Birth rate has a special place among the demographic factors determining the growth of population and the pace of the country's economic development. Solution to the problem of proper fertility in Russia is in building a powerful state demographic policy based on strengthening the key determinants of the reproductive process. The work is devoted to identifying the determinants of making a decision about the birth of a child in Russian families, understanding of which will allow substantiating the ways to improve the effectiveness of the demographic policy to stimulate the birth rate. To study fertility factors, two econometric models were built: a logistic regression for dependent variable of having a child during the year and an ordinal logistic regression for the number of children. The models took into account the problem of endogeneity — there was used instrumental variables method. The main data source was the RLMS HSE statistical database. The primary analysis of the data showed that in Russia the transition to European family type continues: there is an increase in the age at which women have children, and extramarital unions are spreading. As a result of the regression analysis, it was found out that the probability of having a child during the year is influenced primarily by personal and socio-economic factors, as well as working conditions. The number of children a woman has is affected by all types of factors, in particular— socio-economic factors and working conditions. Families that are not sure of their future financial stability, including their living conditions, are less likely to have a large number of children. The paper gives recommendations for assessing the effectiveness of the state demographic policy in Russia.
To achieve carbon neutrality in Russia by 2060, it is necessary to regulate the volume of greenhouse gases at the regional level. Among all regions of Russia, the balance of greenhouse gases by sectors of the economy is calculated only for the Sakhalin region. The study of this article aims to assess the level of greenhouse gas emissions from the Waste sector in Novosibirsk region, taking into account territorial and sectoral characteristics. During the study, the authors used the methodology of the Intergovernmental Panel on Climate Change and the methodological recommendations of the Ministry of Natural Resources and Environment of Russia № 15p, through which the authors evaluated methane (CH4) and nitrogen oxide (N2O) emissions from solid waste disposal and from the treatment of liquid waste and effluents. Greenhouse gas emissions in 2020 were 1.57 mln. t CO2 equivalent, including 1.09 mln. t CO2-equivalent from solid waste disposal and 0.48 mln. t CO2 equivalent from liquid waste and sewage treatment. The main contributor to the growth of greenhouse gas emissions was emissions from solid municipal waste disposal, increasing by 0.06 million tons of CO2-equivalent over the past four years. Analysis of the current state and calculation has shown that the Novosibirsk Region has a low level of infrastructure development for separate waste collection, capacities of waste-sorting plants, as well as equipment of the centralized sewage system and quality of waste and effluent treatment. Therefore, it is necessary to introduce resource-saving and low-waste technology, the formation of a closed-cycle economy, the implementation of the transition to the multi-container separate collection of waste. It is advisable to disseminate technologies for collection of landfill gas and its use as fuel, the direction of organic waste for the production of commercial compost, biogas or feed and feed additives, as well as the development of technologies for obtaining biochar from organic waste and its further use in agriculture.
The article discusses approaches to introducing the financial sector into agent-based models, as well as various options for modeling the behavior of agents (firms and households) directly interacting with the financial system. Agent-based models can explain how some important macroeconomic phenomena can be generated by evolving networks of interactions between boundedly rational agents in economies, where the underlying rules of interaction can evolve endogenously over time. The importance of accounting for financial activity in macroeconomic models for reproducing business cycles and predicting financial crises is emphasized. Consideration of financial blocks in macroeconomic agent-based models includes an analysis of approaches to modeling the choice between household savings and consumption, making decisions about the amount of investment by private sector firms, as well as the rules for setting interest rates and regulatory limits by banks. Possibilities for improving approaches in terms of taking into account interest rates when modeling household savings are proposed, as well as long-term planning based on the calculation of discounted cash flows with an assessment of the impact of changes in output on market prices when forming firms’ investment plans.
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