Christian Weiner’s research while affiliated with Humboldt-Universität zu Berlin and other places

This paper investigates industry classification systems. During the last 50 years there has been a considerable discussion of problems regarding the classification of economic data by industries. From my perspective, the central point of each classification is to determine a balance between aggregation of similar firms and differentiation between industries. This paper examines the structure and content of industrial classification schemes and how they affect financial research. I use classification systems provided by the Worldscope and the Compustat database. First, this study gives a detailed description of the structure and methodology of industrial classification systems and the relevance in leading finance and accounting journals. Second, I construct a benchmark classification system to measure the performance of different systems and provide evidence that some systems a more homogeneous in terms of value drivers than others. Third, I examine how multiple valuation is influenced by industry classification and show that the results vary significantly for different systems.

This paper documents the conglomerate discount for all available German firms and the DAX 30 firms in detail. It shows a moderate discount of about 0.06 based on German comparable firms and of about 0.20 for a combined sample of German and European peer groups. I further examine the relationship between the discount and industry concentration as well as uncertainty of valuation. Finally, I document that corporate governance behavior affects the conglomerate discount.

With this study we are the first to systematically compare today’s two major counterparts as a source of accounting and financial data for researchers: Compustat North America by Standard & Poor’s and Worldscope by Thomson Financial. This investigation is conducted for U.S. and partly Canadian data over an extensive period from 1985 to 2003. We examine more than 650 data items available in both databases and address the question of whether or not the decision for one or the other source may have an impact on the outcome of research projects. It is probably commonly assumed that this impact is minor, but it also leaves room to question certain results. We show that the use of both databases should lead to comparable results, but also find that if, e.g. a size bias, is not treated with care the quality of results may differ considerable. Furthermore after 1998 the number of firms covered by Worldscope exceeds the one covered by Compustat by about one fourth.

With this study we are the first to systematically compare today’s two major counterpartsas a source of accounting and financial data for researchers: CompustatNorth America by Standard and Poor’s and Worldscope by Thomson Financial. Thisinvestigation is conducted for U.S. and partly Canadian data over an extensive periodfrom 1985 to 2003. We examine more than 650 data items available in bothdatabases and address the question of whether or not the decision for one or theother source may have an impact on the outcome of research projects. It is probablycommonly assumed that this impact is minor, but it also leaves room to questioncertain results. We show that the use of both databases should lead to comparableresults, but also find that if, e.g. a size bias, is not treated with care the quality ofresults may differ considerable. Furthermore after 1998 the number of firms coveredby Worldscope exceeds the one covered by Compustat by about one fourth.

This paper investigates which comparables selection method generates the most precise forecasts when valuing European companies with the enterprise value to EBIT multiple. We also consider the USA as a reference point. It turns out that selecting comparable companies with similar return on assets clearly outperforms selections according to industry membership or total assets. Moreover, we investigate whether comparables should be selected from the same country, from the same region, or from all OECD members. For most European countries, choosing comparables from the 15 European Union member states yields the best forecasts. In contrast, for the UK and the US, comparables should be chosen from the same country only.

This paper investigates which comparables selection method generates the most precise forecasts when valuing European companies with the enterprise value to EBIT multiple. We also consider the USA as a reference point. It turns out that selecting comparable companies with similar return on assets clearly outperforms selections according to industry membership or total assets. Moreover, we investigate whether comparables should be selected from the same ountry, from the same region, or from all OECD members. For most European countries, choosing comparables from the 15 European Union member states yields the best forecasts. In contrast, for the UK and the US, comparables should be chosen from the same country only.