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This paper investigates the role of public expenditures and general government debt in microfinance performance. Our panel regression applied to the data of microfinance institutions (MFIs) in Latin America and the Caribbean confirms the high significance of public finance for the growth of MFIs, especially for the size of their total assets and for their yield on gross loan portfolio. Moreover, the results indicate that MFIs, operating in the country with higher growth of GDP, are characterized by higher rate of social efficiency. The positive influence on microfinance is besides public finance also associated with a growth of rural population or an economy openness of the given country.

Poland aims at stimulating the market to reach a target of 50,000 plug-in and battery electric vehicles by 2020. However, as in other Eastern European countries, the market penetration stays very low. In Poland, there were only 475 battery electric vehicles and 514 plug-in electric vehicles registered in 2017. To identify effective support measures, this paper examines the preferences of Polish consumers for three types of electric vehicles: battery, hybrid, and plug-in hybrid vehicles. We use a discrete choice experiment to estimate the willingness to pay of a representative sample of consumers intending to buy a car in Poland. We find that electric vehicles are significantly less preferred than conventional cars, even under a public programme that would enable slow-mode charging in places where respondents usually park. We quantify the marginal willingness to pay for increasing the driving range, reductions in charging time, the availability of fast-mode charging stations, and the provision of policy incentives. The novelty of the paper lies in presenting a scenario with the slow-mode and availability of several levels of fast-mode charging stations and examination of the extent to which the heterogeneity of consumer preferences is driven by place of residence (urban, suburban, rural), intention to buy a new versus a used car, and the annual mileage. This is also the first discrete choice experiment on electric vehicles conducted in Eastern Europe. To stimulate the electric vehicle market, we recommend a pricing policy that affects the operating costs and other incentives along with an effective up-front price incentive scheme.

We describe the export credit agencies in the Czech Republic and the export promotion strategy of the Czech government. The policy part of the paper is focused on the interac- tion of government owned and supported Czech Export Bank with the Czech commercial banks. We argue that the major market share of Czech Export Bank in export credit market may be explained by a number of factors in addition to the competitive advantage provided by lower pro�t margins of Czech Export Bank. These factors may be grouped into strategic factors related to competition among commercial banks and into factors based on Czech Export Bank being state owned specialized export bank as opposed to private general banks.

The corporate bankruptcies legal frameworks and their economic implications are compared for two pairs of post-communist countries (Czech Republic and Slovakia and Croatia and Serbia) originating from common federative republics. Their process of gradual divergence from the common legal and economic framework is shown. All four countries are identified as creditor friendly (Czech Republic, Croatia, Serbia) or neutral countries (Slovakia). The possibilities of further development of bankruptcy proceeding in these countries are outlined.

Abstract We replicate the study of Tabak & Cajueiro (2007): “Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility” published in Energy Economics 29, pp. 28-36. The results have been mostly confirmed. Specifically, we have confirmed that the crude oil markets efficiency could be rejected up till approximately 1994 and this holds for both studied crude oil commodities — Brent and WTI. Analyzing an extended dataset up till June 2017, we find that the markets remained efficient (at least with respect to long-range dependence) until the outbreak of the Global Financial Crisis in 2008. This is confirmed by all three applied methods — the rescaled range analysis used in the original study, and the detrended fluctuation analysis and the Geweke-Porter-Hudak estimator which were added to strengthen validity of the results. The markets returned back to efficiency around 2012 and remained there until 2015 when the Hurst exponent started another rally and stayed rather high until the end of the examined sample. Comparing the two markets, the Brent crude oil shows stronger signs of inefficiency during the inefficient periods compared to the WTI crude oil. This is in hand with the results reported in the original study. Apart from rerunning the analysis on an extended dataset and using two additional methods, we also provide a firmer validity check using the moving-block bootstrap procedure, which outperforms the original shuffling procedure in the provided forecasting study.

The aim of paper is to determine whether macroeconomic development and the size of banking sector affect the range of external funding and consequently the importance of these debt sources for microfinance performance. Our findings reveal that the growth of external sources is positively influenced by economic grow, level of corruption, unemployment or under certain conditions by the development of banking sector, as well. Likewise, their presence can have a positive impact on the number of clients, portfolio quality, margin or cost policy of MFIs. The opposite effect can appear if the ratio of external funding to total assets increases over time.

The paper contributes to the rare literature modeling term structure of crude oil markets. We explain term structure of crude oil prices using dynamic Nelson-Siegel model, and propose to forecast them with the generalized regression framework based on neural networks. The newly proposed framework is empirically tested on 24 years of crude oil futures prices covering several important recessions and crisis periods. We find 1-month, 3-month, 6-month and 12-month-ahead forecasts obtained from focused time-delay neural network to be significantly more accurate than forecasts from other benchmark models. The proposed forecasting strategy produces the lowest errors across all times to maturity.

In this paper we propose a regularization approach for network modeling of German power derivative market. To deal with the large portfolio, we combine high-dimensional variable selection techniques with dynamic network analysis. The estimated sparse interconnectedness of the full German power derivative market, clearly identify the significant channels of relevant potential risk spillovers. Our empirical findings show the importance of interdependence between different contract types, and identify the main risk contributors. We further observe strong pairwise interconnections between the neighboring contracts especially for the spot contracts trading in the peak hours, its implications for regulators and investors are also discussed. The network analysis of the full German power derivative market helps us to complement a full picture of system risk, and have a better understanding of the German power market functioning and environment.