic? Journal of Agricultural Economics, 61(2), 240-258, 2010.)
Focus group	61	USA	Hanson et al. (2004HANSON, J., et al. Risk and risk management in organic agriculture: Views of organic farmers. Renewable agriculture and food systems, 19(4), 218-227, 2004.)
Linear programming simulations	685	Belgium	Kerselaers et al. (2007KERSELAERS, E. et al. Modelling farm-level economic potential for conversion to organic farming. Agricultural Systems, 94(3), 671-682, 2007.)
Investment under uncertainty		Germany and Austria	Musshoff and Hirschauer (2008MUSSHOFF, O.; HIRSCHAUER, N. Adoption of organic farming in Germany and Austria: an integrative dynamic investment perspective. Agricultural Economics, 39(1), 135-145, 2008. )
Logit Regression Model	CF=45 OF=150	Bangladesh	Sarker et al. (2009SARKER, M. et al. Determinants of adoption decisions: The case of organic farming (OF) in Bangladesh. Extension Farming Systems Journal, 5(2), 39, 2009.)
Logistic Regression Analysis	172	Thailand	Thapa and Rattanasuteerakul (2011THAPA, G. B.; RATTANASUTEERAKUL, K. Adoption and extent of organic vegetable farming in Mahasarakham province, Thailand. Applied Geography, 31(1), 201-209, 2011.)
Multi-disciplinary approach(chi-square test)	OF= 29	South Africa	(Niemeyer and Lombard, 2003NIEMEYER, K.; LOMBARD, J. Identifying problems and potential of the conversion to organic farming in South Africa. Paper presented at the Meeting of the Agricultural Economic Association of South Africa (AEASA), Pretoria, South Africa. 2003.))
Multinomial Logit Regression	CF=134 OF=38 IP= 71	France	Mzoughi (2011MZOUGHI, N. Farmers adoption of integrated crop protection and organic farming: Do moral and social concerns matter? Ecological Economics, 70(8), 1536-1545, 2011.)
Multinomial Logit Regression	CF=118 OF=28	USA	Anderson et al. (2005ANDERSON, J. B. et al. Determinants of farmer adoption of organic production methods in the fresh-market produce sector in California: A logistic regression analysis. Paper presented at the 2005 Annual Meeting, July 6-8, 2005.)
Multinomial Logit Regression	CF=696 OF=284	Norway	Koesling et al. (2008KOESLING, M. et al. Factors influencing the conversion to organic farming in Norway. International Journal of Agricultural Resources, Governance and Ecology, 7(1-2), 78-95, 2008.)
Multiple regression analysis	OF=65	Nepal	Kafle (2011KAFLE, B. Factors affecting adoption of organic vegetable farming in Chitwan District. Nepal. 2011.)
Option Theory	CF=167 OF=80	USA	Kuminoff and Wossink (2005KUMINOFF, N. V.; WOSSINK, A. Valuing the option to convert from conventional to organic farming. Paper presented at the AAEA Annual Meeting, Providence, 2005.)
Ordered Probit Model	CF=118 OF=44 PF= 75	Greece	Genius et al. (2006GENIUS, M. et al. Information acquisition and adoption of organic farming practices. Journal of Agricultural and Resource economics, 93-113, 2006.)
Ordered Probit Model	254	Spain	Calatrava-Requena and González (2008CALATRAVA-REQUENA, J.; GONZÁLEZ, M. Technical versus institutional innovation in Andalusian olive tree orchards: an adoption modelling analysis. Paper presented at the 12th Congress of the European Association of Agricultural Economists. Gent, Belgium, 2008.)
Probit Model	CF=107 OF=20	Turkey	Isin et al. (2007ISIN, F. et al. Factors affecting the adoption of the organic dried fig agriculture system in Turkey. Journal of applied sciences, 7, 748-754, 2007.)
Theory of Planned Behavior	CF=4593 OF=230	Latvia and Estonia	Kaufmann et al. (2009KAUFMANN, P. et al. Simulating the diffusion of organic farming practices in two New EU Member States. Ecological Economics, 68(10), 2580-2593, 2009.)

