Economic growth: macroeconomic effects of Public Borrowings at the global level

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The study examines the peculiarities of the impact of public debt on the economic growth of states. The aim of the study was to analyze and identify the determinants of the impact of government borrowing on economic growth. The following research methods have been applied: analysis and synthesis of data and theoretical work, comparative analysis, statistical, correlation, cluster and discriminant analysis. According to the results of the survey, it is established that the growth of government borrowing can have both a negative and a positive effect on the economy, provided that it implements as the share of government debt to GDP, does not exceed 60% and is implemented in the form of financial investments (golden rule of public finance). The state’s deficit is allowed provided that state assets grow; current income from investment fully covers current expenses. The results of clusterization allowed to allocate 3 groups of states: states that demonstrated the economic downturn; states characterized by slow economic growth; states that were characterized by high level of economic growth. The first group of states (the countries with economic downturn) observed a negative high level of government debt and GDP. The results showed the low level of domestic borrowing development in low and middle income countries, which in developed countries allows governments to finance the investment projects on the basis of local loans (municipal bonds, infrastructure bonds, mainly medium and long-term), increase the debt burden in terms of economic recession.

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    • Figure 1. Average GDP per capita and average general goverment debt to GDP in 2002–2018
    • Figure 2. The results of grouping countries by the level of economic growth
    • Table 1. The average govermnent debt (% of GDP) and GDP per capita in the regions of the world in 2002–2018
    • Table 2. Results of stepwise discriminant analysis
    • Table 3. Classification of discriminant models
    • Table A1. Dynamics of external and internal loans in different countries / regions of the world in 2007–2017, million
    • Table B1. Results of constructing a discriminant model
    • Table C1. Classification matrix of discriminant mathematical model
    • Table D1. Test results of a discriminant model using criterion
    • Table E1. Value of coefficients for variables for canonical functions
    • Table H1. Grouping of countries by level of economic growth