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Recent studies have linked differences in aggregate productivity to misallocation of resources across firms. In contrast, the purpose of this paper is to study the macroeconomic performance of OECD economies from a production efficiency point of view and estimated the determinants of (in)efficiency with particular emphasis on misallocation of labor.

Following the pioneering work of Battese and Coelli, the authors proposed a parametric methodology to construct a world frontier that serves as a benchmark to compare the relative position of each country. The non-negative technical inefficiency effects are assumed to be a function of explanatory variables. By doing this, determinants of technical inefficiency are explicitly introduced in the model.

The results revealed that OECD countries to operate efficiently should expand their aggregate output by 22.6 percent without consuming more resources. A novel finding is that higher skill mismatch is associated with higher production inefficiency. Conversely, more flexible labor markets, and better management and human resource practices, lowered the inefficiency in production. The paper also analyzed the underlying factors driving skill misallocation in the job market. In this regard, a well-functioning education and training system and greater flexibility in the determination of wages are associated with lower levels of mismatch between the skills of individuals and those required by the jobs.

The measurement of the productive efficiency of an economy (or country) is crucial to governments. It is important to know how far a given economy can be expected to increase its output by simply increasing its efficiency, without absorbing further resources. In other words, it is relevant to know if a country could produce more with the same resources and, therefore, could increase per capita income and welfare. In this type of analysis what also matters is to identify what factors or variables explain that greater or lesser ability of a country to convert its resources into aggregate production.

Much research on efficiency measurement has focused on the firm or industry level, mainly to study the efficiency of financial institutions. Efficiency studies using aggregated data across countries are rare in the literature of efficiency. This paper aimed to contribute to filling that shortage evaluating the macroeconomic performance of a sample of OECD countries from the production efficiency point of view.

The purpose of this study is to explore the link between aggregate production efficiency and the extent of linguistic clustering in Indonesia.

The author draws on the stochastic frontier model and applies it to the data on Indonesian provinces to compute the effects of various determinants on these provinces' aggregate production efficiency. The key determinant is the spatial index of linguistic clustering that the author believes has never been applied before in this context.

Linguistic clustering is an important determinant of aggregate production efficiency. Linguistic diversity is positively associated with productive efficiency if members of a specific linguistic group are not clustered beyond a certain level.

To the best of the author’s knowledge, this is the first study that links the spatial index of linguistic clustering (because of Massey and Danton) to production efficiency. In other words, the contribution of this study is to introduce a geographical dimension to the mainstream analysis of the association between ethnic diversity and economic performance.

The purpose of this paper is to construct a general theory of the marketing system that addresses the fundamental question: why do marketing systems occur, survive and grow?

The approach integrates the concepts and constructs contained in special and mid-range theories, scattered throughout the history of marketing thought, into a logically coherent set of propositions (including definitions, axioms, theorems, scientific laws, bridge laws and hypotheses) that comprise a general theory of the marketing system.

The theoretical answer to why marketing systems arise, survive and grow is because marketing systems offer the most efficient mechanism for supplying products and services that people demand, thereby increasing economic growth, compared to the opportunity costs of alternative methods of acquisition. Based on just two (of several) marketing efficiency theorems, if the input costs of trading decline (law of reduced transaction costs) and/or the output value increases (law of bulk transactions), then marketing system efficiency rises. This creates an upward spiraling cycle: increasing the extent of the market (law of market size), proliferating opportunities for increasing aggregate production efficiency (through the law of comparative advantage and the law of division of labor), thereby further proliferating opportunities for aggregate marketing system efficiency (e.g. law of central markets, law of marketing specialists), thus fueling further aggregate economic growth (until limited by the law of diminishing returns, the law of the minimum resource or the law of market size). An empirically testable central hypothesis is derived from the propositions: increasing aggregate marketing system efficiency provides both the necessary and sufficient conditions for increasing aggregate economic growth in a society.

The value of developing a general theory of the marketing system is to advance the marketing discipline as a social science. Additionally, a general theory is likely to enhance academic thinking, improve business practice and facilitate interaction among academicians and practitioners. Further, a general theory could also reduce disciplinary fragmentation, avoid identity confusion and lessen the credibility crisis in marketing, among others.

This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence of non-discretionary factors and partial impacts among inputs and outputs in the data envelopment analysis (DEA) framework.

First, inspired by the Imanirad et al.’s model (2013), the authors consider that each decision-making unit (DMU) may consist of several subunits, that each of which can be affected by non-discretionary inputs. After that, the Banker and Morey’s model (1996) is used for modeling non-discretionary factors. For measuring performance of several subunits, which can be considered as DMUs, the aggregate efficiency is suggested. At last, the overall efficiency is computed and compared with each other.

One of the important features of proposed model is that each output in this model applies discretionary input according to its need; therefore, the result of this study will make it easier for the managers to make better decisions. Also, it indicates that significant predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the influence of non-discretionary input. Therefore, the proposed model provides a more reasonable and encompassing measure of performance in participating non-discretionary and discretionary inputs to better efficiency. An application of the proposed model for gaining efficiency of 17 road patrols is provided.

