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The purpose of this paper is to investigate the possible relationship of religion and culture with the social capital in a particular region.

The data of 85 regions from 26 European countries are analysed. Regression analysis is used for analysing cultural dimensions, religion-related aspects and the communist past as possible factors of social capital components. In addition, graphic analysis is used for the generalisation of the results.

The results from both the regression and graphic analyses indicate that cultural dimensions capture the possible reasons for different levels of social capital better than religion-related aspects or the division according to the communist background.

Conclusions can be drawn only for the European regions analysed. Data were not available for regions in all European countries and including control variables was limited by the data availability.

When intending to develop policies for increasing social capital, the culture of a particular region should be assessed in order to predict the success of the policies.

The novelty of this study lies in including cultural dimensions based on Hofstede’s concept to the set of possible factors determining the level of social capital in a region.

With growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate markets for the USA and a select group of seven European developed economies under a cross-country framework in crisis and boom market conditions. Dynamic interdependence is related to four measures of market linkages of “correlation, spillover, connectedness and causality”.

This study adopts a four-step investigation. The authors first estimate “time-varying variance–covariance spillovers and implied correlations” modeled with the bivariate BEKK-MGARCH methods. Second, the methods of Diebold and Yilmaz (2012, 2014) measure the conditional volatility spillover-connectedness effects across the corporate equity and public real estate markets based on a decomposition of the forecast error variance. Third, the authors implement nonlinear bivariate and multivariate causality tests to understand the lead-lag dynamics of the two asset markets' returns, volatilities and net directional volatility connectedness across different sample periods. Finally, the authors conclude the study by providing a portfolio hedging analysis.

The authors find that corporate equity and public real estate are moderately interdependent to the extent that their diversification benefits increases in the longer term. Moreover, the authors find increased corporate equity-public real estate causal dependence of the market groups of the European and international portfolios during the GFC and INTERCRISIS periods. The nonlinear causality test findings indicate that the joint information of asset markets can be a useful source of prediction for future innovation of market risks. Additionally, policy makers may also be able to employ conditional volatility and volatility connectedness as two other measures to manage market stability in the cross-asset market dependence during highly volatile periods.

One major take away from this academic research is since international portfolio investors are not only concerned the long-term price relationship but also the correlation structure and volatility spillover-connectedness, the conditional BEKK modeling, generalized risk connectedness analysis and nonlinear causal dependence explorations from this multi-country study can shed fresh light on the nature of market interdependence and magnitude of volatility connectedness effects in a multi-portfolio framework.

The hedging performance analysis for portfolio diversification and risk management indicates that industrial stocks (“pure” equities) are valuable assets that can improve the hedging performance of a well-diversified corporate equity-public real estate portfolio during crisis periods. For policymakers, the findings provide important information about the nature of causal links and predictability during the crisis and asset-market boom periods. They can then equip with this information to manage and coordinate market stability in cross corporate equity-real estate relationships effectively.

Although traditional research has in general reported at least a moderate degree of relationship between the two asset markets, investors' knowledge of stock-public real estate market linkage is somewhat inadequate and confine mostly to broad stocks (i.e. stocks that are exposed to public real estate influence) in a single-country context. In this paper, the authors examine the interdependence dynamics in a multi-country (multi-portfolio) context. A clear understanding their changing market relationships in a multi-country context is of crucial importance for portfolio investors, financial institutions and policy makers. Moreover, since the authors use an orthogonal stock market index, the authors allow global investors to understand the potential diversification benefits from stock markets that are beyond the public real estate market under different market conditions.

This study investigates the relationship between national culture and the country level of firms' digitalisation, by applying Hofstede's cultural framework to the European Union member states. Although many studies have observed the impact of national culture on firms' innovation and information and communication technology (ICT) adoption, there have been no analyses of how cultural dimensions impact firms' digitalisation at the country level. This study intends to fill that gap.

Using a pooled ordinary least square (OLS) model, this study analyses data from 27 European countries over the period from 2014 to 2018.

