Infrastructure investment has the characteristics of high start-up cost, high initial cost, long cycle, slow recovery, high risk, and high public welfare. Maintenance after completion requires stable financial support, maintenance costs are easily affected by government agencies, and investment efficiency is significantly reduced. This article focuses on the ant colony algorithm audit and supervision to promote the optimization of the new infrastructure investment environment and understands the relevant theories of infrastructure investment on the basis of literature data, and then, the audit supervision based on the ant colony algorithm promotes the optimization of the new infrastructure investment environment. The model is constructed, and the constructed model is tested. The test results show that, first, there is a dynamic equilibrium relationship between total infrastructure investment and GDP, even if it cannot explain the potential relationship between the two. In essence, infrastructure investment has a positive impact on economic growth. As the economic level increases, the demand for infrastructure will increase and infrastructure investment will inevitably increase. Second, the level values of the first order are all nonstationary sequences; after the difference, they are all stable and have the same single integral order. The model meets the preconditions of the cointegration test.
Following rapid growth, China’s economy is entering a period of high-quality economic growth. High-quality economic development has a profound impact on China’s current economic development. It can be said that the improvement of economic quality is an inevitable choice for China’s new stage of economic development. From this point of view, promoting high-quality economic development has become an important practical issue in my country’s current economic and social development. As the integration and innovation of digital technology and taxation, the blessing of digital technology maximizes integration and precision, which can effectively meet the needs of higher stages of economic development. Perfect and inclusive development has become an important support for sustainable and healthy economic development. At present, behind the rapid economic growth, human economic activities have led to the emergence of an ecological and environmental crisis. The growth mode characterized by high input, high consumption support, and high emissions has resulted in insufficient supply of regional ecological and environmental resources, pollution, and damage to the ecological environment and also intensified. Therefore, this paper first examines the concept of digital finance and its enlightenment to economic development, and believes that digital finance has a good role in promoting economic development. Second, an evaluation model for the relationship between environmental environment and economic development is established, and an evaluation index system is obtained. Finally, through the comprehensive evaluation and analysis of economic development and ecological environment, it is concluded that in the era of digital finance, the level of regional economic development has been greatly improved, and my country’s regional economic development has been greatly improved, which is significantly faster than my country’s ecological environment improvement level.
The Credit markets are served as intermediation between the lenders and borrowers. Huge economic activities are invested and obtain results over a small period of such credit market activities. Since it is good at the production of investments, there is a sudden fluctuation in the economic growth due to weak contracts with the borrower, less ability to monitor the invested amount, no credentials on further investment. The above issues gradually decrease economic growth. This research analyses the linkage between the credit market issues and a country’s economic growth during the recession and normal period. A Vector Fault Modification Model (VFMM) is proposed for the analysis. This model investigates the credit markets’ short-term and long-term investments using the fault classification and prediction criteria. The error coefficients (10.5%) are validated based on economic growth and further correlated with the credit markets’ accuracy rate (92.4%). This paper analysis the positive and high impact of economic growth based on credit market strategies.
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