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A random walk for agricultural total factor productivity

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  • James Vercammen

Abstract

Growth in agricultural total factor productivity (TFP), which explains most of the long‐term growth in U.S. agricultural output, may be slowing. The Economic Research Service (ERS) of the USDA is confident that current levels of below‐average growth will eventually regain the long‐term trend line. Others disagree, arguing instead that due to declining public expenditures on agricultural research, TFP growth experienced a downward and seemingly permanent structural shift about 30 years ago. In this paper, I argue that neither perspective is accurate since agricultural TFP is best modeled as a random walk with drift and thus not governed by a deterministic trend line. When I use a first difference model to accommodate the unit root, I do not find a structural break in the rate of drift. However, I acknowledge that this finding may not be general because I show that my test for a structural break has low power. To add theoretical relevance, I develop a simple model of stochastic innovation and farm technology adoption, and then use simulation results from my model to explain why a random walk for agricultural TFP is a theoretically sound proposition. La croissance de la productivité totale des facteurs agricoles (PTF), qui explique l'essentiel de la croissance à long terme de la production agricole américaine, pourrait être en diminution. Le service de recherche économique (ERS) de l'USDA est convaincu que les niveaux actuels de croissance inférieurs à la moyenne finiront par retrouver la ligne de tendance à long terme. Andersen, Alston, Pardey et Smith [2018] ne sont pas d'accord, argumentant plutôt qu'en raison de la baisse des dépenses publiques consacrées à la recherche agricole, la croissance de la PTF a connu un changement structurel à la baisse et apparemment permanent il y a environ 30 ans. Dans cet article, je soutiens qu'aucune de ces perspectives n'est exacte puisque la PTF agricole est mieux modélisée comme une marche aléatoire avec dérive et n'est donc pas régie par une ligne de tendance déterministe. Lorsque j'utilise un modèle en première différence pour prendre en compte la racine unitaire, je ne trouve pas de rupture structurelle dans le taux de dérive. Cependant, je reconnais que cette conclusion n'est peut‐être pas générale, puisque mon test de rupture structurelle a une faible puissance. Pour ajouter de la pertinence théorique, je développe un modèle simple d'innovation stochastique et d'adoption de technologies agricoles, puis j'utilise les résultats de simulation de mon modèle pour expliquer pourquoi une marche aléatoire pour la PTF agricole est une proposition théoriquement solide.

Suggested Citation

  • James Vercammen, 2024. "A random walk for agricultural total factor productivity," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(3), pages 213-233, September.
  • Handle: RePEc:bla:canjag:v:72:y:2024:i:3:p:213-233
    DOI: 10.1111/cjag.12338
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    1. Derek Brewin & Ryan Cardwell & Alan P. Ker, 2024. "Introduction to the special issue in honor of the late Dr. James Rude," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(3), pages 209-211, September.

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