Economic Growth Through Government Spending

Decoding Fiscal Multipliers: How Government Spending Really Impacts the Economy

Soraya Malik in Business & Economy August 2025 • 4 min read.

"A groundbreaking study combines statistical identification with real-world economic proxies to reveal the true impact of fiscal policies."

For decades, economists have debated the true impact of fiscal policy, particularly the size of fiscal multipliers – the measure of how much a change in government spending or taxes affects overall economic output. The traditional approach, using Structural Vector Autoregression (SVAR) models, relies on "proxy variables" to identify fiscal policy shocks. However, different proxies often lead to wildly different conclusions.

Some studies suggest tax cuts have a larger impact, while others champion government spending. This inconsistency stems from a critical flaw: the assumption that these proxy variables are truly exogenous, meaning they aren't influenced by other economic factors. When this assumption fails, the results become unreliable.

A new study offers a compelling solution by combining statistical identification techniques with a novel way of incorporating potentially endogenous proxies. This approach, using a Bayesian non-Gaussian SVAR model, reveals a clearer picture of fiscal policy's impact, challenging conventional wisdom and offering fresh insights for policymakers.

The Fiscal Multiplier Puzzle: Why Do Estimates Vary So Widely?

Economic Growth Through Government Spending

Traditional SVAR models aim to isolate the impact of specific fiscal policy changes (like tax cuts or spending increases) on the broader economy. To do this, they need a reliable way to identify these changes as "shocks" that aren't simply responses to other economic events. This is where proxy variables come in. For example, a researcher might use a measure of consumer confidence or total factor productivity (TFP) as a proxy for unexpected shifts in economic activity that influence government decisions.

The problem is that these proxies are rarely perfect. Consumer confidence might be influenced by anticipated tax changes, and TFP can be affected by government investments in research and development. When these proxies are not truly exogenous—when they are, in fact, influenced by the very economic factors they're supposed to isolate—the resulting estimates of fiscal multipliers become biased and inconsistent.

The core issues with traditional SVAR models using proxy variables include:

Endogeneity: Proxy variables are often correlated with other structural shocks, violating the assumption of exogeneity.
Model Misspecification: The data-generating process of the proxy may not follow a linear process, leading to dependent shocks.

Statistical identification methods offer an alternative. These methods rely on stronger assumptions about the statistical properties of economic shocks (such as non-Gaussianity) to achieve identification without relying on potentially flawed proxies. However, these methods often require larger datasets and can be less precise than proxy-based approaches. The recent study bridges the gap between traditional and statistical identification.

Policy Implications and the Path Forward

This study provides compelling evidence that government spending is a more effective tool for stimulating economic activity than tax cuts, particularly in the current economic environment. By addressing the limitations of traditional SVAR models and incorporating statistical identification techniques, the research offers a more reliable and nuanced understanding of fiscal policy's true impact. Policymakers can use these insights to make more informed decisions about how to best allocate resources and promote sustainable economic growth.

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This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2302.13066,

Title: Estimating Fiscal Multipliers By Combining Statistical Identification With Potentially Endogenous Proxies

Subject: econ.em

Authors: Sascha A. Keweloh, Mathias Klein, Jan Prüser

Published: 25-02-2023

Everything You Need To Know

What are fiscal multipliers, and why are they important in understanding the economy?

Fiscal multipliers measure how much a change in government spending or taxes affects overall economic output. They are crucial because they help economists and policymakers understand the effectiveness of fiscal policies, such as government spending and tax cuts, in stimulating economic growth or mitigating economic downturns. The size of the fiscal multiplier indicates the impact of each dollar spent or taxed by the government on the overall economic activity.

What are the limitations of traditional SVAR models when analyzing fiscal policy?

Traditional Structural Vector Autoregression (SVAR) models often rely on proxy variables to identify fiscal policy shocks. The primary limitation of these models is the assumption that these proxy variables are exogenous, meaning they are not influenced by other economic factors. However, in reality, proxies like consumer confidence or total factor productivity (TFP) can be affected by the very fiscal policies they are meant to isolate, leading to biased and inconsistent estimates of fiscal multipliers. This problem of endogeneity undermines the reliability of the model's results.

How does the new study improve on the traditional methods for estimating fiscal multipliers?

The new study overcomes the limitations of traditional SVAR models by combining statistical identification techniques with a novel approach to incorporate potentially endogenous proxies. This innovative approach, using a Bayesian non-Gaussian SVAR model, allows for a more accurate assessment of fiscal policy's impact. By accounting for the endogeneity of proxies, the study provides a clearer picture of how government spending and tax cuts influence economic growth.

Why is government spending considered a more effective tool than tax cuts, according to the study?

The study provides evidence that government spending is a more effective tool for stimulating economic activity than tax cuts. By addressing the endogeneity issue and improving the accuracy of the estimated fiscal multipliers, the research reveals that government spending has a greater positive impact on economic output compared to the same amount of tax cuts, especially in the current economic environment. This insight can guide policymakers toward more effective resource allocation.

Can you explain the role of proxy variables in the context of SVAR models, and why their reliability is often questioned?

In Structural Vector Autoregression (SVAR) models, proxy variables are used to identify fiscal policy shocks, such as changes in government spending or taxes. These proxies are intended to isolate these changes as events not influenced by other economic factors. However, the reliability of these proxies is often questioned because they are frequently correlated with other structural shocks, violating the assumption of exogeneity. For example, consumer confidence might be influenced by anticipated tax changes, and TFP can be affected by government investments. When proxies are not truly exogenous, the resulting estimates of fiscal multipliers become unreliable, as they fail to accurately measure the effect of fiscal policies on the economy.