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Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.

Recent studies on the welfare implications of internationally mobile capital for a country employing commercial policy have been restricted to constant‐returns‐to‐scale (CRS) production models. It is generally concluded that the pursuit of such policies is welfare‐decreasing under CRS conditions. The analysis to encompass variable‐returns‐to‐scale (VRS) is generalised and it is shown that there is an optimal (second best) combination of import tariff and foreign capital subsidy that will not be “immiserising” for an increasing‐returns‐to‐scale (IRS) industry.

The purpose of this paper is to investigate the role of market power and returns to scale in the determination of farm-value share.

This paper utilizes the equilibrium displacement model to investigate the role of market power and returns to scale in the determination of farm-value share. Contrary to the current literature, the paper incorporates oligopoly power, oligopsony power and non-constant return to scale into one generalized model, which systematically enables us investigate the impacts of market power on the determination and changes of farm-value share.

The results imply that market power as well as non-constant returns to scale is central to the understanding of farm-value share. These, in turn, indicate that ignoring the impacts of market power and degree of return to scale may overestimate or underestimate the impacts of exogenous shocks on changes in farm-value share.

Thus, to the best of the authors’ knowledge, no literature has examined the co-existence of oligopsony power, oligopoly power as well as non-constant return to scale in farm-value share determination. This paper therefore tries to fill this gap.

The purpose of this paper is twofold: to investigate the existence of different degrees of returns to scale in low-tech and high-tech manufacturing industries; and to examine whether the degrees of returns to scale change through time.

The empirical investigation implemented in the paper uses data from the EU KLEMS Database, covering a sample of 12 manufacturing industries in 11 OECD countries over the period 1976-2006. The investigation employed two different estimation methods: instrumental variables and system GMM. The robustness of the results was assessed by employing two different specifications of Kaldor-Verdoorn’s Law, by using lags and five-year averages to smooth business-cycle fluctuations, and by dividing the sample into two time periods.

The results reported in the paper provide strong evidence in support of the hypothesis of substantial increasing returns to scale in manufacturing. The investigation suggests that high-tech manufacturing industries exhibit larger degrees of returns to scale than low-tech manufacturing industries. Finally, the analysis revealed also that the magnitude of the returns to scale in manufacturing have increased in the last decades, driven by increases in the magnitude of returns to scale observed in high-tech industries.

No previous work has assessed the hypothesis that increasing returns to scale vary according to the technological content of industries. Moreover, no previous work has used system GMM or data from EU KLEMS to test Kaldor-Verdoorn’s Law. Most importantly, the findings of the paper present new evidence on the degree of returns to scale in high-tech and low-tech manufacturing industries.

The purpose of this paper is to develop a theoretical model of price transmission from the farm to the retail sector, allowing not only for an interaction between oligopoly power, oligopsony power and non‐constant returns to scale in industry technology, but also allowing for the market power conduct parameters to vary in response to an industry‐wide exogenous shock. Also, the degree of price transmission under imperfect competition relative to that under perfect competition is evaluated.

Conjectural variations are used to parameterize both seller and buyer market power conduct of the industry and then the equilibrium displacement approach is applied to solve a system of six structural equations which describe the demand for and supply of industry retail output and farm and marketing inputs.

First, it is found that given empirical values of retail output demand elasticity, of farm and marketing inputs supply elasticities, of market power conducts, and of the returns to scale measure, the degree of price transmission under imperfect competition is greater than that under perfect competition. Second, it is found that the relative degree of price transmission under imperfect competition could be greater or smaller under the assumption of a varying market power conduct than one under the alternative assumption of a constant market power conduct, depending on whether market conduct is falling or rising, respectively.

The paper makes two original contributions to the literature. First, it allows for an interaction between oligopoly power, oligopsony power and industry technology. Second, it allows both oligopoly and oligopsony power parameters to vary in response to industry‐wide exogenous shocks.

Economic production analysis can provide critical perspectives on an industry’s performance. The purpose of this paper is to investigate the factor input intensity of hospitality and related industries, namely, accommodation, food service and amusement, gaming and recreation (AFAGR), compared to other service industries.

This paper compared AFAGR with other industries categorized as services by the North American Industry Classification System (NAICS). The NAICS code of up to four digits was used to collect data (US Census Bureau).

