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This paper aims to analyze the economic viability of jatropha plantation in North East India.

Economic viability is measured through the net present value and the benefit–cost ratio (BCR) at four different production standards along with four different prices of jatropha seed.

At a very low price and small production, jatropha plantation is economically not feasible. However, when the price of seed increases from INR 5 to 8, BCRs become greater than 1, provided that the discount rate is less than equal to 8 per cent. The minimum threshold of BCR indicates that the threshold of 1.5 BCR at a production level of 1.5 tons/ha can be achieved with a combination of seed price of INR 10 per kg and a discount rate of 1 to 3 per cent. Thus, jatropha cultivation is economically viable but not highly profitable.

Present study analyzes the economic viability of jatropha plantation from purely financial point of view. Social cost and benefit of energy crop plantation is not included in the study. This suggests to adopt social cost–benefit analysis to evaluate the overall feasibility of plantation crops in future studies.

This paper contributes to the academic literature of economic viability of energy plantation crops. Economic viability of jatropha plantation is shown in different cost and revenue conditions with statistical evidences.

Securing a job in an industry is a boon for most of the slum dwellers. When the primary earner of a slum household suffers from occupational illness and injuries, without insurance coverage or partial coverage of insurance, this boon may become a curse in the long run. The occupational security and safety along with the fact that whether such workers are insured is an important aspect and has a close link with the expenditure on illness. Thus, the accessibility to employees’ insurance in the risky industrial occupation, particularly for slum dwellers, is crucial to protect them from falling into poverty. Studies on occupational health of the poor workers are either limited to informal sectors or remain industry specific and the analysis of their accessibility to job insurance is rarely done. The paper aims to discuss these issues.

The research questions are framed to analyze the types of insurance accessible to workers across various industries; the accessibility to insurance, however, varying across risk intensities of various industries; and the determinants of insurance accessibility of the industrial workers living in slums. The determinants of accessibility of job insurance are analyzed with a binary Logit model. A multi-stage random sampling technique is used to collect the primary data from 320 industrial workers living in the slums of the Indian state of West Bengal.

The industrial workers, irrespective of the types of industries, are exposed to a high-risk category without proper job insurance. The higher industrial income is not adequate to prevent financial hardships. Access to insurance is more likely for the respondents with job tenure of more than two years and less likely for the workers who are working for more than eight hours per day.

This study provides a significant insight to the policymakers concerning health dynamics of the slum dwellers, which can improve their livelihood.

The analysis of the industry-specific risk intensities with accessibility to insurance contributes to understanding the coverage of the insurance scheme for the workers in slums.

The purpose of this paper is to focus on the determinants of occupational choice of workers in the handloom industry in Assam and to examine the variables that influence the occupational choice of the workers.

Primary data were collected from nine handloom concentrated districts in Assam. Multinomial and binary logistic regression models are used to analyse the data of three mutually exclusive occupations of workers namely owners, weavers, and reelers.

The results from the tested empirical model show that annual income, education, access to modern technology, and family size are the significant variables that help in transforming the reelers to owners. Similarly, annual income, education, and access to formal credit are the important variables that help in transforming the reelers to weavers. Access to modern technology appears as the most important factor in the occupational shift from weavers to handloom owners.

Present study has some limitations. It considers only a few variables related to economic and socio-demographic issues. There is further scope of research incorporating more variables such as personal savings, healthcare facilities, availability of hank yarn, marketing facilities, etc. Limitation of data in the worker category helper is another finding constraint.

Such studies in the handloom sector in Assam are limited and thus the present study greatly extends the understanding of the occupational choice of the workers in Assam's handloom industry.

Previous studies on handloom industry concentrated predominantly on the economic condition of the workers using mostly multiple regression technique. The present study deviates from normal research by using multinomial and binomial logistic regressions, which analyse the likelihood of occupational shift of the workers. The findings can be generalized to other handicraft-based small industry.

The forecasting power of commodity futures is a matter of intensive research as evidenced by a number of related publications. The purpose of this paper is to illustrate how advanced forecasting techniques improve the predictability of sugar futures in the Indian commodity market.

The forward premium is estimated using ordinary least square regression technique. Different linear and nonlinear models are used to forecast the sugar future spot prices from the futures prices. The forecasting accuracy of each pair of models is then compared by estimating the corresponding Diebold-Mariano test statistics.

