Methodological Advancements in Assessing Tariff Impacts on Sustainable Development Goals

Initial Methodological Challenges and SDG Implications

An accurate assessment of the distributional impact of tariffs is critical for developing policies that align with the Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). Initial estimation methodologies faced significant challenges related to data integrity.

• The primary method relied on the ratio of consumption to after-tax-and-transfer income (the “C/Y ratio”) from the Consumer Expenditure Survey (CEX).
• A well-documented issue with the CEX is the underreporting of income, especially among lower-income groups.
• This data limitation led to inflated C/Y ratio estimates for vulnerable populations, resulting in a potential overestimation of tariff regressivity. Such inaccuracies can misinform policy actions intended to support progress on SDG 1 and SDG 10.

Evolution of the Estimation Model for Enhanced Accuracy

In response to these challenges, the methodology has evolved through two distinct approaches to better quantify the economic burden of tariffs on households.

1. Consumption-to-Income (C/Y) Ratio Approach:
   • Basis: Directly utilized the C/Y ratio from the CEX.
   • Limitation: Prone to overstating regressivity due to income underreporting in the CEX, affecting the precision of analyses related to SDG 10 (Reduced Inequalities).
2. Consumption Share Imputation Approach:
   • Basis: This approach, introduced in a June report, used each income decile’s share of total consumption in the CEX to impute consumption levels onto Congressional Budget Office (CBO) distribution data. It incorporates only the rank-order of income from the CEX, not its absolute level.
   • Limitation: While addressing the overreliance on CEX income levels, this method produced imputed C/Y ratios that were not strictly monotonically decreasing by income, a pattern that contradicts established economic theory and could complicate modeling for SDG 8 (Decent Work and Economic Growth).

Adoption of a Hybrid Methodology for Balanced and Robust Analysis

Following further review, a new, updated methodology has been adopted to balance the advantages and disadvantages of the previous approaches. This hybrid model is designed to provide a more robust foundation for policy analysis in support of the SDGs.

• Core Principle: The updated methodology imputes consumption for each income decile by taking a simple average of the results from the two prior approaches, with each being assigned a weight of 50 percent.
• Special Exception: For the bottom income decile, only the Consumption Share Imputation Approach is applied. This is due to the C/Y ratios from the CEX for this group being considered highly implausible.
• Contribution to SDGs: This blended methodology offers a more balanced and defensible estimation of the distributional impact of tariffs. The enhanced accuracy is critical for policymakers designing interventions that effectively advance SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities) by ensuring economic policies do not disproportionately burden vulnerable households.
• Commitment to Transparency (SDG 17): In alignment with SDG 17 (Partnerships for the Goals), the technical methodology and replication code are publicly available to promote transparency, collaboration, and data-driven policy evaluation.

SDGs Addressed in the Article

SDG 10: Reduced Inequalities

• The article’s central theme is the “distributional impact of tariffs,” which directly relates to understanding and measuring economic inequality. It explicitly discusses methodologies for calculating how fiscal policies (tariffs) affect different “income deciles,” with a particular focus on “lower income groups” and the “bottom decile.” The analysis of “regressivity” is a core concept in the study of inequality, examining whether a policy disproportionately burdens the poor.

SDG 17: Partnerships for the Goals

• The article exemplifies the principles of data, monitoring, and accountability. It describes a methodological effort by a research lab (“Budget Lab at Yale”) to improve statistical accuracy by combining and refining data from multiple sources, namely the “Consumer Expenditure Survey (CEX)” and the “CBO [Congressional Budget Office] distribution data.” This work directly contributes to enhancing the capacity to produce reliable, disaggregated data, which is a foundation for monitoring progress on all other SDGs.

Specific SDG Targets Identified

SDG 10: Reduced Inequalities

1. Target 10.1: By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national average. The article’s focus on the “bottom decile” and “lower income groups” and its attempt to accurately measure their consumption and income levels in relation to tariffs are essential for assessing policies that impact this target.
2. Target 10.4: Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality. Tariffs are a form of fiscal policy. The article is an in-depth analysis of the distributional effects of this specific policy, providing the evidence needed to design fiscal measures that do not exacerbate inequality.

SDG 17: Partnerships for the Goals

1. Target 17.18: By 2020, enhance capacity-building support… to increase significantly the availability of high-quality, timely and reliable data disaggregated by income… The entire article is a demonstration of this target in action. It details a sophisticated effort to resolve issues with “underreporting of income” in survey data to produce more reliable data disaggregated by “income decile.”
2. Target 17.19: By 2030, build on existing initiatives to develop measurements of progress on sustainable development that complement gross domestic product… The analysis of the “distributional impact of tariffs” is a measurement that goes beyond simple economic aggregates like GDP. It provides a nuanced view of economic well-being and inequality, which is a key aspect of sustainable development.

Indicators Mentioned or Implied

• Consumption-to-Income Ratio (C/Y ratio): The article explicitly mentions using the “C/Y ratio” as a key metric for its initial estimates. This ratio is a direct indicator of the economic burden on different income groups.
• Share of Total Consumption by Income Decile: The second methodology described uses “each income decile’s share of total consumption in the CEX” as a primary indicator to impute consumption levels, directly measuring economic activity across the income spectrum.
• Data Disaggregated by Income Decile: The use of “income decile” data from both the CEX and CBO is the foundational indicator for the entire analysis. It allows for a granular measurement of inequality.
• Regressivity of Tariffs: While not a single number, the estimation of “regressivity” is the ultimate goal of the analysis. It serves as a qualitative and quantitative indicator of whether a fiscal policy is equitable.
• Methodological Improvement in Statistical Modeling: The development of the “blending” or “averaging” of two different approaches is itself an indicator of progress towards more robust and reliable statistical capacity for measuring inequality, as called for in SDG 17.

SDGs, Targets, and Indicators Analysis

Source: budgetlab.yale.edu