This paper discusses the problems of modeling efficiency of firms. There are two the most popular methods to estimate efficiency of firms: DEA (data envelopment analysis) and SFA (stochastic frontier analysis), and popularity of the last one is fast growing. There are a lot of different SFA models, so most researches often choose in advance one or two models, which they are going to estimate. So survey of different SFA models is one of goals of this paper. We discuss 15 popular SFA models. Also we discuss problems of SFA models and their prospects. In our paper we compare models, estimated by classical method of moments (MoM), and models, estimated by maximum likelihood approach (MML). Today there are no such papers, so we try to discuss pros and cons of using method of moments approach in SFA models. Interesting, that this method is very unpopular today, but its’ estimates are asymptotical normal and consistent. Because there are no formal criteria to compare different SFA models, we investigate the estimation results from 9 SFA models on the concrete industry data. We use correlation analysis of estimates of efficiency ranks and also we try to find out the causes of the most serious differences between models.
In this paper, we investigate differences in and determinants of technical efficiency across three groups of OECD, Asian and Latin American countries. As technical efficiency determines the capacity with which countries absorb technology produced abroad, these differences are important to understand differences in growth and productivity across countries, especially for developing countries which depend to a large extend on foreign technology. Using a stochastic frontier framework and data for 22 manufacturing sectors for 1996-2005, we find notable differences in technical efficiency between the three country groups we examine. We then investigate the effect of human capital and domestic R&D, proxied by the stock of patents, on technical efficiency. We find that while human capital has always a strongly positive effect on efficiency, an increase in the stock of patents has positive effects on efficiency in high-tech sectors, but negative effects in low-tech sectors.
This paper investigates the cost efficiency of Russian banks with regard to their heterogeneity in terms of ownership form, capitalization and asset structure. Using bank-level quarterly data over the period 2005–2013, we perform stochastic frontier analysis (SFA) and compute cost efficiency scores at bank and bank group level. We deduct from gross costs the negative revaluations of foreign currency items generated rather by official exchange rate dynamics than by managerial decisions. Results indicate that the core state banks, as distinct from other state-controlled banks, were nearly as efficient as private domestic banks during and after the crisis of 2008-2009. Foreign banks appear to be the least efficient market participants in terms of costs, which might reflect their lowest (and decreasing over time) penetration into the Russian banking system. We further document that group ranking by cost efficiency is not permanent over time and depends on the observed differences in bank capitalization and asset structure. We find that foreign banks gain cost efficiency when they lend more to the economy. Core state banks, conversely, lead in terms of cost efficiency when they lend less to the economy, which can result from political interference into their lending decisions in favor of unprofitable projects. Private domestic banks that maintain lower capitalization significantly overcome foreign banks and do not differ from the core state banks with this respect.