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The purpose of this paper is to investigate the relation between industrial concentration and technical inefficiency in the Indonesian food and beverages industry using a dynamic performance measure (dynamic technical inefficiency) that accounts for the presence of adjustment costs.

This research uses panel data of 44 subsectors in the Indonesian food and beverages industry for the period 1980-2014. The dynamic input directional distance function is applied to estimate the dynamic technical inefficiency. Further, the Granger causality between industrial concentration and dynamic technical inefficiency is tested using a dynamic panel data model. A bootstrap truncated regression model is finally applied to estimate the relation between industrial concentration and dynamic technical inefficiency based on the results from the Granger causality test.

The results show that the Indonesian food and beverages industry has a high dynamic technical inefficiency. Investigation of the causality of the relation shows that industrial concentration has a positive effect on dynamic technical inefficiency at the subsector level, with no reversed causality. The results suggest that the quiet life hypothesis applies to the Indonesian food and beverages industry.

The literature investigating the relation between industrial concentration and performance relies on static measures of performance, such as technical efficiency. Static measures provide an incorrect metric of the firms’ performance in the presence of adjustment costs associated with investment. Therefore, this research has a contribution in measuring dynamic technical inefficiency that accounts for the presence of the adjustment cost as well as its relation with industrial concentration in the Indonesian food and beverages industry.

The traditional predictor of technical inefficiency proposed by Jondrow, Lovell, Materov, and Schmidt (1982) is a conditional expectation. This chapter explores whether, and by how much, the predictor can be improved by using auxiliary information in the conditioning set. It considers two types of stochastic frontier models. The first type is a panel data model where composed errors from past and future time periods contain information about contemporaneous technical inefficiency. The second type is when the stochastic frontier model is augmented by input ratio equations in which allocative inefficiency is correlated with technical inefficiency. Compared to the standard kernel-smoothing estimator, a newer estimator based on a local linear random forest helps mitigate the curse of dimensionality when the conditioning set is large. Besides numerous simulations, there is an illustrative empirical example.

This study examines the performance of India's food processing sector by estimating its output growth, technical efficiency (TE) and input-driven growth (IDG)

This study used panel data from six food processing manufacturing industries for the period 2000–01 to 2017–18. Technical efficiency and input-driven growth was measured using the parametric half-normal stochastic frontier production function.

The findings of this study showed that the estimated average technical efficiency is 86.6%, which specifies that the Indian food processing sector is technically inefficient. In addition, the output growth rate is 5.5%, driven by high doses of inputs (5.7%), whereas there is no indication of constant returns to scale. However, the food processing sector has experienced more input-driven expansion than either technological or efficiency changes.

This study is limited to India's organized manufacturing food processing sector; the aggregate macro data at a three-digit level based on the national industrial classification (NIC) was used. This study provides robust estimates for industrialists and processors, as well as concrete policy formulations on how overdoses of inputs may lead to high exploitation of resources, whereas outputs can be augmented by implementing upgraded and new technologies.

Previous research has estimated the total factor productivity and technical efficiency only in order to analyze the food sector's performance, but none of the studies have evaluated the share of inputs in growth performance and efficiency. Therefore, this study contributes by measuring growth performance and the share of inputs in the growth performance of India's food processing sector.

The purpose of this paper is to investigate the technical efficiency (TE) of micro and small enterprises (MSEs) and its determinants in the Indonesian manufacturing sector covering comprehensive subsectors.

This research uses the data from the micro and small industry survey sourced from the Indonesian Bureau of Central Statistics for the period 2010–2015. The TE is estimated using data envelopment analysis (DEA) with bootstrapping approach. The TE is also estimated at the firm-level survey data, classified at the five-digit level of the International Standard Industrial Classification system. In addition, a truncated regression model is applied to estimate the effects of the determinants on the TE.

This research finds that there is a low average TE of the MSEs for the subsectors investigated. It is also found that the TE is associated with firm size, location, export orientations on domestic and world markets, firm age, level of technology, and owner education.

