Декан — Рогова Елена Моисеевна
ул. Кантемировская д. 3, корп. 1, лит. А
+7 (812) 644-59-11 доб.
доб. 61515 (менеджмент)
high-growth firms, high-skilled migration, university graduates, Russian regions
We develop a monopolistic competition model with heterogeneous agents who self-select into occupations (entrepreneurs and workers) depending on innate ability. The effect of market size on the equilibrium occupational structure crucially hinges on properties of the lower tier utility function—its scale elasticity and relative love for-variety.When combined with the underlying ability distribution, the share of entrepreneurs and income inequality can increase or decrease with market size. When extended to allow for the endogenous sorting of mobile agents between cities, numerical examples suggest that sorting may increase inequality within and between cities.
Standard measures of competitive toughness fail to capture the fact that, as consumers optimize intertemporally, firms operating today compete with (yet non-existent) businesses which will be started tomorrow. We develop a two-tier CES model of dynamic monopolistic competition in which the impact of product differentiation on the market outcome depends crucially on the elasticity of intertemporal substitution (EIS). The degree of product differentiation per se fails to serve as a meaningful indicator of competitive toughness: what matters is its cross-effect with EIS. We also extend the model to the case of non-CES preferences to capture variable markups.
The paper examines correlation in planning and organizing logistics of supplying goods and the issue of safety at urban roads; a model to determine the time of goods delivery is proposed on the basis of logistic concept “just-in-time” that takes into account the requirements of road safety on the one hand, and the customer-oriented approach of delivery, applied technologies and management solutions, on the other. The model is based on an integrated approach to the management of logistics processes; it can serve as a basis for decision making among departments in transport enterprises, logistics departments at industrial and trade enterprises, and corporate consumers. The paper also proposes to add the second level parameters to the system of logistics key performance indicators (KPI); these parameters would allow evaluating the target performance in goods transportation, as well as actual performance of logistics operations, including transportation in terms of road safety.
In this study we develop a model for early box office receipts forecasting that, in addition to traditionally used regressors, uses several inputs that have never been used before, but appeared to be very useful predictors according to our variable importance analysis. New predictors account for the power of actors and directors, as well as for the intensity of competition at the time of movie release. Instead of Motion Picture of Association of America (MPAA) ratings commonly used in movie success prediction, textual information about the reasons for giving a movie its MPAA rating was formalized using word frequency and principal components analyses. The expert system is based on the Random forest algorithm, which outperformed a stepwise regression and a multilayer perceptron neural network. A regression tree-based diagnostic approach allowed us to detect the heterogeneity of model accuracy across segments of data and assess the applicability of the model to different movie types.