Agricultural Productivity and technological gap between MENA ...

where yitand thethe time trend andM M Mk k 1kit= β0 + ∑βm it+2∑∑βmh mt htm=1m hMk k 1 k 2k k k+ ( βt + βc confit ) t +2βtt t ++ ∑ βmt xitt + vit −uitm=1y x x xmxit’s are the logarithm of output and inputs levels respectively, t stands forkvitandkuitare specified above.(8)confitis a proxy variable of the intensity ofan armed conflict (if there is) in a country (further details on this variable are granted in thenext section). This variable is associated to the time trend in order to assess possible shift inthe stochastic frontier caused by armed conflicts. In other words, this implementationprovides the possibility to depict the effects of armed conflicts on the technological changekthrough the parameter βc.Determinants of Technical EfficiencyBattese and Coelli (1995) suggested that the technical inefficiency effects, uitin (1) could bereplaced by a linear function of explanatory variables reflecting country-specificcharacteristics. This approach gives the opportunity of accounting for resources qualitydifferences across countries and socio-political and institutional differences that might haveaffected behavior.The technical inefficiency effects are assumed to be independent and non-negativetruncations (at zero) of normal distributions with unknown variance and mean. Specifically 3 ,mjuit = δ0+ ∑ δjzit + ωit(9)whereinefficiencies; δ0andmean and finite variancej=1jzit’s are farm and time specific explanatory variables associated with technicaljit 0 j j itδjare parameters to be estimated and ω is a random variable with zero2σωdefined by the truncation of the normal distribution such thatjω ≥− ( δ +∑ δ z ). This implies that the means, µit= δ0+∑δjzitof the uitaredifferent for different units but the variance but share the same variance.Two routes are possible in investigating the determinants of technical efficiency variationamong the units in the sample. The two stage approach is the most intuitive and involves theestimation of the technical efficiency effects from both models and regressing these on a setof unit specific characteristics. This approach, though widely used, implies that theinefficiency effects which are assumed to be independently and identical distributed in theestimation of the stochastic frontier are a function of the units’ specific effects in the secondstage, thus violating the assumption that the efficiency effects are identically distributed(Battese and Coelli., 1995). The inefficiency effects would only be identically distributed ifthe coefficients of the farm specific factors are simultaneously equal to zero (Coelli et al.,1995). It is possible to overcome this problem by the use of a single stage maximumlikelihood approach (Battese and Coelli, 1995). The technical inefficiency effects arespecified to be a function of a vector of unit specific variables and a random error as in (8)and a single stage maximum likelihood estimation technique is used to estimate theparameters of the production frontier and of the technical inefficiency variablessimultaneously.mj=13 Region index subscript is dropped for convenience.6