This article analyzes the determinants of the European venture capital market, extending the equilibrium model from Jeng and Wells (2000). Our empirical model includes many of the determinants already tested in previous studies. In addition, we test whether the unemployment rate, the trade sale divestment and the price/book ratio are important factors in explaining venture capital. We use aggregated data from the European venture capital market as well as macroeconomic data, to estimate panel data models, with fixed and random effects. The random effects models revealed to be the most adequate. Our results confirm the importance of some of the already known factors and show that the unemployment rate and trade sale divestments are important determinants in the European venture capital market.

Purpose: This study aims to compare the prediction accuracy of traditional distress prediction models for the firms which are at an early and advanced stage of distress in an emerging market, Pakistan, during 2001–2015. Design/methodology/approach: The methodology involves constructing model scores for financially distressed and stable firms and then comparing the prediction accuracy of the models with the original position. In addition to the testing for the whole sample period, comparison of the accuracy of the distress prediction models before, during, and after the financial crisis was also done. Findings: The results indicate that the three-variable probit model has the highest overall prediction accuracy for our sample, while the Z-score model more accurately predicts insolvency for both types of firms, i.e., those that are at an early stage as well as those that are at an advanced stage of financial distress. Furthermore, the study concludes that the predictive ability of all the traditional financial distress prediction models declines during the period of the financial crisis. Originality/value: An important contribution is the widening of the definition of financially distressed firms to consider the early warning signs related to failure in dividend/bonus declaration, quotation of face value, annual general meeting, and listing fee. Further, the results suggest that there is a need to develop a model by identifying variables which will have a higher impact on the financial distress of firms operating in both developed and developing markets.

Purpose The purpose of this paper is to analyse the impact of gender (F/M), at the management level, on the family company’s performance. Design/methodology/approach Company size, age, region and business sector were used as control variables in order to confirm the adjustment of the model to the theory. GMM dynamic panel models were used in order to control for: endogeneity; time-invariant characteristics; possible collinearity between independent variables; effects from possible omission of independent variables; elimination of non-observable individual effects; and the correct estimation of the relationship between the dependent variable in the previous and current periods. The study used data from 199 Portuguese family companies, from 2006 to 2014. Findings The results confirm the hypothesis from corporate governance literature, which argues that board diversity is potentially positively related to firm performance, showing that the presence of a female element in family firms’ direction has positive impacts on their performance, compared to those with only male elements. Also, the results show that region and sector of activity are factors influencing family firm performance. Finally, the study confirms that company size and age are variables helping to explain these companies’ life-cycle. Originality/value The study contributes to the literature on family firms regarding the effect of gender on family firm performance. The use of dynamic panel data models will make a strong contribution to this, as the problem of endogeneity is dealt with correctly here through using these models, and the possible collinearity between independent variables and correct estimation of the relationship between the dependent variable in previous and current periods.

This paper examines the impact of microcredit on poverty reduction, controlling for income and its distribution, employment, inflation rate and education, in 11 developing countries in southeast Asia. Static and dynamic panel data models were used in the growth-poverty model initially suggested by Ravallion (1997), with data from 2007 to 2016. The results indicate that microcredit reduces poverty (as measured by the headcount index, poverty gap and squared poverty gap). They also indicate that employment and education can reduce the level of poverty.

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