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In this paper, the authors aim to investigate the short‐run as well as long‐run market efficiency of Indian commodity futures markets using different asset pricing models. Four agricultural (soybean, corn, castor seed and guar seed) and seven non‐agricultural (gold, silver, aluminium, copper, zinc, crude oil and natural gas) commodities have been tested for market efficiency and unbiasedness.

The long‐run market efficiency and unbiasedness is tested using Johansen cointegration procedure while allowing for constant risk premium. Short‐run price dynamics is investigated with constant and time varying risk premium. Short‐run price dynamics with constant risk premium is modeled with ECM model and short‐run price dynamics with time varying risk premium is modeled using ECM‐GARCH in‐Mean framework.

As far as long‐run efficiency is concerned, the authors find that near month futures prices of most of the commodities are cointegrated with the spot prices. The cointegration relationship is not found for the next to near months futures contracts, where futures trading volume is low. The authors find support for the hypothesis that thinly traded contracts fail to forecast future spot prices and are inefficient. The unbiasedness hypothesis is rejected for most of the commodities. It is also found that for all commodities, some inefficiency exists in the short run. The authors do not find support of time varying risk premium in Indian commodity market context.

In context of Indian commodity futures markets, probably this is the first study which explores the short‐run market efficiency of futures markets in time varying risk premium framework. This paper also links trading activity of Indian commodity futures markets with market efficiency.

The National commodity exchanges were established in India in the year 2003-2004 to perform the functions of price discovery and price risk management in the economy. The derivatives market can perform these functions properly only if they are efficient and unbiased. So, there is a need to properly evaluate these aspects of the Indian commodity derivatives market. The purpose of this paper is to test the market efficiency and unbiasedness of the Indian soybean futures markets.

The paper uses cointegration and a QARCH-M-ECM-based framework to test the market efficiency and unbiasedness in the soybean futures contract traded in the National Commodity Derivatives Exchange (NCDEX). The cointegration test is used to test the long-run unbiasedness and market efficiency of the contract, while the QARCH-M-ECM model is used to test the short-run market efficiency and unbiasedness of the contract by allowing for a time-varying risk premium. The price data is also tested for presence of structural breaks using a Zivot and Andrews unit root test.

The soybean contract is unbiased in the long run, but there are short-run market inefficiencies and also a presence of a time-varying risk premium. Though the weak form of market efficiency is rejected in the short run, the semi-strong market efficiency is not rejected based on the forecasts.

This is the first paper to consider time-varying risk premium while performing the tests of market efficiency and unbiasedness on Indian commodity markets.

Purpose: The advent of the fintech revolution has brought a tremendous increase in the dissemination of digital financial services. Although digital financial services increase financial inclusion through financial intermediation, it also increases the chances of systematic risk.

Need: In the quest to satisfy the curious minds, the authors have examined the influence of digital financial services on banking stability and efficiency.

Methodology: To achieve the above objectives, the authors have used the Auto-Regressive Distribution Lag (ARDL) estimation technique on the annual data set of India and the United States from 2004 to 2018. In addition, to estimate the long-run cointegration, the ARDL bound approach is also used.

Findings: The empirical analysis concludes that in the short run, the expansion of digital financial services in India in the form of internet-based transactions and mobile money transactions creates a negative and significant impact on banking efficiency and stability. Meaning, banking sector efficiency and stability fall by 0.09% and 0.05% with a 1% increase in digital financial services. However, in the long run, digital financial services enhance banking stability and efficiency in India. Besides, the study also reveals that in a developed country like the United States, both in the short run and long run, expansion of digital financial services helps in improving banking efficiency and stability. Furthermore, in context to control variables, the findings suggest that in the short run, industrial productivity has a negative influence on the Indian banking sector efficiency and stability, compared to the positive impact in the long run. This is unlike the United States, where both in the long-run and short-run, industrial productivity has a positive influence on the banking sector’s efficiency and stability.

Practical implication: The findings reveal several policy implications and suggest policy synergies between digital financial services, banking stability and efficiency.

Using a panel of 1,122 UK firms listed on the London Stock Exchange over the period of 1981-2009, corporate efficiencies are predicted in this paper as inverse proxies of agency cost and the agency cost hypotheses are tested. The paper aims to discuss this issue.

Stochastic frontier analysis is used to estimate corporate efficiency of firms, but from two different perspectives. The long-run and short-run corporate efficiencies are predicted focussing on modern approach of value maximization and traditional approach of profit maximization, respectively.

The estimation results reveal that, an average firm in the sample achieves 74.5 percent of its best performing peer's market value and 86.6 percent of its best performing peer's profit and both of them are highly significant in the analysis. The long-run market value efficiency supports the agency cost of outside equity and the short-run profit efficiency supports the agency cost of outside debt hypothesis. Also there is a positive rank correlation between these two efficiencies which confirms that an average firm in the UK suffers from inefficiency or agency conflicts to a certain extent, no matter whether the firm is driven by short-run or long-run growth perspectives.

The predicted broad measures of agency costs in the paper have wider implications in enhancing the understanding of the UK firms’ corporate performance especially when they operate under a relatively free and market based governance and financial system.

