The space economy, encompassing sectors from satellite telecommunications to space tourism, is a burgeoning field with immense potential. However, estimating its growth and understanding its dynamics present unique challenges. A variety of economic estimating methodologies can help navigate these challenges, each with its own strengths, weaknesses, and applications in the space economy.
Trend Extrapolation
Trend extrapolation extends past trends into the future. In the space economy, this could involve examining the historical growth rate of Government space-related budgets, satellite launches, or space investments. For example, if the number of satellite launches has been increasing at a steady rate, this trend could be extrapolated into the future. This method is straightforward but assumes that the factors influencing past growth will continue to apply, which may not always be the case in a rapidly evolving field like the space economy.
The FAA estimate for the number of licensed and permitted operations is an example of trend extrapolation. In the case of the FAA, their estimates are also informed by commercial launch service provider plans that they have access to as a consequence of their role as regulator.
Leading Indicators
Leading indicators are variables that change before the overall economy, potentially signifying future trends. In the context of the space economy, indicators such as the amount of investment in space startups, the number of patents filed for space technologies, Government policy, or the number of students enrolling in aerospace engineering programs could serve as leading indicators.
The UK Space Agency report on the “Size and Health the UK Space Industry” is an example of an estimation focused on leading indicators.
Econometric Modeling
Econometric models are statistical models that are used in economics to test hypotheses and forecast future trends. These models use a range of statistical methods to analyze economic data and draw conclusions based on this analysis.
Econometric models can be used to estimate the relationships between different economic variables, such as the relationship between demand for a product and its price, the impact of changes in government policy on economic growth, or the effect of economic conditions on unemployment rates.
In the context of the space economy, econometric models could be used in a number of ways to analyze and forecast trends, for example:
Demand for Satellite Services: An econometric model could be used to analyze the relationship between demand for satellite services and different factors, such as the price of these services, the level of economic activity, and technological advancements. This could provide insights into how changes in these factors might affect future demand for satellite services.
Impact of Government Policy: Econometric models could be used to analyze the impact of government policy on the space economy. For example, a model could be used to estimate the effect of changes in government funding for space research and exploration on the growth of the space economy. This could help policymakers understand the potential impacts of their decisions and make more informed choices.
Space Tourism Market: In the emerging market of space tourism, an econometric model could be used to analyze the relationship between the price of space travel, the number of potential customers, and the revenue generated by space tourism companies. This could provide insights into how changes in these factors might affect the future growth of the space tourism market.
These examples illustrate the potential applicability of econometric models to the space economy. However, it’s important to note that these models are based on the assumption that the relationships between variables are stable over time. This assumption may not always hold in a rapidly evolving field like the space economy.
Input-Output Analysis
Input-output analysis involves modeling how different sectors of the economy interact. For the space economy, it could highlight the interrelationships between different industries such as satellite manufacturing and launch services.
The US Department of Commerce BEA estimate for the US space economy is an example of an input output analysis.
Time-Series Analysis
Time-series analysis involves examining a series of data points over time to identify patterns, trends, and cycles. It could be used to identify patterns and trends related to such things as broadband satellite services adoption, launch services demand, Government spending, or private investments.
Scenario Analysis
Scenario analysis involves creating different scenarios based on assumptions about future events and conditions. For the space economy, one scenario might assume a significant increase in government funding for space exploration, while another might assume a major reduction in launch costs.
Computable General Equilibrium (CGE) Models
Computable General Equilibrium (CGE) models are a class of economic models that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. CGE models are highly detailed, capturing the interplay between different sectors of the economy, and how changes in one sector might affect the rest of the economy.
In the context of the space economy, CGE models could be used to simulate the complex interactions between different components of the space economy and to analyze the potential impacts of different changes or developments. Here are some specific examples:
Changes in Launch Costs: Suppose there’s a significant technological breakthrough that reduces the cost of launching satellites into space. A CGE model of the space economy could be used to analyze the potential effects of this change. Lower launch costs could lead to an increase in the number of satellite launches, which could spur growth in the satellite manufacturing sector. This could in turn lead to increased demand for components and materials used in satellite manufacturing, affecting other sectors of the economy.
Policy Changes: Suppose a government decides to increase funding for space exploration or to implement new regulations affecting the space industry. A CGE model could be used to analyze how these policy changes might affect various components of the space economy. For example, increased government funding could stimulate growth in the space exploration market segment, which could have knock-on effects on other market segments such as research and development, manufacturing, and education.
Emergence of New Markets: New markets like space tourism or asteroid mining could emerge in the future. A CGE model could be used to analyze the potential impacts of these new markets on the space economy. For instance, the emergence of space tourism could stimulate demand for launch services, space vehicles, and other related services.
Changes in Global Economic Conditions: CGE models could also be used to analyze how changes in the global economy might affect the space economy. For example, if there’s a global economic downturn, this could reduce demand for satellite services, which could impact the satellite manufacturing and launch market segments.
These examples illustrate how CGE models can be a potentially useful tool for analyzing the complex interactions within the space economy and predicting the potential impacts of various changes or developments.
Digital Twin
A digital twin of the space economy could potentially be used for forecasting. A digital twin is a virtual model of a process, product, or system that can be used for simulation and analysis. It allows for the testing of different scenarios and understanding potential outcomes without having to implement these changes in the real world first.
In the context of the space economy, a digital twin could be constructed to represent the components of the space economy, such as satellite manufacturing, launch services, space exploration, and space tourism. This digital twin could then be used to simulate the effects of “what if” changes or developments.
For example, suppose there’s a significant technological breakthrough that reduces the cost of launching satellites into space. This change could be implemented in the digital twin of the space economy, and the effects on various sectors could be observed. This could provide valuable insights into how the real space economy might react to such a change.
Similarly, the digital twin could be used to simulate the effects of policy changes, the emergence of new markets, changes in global economic conditions, and other scenarios. This could provide valuable information for decision-makers in government and industry, helping them to plan and prepare for various potential futures.
Expert Opinion
Despite advances in statistical and computational methods, expert opinions remain valuable in economic forecasting. Experts in the space industry can provide insights based on their knowledge and experience. Their opinions can inform forecasts of the space economy, especially in areas where data is scarce or uncertain.
Looking to the Future
Note that these methodologies are not mutually exclusive, and a comprehensive forecast of the space economy would likely incorporate several of these methods. As the space economy continues to evolve, it’s important that forecasts are regularly updated and methodologies are iteratively refined to reflect new data and changes in the industry.