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This paper examines India's socio-economic attributes and different financial dimensions of financial inclusion (FI).

The paper uses a principal component analysis (PCA) to build indexes related to financial dimensions. It applies the logistics regression model and the Fairlie decomposition method to determine India's socio-economic and financial characteristics of FI.

Based on the logistic regression, socio-economic factors like age, gender, marital status, level of education and religion have an impact on FI. The use of financial institutions has positively contributed to the probability of FI, while the low proximity of financial service providers retards the process of FI. Fairlie decomposition concludes regional disparity and gender disparity in FI; however, the rural–urban gap in FI is not captured by the variables included in the study. The main reasons for the discrepancy are lack of education, financial literacy, the proximity of financial service providers and lack of financial institutions.

This paper makes two important contributions: first, it presents a micro-level analysis of FI across the socio-demographic strata of India, and second, it demonstrates the regional, rural–urban and gender disparity in FI in India.

A case‐based research approach is used to illustrate the power of modelling manufacturing performance measures and to help develop insights into the nature and problems evident when attempting to use simulation across different enterprise sectors. The research methodology used considered three specific companies, each with distinctive characteristics and attributes; a small to medium enterprise, a medium to large enterprise and a large enterprise. From a cross‐case analysis of the use of discreet‐event (DE) simulation when applied in these instances, the research attempts to develop policy implications that will provide a better understanding of how simulation studies should be approached across different manufacturing enterprises.

The purpose of this paper is to better understand the origins and forms of organised crime and develop policy conclusions for deterrence efforts.

The paper begins by contrasting two theories of justice and evaluating their merits with respect to organised crime. Sociological and economic origins of organised crime, its institutional forms and law enforcement responses are identified. Research into the theory of organised crime is complemented by historical examples from Italy and the USA.

The paper finds that analysis of organised crime must go beyond the institutions of the state and its social contract with the populace. It must recognise relevant social and economic causative factors, and include institutional and rational choice analysis in order to better understand the nature of criminal organisations.

Policy implications for deterrence efforts include support for the establishment of ad hoc enforcement agencies, infiltration of criminal networks, targeting the proceeds of crime, and statutes allowing prosecution for conspiracy or a broad range of racketeering offences.

The paper presents a conceptual view of organised crime which provides useful policy conclusions and a basis for future research.

The purpose of this paper is to present a new methodology to assess the outward connectivity among regional economies in the European Union (EU) and derives policy lessons for the design of regional innovation and competitiveness-enhancing strategic frameworks, with particular reference to research and innovation strategies for smart specialisation (RIS3).

The authors study the network of inter-regional trade flows in the EU25 in the year 2007. Trade data are taken from the PBL Netherlands Environmental Assessment Agency database and mapped onto weighted directed networks in which the nodes represent regions and the links are flows of goods. The authors measure several structural characteristics of the networks, both global properties and centrality indicators describing the position of individual regions within the system.

European regions appear to be mostly integrated in the European single market. Strengths and weaknesses of individual regions are discussed based on rankings obtained from network centrality indicators. Specific policy implications in the context of RIS3 are derived in the case of the Spanish region of Andalusia.

The authors show the potential of the methodology for providing a new family of indicators of the external connectivity of regional economies that can be used by regions wishing to develop their own RIS3 for 2014-2020, as required by the EU in the context of the new cohesion policy framework.

The characteristics of a EU-wide inter-regional network of trade flows are obtained and thoroughly discussed for the first time. A unique and original instrument suitable for inter-regional comparison is developed and tested.

This study quantifies empirically the induced impact of income distribution and consumption expenditure on the structures of agriculture production of Nigerian economy.

The study calibrates an extended input-output model on a social accounting matrix (SAM) for Nigeria for the year 2010. Moreover, the study conducts a dispersion analysis to identify the key agriculture sectors/subsectors both in exogenous and endogenous setup.

This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup. The comparison of both findings confirms that the composition of income distribution and consumption expenditure significantly influences the composition and the aggregated and disaggregated order of structure of agriculture production.

Knowledge of interindustry connections is vital in policy implications since the policy makers prefer strongly interconnected sectors to the sectors with poor industry linkages. These connections are estimated as forward and backward linkages, which provide indices to set the criteria for key sectors identification. This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup.