The work is distinguished by the large panel of UK firms and a long period of time that is considered. Emphasizing on the empirical implications of the distinctions between short-run and long-run efficiency is also novel.

This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy.

This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis.

The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods.

The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management.

The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency.

The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.

In this chapter, we utilize the residual concept of productivity measures defined in the context of normal-gamma stochastic frontier production model with heterogeneity to differentiate productivity and inefficiency measures. In particular, three alternative two-way random effects panel estimators of normal-gamma stochastic frontier model are proposed using simulated maximum likelihood estimation techniques. For the three alternative panel estimators, we use a generalized least squares procedure involving the estimation of variance components in the first stage and estimated variance–covariance matrix to transform the data. Empirical estimates indicate difference in the parameter coefficients of gamma distribution, production function, and heterogeneity function variables between pooled and the two alternative panel estimators. The difference between pooled and panel model suggests the need to account for spatial, temporal, and within residual variations as in Swamy–Arora estimator, and within residual variation in Amemiya estimator with panel framework. Finally, results from this study indicate that short- and long-run variations in financial exposure (solvency, liquidity, and efficiency) play an important role in explaining the variance of inefficiency and productivity.

The paper's objectives are: to address the issue of cointegration (efficient market hypothesis) between Greek spot and futures markets over the period of the crisis, 1999‐2001; to investigate the short‐run and long‐run efficiency of the FTSE/ASE‐20 stock index futures contract and FTSE/ASE Mid 40 stock index futures contract traded on the Athens Derivatives Exchange (ADEX).

This paper examines efficiency of the Greek stock index futures market from 1999 to 2001. A variety of econometric models are employed to test for cointegration between prices. The paper uses daily data from the Athens Stock Exchanges (ASEs) and the ADEX. A more detailed discussion on the causal relationship between spot and futures price in ADEX is obtained by using the impulse response functions of the vector error‐correction model (to study the behaviour of series from real shocks).

The results show that the Greek futures and spot prices form a stable long‐run relationship. For both FTSE/ASE‐20 and FTSE/ASE Mid 40, futures markets play a price discovery role, implying that futures prices contain useful information about spot prices. Futures markets are informationally more efficient than underlying stock markets in Greece.

The results have important implications for both traders and speculators. The findings are strongly recommended to financial managers dealing with Greek stock index futures.

The contribution of this paper is to provide evidence using data from the early stage of the ADEX (started its official operation on 27 August 1999). It also investigates whether the hypotheses exist after the dramatic rise of ASE stock prices.

The representative firm model is used to demonstrate that competitive markets yield least‐cost production in the long run. This model is deficient in two respects: The demonstration's validity is suspect and it fails to show that least‐cost production occurs in the short run as well.

The objective of the paper is to get a better understanding of capacity utilisation (CU) in Indian public bus companies. More specifically, this paper would be measuring CU and identifying the drivers of the same. Finally, the influence of CU on the financial performance of Indian bus companies is examined.

The study adopted data envelopment analysis (DEA) to measure the CU in Indian public bus companies. Truncated regression was used to identify the drivers of CU. Subsequently, the ordinary least squares (OLS) regression was used to analyse the influence of CU on Indian bus companies' financial performance. The period of study was from 2013 to 17.

The significant drivers of CU were fleet age, passenger lead and fleet utilisation. Additionally, it was found that CU had a significant positive influence on the financial performance of Indian public bus companies and a unit increase in unused capacity has led to an increase of 7% in the operating ratio of the bus companies.

Getting insights into CU, apart from technical efficiency, is of immense use to both public transport researchers and practitioners. Managers of public bus companies should be mindful of CU as it has a significant bearing on their financial performance.

This is the first study in public transport, which establishes the linkage between CU and financial performance. Besides, a modified measure of cost-efficiency has also been conceptualised in this study.

The purpose of this study is to examine the influence of urbanization on energy consumption, including economic growth, globalization and “foreign direct investment (FDI)” inflow as control variables.

This study uses yearly panel data from 19071 to 2018 on five selected South Asian economies. It applies the “pooled mean group (PMG)” estimator and the “Dumitrescu-Hurlin (D-H)” panel causality test.

The PMG estimators reveal that urbanization causes energy consumption negatively in the long run because of an unusual and messy urbanization process. At the same time, it has no impact on the latter in the short run. Per capita income has both long- and short-run positive influences on energy use. Globalization causes energy consumption positively in the long run but does not affect it in the short run. FDI inflow has a strong positive impact on energy use in the long run and adverse effects in the short run. The Dumitrescu–Hurlin causality test reveals feedback relationships between “urbanization and energy consumption,” “globalization and energy consumption” and one-way causation from “per capita income to energy consumption.” It validates the findings of the PMG estimators.

The results of this study indicate that South Asia may focus on enhancing the availability of energy in the region and producing more renewable energy to add to its energy portfolio to meet growing energy demand, particularly among urban dwellers. Moreover, they should raise their real per capita incomes and augment the standard of living of low-income city dwellers to make urbanization more serviceable and comfortable.

This study is original. As far as the author is aware, this is a maiden attempt to investigate urbanization's effects on energy usage in South Asia in the preview of globalization and FDI.