The cross-section of currency volatility premia

We identify a global risk factor in the cross-section of implied volatility returns in currency markets. A zero-cost strategy that buys forward volatility agreements with downward sloping implied volatility curves and sells those with upward slopes–a volatility carry strategy–generates significant excess returns. The covariation with volatility carry returns fully explains the cross-sectional variation of our slope-sorted portfolios. The lower the slope, the more the forward volatility agreement is exposed to volatility carry risk.     

Predictive density estimators for daily volatility based on the use of realized measures

The main objective of this paper is to propose a feasible, model free estimator of the predictive density of integrated volatility. In this sense, we extend recent papers by Andersen et al. [Andersen, T.G., Bollerslev, T., Diebold, F.X., Labys, P., 2003. Modelling and forecasting realized volatility. Econometrica 71, 579–626], and by Andersen et al. [Andersen, T.G., Bollerslev, T., Meddahi, N., 2004. Analytic evaluation of volatility forecasts. International Economic Review 45, 1079–1110; Andersen, T.G., Bollerslev, T., Meddahi, N., 2005. Correcting the errors: Volatility forecast evaluation using high frequency data and realized volatilities. Econometrica 73, 279–296], who address the issue of pointwise prediction of volatility via ARMA models, based on the use of realized volatility. Our approach is to use a realized volatility measure to construct a non-parametric (kernel) estimator of the predictive density of daily volatility. We show that, by choosing an appropriate realized measure, one can achieve consistent estimation, even in the presence of jumps and microstructure noise in prices. More precisely, we establish that four well known realized measures, i.e. realized volatility, bipower variation, and two measures robust to microstructure noise, satisfy the conditions required for the uniform consistency of our estimator. Furthermore, we outline an alternative simulation based approach to predictive density construction. Finally, we carry out a simulation experiment in order to assess the accuracy of our estimators, and provide an empirical illustration that underscores the importance of using microstructure robust measures when using high frequency data.     

Estimates regarding demographic developments in Romania by quantitative and qualitative assessments

The enlargement of the European Union and the liberalization of the labour market will substantially influence the demographic indicators in New Member States. The paper aims to identify and synthetically present some factors of influence which triggered by the end of the 20th century and the beginning of the 21st century a series of characteristics defining the changes of the demographic model and structure of population on age brackets. Romania＇s population lost in the period 1992-2007 about 1250 thousands persons, which represents more than the population increase effort by restrictive policies （abortion prohibition） during the period 1977-1992. Also, this paper presents the most important factors that determine the demographic decline beginning in the last decade of the 20th century, both at national and regional levels. For Romania, another phenomenon is represented by the demographic dregs due to the emigration of the feminine population of fertile age. The increase of the share of female population in the emigration flows became more noticeable in the period 2002-2007. Supposing that from those women who migrate, less than 2/3 are going to give birth to children abroad, （1.3 represents the fertility rate at present）, we can estimate, for example, that during the period 2000-2007 Romania has lost more than 69,099 persons. The paper presents some theoretic considerations on the Markov-type model, and the results obtained by using it for studying the development of demographic indicators in Romania, and their forecasting as well.     

Scope economies from rural and urban microfinance services

Microfinance institutions (MFIs) operate in both rural and urban credit markets and provide financial services to the poor not served by commercial banks. MFIs must keep operating costs low to better serve their clients. We evaluate whether MFIs can lower their costs by exploiting economies of diversification from serving both rural and urban markets rather than specializing in only one. We apply a novel method to estimate scope economies that minimizes the well-known “excessive extrapolation” and accommodates MFIs' heterogeneity. Analyzing panel data on MFIs from 105 countries over 2008–2018, we find that about half of loan-only MFIs benefited from diversification and enjoyed scope economies of 16.6% while over two thirds of savings-and-loan MFIs experienced scope diseconomies of 11.7% suggesting advantages from specialization. Over time, the declining magnitudes and the prevalence of scope (dis)economies in both groups suggest that loan-only MFIs have been able to serve costlier marginal clients while savings-and-loan MFIs have been learning and decreasing their scope diseconomies. Stakeholders encouraging the transformation of MFIs into regulated savings-and-loan institutions that serve both rural and urban markets should be aware of the presence of scope diseconomies for that business type and offer adequate support.     

Is the model “loans‐plus‐savings” better for microfinance in Eastern Europe and Central Asia? A propensity score matching comparison

Microfinance institutions are gradually evolving into multiservice organizations offering not only loans but also savings, and other financial and nonfinancial services. We contribute to the literature aimed at identifying how combining credit with savings affects outreach and sustainability in microfinance institutions (MFIs). We apply the propensity score matching method as well as its augmented dose–response version to compare the performance of loans‐plus‐savings MFIs with that of lending‐only in a sample of 710 observations from Eastern Europe and Central Asia. Owing to our unique capital structure data, we control for the use of subsidized capital, which related work ignores while existing evidence points to tradeoffs between subsidies and savings. We find that financial performance and breadth of outreach are positively associated with savings mobilization, while the evidence on depth of outreach points to a possible mission drift.     

Relationship lending and innovation: empirical evidence on a sample of European firms

This paper investigates the impact of relationship lending on innovation (the probability to innovate and the intensity of innovation). Using a unique dataset providing detailed information on bank–firm relationships across European firms, we relate different proxies of relationship lending (soft information, long-lasting relationships, number of banks and share of the main bank) to innovation. We find a very strong and robust positive effect of ‘soft-information-intensive’ relationships, a less robust positive effect of long-lasting relationships and a negative effect of credit concentration as measured by the number of banking relationships. We also find that ‘soft-information-intensive’ relationships reduce credit rationing for innovative firms, while long-lasting relationships seem to favour innovation via other relational channels. These results raise some concern on the impact of screening processes based on automatic procedures, as those suggested by the Basel rules, on firms' capability to finance innovative activities in Europe.     

Managing customer knowledge through the use of big data analytics in tourism research

The use of big data is growing in relevance and importance in tourism management research. Companies operating in this industry are exploiting big data analytics and developing systems to manage customer knowledge and provide the best service in the right place at the right time. This paper aims to provide a systematic literature review to present issues associated with the use of big data in tourism and identify future research directions on the topic. To achieve this aim, this paper develops a citation network analysis methodology to drive the content analysis and explore the content of 109 selected papers. The findings of this review highlight that although there is an increasing number of contributions on the topic, there are yet some issues that require to be further developed. In particular, the paper identifies research gaps and consequent research questions that represent an agenda for both researchers and practitioners.     

Subsidiary’s Network Competence: Finnish Multinational Companies in Russia

We provide clear insights into the key foreign direct investment obstacles for the manufacturing sector in FYR of Macedonia, an EU candidate country. The survey results, based on data for 79 manufacturing companies, revealed that the investors in this particular sector perceive the bureaucratic and administrative constraints, corruption and bribery, and the lack of law enforcement as three major investment obstacles. Furthermore, we found that the perception of the investment obstacles largely differ depending on the industry the companies operate in, the country of origin, and the export orientation. Therefore, we recommend a tailor-made approach in pursuing the national investment promotion policies and strategies.