Mortensen Pissarides ModelEdit
The Mortensen Pissarides Model, often referred to as the Diamond-Mortensen-Pissarides framework, is a foundational tool in modern labor economics. It brings together a realistic picture of how job seekers and firms meet (the matching process) with a wage negotiation that determines pay. The result is a tractable, dynamic explanation for why unemployment can persist even when there are willing employers and open jobs, and why unemployment and vacancies move together in response to shocks. The model sits at the intersection of labor economics, macroeconomics, and policy analysis, and it has become a standard reference for understanding how frictional forces in the labor market shape macro outcomes.
The core insight is simple in words but powerful in implications: labor markets are not perfectly liquid. People must search for jobs, and firms must search for workers. The rate at which matches form depends on how many job seekers there are and how many vacancies firms post, as captured by a matching function. Once a match is formed, wages are not arbitrary; they reflect a bargaining process between two sides with outside options, typically unemployment benefits on the worker side and the option to hire elsewhere or wait for a better candidate on the firm side. These ingredients generate unemployment even when the economy could in principle sustain more matches, because matches arrive only at a certain pace and wages adjust to balance the interests of workers and firms.
Origins and development
The MP framework builds on a line of work that begins with the idea of search frictions in the labor market. The early 1970s introduced the notion that matching processes matter for unemployment, and subsequent work by Dale T. Mortensen and Christopher A. Pissarides formalized a dynamic theory in which labor demand, job creation, and wage setting interact across time. The model is often presented alongside the Diamond-Duffie tradition of search theory, with the broader family sometimes called the Diamond-Mortensen-Pissarides (DMP) model. In 2010, the model’s central role in understanding equilibrium dynamics in the labor market was recognized with the Nobel Prize in Economic Sciences awarded to Peter A. Diamond, Dale T. Mortensen, and Christopher A. Pissarides. See Nobel Prize in Economic Sciences; see also Dale T. Mortensen; see also Christopher A. Pissarides; see also Peter A. Diamond.
Core components of the model
Matching process: A central object is the matching function M(U,V), which maps the number of unemployed workers U and the number of vacancies V into the flow of new job matches. This function is typically assumed to exhibit constant returns to scale, so when both U and V scale up, matches scale proportionally. The “tightness” of the labor market, often defined as theta = V/U, summarizes how easy it is to find a job or fill a vacancy. See matching function; see also unemployment and vacancy.
Flow in and out of unemployment: People leave unemployment through successful job matches, while employed workers can separate from their job. The separation rate (often denoted s) and the vacancy-filling rate together determine how unemployment and vacancies evolve over time. See unemployment; see also job vacancy.
Wage determination: Wages arise from a Nash bargaining process between workers and firms who are negotiating over the surplus from a match. The outside option for the worker is unemployment benefits or the value of unemployment, while the firm weighs the profit from the position against the costs of posting and filling a vacancy. See Nash bargaining solution; see also wage.
Value functions and dynamic optimization: The model is typically presented in a dynamic programming or value-of-state framework, where the value of being unemployed versus employed feeds back into the willingness to search, hire, or accept offers. See dynamic optimization.
Policy levers and frictions: Because the model connects unemployment to matching efficiency and wage bargaining, it provides a structured way to think about policies that affect search, matching, and incentives—such as unemployment insurance, job training, or hiring subsidies. See unemployment insurance; see also labor market policy.
Predictions and implications
Beveridge curve and labor market tightness: The MP framework naturally generates a Beveridge curve relationship between unemployment and vacancies. When the labor market is tight (high vacancy posting relative to unemployment), unemployment tends to be lower for a given productivity level, and vice versa. See Beveridge curve; see also labor market tightness.
Response to shocks: Productivity changes, separations, or matching efficiency affect both unemployment and vacancies. A positive productivity shock raises the value of matches and can reduce unemployment, while a higher separation rate tends to push unemployment up unless compensated by faster matching. See productivity; see also separation rate.
Wage dynamics and job creation: Since wages reflect bargaining between workers and firms, changes in outside options (e.g., unemployment benefits) or in bargaining power influence wage levels, which in turn affects firms’ incentive to post vacancies and hire. See bargaining theory; see also unemployment insurance.
Policy interpretation: The model clarifies how policies that reduce search frictions can lower unemployment by increasing the rate of matches, while policies that raise the cost of posting vacancies or reduce the incentives to hire can have the opposite effect. See job matching policy; see also minimum wage and unemployment insurance as policy levers.
Implications for policy debates and extensions
Job matching programs and activation policies: Since the MP model emphasizes the flow of matches, investments that improve the efficiency of the search process—such as better matching services, job placement, or information about openings—can reduce unemployment without necessarily depressing wages. See labor market policy; see also matching efficiency.
Unemployment benefits and incentives: The model implies that generous unemployment insurance can increase the duration of unemployment if it dampens the incentive to search aggressively, but the net effect depends on how benefits interact with the matching process and the wage bargain. This line of inquiry informs debates about UI generosity and labor market activation. See unemployment insurance.
Wage setting and flexibility: The Nash bargaining mechanism links wage outcomes to both outside options and the bargaining environment. Critics and proponents alike discuss how rigidities or reforms to bargaining power affect unemployment, vacancies, and growth. See Nash bargaining.
Extensions to capture real-world features: The MP framework has been extended to incorporate on-the-job search, skill heterogeneity, job-to-job transitions, and sectoral or regional differences. These refinements aim to improve empirical fit and policy relevance. See on-the-job search; see also heterogeneous agents.
Empirical evidence and critiques
Empirical calibration and estimation: The MP model has been estimated across countries and time periods to quantify parameters such as the matching efficiency and the separation rate. These estimates help explain differences in unemployment and vacancy dynamics across economies. See empirical evidence; see also cross-country comparison.
Strengths: The model captures key qualitative patterns of unemployment and vacancies and provides a coherent mechanism linking macro shocks to labor market outcomes. It is widely used to interpret business cycle fluctuations in a parsimonious framework. See labor economics.
Critiques and limitations: Some critics argue the standard form oversimplifies wage rigidity, worker heterogeneity, and long-run unemployment dynamics. Others point out that long-term unemployment and hysteresis effects are not always well explained by the basic MP setup, prompting a rich literature on extensions. See criticism of economic models; see also hysteresis in unemployment.
Relation to other strands: The MP model sits alongside broader search and matching literature and interacts with models of macro stabilization, structural unemployment, and labor market reform. See search theory; see also macro_policy.
Variants and extensions
On-the-job search and skill upgrading: Extensions allow workers to search for better matches while employed, and to accumulate human capital while in work. See On-the-job search; see also human capital.
Heterogeneity and shocks: Models incorporating heterogeneity across workers and firms, regional frictions, and sectoral shifts help explain observed diversity in unemployment dynamics. See heterogeneous agents; see also regional economics.
Policy-centered variants: Additional work explores how unemployment insurance, payroll taxes, and hiring subsidies alter the dynamic outcomes predicted by the MP framework. See unemployment insurance; see also tax policy.