Recovery of the Consumer Multiattributive Utility Maximization Problem
This article contains a prediction model for the demand for the consumer commodities. I consider the classical model of the consumer utility function maximization in a given budget constraint where there are two products: the first one for which the demand is being estimated, and the rest of the consumption bundle which is the second product. The utility function is introduced as multiattributive utility function with an unidentified number of attributes. An approach to estimate the exact number of attributes and the parameters of the model in a given class of utility functions for each attribute was proposed. The estimation is derived through the optimization of corrected Akaike information criterion, where the parameters of the utility function are continuous and the number of attributes is integer and positive. This model was tested on the prediction of the homogenous product demand with the Giffen effect.
Unlike actual sales figures, sales ranks are widespread in the field of electronic commerce, which motivates economists and marketing scholars to look for the avenues of converting sales ranks into actual sales or market shares that are needed for demand estimation. In this study the relationship between actual sales and sales ranks is calibrated using a large online store's unique data on 11 product categories, for which this relationship has never been calibrated before. By allowing the shape parameter of the power law to vary with the sales rank we managed to increase a traditionally used model's fit for most of the product categories. Our parameter estimates can be used by researchers that would like to get a reasonably good approximation of market shares based on sales ranks. We also validated and modified Garg and Telang's (2013) approach to inferring market shares using data on product price, sales rank and revenue rank. The approach, especially its modified version, was shown to lead to a reasonably low market shares prediction error, making it possible for researchers to infer the shares of sales based solely on sales and revenue rankings from companies that prefer not to disclose actual sales data.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.