Dynamic efficiency in economics relates to efficient growth over time, and specifically growth caused by new innovations and improved technology. It assumes that the economy is already fully utilizing all available resources and efficiently allocating goods and services.
The word dynamic refers to a state of constant change, and all economies change over time as the level of technology changes. Usually this is a source of growth, because technology usually improves, but there are many examples where the rate of technological improvement is very slow e.g., in subsistence economies.
In some rare cases a country can even experience negative technological advancements e.g., after a war, but in the majority of cases technology improves over time via breakthroughs in research and development.
The question is, what is the efficient rate of improvement, which means what is the efficient rate of investment in research and development? For less developed countries a little investment goes a long way since there are available existing technologies in more developed countries that can be replicated. For the developed world, progress is slower and more expensive.
Dynamic efficiency and Endogenous Growth Theory are closely related concepts in economics, both emphasizing the role of internal factors within the economy over external shocks or inputs. Instead of relying solely on external factors like capital accumulation, they emphasize the role of endogenous (internal) processes and decisions, especially new innovations and human capital development, in generating sustained economic growth.
Joseph Schumpeter's ideas of "creative destruction" and the role of entrepreneurship in driving economic growth are compatible with dynamic efficiency theory. Innovation-driven growth aligns with Schumpeterian concepts and the dynamic efficiency principle of continuous adaptation and change.
While the concept of dynamic efficiency is simple, there is no specific universally accepted model that can formulate how to achieve it as it varies across industries, countries, and time periods. I think that the best existing models to consider relate to the Neoclassical Growth Models. The two foremost of these are:
As far as key metrics are concerned, economists and policymakers use several approaches to gauge and encourage technological improvement efficiently.
Economists often look at productivity growth rates as an indirect measure of technological improvement. Higher productivity is indicative of improved efficiency, which can result from technological advancements.
Total Factor Productivity measures the efficiency with which inputs (capital and labor) are used in the production process. An increase in TFP is associated with technological progress, as it reflects improvements beyond what can be attributed to increases in the amounts of inputs used in the production process.
Analyzing technological improvements in similar industries or comparing technological progress across countries can provide insights into what might be considered efficient. Benchmarking against peers helps identify areas where improvement is needed.
The number and quality of patents filed can provide insights into the level of innovation and technological improvement within an industry or a country.
As I mentioned above, the definition of dynamic is constant change, and that is the opposite case of a static state. Static efficiency refers to an efficient allocation of resources and goods while holding the level of technology constant. This does have the disadvantage of being incomplete, but the theory here is much more developed than for dynamic models.
For more information on this, the most popular static models relate to:
It's important to recognize that the optimal level of technological improvement is context-dependent and can evolve over time. Different industries may require different rates of technological progress, and societal preferences may shift in response to changing needs and values.
The Neoclassical growth models offer a basis for understanding how growth in an economy occurs, but these models are not universally accepted, and they do not take non-economic concerns into account.
Ultimately, a combination of quantitative and qualitative measures, along with a deep understanding of the economic and social context, is necessary to make informed judgments about the dynamic efficiency of technological improvement.