From the estimated forward premiums, it is found that there is more volatility toward the date of maturity for a three-month horizon compared to six-month, and 12-month horizons. It is established that the futures prices of sugar, when used in a model, are able to generate better forecasts for the future spot prices. Moreover, the forecasting accuracy is found to be better for a shorter futures horizon.

The present study is restricted only to sugar. If sufficient data are available, the same study could be extended to other commodities as well. The findings imply that technical traders would benefit by using advanced forecasting techniques along with futures prices of sugar to determine the expected future spot prices.

The findings in this paper suggest that though simple statistical models may be adopted to relate future spot prices to futures prices, more accurate prediction of the price behavior is possible with advanced forecasting methods like the artificial neural network.

The findings will help market participants such as traders to be better informed about the future spot prices and hence get a better deal.

This is one of the first investigations to assess the predictability of commodity futures by employing advanced forecasting techniques.

This paper aims to explore the ways in which religious tourism in India fosters religious tolerance.

The paper uses a conceptual apparatus derived from the basic structure of religious tourism comprising motivation, journey and destination, to understand various aspects of tolerance. Tolerance, with the implicit meaning of diversity and pluralism, is examined at two levels – intra-religion and inter-religion – using field investigations from three Hindu pilgrimage sites, namely, Vrindavan, Tuljapur, Shegaon and review of one Muslim site called Ajmer Sharif. These sites exhibit a range of combinations, sectarian traditions within Hindu and their interactions with others, including Muslims and foreigners.

Each of the sites provides different sets of opportunities for the “others” to get exposed to religious and cultural aspects. It is found that tolerance within the Hindu sects and with non-Hindus from other religious faiths is a function of their engagement with cultural performances and participation in the religious tourism economy in a pilgrimage site.

On a broader level, this paper argues that conceptualising tolerance within a social and cultural sphere helps in a better understanding of tolerance and identifying areas within religious tourism where it can be promoted. A conscious effort to promote tolerance through religious tourism will add value to religious tourism and help it thrive.

To study the key determinants of chronically high inflation in Iran.

Relying on annual data from 1978 to 2019, the authors employ an Auto-Regressive Distributed Lag (ARDL) model and Error Correction Model (ECM) to study the inflationary effects of monetary and fiscal policies as well as exchange rate swings and sanctions intensification.

The authors find that increase in money supply, depreciation of nominal exchange rate, increase in fiscal deficit and intensification of sanctions are among the key drivers of inflation in Iran. Their impact is profound in the long run, but in the short run only money supply and currency depreciation are significant. Also, when exploring the inflation in different components of Consumer Price Index (CPI), we find robust long- and short-run effects from money supply and exchange rate, while the effects of fiscal deficit and sanctions vary across different components.

The authors contribute to the literature by setting apart the long-vs short-run effects of key variables on inflation in Iran. The authors also employ improved measures of fiscal deficit and sanctions that are shown to be of significance in the long run. Lastly, the authors go beyond the aggregate index and examine the variations in different CPI components.

This study aims to analyse the relative prominence of antecedents of digital accounting practices in the micro, small and medium enterprises (MSME) industry. The Ministry of MSME defines the sector as comprising manufacturing enterprises and enterprises rendering services in terms of investment in plant and machinery and the annual turnover. The study is motivated by the rapid usage of digitalisation that has become the driving force guiding organisational development.

This study builds on technological–organisational–environmental framework to analyse the objective. It identifies five technological sub-antecedents, six organisational sub-antecedents and five environmental sub-antecedents. Data were gathered from 202 accounting professionals from MSMEs and academicians. Semi-structured interviews with experts were also conducted to corroborate the analysis of results. Then, the study applied fuzzy analytic hierarchy process to analyse the prominence.

This study finds that the technological antecedent captures the topmost position among all three antecedents, followed by organisational antecedent. They play a critical role in driving digitalisation in accounting practices. Among sub-antecedents, the highest priority is provided to technological accounting infrastructure, followed by cybersecurity precautions, training and allied services for accounting software, support from management and availability of accounting resources.

The study contributes to the scant literature by establishing hierarchy of relevance of different antecedents of digital accounting practices in MSMEs. It offers valuable insights to accounting practitioners and MSME owners/managers. They can pay attention to the prominent antecedents identified in this study to build a robust innovation structure for implementing digitalised accounting practices. The study also has significance to policymakers, specifically when they are more focused on the growth and development of MSMEs.