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economics of on-farm development - Institute for Social and ...

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the knowledge <str<strong>on</strong>g>of</str<strong>on</strong>g> innovati<strong>on</strong> (ii) to <strong>for</strong>ming an altitude towards an innovati<strong>on</strong>,<br />

(iii) to dccide whether to adopt or reject, (iv) to implement the new idea, <strong>and</strong> (v)<br />

the c<strong>on</strong>firmati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> this decisi<strong>on</strong>. Thc final outcome as regards the decisi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

adopti<strong>on</strong> or other wise <str<strong>on</strong>g>of</str<strong>on</strong>g> the technological interventi<strong>on</strong> is c<strong>on</strong>diti<strong>on</strong>ed by<br />

c<strong>on</strong>crete or discrete set <str<strong>on</strong>g>of</str<strong>on</strong>g> variables. The c<strong>on</strong>crete set <str<strong>on</strong>g>of</str<strong>on</strong>g> variables provides some<br />

definite measure or evidence (both quantitative <strong>and</strong> qualitative) <strong>for</strong> the adopti<strong>on</strong><br />

or otherwise <str<strong>on</strong>g>of</str<strong>on</strong>g> the technology. On the other h<strong>and</strong>, discrete variables indicate<br />

whether or not a specific technology or <strong>farm</strong>ing practice is adopted in a binary<br />

choice model framework where the choice between two alternatives depends <strong>on</strong><br />

the specific nature <str<strong>on</strong>g>of</str<strong>on</strong>g> the problem analysed.<br />

There are two distinct approaches to explain the 'adopti<strong>on</strong> behaviour' <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

<strong>farm</strong>ers. The first approach is to identify the various factors influencing the<br />

adopti<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> a specific technology am<strong>on</strong>g the <strong>farm</strong>ers by using a linear multiple<br />

regressi<strong>on</strong> model (LMR). Sec<strong>on</strong>d approach is to logistically explain the adopti<strong>on</strong><br />

or otherwise <str<strong>on</strong>g>of</str<strong>on</strong>g> a technology based <strong>on</strong> the probability models, viz., logit <strong>and</strong><br />

probit models 10.<br />

7.2.1: Specificati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> the model <strong>and</strong> variables<br />

Given the nature <str<strong>on</strong>g>of</str<strong>on</strong>g> the problem <strong>and</strong> availability <str<strong>on</strong>g>of</str<strong>on</strong>g> <strong>farm</strong> level data, we try to<br />

explain the <strong>farm</strong> level adopti<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> OFD in the two irrigati<strong>on</strong> projects in Rerala<br />

in terms <str<strong>on</strong>g>of</str<strong>on</strong>g> the linear regressi<strong>on</strong> model based <strong>on</strong> ordinary least squares (OLS).<br />

Although the estimates based <strong>on</strong> OLS are likely to have problems <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

autocorrelati<strong>on</strong> <strong>and</strong> hetroscedasticity, these are taken care <str<strong>on</strong>g>of</str<strong>on</strong>g> by omitting such<br />

10 A detailed analysis <str<strong>on</strong>g>of</str<strong>on</strong>g> this, see Green <strong>and</strong> Ng'<strong>on</strong>g'ola (1993) <strong>and</strong> Saleth, 1991.<br />

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