Results of this paper confirm extant literature that food service is more labor-intensive than other service industries; however, this was not true of accommodation and AGR industries. Similarly, while food service industry was relatively less intermediate input intensive than other service industries, accommodation and AGR were not. There were no significant differences between hospitality and other service industries (AFAGR) in their capital intensity. Another important finding was that while accommodation had constant results to scale, AGR had increasing returns to scale and food service industry was found to have decreasing returns to scale.

This investigation only looked at the four-digit NAICS-coded industries. International differences could also be investigated in the future.

Based on theoretical arguments, high labor intensity together with low intermediate input in food service industry suggests that efficiencies could be gained in these businesses. This may also be evident by the decreasing returns to scale that this paper found for the food service industry. These comparisons could guide additional research about the causes, consequences and potential sources of improvement of efficiency of economic productivity in AFAGR. Managers in AFAGR would find it valuable to understand how they might be able to enhance economic output, particularly in the context of the role of labor. Furthermore, any changes in one economic input would have implications on other inputs and possibly on productivity.

Any future recalibration of input intensity in hospitality industries could have both social and economic consequence.

This paper enhances our understanding of how hospitality industries use economic factors of production. Labor in AFAGR is viewed as a given. This study suggests that food service industry may need to reevaluate its labor productivity, the way it is measured and how it might affect efficiencies. Such understanding could better inform the sources and causes of economic efficiencies in AFAGR industries. Until now, this understanding has mostly been based on relatively scarce comparative systematic analysis.

To examine whether Japanese commercial banks exhibited economies of scale and economies of density at the time when the mega‐merger wave in Japanese banking began in the late 1990s. Since this merger wave has not yielded efficiencies, this analysis aims to shed light on whether banks, at the start of the wave, had reason to believe that larger banks would be more efficient.

Using a modified version of the translog cost function, the analysis estimates economies of scale and economies of density for Japanese city banks, trust banks, and regional banks. Then, the relationship between size and economies of scale/density and that between profitability and scale/density are explored using regression analysis.

Results suggest that larger banks (as measured by value of assets/loans/ deposits/investments, and number of employees/branches) were more likely to be in the decreasing/constant returns to scale/density region than smaller banks, The finding was statistically significant for all three types of Japanese banks. On average, city banks exhibited diseconomies of scale/density; trust banks exhibited constant returns to scale and increasing returns to density, and regional banks exhibited increasing returns to scale and density. This suggests that unions between city banks and either regional banks or trust banks may have been more likely to yield cost‐efficiencies, and raises questions concerning the efficiency motivations of the mega‐bank mergers. The findings further indicate that banks with higher sales were more likely to have exploited scale/density efficiencies, and that banks with higher net incomes were more likely to be in the increasing returns region.

This paper suggests that the mega‐merger wave in Japan in the late 1990s may not have been motivated by a desire for greater efficiencies through utilization of under‐utilized branch networks. Unlike other studies, this analysis differentiates between economies of scale and economies of density.

The main purpose of this paper is to select the most suitable production model for measuring the production process of some major manufacturing industries in Oman.

This empirical paper looks into an analytical justification to use Cobb‐Douglas (C‐D) production model in order to estimate and test the coefficients of the production inputs for each of the selected manufacturing industries using annual industrial statistical data over the period 1994 through 2007 published by Ministry of Commerce and Industry, Sultanate of Oman.

The results of the paper indicate that for most of the selected industries the C‐D function fits the data very well in terms of labor and capital elasticity, return to scale measurements, standard errors, economy of the industries, high value of R² and reasonably good Durbin‐Watson statistics. The estimated results suggest that the manufacturing industries of Oman generally seem to indicate the case of increasing return to scale. Of the nine industries, seven exhibit increasing return to scale and only the rest two show decreasing return to scale. The paper finds no industry with constant return to scale.

The paper could not consider a good number of manufacturing industries and a long period of time series data in the study because of lack of data availability.

Recently, businessmen as well as industrialists are very much concerned about the theory of firm in order to make correct decisions regarding what items, how much and how to produce them. All these decisions are directly related with the cost considerations and market situations where the firm is to be operated. In this regard, this paper should be helpful in suggesting the most suitable functional form of production process for the major manufacturing industries of developing countries like Oman.

The paper shows originality in substance and makes a unique contribution to the literature on industrial economics in Oman.

The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.

Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.

The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.

As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.