The results suggest the existence of a negative, significant, relationship between both masculinity and uncertainty avoidance, and the country level of firms' digitalisation. Indulgence is found to positively and significantly influence a country's level of digitalisation. Contrary to expectations, this study indicates a negative, significant, relationship between individualism and the degree of digitalisation. Power distance is found to have no significant impact.

This study contributes to the literature by showing how a country's various cultural dimensions help or hinder the level of firms' digitalisation in that country. Theoretical and managerial implications are presented, including suggestions for future research.

The purpose of this paper is to determine the relationship between inflation, inflation uncertainty, growth and growth uncertainty for Australia.

Multivariate EGARCH models has been used to estimate the relationship between inflation, inflation uncertainty, growth and growth uncertainty for Australia.

Using quarterly data in multivariate EGARCH models, this study finds that both inflation uncertainty and output uncertainty have negative and significant effects on output growth. The paper also finds that, while inflation uncertainty has a positive and significant effect on inflation, output uncertainty has a negative and significant effect on inflation. The study uses a newly constructed oil price dummy as a control variable and finds that oil price changes significantly increase inflation uncertainty. The study also finds that inflation uncertainty and the inflation level have both declined since the adoption of a formal inflation‐targeting monetary policy in Australia.

Multivariate EGARCH model can be used to estimate the effects of inflation, inflation uncertainty, growth and growth uncertainty for cross‐country analysis.

This is the first study of the effect of inflation uncertainty and growth uncertainty on inflation and growth in Australia using a newly constructed oil price dummy in a multivariate EGARCH framework.

The purpose of this paper is to provide a systematic and comprehensive review of the existing literature on the determinants of firms reporting practices.

Following a systematic method, the sample literature of 135 studies was collected from the Scopus database. These studies were evaluated in terms of the theoretical lenses applied in the literature, yearly trend, regional distribution, research settings and prior studies finding to provide some recommendations for further research.

The investigation revealed that the literature was more interested in the agency theory in investigating the drivers of voluntary reporting such as company size, age, leverage, liquidity, profitability, corporate governance and ownership structure. Although firm-specific determinants were the most examined in the previous studies, however, the result is still inconclusive. Also, limited work was found on the country-related factors, while internal audit impact has yet to be explored.

Being the first of its kind, this research provides a comprehensive review of the current research landscape on the drivers of environmental or social disclosure and highlights several interesting opportunities for future research.

Several lessons learnt from a Bayesian analysis of basic macroeconomic time-series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic models, to forecasting with near-random walk models and to clustering of several economic series in a small number of groups within a data panel. Two canonical models are used: a linear regression model with autocorrelation and a simple variance components model. Several well-known time-series models like unit root and error correction models and further state space and panel data models are shown to be simple generalizations of these two canonical models for the purpose of posterior inference. A Bayesian model averaging procedure is presented in order to deal with models with substantial probability both near and at the boundary of the parameter region. Analytical, graphical, and empirical results using U.S. macroeconomic data, in particular on GDP growth, are presented.

China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries.

This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants.

Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India.

The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth.

Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

Understanding and defining the characteristics of environmentally conscious or concerned consumers has received attention from academic researchers, commercial sector, and policy makers. The purpose of this paper is to identify distinct market segments in three countries (China, Germany, and Turkey) based on several “green” attitude and behavior variables.

A survey was administered in three countries, yielding a total of 1,415 valid survey responses.

Four clusters, ranging from the “greenest” to the “least green” segment, were identified and characterized for each country. Inter- and intra-country similarities and differences are discussed. Existence of cross-national segments was confirmed.

There is a potential gap between actual behavior and reported behavior.

The segment profiles can be valuable to firms, particularly to those competing in multinational markets. By delineating areas of similarity among international diversity, enterprises can develop effective global marketing strategies.

Understanding market segments in this respect is critical for policy makers who try to focus their policies that seek to promote green consumption.

This is the first study that uses cross-national data for segmenting the market based on “green” criteria, to the authors’ knowledge. Methodologically, the paper uses techniques and instruments that have not been used in this context before.