Explaining the demand for structured financial products: survey and field experiment evidence

In many countries structured investment products are popular among retail investors. We explain the demand for these products using unique field data where we let subjects freely design their “favorite” structured product. Results suggest that the supply with capital protected products (guarantee certificates) might indeed be demand-driven. This does not seem to be the case for other product categories where marketing and sales practices might play a more important role. In a survey among financial practitioners we find furthermore that a demand for capital protected products can be explained by loss aversion and saving motifs, e.g. for buying a house.     

CDS and rating announcements: changing signaling during the crisis?

In parallel with the development of credit derivatives market, researchers have begun to explore the relationship between Credit Default Swap (CDS) market and rating events. Many papers, via classical event-study methodology, show that CDS market is able to signal future negative rating events announced by credit rating agencies. In this work, we incorporate into the event-study methodology the ability of Markov switching models in modeling state-dependent means and variances. This approach allows to get over the drawbacks of the classical methodology, which ignores the heteroscedasticity and volatility clustering often affecting financial time series. The proposed methodology is applied to study the reactions of CDS quotes to reviews for downgrading and effective downgradings announced by the three major credit rating agencies (Fitch Ratings, Moody’s, Standard and Poor’s), in order to examine if and to what extent CDS market anticipates announcements related with a company’s creditworthiness. The analysis, focusing mainly on volatility, is performed on two periods, 2004–2006 and 2007–2009, in order to verify whether a change in the signaling power of CDS quotes can be ascribed to recent financial turmoils.     

Innovation in family firms: an empirical analysis linking organizational and managerial innovation to corporate success

Family firms play a significant role in national economies worldwide, accounting e.g. for 85% of all enterprises in the OECD countries as well as for the majority of companies in Central Europe. Previous scholarly research on family firms has mostly focused on the question of how they differ from public corporations, describing family firms as being more conservative, less risk-raking, or reluctant to grow—in sum, as being less entrepreneurial than their non-family counterparts. Similarly, the existing literature often criticizes the lack of innovation in family firms. But since innovation has long been discovered as one of the key drivers to company success, it is surprising that its role in family firms has been mostly neglected in existing academic research so far. The aim of this article is therefore to study the role of (managerial and organizational) innovation in family firms compared to non-family firms on the basis of an empirical survey of 533 companies from Finland, using structural equation modelling (MPlus) for the statistical analyses.     

Extreme ranking analysis in robust ordinal regression

We extend the principle of robust ordinal regression with an analysis of extreme ranking results. In our proposal, we consider the whole set of instances of a preference model that is compatible with preference information provided by the DM. We refer to both, the well-known UTA^GMS method, which builds the set of general additive value functions compatible with DM's preferences, and newly introduced in this paper PROMETHEE^GKS, which constructs the set of compatible outranking models via robust ordinal regression. Then, we consider all complete rankings that follow the use of the compatible preference models, and we determine the best and the worst attained ranks for each alternative. In this way, we are able to assess its position in an overall ranking, and not only in terms of pairwise comparisons, as it is the case in original robust ordinal regression methods. Additionally, we analyze the ranges of possible comprehensive scores (values or net outranking flows). We also discuss extensions of the presented approach on other multiple criteria problems than ranking. Finally, we show how the presented methodology can be applied in practical decision support, reporting results of three illustrative studies.     

Financial instruments used by Polish municipalities in response to the first wave of COVID-19

Public Organization Review - Studies on the influence of COVID-19 on municipalities are scarce, although it was precisely municipalities that stood in the first line of combat. It is important to...     

Neighborhood context and racial differences in early adolescent sexual activity

Evidence suggests that African American youths initiate sexual activity at earlier ages than do European American or Latino youths. Using data from a multilevel study in Chicago, we developed and tested a neighborhood-based model of the timing of first adolescent intercourse that emphasizes the impact of neighborhood structural disadvantage and collective efficacy on early sexual activity (at ages 11 to 16). In turn, we explored the extent to which neighborhood factors account for racial differences in the timing of first intercourse. The findings indicate that demographic background, family processes, peer influences, and developmental risk factors account for about 30% of the baseline increased likelihood of early sexual onset for African American youths compared with European American youths. However, a significant residual racial difference remained even after we considered a host of micro-level factors. Neighborhood-level concentrated poverty largely explained this residual racial difference. Collective efficacy also independently contributed to the delay of sexual onset. No significant baseline difference in age of sexual initiation was found between Latino and European American youths.     

Effect of family structure on life satisfaction: australian evidence

How do family arrangements affect subjective well-being? We investigate this issue using data pooled from the IsssA and HILDA, both large, representative national samples of Australia (pooled n=38 447). Our regression analysis of cross-sectional and panel data examines how large are the differences in life satisfaction according to marital status and cohabitation. We find that women and men in formal marriages experience higher levels of life satisfaction than do people in other family arrangements. Moreover, both multiple tests in the cross-section, and tests controlling for prior happiness in the panel analysis, suggest that this is a causal relationship. Aggregating up the levels of life satisfaction generated by different marriage and cohabitation arrangements across a lifetime, suggests that a life-long marriage is the most satisfying. Early divorce followed by an enduring second marriage is little worse (because little time is spent outside the married state). But divorce without remarriage, or long lasting cohabitation without formal marriage, reduce the lifetime sum of subjective well-being by 4–12% for both women and men.     

Inequality and welfare evaluation of heterogeneous income distributions

This paper establishes the principles that should govern the welfare and inequality analysis of heterogeneous income distributions. Two basic criteria – the equity preference condition and the compensation principle – are shown to be fundamentally incompatible. The paper favours the latter, thereby vindicating the traditional method of dealing with heterogeneous samples. However, inequality and welfare comparisons will usually be well defined only if equivalent incomes are obtained using constant scale factors; and researchers will need to distinguish clearly between inequality of nominal incomes and inequality of living standards. Furthermore, household observations must always be weighted according to family size.