Factory with thought bubbles representing future expectations

Decoding Productivity: How Subjective Expectations Can Revolutionize Business

Jordan Keane in Business & Economy December 2025 • 4 min read.

"New research reveals how tapping into a company's collective intuition can unlock hidden potential and drive unprecedented growth."

The ‘production function,’ representing how inputs translate into outputs, has long captivated economists. Understanding this process is crucial for analyzing technological change, productivity dispersion, firm markups, and the impact of policy. Recent productivity growth slowdowns have only amplified the need for accurate and reliable methods.

For years, economists have grappled with estimating production functions, facing challenges like input endogeneity – the unobservable correlation between a firm's productivity and its input choices. Traditional methods, including fixed effects models and lagged input values, often fall short, yielding implausible results or requiring extensive data.

A new approach is emerging, leveraging data on firms' subjective expectations of future output and inputs. This method offers a way to obtain consistent production function parameter estimates while relaxing assumptions about input demand policies. By tapping into a company's collective intuition, this innovative technique promises to revolutionize how we understand and estimate productivity.

Why Subjective Expectations Matter: A New Perspective on Productivity

Factory with thought bubbles representing future expectations

Traditional methods for estimating production functions, such as those pioneered by Olley and Pakes (OP) and Levinsohn and Petrin (LP), rely on assumptions about input choices. They often require a strictly monotonic relationship between a firm's input demand and productivity. This can be problematic, as factors like input adjustment costs, varying prices, and optimization errors can undermine this relationship.

The new method, outlined in a recent research paper, introduces a different approach. It uses data on firms’ expectations of future output and inputs to estimate production function parameters. This leverages the idea that a firm’s expectations contain information about its anticipated future productivity, providing a new way to control for unobserved variables.

Here's how this new method stacks up against traditional approaches:

Relaxed Assumptions: Unlike OP, LP, and ACF, this new approach does not require firms' decisions to be perfectly optimal.
Flexibility: It can accommodate non-linear productivity dynamics, while dynamic panel methods typically require linearity.
Data Efficiency: The method can identify production function parameters from a single cross-section of data, removing the need for multiple observations per firm.

While this new method requires data on firms’ subjective expectations, such data are becoming increasingly available through surveys like the Management and Expectations Survey (MES). This makes the approach a viable and attractive alternative to traditional methods.

A New Era of Productivity Analysis

This research offers a compelling new approach to estimating production functions. By leveraging firms' subjective expectations, it relaxes restrictive assumptions about input choices and opens new avenues for understanding productivity. As data on subjective expectations become more readily available, this method has the potential to transform how businesses and policymakers analyze and promote economic growth.

About this Article -

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This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2407.07988,

Title: Production Function Estimation Using Subjective Expectations Data

Subject: econ.em

Authors: Agnes Norris Keiller, Aureo De Paula, John Van Reenen

Published: 10-07-2024

Everything You Need To Know

What is a production function and why is it important in business and economics?

The production function represents how inputs translate into outputs. It's a fundamental concept for understanding technological change, productivity dispersion, firm markups, and the impact of policy. Accurately estimating the production function is critical for analyzing economic growth and understanding how efficiently businesses utilize resources. Recent slowdowns in productivity growth have amplified the need for reliable methods to analyze this relationship and make informed decisions.

What are the challenges in estimating a production function using traditional methods?

Traditional methods face challenges like input endogeneity, where a firm's productivity and input choices are correlated in unobservable ways. Methods like fixed effects models and lagged input values often fall short, yielding implausible results or requiring extensive data. Moreover, these approaches, such as those pioneered by Olley and Pakes (OP) and Levinsohn and Petrin (LP), rely on restrictive assumptions about input choices, such as a strictly monotonic relationship between input demand and productivity. These assumptions can be problematic due to factors like input adjustment costs, varying prices, and optimization errors.

How does the new method using subjective expectations differ from traditional approaches like Olley and Pakes (OP) and Levinsohn and Petrin (LP)?

The new approach leverages data on firms' subjective expectations of future output and inputs to estimate production function parameters. Unlike OP, LP, and ACF, this method relaxes assumptions about input choices, accommodating non-linear productivity dynamics, and requiring less data. It can identify production function parameters from a single cross-section of data. Traditional methods often require multiple observations per firm and make more restrictive assumptions about how firms make decisions.

What is the role of subjective expectations in the new approach to estimating production functions?

The new method utilizes firms' expectations of future output and inputs. These expectations contain information about a firm's anticipated future productivity, providing a new way to control for unobserved variables, like input endogeneity. By tapping into a company's collective intuition, this innovative technique promises to revolutionize how we understand and estimate productivity. The Management and Expectations Survey (MES) is an example of how such data is being collected to facilitate this new approach.

How can businesses and policymakers benefit from this new method of analyzing productivity?

By leveraging firms' subjective expectations, the new method offers a more flexible and accurate approach to understanding productivity. This allows businesses to make better-informed decisions about resource allocation, investment, and innovation. Policymakers can use this method to gain deeper insights into economic growth drivers and the impact of various policies. As data on subjective expectations becomes more readily available, this method has the potential to transform how businesses and policymakers analyze and promote economic growth.