This article provides estimates of a social discount rate (SDR) to inform government policy in Russia. We find that a SDR should be determined for the whole country as well as for particular regions. We apply the social rate of time preferences approach and estimate values for public sector projects at national and regional levels. All calculations are based on data from the Federal State Statistics Service of Russia. Findings help the decision-making process in the public sector of economics. Suggestions are useful for Russia as well as for post-Soviet countries and other developing economies with regional diversity.
The problem of developing a chain of charging stations for electric vehicles along a highway crossing a geographic region is considered. A tool for determining an optimal structure of this chain is proposed. The use of the tool, particularly, allows one to estimate the cost of (and thus the needed volume of investment for) developing the chain proceeding from a) the demand for electricity in the chain, b) the existing technological and legal requirements to the structure of such a chain, c) the expected production capacities of all the types of renewable sources of energy, which can effectively be deployed at each charging station from the chain, and d) the cost of the equipment to be acquired and installed at each charging station to provide the chain customers with electricity to be received by each charging station in the chain from both electrical grids and renewable sources of energy, the cost of maintaining this equipment, and the cost of operating it. The problem under consideration is formulated as a nonlinear mixed programming one of maximizing the minimum function of a sum of several linear and two bilinear functions of vector arguments. It is proven that under certain natural and verifiable assumptions, finding solutions to this problem turns out to be reducible to solving either a mixed programming problem with linear constraints or a linear programming problem and an integer programming one. For a set of model data, an illustrative example of formulating and solving the problem under consideration is provided, and the way to use the tool in negotiations with potential investors in the project is discussed.
This article analyses how the intensification of centralized monitoring within public organization may impact incentives for efficiency in those divisions of the organization that have different levels of financial autonomy. The efficiency of divisions’ activities was estimated through their procurement effectiveness. All the divisions were classified as non-commercial units (NCU) funded by the government or as income earning units (IEU) operating in the market and having broader financial autonomy. The results show that under standard monitoring, the IEU had more efficient procurements compared to the NCU. After intensification of centralized monitoring, the differences in performance became insignificant. These findings show that stricter monitoring is efficient for organizations with soft budget constraints, while for organizations with hard budget constraints it is preferable to use more flexible regulations.
The combination of two reforms in Russia, reform of public-sector entities and of public procurement, enables us to estimate the results of a transition from rigid to more flexible regulations in public procurement (PP). We consider two public universities in 2011–2012. The procurements of one university were regulated by rigid Federal Law during the entire period; the procurements of the other university were regulated by Federal Law until June 2011 and then by a more flexible regulation. Using the difference-in-differences methodology, we assess how the transition to this new regulation affects the main PP parameters. We show that more flexible regulation leads to a decline in bid competition but improves contract execution.