This paper detects US recessions in real time using unemployment and vacancy data. By selecting perfect recession classifiers on the high-precision segment of the anticipation-precision frontier, the algorithm detects recessions not only early but also precisely.
This paper develops the Michez rule, a fast and robust method to detect US recessions using data on unemployment and job vacancies. In December 2024, the rule gives a recession probability of 27%; this recession risk was first detected in March 2024.
This paper builds a Beveridgean model of the Phillips curve. Prices respond to slack so the divine coincidence holds: prices are stable at full employment. The Phillips curve is kinked if wage cuts are more costly to producers than price hikes.
This paper finds that in the United States the full-employment rate of unemployment (FERU) is the geometric average of the unemployment and vacancy rates. Between 1930 and 2024, the FERU averages 4.1% and is very stable.
This paper develops a sufficient-statistic formula for the unemployment gap. The formula depends on the elasticity of the Beveridge curve, cost of unemployment, and recruiting cost. In the United States the unemployment gap is countercyclical and often positive.