The purpose of this study was to research and understand the interrelations between the growth of gross fixed capital formation (GFCF), the volume of construction industry, supply of interindustry balance, and amount of fixed-asset investments in Russia between 2000 and 2016. The autoregressive distributed-lagged (ARDL) bound testing methodology and regression analysis were applied to evaluate the cointegration and influence of construction industry volume on gross fixed-capital formation. Empirical studies on the role of the construction industry are at the forefront of economic research; however, ARDL modeling studies of GFCF have yet to be conducted in Russia. The study revealed a non-linear causation between construction industry volume and the growth in GFCF over a long time period. The correlation was stationary and cointegrated. Fixed investment positively affected gross fixed capital formation only in periods of economic expansion, whereas the effectiveness of fixed-asset investments had greater volatility in times of crisis. The construction industry was not practically affected by crisis shocks, demonstrating a permanent stationarity in the causal relationship with GFCF, whereas causal relations between GFCF and the supply of interindustry balance were absent. The results are important for further research in the field of economic growth, the development of a national budget and investment policy, as well as investment project selection.

This study aims to examine the impact of foreign direct investment (FDI), investment in construction and poverty in various countries. The Russian Federation invests heavily in construction and it is located both in Europe and Asia. Russia is usually described as a European country (while 70% of its territory is in Northern Asia, 80% of the population resides in Europe). That is why in this document both developed and emerging countries are considered; the former are represented by the EU members of different economic levels and the latter by BRICS countries. We looked at economically different countries to determine the best differentiated data in order to answer the question: “Why does a high level of poverty persist in Russia if Russian officials have repeatedly reaffirmed their commitment to the implementation of the Sustainable Development Goals (SDGs) by investing heavily in construction and attracting FDI?”. For the estimation, we used an autoregressive distributed lag (ARDL), considering cointegration and heteroscedasticity, in which the current values of the series depend both on the past values of this series and on the current and past values of other time series. Having received statistical data, we were able to compare the economic development of countries with some economic growth theories. 4–5% FDI share of the GDP helps to contain the negative impact of financial crises. Investment in construction supports the economies of countries in the long term and maintains or reduces the poverty level by increasing the assets of the population. Empirical data also helped us to evaluate the economic growth patterns and poverty in these seven countries. China and the Russian Federation will find themselves at different “poles”. China uses several theories and models simultaneously for economic development and poverty reduction and the Russian Federation does not keep to an established theory or a model of economic growth.

The infrastructure spatial planning is at the heart of modern sustainable development issues. The methods for selecting an infrastructure project for construction are an important conceptual basis for sustainable development, which provide effective assistance to the development of territories. The study is aimed at finding and analyzing existing approaches and tools for assessing territorial development in the reproductive structure of the economy, as well as developing a methodological and procedural assessment of large infrastructure projects to solve socio-economic problems. The methods of analysis of causes and effects, as well as methods of investment planning are used. At the same time, according to the authors, the main conceptual and methodological prerequisite that distinguishes the proposed approach should take into account the effects of intersectoral interaction. It is necessary to assess the contribution to the sustainable development of territories “with a project” and “without a project”.

Measures to reduce environmental risks within the infrastructure construction are mainly reduced to recommendations on use of renewable energy sources, and use of vehicles with hybrid and electric motors. The article shows that the predominant factor in reducing environmental risks is investment in fixed assets for environmental protection. The analysis performed using OLS confirmed that the degree of P-value dependence in all three constructed models was obtained for the Investments variable.