The literature investigating the TE of the MSEs and its determinants is still rare in Indonesia. Most of the previous research limited the studies for specific subsectors and/or specific small regions. Therefore, this research has a contribution in measuring the TE of the MSEs for comprehensive subsectors as well as its relation with the determinants in the Indonesian manufacturing sector. Also, the DEA with bootstrapping approach is applied to estimate the TE of the firms based on each relevant subsector, which is rare in the previous research of the Indonesian MSEs.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The purpose of this paper is to provide new evidence about the technical efficiency and its determinants in Spanish textile sector during the period 2002-2009. The empirical results suggest that the effects of trade liberalization have led to higher levels of inefficiency in the Spanish sector, due to the lack of flexibility of firms to adjust to the environment, and perhaps to aggressive competition with fuzzy rules of the game. Controlling for specific factor like age, intensity of capital, salary by worker, regions and market share, the authors have obtained that the interaction between market share and size indicates that as firms have more size are also more inefficient.

In this paper, the stochastic frontier production function is considered, specifically, a panel data version of Battese and Coelli (1995), in which the technical inefficiency is estimated from the stochastic frontier and simultaneously explained by a set of variables. This approach avoids the inconsistency problems of the two-stage approach used in other empirical works when analyzing the inefficiency determinants.

This work provides new evidence about the technical efficiency and its determinants can be due to environmental or firm-specific factors in Spanish textile sector during the period 2002-2009. The authors have estimated the Cobb-Douglass stochastic production frontier following Battese and Coelli (1995) model to analyze an unbalanced panel.

The empirical results suggest that the trend of the inefficiency shows a curvilinear behavior in the form of U (turning point third-quarter of 2004). This result is related to the efficiency analysis through Kernel distributions (in static and dynamic form) confirmed a clear process of divergence. In the period 2002-2005 the efficiency of the firms analyzed maintained higher levels than the 2005-2009 period where there is deterioration. This may be related to the increased competition due to the end of the Multi-Fiber Arrangement in January 2005 and the entry of Chinese products in 2004.

The paper investigates relative efficiency of the banking industry in Bahrain by employing a panel of 31 banks for the years 1998 and 2000. We employ non‐parametric (Data Envelopment Analysis) to examine five efficiency measures, namely, cost, allocative, technical, pure technical and scale efficiency scores. We also investigate the conventional accounting measures of performance, and correlate them with five measures of efficiency to investigate whether higher accounting performance impact the bank cost efficiency. Our results show that, on the average, the banking industry in Bahrain is profitable with average ROE and ROA being 10.36% 1.622% in 1998 while 13.49% and 2.097% in 2000 respectively. The average allocative efficiency (inefficiency) is about 73% (37%), whereas the average technical efficiency (inefficiency) is about 56% (78%). This indicates that the dominant source of inefficiency in Bahrain banks is due to technical inefficiency rather than allocative inefficiency, which is mainly attributed to diseconomies in scale. Overall, average scale efficiency (inefficiency) is about 79% (26%), and average pure technical efficiency (inefficiency) is about 71% (41%), suggesting that the major source of the total technical inefficiency for Bahrain banks is pure technical inefficiency (input related) and not scale inefficiency (output related). The results also indicate that all banks have improved their efficiency levels and experienced some gains in productivity. Finally, regression analysis is used to investigate the determinants of the overall efficiency scores. We find that larger and profitable banks are more likely to operate at a higher level of efficiency. Also, another finding reveals that market power plays an important role in cost and technical efficiencies. Notably, banks with greater contribution from shareholders tend to be more technical efficient

Countries in Africa have a common goal policy of industrialisation that is expected to be driven by investing in innovation that yields efficiency. The purpose of this paper is to investigate the technical efficiency effects arising from innovation inputs including internal R&D, human capital development (HCD), and foreign technology adoption in manufacturing firms in Africa.

This study uses cross-sectional firm-level survey data from the 2013 World Bank Enterprise Survey and the linked 2013 Innovation Follow-up Survey. A heteroscedastic half-normal stochastic frontier is used for analysing the technical efficiency effects of innovation inputs of 418 firms.

This study reveals that internal R&D, and foreign technology have negative effects on technical efficiency. Notwithstanding, the combination of foreign technology and internal R&D, and foreign technology and HCD reinforce each other’s effects on technical efficiency.

This study provides evidence that whereas individual innovation inputs may not yield positive efficiency outcomes, the combination of absorptive capacity enhancing inputs comprising internal R&D and HCD with foreign technology is vital for enhancing technical efficiency in manufacturing firms in Africa. This study offers important lessons for managers in manufacturing firms in Africa.

This study is virtually the first to investigate the relationship between innovation inputs and efficiency in Africa. This study demonstrates that investing in foreign technology in isolation from absorptive capacity enhancing innovation inputs diminishes efficiency. HCD and internal R&D are imperative for building absorptive capacity that enhances efficiency outcomes arising from foreign technology.