Ownership characteristics and access to finance:evidence from a survey of large privatised companies in Hungary and Poland

We examine financial constraints and forms of finance used for investment, by analysing survey data on 157 large privatised companies in Hungary and Poland for the period 1998 - 2000. The Bayesian analysis using Gibbs sampling is carried out to obtain inferences about the sample companies' access to finance from a model for categorical outcome. By applying alternative measures of financial constraints we find that foreign companies, companies that are part of domestic industrial groups and enterprises with concentrated ownership are all less constrained in their access to finance. Moreover, we identify alternative modes of finance since different corporate control and past performance characteristics influence the sample firms' choice of finance source. In particular, while being industry-specific, the access to domestic credit is positively associated with company size and past profitability. Industrial group members tend to favour bond issues as well as sells-offs of assets as appropriate types of finance for their investment programmes. Preferences for raising finance in the form of equity are associated with share concentration in a non-monotonic way, being most prevalent in those companies where the dominant owner holds 25%-49% of shares. Close links with a leading bank not only increase the possibility of bond issues but also appear to facilitate access to non-banking sources of funds, in particular, to finance supplied by industrial partners. Finally, reliance on state finance is less likely for the companies whose profiles resemble the case of unconstrained finance, namely, for companies with foreign partners, companies that are part of domestic industrial groups and companies with a strategic investor. Model implications also include that the use of state funds is less likely for Polish than for Hungarian companies.

Endogenous ownership structure:factors affecting the post-privatisation equity in largest Hungarian firms

Using a data set for the 162 largest Hungarian firms during the period of 1994-1999, this paper explores the determinants of equity shares held by both foreign investors and Hungarian corporations. Evidence is found for a post-privatisation evolution towards more homogeneous equity structures, where dominant categories of Hungarian and foreign owners aim at achieving controlling stakes. In addition, focusing on firm-level characteristics we find that exporting firms attract foreign owners who acquire controlling equity stakes. Similarly, firm-size measurements are positively associated with the presence of foreign investors. However, they are negatively associated with 100% foreign ownership, possibly because the marginal costs of acquiring additional equity are growing with the size of the assets. The results are interpreted within the framework of the existing theory. In particular, following Demsetz and Lehn (1985) and Demsetz and Villalonga (2001) we argue that equity should not be treated as an exogenous variable. As for specific determinants of equity levels, we focus on informational asymmetries and (unobserved) ownership-specific characteristics of foreign investors and Hungarian investors.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.

Determinants of civil society influence:the case of international development and humanitarian NGOs in the Czech Republic and Hungary

Accession to the EU has had ambiguous effects on civil society organizations (CSOs) in the East Central European countries. A general observation is that accession has not led to the systematic empowerment of CSOs in terms of growing influence on national policy making. This article investigates the determinants of successful CSO advocacy by looking at international development and humanitarian NGOs (NGDOs) in the Czech Republic and Hungary. Reforms in the past decade in the Czech Republic have created an international development policy largely in line with NGDO interests, while Hungary’s ministry of foreign affairs seems to have been unresponsive to reform demands from civil society. The article argues that there is clear evidence of NGDO influence in the Czech Republic on international development policy, which is because of the fact that Czech NGDOs have been able solve problems of collective actions, while the Hungarian NGDO sector remains fragmented. They also have relatively stronger capacities, can rely on greater public support and can thus present more legitimate demands towards their government.

A cautionary tale of two ‘tigers’: Industrial policy ‘lessons’ from Ireland and Hungary?

This paper draws industrial policy lessons for small Central and Eastern European states through a critical evaluation of recent Irish and Hungarian experiences. The paper outlines a ‘holistic view’ of industrial policy before exploring the experiences of the two economies. Whilst both have managed to ‘do’ policy well in some regards, substantial challenges remain in making FDI attraction the centrepiece of industrial policy, as has been highlighted recently. Overall, the paper suggests that wholesale emulation of the Irish and Hungarian approach is problematic for small open CEE states, and that more balanced approaches to development - and hence industrial policy – are warranted.