Interconnected global economies with spillover effects

Beyond Traditional Methods: How to Get a More Accurate View of Economic Trends

Beau Callahan in Business & Economy September 2025 • 4 min read.

"The Inclusive Synthetic Control Method (iSCM) offers a fresh perspective on analyzing economic interventions and spillover effects, leading to potentially more reliable results."

Economic analysis often relies on methods to isolate the impact of specific events or interventions. The synthetic control method (SCM) has emerged as a powerful tool in this field, allowing researchers to construct a counterfactual scenario to estimate the causal effect of a policy or event. However, traditional SCM has limitations, particularly when dealing with spillover effects or situations where including treated units in the donor pool is essential.

Enter the inclusive synthetic control method (iSCM), a modification of SCM designed to address these limitations. The iSCM allows researchers to include units in the donor pool that may be directly or indirectly affected by the intervention. This is especially useful when spillover effects are suspected or when including treated units improves the accuracy of the analysis.

Imagine trying to assess the economic impact of German reunification. Traditional SCM might exclude Austria, a country closely linked to Germany, from the donor pool. However, if reunification had spillover effects on Austria, excluding it could skew the results. The iSCM provides a way to include Austria while accounting for any potential spillover effects, leading to a more accurate assessment.

What Makes iSCM Different, and Why Does It Matter?

Interconnected global economies with spillover effects

The core idea behind iSCM is to create a synthetic control that accounts for the potential effects on all units in the donor pool, including those that might be affected by the intervention. This is achieved by constructing a system of equations that estimates the treatment effect on the main treated unit as well as the spillover effects on other units.

Here's a breakdown of how iSCM works:

Identify Potentially Affected Units: The first step is to identify which units in the donor pool might be directly or indirectly affected by the intervention. This requires careful consideration of the economic and geographic relationships between the treated unit and other units in the donor pool.
Construct Synthetic Controls: Next, synthetic control versions are created for all potentially affected units, including the main treated unit. This involves finding a weighted combination of other units in the donor pool that best replicates the pre-intervention characteristics of each affected unit.
Solve the System of Equations: The iSCM then solves a system of equations to estimate the treatment effect on the main treated unit and the spillover effects on the other affected units. This system of equations takes into account the weights assigned to each unit in the synthetic controls.
Interpret the Results: Finally, the results are interpreted to assess the overall impact of the intervention, taking into account both the direct effect on the treated unit and the spillover effects on other units.

By explicitly modeling spillover effects, iSCM offers a more nuanced and potentially more accurate assessment of economic interventions. It acknowledges that economic events rarely occur in isolation and that their effects can ripple through interconnected economies.

The Future of Economic Analysis: Embracing Complexity

The inclusive synthetic control method represents a step forward in economic analysis by providing a framework for incorporating spillover effects and treated units into the donor pool. As economies become increasingly interconnected, methods like iSCM will be essential for understanding the true impact of economic events and policies. By embracing complexity and accounting for spillover effects, researchers can gain a more accurate and nuanced understanding of the economic landscape.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2403.17624,

Title: The Inclusive Synthetic Control Method

Subject: econ.em

Authors: Roberta Di Stefano, Giovanni Mellace

Published: 26-03-2024

Everything You Need To Know

What is the Inclusive Synthetic Control Method (iSCM), and how does it differ from the traditional Synthetic Control Method (SCM)?

The Inclusive Synthetic Control Method (iSCM) is a modification of the Synthetic Control Method (SCM) designed to address limitations in traditional economic analysis, particularly when dealing with spillover effects or when including treated units in the donor pool is essential. Unlike the traditional SCM, which may exclude units affected by the intervention, the iSCM allows researchers to include these units, acknowledging that economic events rarely occur in isolation. The core difference lies in iSCM's ability to construct a synthetic control that accounts for potential effects on all units, including those affected by the intervention, leading to a more accurate assessment by explicitly modeling spillover effects.

Why is the iSCM useful in analyzing economic interventions, and what are some real-world examples where it could be applied?

The iSCM is useful because it provides a framework for incorporating spillover effects and treated units into the donor pool, which is crucial for understanding the true impact of economic events and policies. A real-world example of its application is assessing the economic impact of German reunification. Traditional SCM might exclude Austria, but iSCM can include Austria, accounting for any spillover effects, thus leading to a more accurate understanding of the event's economic consequences. This is particularly important in today's interconnected economies, where events have far-reaching effects.

How does the iSCM account for spillover effects, and what steps are involved in its methodology?

The iSCM accounts for spillover effects by constructing a system of equations that estimates the treatment effect on the main treated unit as well as the spillover effects on other units. The methodology involves several steps: First, identifying potentially affected units in the donor pool. Second, creating synthetic controls for all potentially affected units, including the main treated unit. Third, solving a system of equations to estimate the treatment effect and spillover effects, considering the weights assigned to each unit in the synthetic controls. Finally, interpreting the results to assess the overall impact, accounting for both direct and spillover effects.

What are the potential benefits of using iSCM over traditional methods, and what kind of insights can it provide?

The potential benefits of using the iSCM over traditional methods include a more accurate and nuanced assessment of economic interventions. By accounting for spillover effects and including treated units, iSCM acknowledges the complexity of economic events and provides a more comprehensive understanding of their impacts. It can offer insights into how economic events ripple through interconnected economies, revealing the indirect effects that might be missed by traditional methods. This leads to a better understanding of the true economic landscape and the effectiveness of policies or events.

In what ways does the iSCM represent a step forward in economic analysis, and what implications does it have for future research?

The iSCM represents a step forward in economic analysis by providing a framework to incorporate spillover effects and treated units into the donor pool. This is crucial for understanding the true impact of economic events and policies in increasingly interconnected economies. Future research can leverage the iSCM to analyze complex economic scenarios, providing more accurate insights into the effects of interventions and policies. By embracing the complexity of economic interactions, researchers can gain a more nuanced understanding of the economic landscape and make more informed decisions.