Upper and Lower Bound Estimates of Inequality of Opportunity: A Cross-National Comparison for Europe

I provide lower and upper bound estimates of inequality of opportunity (IOp) for 32 European countries, between 2005 and 2019. Lower bound estimates use machine learning methods to address sampling variability. Upper bound estimates use longitudinal data to capture all-time invariant factors. Across all years and countries, lower bound estimates of IOp account from 6 percent to 60 percent of total income inequality, while upper bound estimates account from 20 percent to almost all income inequality. On average, upper bound IOp saw a slight decrease in the aftermath of the Great Recession, recovering and stabilizing at around 80 percent of total inequality in the second half of the 2010s. Lower bound estimates for 2005, 2011, and 2019 show a similar pattern. My findings suggest that lower and upper bound estimates complement each other, corroborating information and compensating each other's weaknesses, highlighting the relevance of a bounded estimate of IOp.     

The external cost of prostitution: Evidence from shutting down red light districts in the Netherlands

This article examines the value of externalities created by the presence of sex workers in the city. Although a legal paid-sex industry might contribute to the economy, it may also generate negative externalities. To identify the net impact of overt prostitution, we estimate changes in housing prices following the sudden closure of the two red light districts (RLDs) in the Dutch City of Utrecht. Our results show that the capitalization effect of RLDs is spatially heterogeneous. While some areas are unaffected, others are up to 12% more expensive if far from operating brothels. Interestingly, though, evidence also shows that RLDs increase local employment in a variety of sectors. All the aversion to living near RLDs is instead explained by petty crimes.     

Neural networks for estimating Macro Asset Pricing model in football clubs

The recent crisis caused by COVID-19 directly affected consumption habits and the stability sof financial markets. In particular, the football industry has been hit hard by this pandemic and therefore has more volatile stock prices. Given this new scenario, further research is needed to accurately estimate the value of the shares of football clubs. In this paper, we estimate an asset pricing model in football clubs with different compositions of risk nature using non-linear techniques of artificial neural networks. Usually, asset pricing models have been estimated with linear methods such as ordinary least squares. Our results show a precision higher than 90% for all the estimated models, which far exceeds those shown by linear methods in the previous literature. We find that the residual represents about 40% of the variance of the price-dividend ratio. Long-term risks follow in importance, and above all, the habit component and its behaviour in the face of changes. The importance of the residual component exists due to a low correlation between the asset price and consumer behaviour, but to a much lesser extent than that shown in previous studies. The estimation carried out with artificial neural networks, both the Deep Learning methods and especially the Quantum Neural Network, opens up new possibilities to estimate more efficiently the pricing of financial assets in the football industry.     

Do related party transactions affect family firm valuations?

We examine the likelihood and value relevance of related party transactions in family firms. Based on an extensive hand-collected sample, we find that founder-led family firms are more likely to enter into related party transactions than other firms. We also find that the founder-led family firm valuation premium is reduced when these firms disclose related party transactions, especially opportunistic related party transactions. We also examine the significant change in related party transaction reporting regulations enacted in 2006 and find that it led to a decline in the number of value-decreasing related party transactions for founder-led family firms. We find a corresponding decrease in the detrimental effect of related party transactions on founder-led family firms’ valuation. Our results suggest that changes in the 2006 SEC related party transaction reporting regulations better protected minority shareholders from wealth extraction via related party transactions in founder-led family firms.     

Top Income Adjustments and Inequality: An Investigation of the EU-SILC†

This paper provides a novel assessment of how the World Inequality Database (WID) top income adjustment applied by Blanchet, Chancel, and Gethin (2021) to European Union Statistics on Income and Living Conditions (EU-SILC) data for 26 countries over 2003–2017 for Distributional National Accounts purposes affects inequality in equivalized gross and disposable household income. On average, the Gini is increased by around 2.4 points for both gross and disposable income, with notable differences across countries but limited impact on trends. EU-SILC countries that rely on administrative register data see relatively small effects on inequality. Comparing with two other recent studies, differences in impacts on measured inequality depend less on the adjustment method and more on whether external data sources are used.