Abstract
This research uses a production function of the type proposed by Mankiw et al. (1992) to study the effect of logistics and information and communication technologies (ITC) on domestic technical efficiency using stochastic frontier analysis for thirty-four countries over the period 2007–2012. We find that logistics and ICT are important channels for improving efficiency. This paper contributes to the literature by estimating the contribution of logistics and ICT to domestic technical efficiency. The economic impact of logistics measured using the LPI (Logistics Performance Index) on technical efficiency is estimated at 0.59 % for every 1 % increase in LPI, ceteris paribus.
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Notes
In this study we use the LPI variable to approximate the level of logistics performance of each country. The World Bank has only published the International LPI for the periods mentioned.
See Coelli et al. (2005) for a more thorough review of the literature related to efficiency and productivity.
In the specification made by Battese and Coelli (1995), the function which explains inefficiency is estimated in a single step with production technology, which avoids the problem of inconsistency in the estimate in two stages. Wang and Schmidt (2002) cautioned against using the two-step procedure to calculate the effect of the measured covariates, the ‘z’s’, on estimates, arguing that the omission of the covariates at the ‘first step’ is tantamount to the omitted variable problem in ordinary regression. Nonetheless, this procedure is common, and, indeed, is routine in DEA literature.
In order to avoid heterogeneity problems in the sample, only countries that the World Bank considers within the Upper middle Income and High income group have been taken into account.
The capital stock for each country was cumulatively calculated from gross capital formation (constant 2005 US dollars). We followed the methodology of Dhareshwar and Nehru (1994).
Coelli et al. (2005) point out that if γ = 0, the deviations from the frontier are entirely due to noise. γ parameter can be used to perform a diagnostic likelihood-ratio (LR) test.
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Coto-Millán, P., Fernández, X.L., Pesquera, M.Á. et al. Impact of Logistics on Technical Efficiency of World Production (2007–2012). Netw Spat Econ 16, 981–995 (2016). https://doi.org/10.1007/s11067-015-9306-6
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DOI: https://doi.org/10.1007/s11067-015-9306-6