Variable	Impact direction	Variable	Impact direction
Education	Positive	Risk-averse	Negative
Age	Negative	Farming experience	Negative
Farm size	Negative	Farmer lives in an urban area	Positive
Other economic activity	Positive	Home to farm distance	Negative
Attitude towards conversion	Positive	Soil analysis	Positive
Consideration of degradation of soil	Positive	Use of information technology	Positive
Irrigation facility	Positive	Neighbor Organic farm	Positive
Soil fertility	Positive	Agriculture conference	Positive
Family labor	Positive	Concern for human health	Positive
Hired labor	Positive	Government Or external support	Positive
Information source	Positive	Access to credit	Negative
Protection of the environment	Positive	Food safety	Positive
Farmer organization	Positive	Social contact	Negative
-------------------Source: Elaboration based on literature review--------------------

---------------------------------------Perception of an economic agent's approach towards organic agriculture----------------------------------------
Variable		Commercial prospect (C1)	Social prospect (C2)
Consumer		0.841	0.043
Retailer		0.737	0.141
Financial institution		0.713	0.139
Other farmers in the region		0.634	0.142
Farmer’s Union		0.240	0.795
Membership of agriculture organization		0.107	0.733
Household member		0.140	0.634
----------------------Cronbach’salpha:0.71\|Rotation: Varimax\|KMO: 0.71\|Bartlet: 134.84 [0.00]\|Variance explained: 52.3%--------------------
----------------------------------------------------The motivation of farmer to adopt organic methods----------------------------------------------------
Variable	Domestic and Foreign (C3)	Financial incentive (C4)	Personal Inspiration (C5)
Foreign market has a positive aspect	0.818	0.047	0.131
The domestic market has a positive aspect	0.695	0.119	0.213
There is an economic facility to adopt organic farming	0.199	0.839	-0.089
Expensive input is used in conventional farming	-0.219	0.719	0.399
Appropriate channel diversification	0.397	0.510	0.028
Organic farming helps improve household health	0.144	0.026	0.831
Healthy food produce leads to personal satisfaction	0.211	0.066	0.610
-------------------Cronbach’s alpha: 0.65\|Rotation: Varimax\|KMO: 0.65\|Bartlet: 95.22 [0.00]\|Variance explained: 62.01%---------------------
--------------------------------------------------------Farmer’s understanding of organic farming---------------------------------------------------------
Variable		Perception of organic products (C6)	Future sustainability (C7)
Soil fertility is improved with organic farming		0.778	0.224
Conventional products are not as good in quality as organic products		0.644	0.164
Organic agriculture creates a good image for the farm		0.578	0.111
Conventional products are not as healthy compared to organic products		0.386	-0.013
Organic products are sold at a premium price to compensate for their lower yield		0.186	0.851
Organic farming has economic viability		0.415	0.789
The risk is high in organic farming due to yield variation		0.439	-0.594
Organic farming is not as hectic as conventional farming		0.077	0.510
-------------------Cronbach’salpha:0.585\|Rotation: Varimax\|KMO: 0.68\|Bartlet: 149.97 [0.00]\|Variance explained: 45.96%--------------------

	-------Financial Goal (WG₁)-------			----Environmental Goal(WG₂)-----		---------Social Goal (WG₃)---------
	Conventional	Organic	Conventional	Organic	Conventional	Organic
Geometric mean (Aggregate weight)	0.784	0.457	0.138	0.371	0.078	0.172
Arithmetic mean	0.741	0.445	0.139	0.364	0.120	0.191
Trimmed mean^*	0.819	0.356	0.117	0.316	0.064	0.169
Variance	0.054	0.031	0.010	0.021	0.013	0.012
Median	0.810	0.446	0.143	0.318	0.061	0.159

Variable	Description	-------Organic-----		-----Conventional----
		Mean	Std. dev.	Mean	Std. dev.
WG₂/WG₁	Comparative weight between "Environmental and Financial" goals	4.71	5.36	9.63	10.36
WG₁/WG₃	Comparative weight between "Financial and Social" goals	0.89	1.09	4.41	19.49
WG₂/WG₃	Comparative weight between "Environmental and Social" goals	0.24	0.10	0.13	0.34
Wg_1.1/Wg_1.2	Comparative weight between "Optimum yield and Increase farm & non-farm income"	0.92	0.95	0.75	1.43
Wg_1.1/Wg_1.3	Comparative weight between "Optimum yield and Farm profit"	0.48	0.58	0.94	3.11
Wg_1.2/Wg_1.3	Comparative weight between "Increase farm & non-farm income and Farm profit"	2.74	2.49	2.99	2.44
Wg_2.1/Wg_2.2	Comparative weight between "Encourage environmentally friendly methods and Improve soil fertility."	1.76	2.68	1.93	4.08
Wg_2.1/Wg_2.3	Comparative weight between "Encourage environmentally friendly methods and Conserve water"	1.01	0.96	1.08	1.71
Wg_2.2/Wg_2.3	Comparative weight between "Improve soil fertility and Conserve water "	1.67	2.33	1.96	2.20
Wg_3.1/Wg_3.2	Comparative weight between "Create employment opportunities in the specific region and Follow and maintain social and cultural values."	3.83	2.60	3.30	3.59
Wg_3.1/Wg_3.3	Comparative weight between "Create employment opportunities in the specific region and Discourage the urbanization (migration from rural to urban areas)"	6.90	5.99	4.27	4.33
Wg_3.2/Wg_3.3	Comparative weight between "Follow and maintain the social and cultural values and Discourage the urbanization (migration from rural to urban areas)"	2.45	2.14	2.71	3.45

