An accurate global projection algorithm is critical for quantifying the basic moments of the Diamond–Mortensen–Pissarides model. Log linearization understates the mean and volatility of unemployment, but overstates the volatility of labor market tightness and the magnitude of the unemployment–vacancy correlation. Log linearization also understates the impulse responses in unemployment in recessions, but overstates the responses in the market tightness in booms. Finally, the second‐order perturbation in logs can induce severe Euler equation errors, which are often much larger than those from log linearization.

Search frictions unemployment projection perturbation nonlinear dynamics parameterized expectations finite elements E24 E32 J63 J64