A magnifying glass focusing on an economic landscape, highlighting the uneven adoption of modern research tools.

Is the 'Credibility Revolution' in Economics Leaving Some Fields Behind?

Nico Varela in Business & Economy July 2025 • 4 min read.

"A new analysis reveals that while some areas of economics have embraced rigorous research methods, others are lagging, potentially impacting the reliability of their findings."

For the past two decades, economics has undergone a significant transformation known as the 'credibility revolution'. This movement emphasizes the use of transparent, credible research designs, leveraging new data to generate profound insights. Pioneered by figures like Joshua Angrist and Jörn-Steffen Pischke, the revolution aims to enhance the reliability and validity of economic research, addressing pressing questions from economic growth to the impacts of social and educational policies.

However, a recent study casts light on a concerning trend: the uneven adoption of these rigorous methods across different fields within economics. While some areas have fully embraced the credibility revolution, others are lagging behind, potentially undermining the robustness of their conclusions. This raises critical questions about whether the movement's initial momentum, identified by Angrist and Pischke, is still continuing apace, and whether certain empirical techniques are being favored over others.

Building on the work of Currie, Kleven, and Zwiers, this analysis examines the credibility revolution across various fields, including finance and macroeconomics. By analyzing over 32,000 National Bureau of Economic Research (NBER) working papers, the study identifies the frequency of phrases related to different empirical techniques, providing a comprehensive view of how these methods are being applied—or not—across the discipline.

The Uneven Landscape of Credibility in Economics

A magnifying glass focusing on an economic landscape, highlighting the uneven adoption of modern research tools.

The study reveals that while the overall trends identified by Currie et al. continue to advance, significant heterogeneity exists across fields. Applied microeconomics has wholeheartedly embraced empirical techniques that emphasize research design, such as difference-in-differences, event studies, and randomized trials. In contrast, finance and macroeconomics are lagging in the uptake of these methods.

Within finance, corporate finance has shown robust growth in difference-in-differences designs, but the use of instrumental variables, regression discontinuity, and experimental methods remains limited. The adoption of popular tools like Bartik and shift-share instruments is also uneven, with rapid growth in applied micro areas like labor, trade, and economic history. Meanwhile, other tools, like synthetic controls, appear to have peaked in popularity.

Difference-in-differences dominate finance and macroeconomics.
Bartik and shift-share instruments are primarily used in applied micro areas.
Synthetic controls have plateaued in popularity.

These findings challenge the notion of a credibility revolution rapidly sweeping across all areas of economics. Instead, the picture is more nuanced, with the frontier of empirical work using credible, transparent research designs still centered in applied microeconomics, while other fields make progress at a slower pace. This raises concerns about the reliability of research in fields that have not fully embraced these rigorous methods.

The Path Forward: Diversifying Research Methods

The growing interest in and impact of difference-in-differences research across economics highlights how a single empirical technique, when widely adopted, can meaningfully shift the trajectory of an entire academic field. However, given some of the recent econometrics work flagging sensitivities and weaknesses in difference-in-differences, there may be value in researchers attempting to more broadly diversify their research methods portfolio. It is also quite striking that given the popularity of difference-in-difference that synthetic control methods have not grown further, as these methods have very similar properties.

About this Article -

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This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2405.20604,

Title: Tracking The Credibility Revolution Across Fields

Subject: econ.gn q-fin.ec

Authors: Paul Goldsmith-Pinkham

Published: 30-05-2024

Everything You Need To Know

What is the 'credibility revolution' in economics and why is it important?

The 'credibility revolution' is a significant transformation in economics, emphasizing transparent and credible research designs. This movement, championed by figures like Joshua Angrist and Jörn-Steffen Pischke, focuses on enhancing the reliability and validity of economic research. It leverages new data and rigorous methods to provide profound insights into various economic issues, such as economic growth and the impacts of social and educational policies. The importance lies in ensuring that economic research findings are trustworthy and can inform effective policy decisions. Without embracing credible methods, the conclusions drawn might be unreliable, leading to flawed understanding and potentially detrimental policy implementations.

How does the adoption of the 'credibility revolution' vary across different fields within economics?

The adoption of rigorous research methods from the 'credibility revolution' varies significantly across different fields. Applied microeconomics has widely embraced empirical techniques like difference-in-differences, event studies, and randomized trials. However, finance and macroeconomics have been slower to adopt these methods. While corporate finance shows growth in difference-in-differences designs, other methods like instrumental variables, regression discontinuity, and experimental methods are less common. This uneven adoption indicates that the credibility revolution's influence isn't uniform across all areas of economics, impacting the reliability of research outcomes differently depending on the field.

What are 'difference-in-differences' and 'synthetic control' methods, and how are they used in economic research?

'Difference-in-differences' is an empirical technique used to estimate the causal effect of a treatment by comparing the changes over time in an outcome variable for a group that is exposed to the treatment (the treatment group) to the changes over time in the same outcome variable for a group that is not exposed to the treatment (the control group). 'Synthetic control' is a method used to estimate the effect of an intervention (such as a policy change) by comparing the outcomes in a treated unit to a synthetic control group. This synthetic control group is constructed as a weighted average of control units, designed to closely resemble the treated unit before the intervention occurred. Both methods are examples of the types of research design that the 'credibility revolution' emphasizes. The choice and implementation of these methods are crucial for ensuring the validity and reliability of research findings.

Why is it concerning that finance and macroeconomics are lagging in adopting rigorous research methods?

It is concerning because the slow adoption of rigorous research methods in finance and macroeconomics could undermine the reliability of research findings in these fields. Without embracing the transparent and credible research designs promoted by the 'credibility revolution', conclusions may be less robust and potentially misleading. This could have significant implications for policy decisions and economic understanding. For example, if research in macroeconomics relies on less rigorous methods, policymakers might make decisions based on flawed evidence, leading to ineffective or even harmful economic policies. Similarly, in finance, unreliable research can lead to poor investment strategies and market instability. Therefore, the uneven adoption of rigorous methods across economics raises questions about the credibility of research and its implications for practical applications and broader societal impact.

What are 'Bartik' and 'shift-share instruments,' and in which areas of economics are they primarily used?

'Bartik' and 'shift-share instruments' are both empirical techniques used in economic research to estimate the causal effects of various economic interventions or events. Bartik instruments, also known as 'supply-side instruments,' often use initial conditions and national trends to predict economic changes in local areas. Shift-share instruments are often used to predict local economic outcomes by combining national trends with a local area's industry composition. They are primarily used in applied micro areas such as labor economics, trade, and economic history. Their adoption is uneven across different fields, with rapid growth in applied micro areas. Understanding the applications of these instruments highlights the varied approaches within the 'credibility revolution' and how certain fields are more actively embracing them than others.