More non-discretionary and discretionary inputs can be taken into consideration for a better analysis. This study provides us with a framework for performance measures along with useful managerial insights. Focusing upon the right scope of operations may help out the management in improving their overall efficiency and performance. In the recent highway maintenance management systems, the environmental differences exist among patrols and other geotechnical services under the climate diverse. Further, in some cases, there might exist more than one non-discretionary factor that can have different effects on the subunits’ performance.

The purpose of this paper was to measure the performance of a set of the roadway maintenance crews and to analyze the impact of non-discretionary inputs on the efficiency of the roadway maintenance. The application of the proposed model, on the one hand, showed that each output in this model uses discretionary input according to its requirement, and on the other hand, the result showed that meaningful predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the impact of non-discretionary input.

Providing information on resource sharing by taking into account non-discretionary factors for each subunit can help managers to make better decisions to increase the efficiency.

The purpose of this paper is to present an empirical study of the contribution of the services sector to per capita economic growth for Pacific Island countries.

Within the new growth theory framework, the empirical procedure consisted of the regression analysis of data using the panel data fixed effects procedure.

The results confirm the positive and statistically significant correlation of services growth to per capita gross domestic product growth.

Limitations largely centre on the use of aggregate cross‐country data. Variations may be found in what actually drives the services growth at the country level. Thus, a country‐specific study would be more appropriate in order to get more robust results. Also, the data do not capture the effect of non‐market services. Disaggregate services data that separate market data services with non‐market services would provide a more accurate picture of the influence of non‐market services.

The practical implication is that that service sectors in the Pacific Island countries ought to be given greater support, for example, investment in physical and institutional infrastructure, market access, financial support, skill development and investment incentives.

Pacific Islands services sectors contribute to household welfare through paid employment and meet household demands of service sector output.

This paper presents the first study among the Pacific Island countries that has examined the importance of services sector and its contribution to growth. The findings of this study are useful to Pacific policy makers in terms of improving the services sector through instituting appropriate growth enhancing policies.

The paper aims to investigate factors that drive the total factor productivity (TFP) and its growth in the Czech food industry over 2003–2017. The authors’ analysis focuses on firm-level characteristics such as location choice, sub-sector affiliation, use of debt, liquidity, asset turnover, firm size and firm age.

The determinants of productivity were tested econometrically by estimation of multivariate regression models. The firm-level panel data set consisted of 14,488 observations (data of 980 firms spanning 15 years). TFP was estimated by three regression-based techniques – ordinary least squares (OLS) regression, instrumental variables (IV) approach and two-way generalized method of moments (GMM) regression. All three measures of TFP were used as outcome variables to estimate the impact of firm-level determinants on both TFP level and growth.

The results have shown statistically significant and reversed U-shaped relationship between the firm age and the TFP level (with a turning point in the age of 12.5 years). However, the dynamic models investigating the TFP growth have found that younger firms achieve higher productivity growth in comparison with older ones. Higher market share and assets turnover were positively associated with both TFP level and its growth.

This study brings several relevant propositions for future research. First, the authors recommend future researchers to study not only differences in the levels of productivity but also determinants of its growth. Second, the authors believe that adding a non-linear component to age as a factor explaining changes in the levels of productivity might be a very relevant contribution to the literature.

Although it is generally accepted that successful and sustainable growth of firms, regions and economies can be achieved particularly through viable companies with high productivity, there is still a limited number of firm-level studies explaining the determinants of productivity levels and growth in agribusiness sectors in transition economies. Therefore, this study is expected to contribute to a better understanding of this important topic.

The purpose of this paper is to measure technical efficiency of Indian thermal power sector employing the recent by-production approach.

The by-production approach is used in conjunction with data from the Central Electricity Authority (CEA) of India to compute the output-based Färe, Grosskopf, Lovell (FGL) efficiency index and its decomposition into productive and environmental efficiency indexes for the ITPPs

The authors show that given the aggregated nature of data on coal reported by CEA, CEA’s computation of CO₂ emissions through a deterministic linear formula that does not distinguish between different coal types and the tiny share of oil in coal-based power plants, the computed output-based environmental efficiency indexes are no longer informative. Meaningful measurement of environmental efficiency using CEA data is possible only along the dimension of the coal input. Productive efficiency is positively associated with the engineering concept of thermodynamic/energy efficiency and is also high for power plants with high operating availabilities reflecting better management and O&M practices. Both these factors are high for private and centrally owned as opposed to state-owned power-generating companies. The example of Sipat demonstrates the importance of (ultra)supercritical technologies in increasing productive and thermodynamic efficiencies of the ITPPs, while also reducing CO₂ emitted per unit of the net electricity generated.

This paper uses the by-production approach for the first time to measure technical efficiency of ITPPs and highlights how the nature of the Indian data impacts on efficiency measurement.