Research on Municipal Financing Based on Linear Regression to Promote Urban Competitiveness

With the development of economic globalization and regional integration, the development of countries, regions, and cities is continuously accelerating. At the same time, it also means that competitions between countries, regions and cities are becoming increasingly fierce. Today, improving the competitiveness of cities has become the main goal of a country. The economic competition between countries is now specifically represented by city-level competition. If a country does not have a city that can be listed as a first-class economic zone in the world, then there is no way for the country to lead in the economic wave. Urban competitiveness determines the resources, capabilities and rights that cities can get, and the improvement of urban competitiveness cannot be achieved without the help of municipal financing. Municipal financing is in a severe situation now. If we want to achieve the sustainable development goal of the city, we need insight capital as a necessary input basis, that is, municipal financing of the city is an important influencing factor to guarantee the constant improvement of urban competitiveness and realize city's sustainable development. At the same time, the local government is the government entity that closely manages the city. The municipal government plays a decisive role in public services, education, business environment, and affecting the quality of local life. However, today's municipal financing has many shortcomings in terms of resources, capabilities, and rights, which limit local empiricism to provide cities with the development momentum they need. Therefore, improving the financial status of municipalities and promoting the development of municipal financing are vital to urban development. This article will analyze the impact of municipal financing on promoting urban competitiveness, and explore the relationship between municipal financing and urban competitiveness by establishing a multiple linear regression model.