An accurate global algorithm is critical for quantifying the dynamics of the Diamond-Mortensen-Pissarides model. Loglinearization understates the mean and volatility of unemployment, overstates the unemployment-vacancy correlation, and ignores impulse responses that are an order of magnitude larger in recessions than in booms. Although improving on loglinearization, the second-order perturbation in logs also induces large errors. We demonstrate these insights in the context of Hagedorn and Manovskii (2008). Once solved accurately, their small surplus calibration fails to explain the Shimer (2005) puzzle. While the volatility of labor market tightness is close to the data, the unemployment volatility is too high.