By considering the rapid and continuous increase of housing prices in Turkey recently, this study aims to examine the determinants of the residential property price index (RPPI). In this context, a total of 12 explanatory (3 macroeconomic, 8 markets and 1 pandemic) variables are included in the analysis. Moreover, the residential property price index for new dwellings (NRPPI) and the residential property price index for old dwellings (ORPPI) are considered for robustness checks.

A quantile regression (QR) model is used to examine the main determinants of RPPI in Turkey. A monthly time series data set for the period between January 2010 and October 2020 is included. Moreover, NRPPI and ORPPI are examined for robustness.

Predictions for RPPI, NRPPI and ORPPI are carried out separately at the country (Turkey) level. The results show that market variables are more important than macroeconomic variables; the pandemic and rent have the highest effect on the indices; The effects of the explanatory variables on housing prices do not change much from low to high levels, the COVID-19 pandemic and weighted average cost of funding have a decreasing effect on indices while other variables have an increasing effect in low quantiles; the pandemic and monetary policy indicators have a negative and significant effect in low quantiles whereas they are not effective in high quantiles; the results for RPPI, NRPPI and ORPPI are consistent and robust.

The results of the study emphasize the importance of the pandemic, rent, monetary policy indicators and interest rates on the indices, respectively. On the other hand, focusing solely on Turkey and excluding global variables is the main limitation of this study. Therefore, the authors encourage researchers to work on other emerging countries by considering global variables. Hence, future studies may extend this study.

The COVID-19 pandemic and market variables are determined as influential variables on housing prices in Turkey whereas macroeconomic variables are not effective, which does not mean that macroeconomic variables can be fully ignored. Hence, the main priority should be on focusing on market variables by also considering the development in macroeconomic variables.

Emerging countries can make housing prices stable and affordable, which will increase homeownership. Hence, they can benefit from stability in housing markets.

The QR method is performed for the first time to examine housing prices in Turkey at the country level according to the existing literature. The results obtained from the QR analysis and policy implications can also be used by other emerging countries that would like to increase homeownership to provide better living conditions to citizens by making housing prices stable and keeping them under control. Hence, countries can control housing prices and stimulate housing affordability for citizens.

The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

This paper analyzes the logistics patterns of Korea to elaborate the strategies of Korean Free Economic Zones (FEZs) in relation to Northeast Asian logistics hubs. As the surface transportation of Korea, China and Japan, is cut off by geographical factors and by political border lines, this paper confines the analysis scope to air and maritime transportation.

From the analysis of air and maritime transportation in Northeast Asian region, this paper tries to understand the cargo flow from and to Korean airports and ports by region and by commodity types, and thereby, to identify the main counterpart regions of trade by commodity types and by modes. The policy implications for the development strategy of Korean FEZs (Incheon, Busan, and Gwangyang) are described from those analyses.

In recent years Adrian Ziderman has applied the tools of cost‐benefit analysis to the evaluation of government training and his latest paper analyses the regional location of Government Training Centres (GTCs). Although he is kind enough to suggest that his paper was stimulated by an earlier paper of my own, he has nevertheless been severe in his criticism of me. He claims that I eschew the cost‐benefit approach because I find it wanting. Furthermore, he argues that the alternative criteria that I suggest for evaluating the regional location of GTC capacity are seriously deficient and give rise to policy recommendations which must be “treated with caution”. Here I attempt to meet Ziderman's criticisms of my earlier paper and in passing I comment very briefly upon the paper by Nicholas Adnett which is also critical of the main policy implications of my analysis.

The aim of the study is to analyse the value creation processes in multifunctional wineries. Specifically, the paper poses the following research questions: can the creation of public goods (i.e. multifunctionality) open up new paths of value creation for wineries? And if so, can multifunctionality be only compensated through policy instruments? Or, is there a form of market compensation?

An empirical analysis was carried out on selected wineries that sell directly. The study implemented the “value portfolio” model that identifies specific variables, both internal and external to the farm, which contribute to the value creation. The methodology adopted is a structural equation modeling (SEM) approach that offers a theoretical basis for developing an understanding of the relationships between group of variables.

The empirical analysis confirms the assumptions developed. Indeed, the localized public goods generated by multifunctional farms can benefit from compensation on the market through the direct sale of products and services.

The study’s findings are quite innovative in the field of agricultural economics and open the way for interesting policy implications.