Brasil

Brasil

Investigando as principais formas de impulsionar a agricultura orgânica: uma análise de sobrevivência

RESUMO:

Variables Descriptions		--------------Organic-------------		-----------Conventional-----------
		Mean	Std. Deviation	Mean	Std. Deviation
-----------------------------------------------------------------Farmer personal attributes (Pi)/>---------------------------------------------------------------
Age of the respondent(Years)		43.20	12.74	45.14	12.71
Manage holding(Farm)(year)		1992.91	12.56	1990.86	12.71
Other job apart from agriculture		0.46	0.50	0.39	0.49
Structural management of farm (Si)
Size of the farm (hectares)		5.47	6.06	5.75	10.19
Farm has the canal irrigation facility		0.64	0.48	0.61	0.49
-----------------------------------------------------------------Operational Management of farm (Mi)------------------------------------------------------
Annual income of the Respondent (PKR)		442450.32	458828.69	592222.34	1082793.47
------------------------------------------------------------------------External variables (Ei)------------------------------------------------------------------
Source of information	Conference before the start of new season	0.42	0.50	0.33	0.47
	Guidance from govt. authorities	0.18	0.39	0.21	0.41
	Member of any farming organization	0.45	0.50	0.31	0.46
	Has subscription of farming magazines/journals/blog	0.31	0.46	0.24	0.43
Hurdles to get loan (0 = easiest, 10 = most difficult)	Credit difficulty <6	0.51	0.50	0.45	0.50
	Credit difficulty <10	0.44	0.50	0.39	0.49
Price of wheat PKR/KG		35.70	1.22	30.96	1.17
Dummy Variable 2008		0.16	0.36	0.10	0.30
----------------------------------------------------------------Farmer’s opinion and approach (Oi)----------------------------------------------------------
PCA outcome about the perception of economic agent's approach toward organic agriculture	Social prospect	0.73	0.93	-0.11	0.83
PCA outcome about the motivation of farmer to adopt the organic method	Financial incentive	-0.69	1.15	0.17	0.82
PCA outcome about farmer understanding of organic farming	Perception of organic products	0.77	0.83	-0.19	0.92
Attitude toward risk (0 = most risk averse, 10 = most risk taker)	Risk < 6	0.10	0.30	0.39	0.49
	Risk < 10	0.78	0.41	0.50	0.50
-------------Do not use pesticides and herbicides in the farm-----------		0.88	0.27	0.53	0.20

Variable	Parameter	Standard error	Hazard Ratio
Comparative weight between "Environmental and Financial" goals	0.734^**	0.335	2.147
Comparative weight between "Encourage environmentally friendly methods and Conserve water."	0.246^***	0.132	1.313
Comparative weight between "Creating employment opportunities in the specific region and Discouraging urbanization (migration from rural to urban areas)"	0.741^***	0.251	2.041
Age of respondent	-0.342^***	0.131	0.836
Manage holding(Farm)	0.135^**	0.130	1.140
Other job apart from agriculture (0 = No, 1 = Yes)	2.604^**	1.015	13.261
Annual income of respondent	0.031^*	0.024	1.416
Size of farm	-0.104^***	0.106	1.024
Farm has a canal irrigation facility (0 = No, 1 = Yes)	2.015^**	0.684	4.631
Guidance from Govt. authorities (0 = No, 1 = Yes)	4.338^***	1.428	86.041
Credit difficulty (0 < 6, 1 > 5)	2.324^***	0.756	10.134
Price of wheat	1.002^**	0.401	2.517
Dummy variable 2008 (0 = before 2008, 1 = after 2008)	4.317	1.614	74.153
Risk (0 < 6, 1 > 5)	2.147^**	0.942	10.247
Does not use pesticides or herbicides in the farm (0 < 6, 1 > 5)	1.957^***	0.785	10.235
PCA outcome about the perception of an economic agent's approach towards organic agriculture	1.324^**	0.510	2.978
PCA outcome about motivation of farmer to adopt organic method	-1.525^***	0.550	0.159
PCA outcome about farmer’s understanding of organic farming	1.487^***	0.491	3.992