The studies of tobacco demand accounting for product diversity haveattracted much attention in the literature, but theex antemeasurements ofthe effects of product bans are relatively scarce. This paper aims to fill this gapand considers the 2020 EU-induced ban on menthol cigarettes as an example,focusing on the Polish market. In the proposed approach, a 2004-2017 product-level dataset for Poland is used to estimate a random coefficients logit modeland simulate the effects of the menthol ban and, for comparison, a cigaretteexcise hike. The dataset is unique as it encompassess substantial changes inthe tobacco tax level and structure that took place in Poland over the sampleperiod. The simulations suggest that the ban, despite switching of consumerstowards non-menthol cigarettes, results in relatively strong reduction in demandfor duty-paid cigarettes, stronger than in the case of the excise hike.
Various quantile regression approaches are implemented to analyze thecharacteristics of Italian data on earnings in the tails. A changing coefficientspattern across quantiles shows increasing returns to education along the wagedistribution. A quantile decomposition approach shows that higher educationgrants higher return at all quantiles, thus implying additional, non-linear returnsto higher education throughout the entire pattern of the earning distribution.Wage gender gap displays a decreasing pattern across quantiles, and it doesnot disappear at the higher quantiles. The southern workers penalty decreasesacross quantiles as well for highly educated workers.
Initial public pensions are indexed to the economy-wide average wages, butpensions in progress are indexed to prices, average wages or their combinations– varying across countries and periods. We create a simple overlapping cohortsframework to study the properties of indexing pensions in progress – emphasizinga neglected issue: close wage paths should imply close benefit paths even at realwage shocks. This robustness criterion of an equitable pension system is onlysatisfied by wage indexing, which in turn requires the adjustment of the accrualrate. To minimize the redistribution from low-earning short-lived citizens tohigh-earning long-lived ones, progression should be introduced.
The Internal Rating Based (IRB) approach requires that financialinstitutions estimate the Loss Given Default (LGD) parameter not only based onclosed defaults but also considering partial recoveries from incomplete workouts.This is one of the key issues in preparing bias-free samples, as there is aneed to estimate the remaining part of the recovery for incomplete defaultsbefore including them in the modeling process. In this paper, a new approachis proposed, where parametric and non-parametric methods are presented toestimate the remaining part of the recovery for incomplete defaults, in pre-defined intervals concerning sample selection bias. Additionally it is shown thatrecoveries are driven by different set of characteristics when default is aging.As an example, a study of major Polish bank is presented, where regressiontree outperforms other methods in the secured products segment, and fractionalregression provides the best results for non-secured ones.
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