A pénzintézetekben használt, hitelkockázati modellek alkalmazásának néhány problémája

Bánfi Tamás 1991-ben tanársegédként lehetőséget biztosított számomra az egyetemi oktatói pálya elkezdésére. Nála mindig a józan észnek volt elsőbbsége, gyanakodva tekintett a bonyolult modellek furcsa következtetéseire. Ebben a szellemben írtam a következő cikket. A kockázatot számszerűsítő modellek azt ígérik, hogy néhány mutatószámba sűrítenek olyan bonyolult dolgokat, mint pl. egy hitelportfólió kockázata. Ezek a mutatók azonban esetenként elég furcsán viselkednek, ami joggal keltheti fel a gyanakvásunkat az alkalmazott módszerekkel kapcsolatosan. Ennek egy elemét vizsgálja az alábbi írás

Socially Optimal Taxation of Alcohol: The Case of Czech Beer

The proposed paper belongs to the literature on food demand and optimal taxation and to the literature dealing with economics of alcohol production and consumption. We investigate the question of optimal taxation for the commodity whose consumption has positive and negative features both for individual consumer and for the society. The commodity we analyze is the Czech beer.Almost Ideal Demand System, alcohol, beer, brewing industry, consumption, the Czech Republic, elasticity, price, spirits, tax, wine., Agricultural and Food Policy, Consumer/Household Economics, Demand and Price Analysis, Health Economics and Policy, Public Economics, D12, L66, Q18,

STOCHASTIC TRAFFIC DEMAND PROFILE: INTERDAY VARIATION FOR GIVEN TIME AND DAY OF WEEK

Traffic surveys routinely estimate the profile of traffic demand in a certain road section, showing the expected evolution of the demand over a workday or weekend. However, the actual demand fluctuates around this value. That can lead to brief excess of the capacity at the moment of high demand and consequent congestion due to the capacity drop. This type of traffic demand variability has not yet been properly studied despite the fact it can play significant role in traffic modelling and engineering applications. This paper presents results of analysis of demand variability in five-minute aggregation intervals. The results do not clearly show a single random distribution that would accurately model the demand variability. Normal, lognormal and gamma distributions all show reasonably well fit to the data for individual intervals. Based on count of best fits, the lognormal distribution seems best, but in most cases, the difference between the distributions is not statistically significant. There appears to be a pattern where certain distributions have better fit in different times of day and week. The regularity and magnitude of demand (e.g. morning peak hour) probably play a role in this, as well as the aggregation interval