This text is an automatic translation from Русский. It was generated by AI and may contain inaccuracies.
Read original →The Achilles' Heel of the American Supply-Side Economic Model
Can tax cuts and business incentives guarantee sustainable economic growth? The U.S. experience has exposed the limitations of the classic supply-side model. Today, it's being augmented with a focus on science and innovation. Will this become the new recipe for American success?
The United States' recurring use of supply-side economics (SSE) in its policy has been accompanied by its significant evolution.
This evolution is driven by the need to address gaps in SSE's prescriptions, which are rooted in the concept's ideas about stimulating economic growth and development, overcoming or curbing stagflation, and increasing budget revenues through lower tax rates and the introduction of a flat tax.
The experience of the U.S., as the originator of such practices, showed that these measures, at best, yielded partial growth effects, limited to 1-2 years. After tax burdens were reduced, growth in the country did indeed accelerate, but its scale and duration varied significantly from case to case. Inflation tended to decrease both during SSE implementation periods and at other times. Labor productivity growth, as one of the most important indicators of production development, did not show a direct correlation with SSE.
The reasons stemmed from an underestimation of the limitations on SSE application, noted by SSE's own authors (A. Laffer et al.), as well as methodological flaws in their concept identified by SSE critics.
The former pointed to the importance of initial tax regimes, the correct determination of the magnitude of rate changes, the timing and location of their implementation; the potential for businesses to go underground, various loopholes in tax legislation that reorient production from scaling to alternative directions; and the state of external conditions.
The latter emphasized the illegitimacy of equating a reduction in the tax burden on businesses with a change in their behavioral vector; equating budget revenues with national income, ignoring the intensification of socio-economic differentiation due to a unified reduction in tax rates, and so on. Serious shortcomings also included an underestimation of the role of innovation and technology in economic growth and competitiveness.
The first official acknowledgments of the need to transition to a "new" SSE and adjust its "classical" approaches came in U.S. Treasury Secretary J. Yellen's well-known speeches in 2022, which highlighted the long-term necessity of strengthening U.S. manufacturing and international competitiveness through the development of science and technology.
This step also served as the U.S. response to the problems of losing global leadership, which became clearly evident in the first decades of the current century. (See Fig. 1)
America has increasingly begun to cede ground to China, not only in science and technology-intensive industries but also in their infrastructure and R&D sectors.
The first major steps to address the evolving situation were taken in the late 2010s, when traditional economic policy measures were increasingly supplemented by technology development strategies (quantum, artificial intelligence, space nuclear power, etc.), intellectual property protection measures, and restrictions on access for several foreign—especially Chinese—companies to American technologies and markets.
Such actions intensified in the 2020s with the legislative adoption of measures to strengthen the national semiconductor industry and its infrastructure, stimulate the development of AI, space and biotechnologies, robotics, and protectionist measures against imports from China and some other countries.
However, these steps, combined with the application of traditional economic policy tools, were deemed insufficient.
A new vector for modern economic policy emerged with decisions to advance science and innovation as part of the transition to a "Golden Age of American Innovation." This transition is managed using an ecosystem approach, differentiating and optimizing departmental tasks and portfolios based on the diverse forms of organizing and conducting scientific research and development, the scale and duration of their results' utilization, the degree of solution standardization, the demand for scientific rather than administrative competence among scientists and researchers, and the direct involvement of these individuals instead of scientific institutions, among other parameters.
The frameworks developed now await practical verification.