We propose a three-step factor-flows simulation-based approach to forecast the duration distribution of unemployment. Step 1: estimate individual transition hazards across employment, temporary layoff, permanent layoff, quitter, entrant, and out of the labor force, with each hazard depending on an aggregate component as well as an individual's labor force history. Step 2: relate the aggregate components to the overall unemployment rate using a factor model. Step 3: combine the individual duration dependence, factor structure, and an auxiliary forecast of the unemployment rate to simulate a panel of individual labor force histories. Applying our approach to the July Blue Chip forecast of the COVID-19 recession, we project that 1.6 million workers laid off in April 2020 remain unemployed six months later. Total long-term unemployment rises thereafter and eventually reaches more 4.5 million individuals unemployed for more than 26 weeks and almost 2 million individuals unemployed for more than 46 weeks. Long-term unemployment rises even more in a more pessimistic recovery scenario, but remains below the level in the Great Recession due to a high amount of labor market churn.

This paper presents a flow-based methodology for real-time unemployment rate projections and shows that this approach performed considerably better at the onset of the COVID-19 recession in the spring 2020 in predicting the peak unemployment rate as well as its rapid decline over the year. It presents an alternative scenario analysis for 2021 based on this methodology and argues that the unemployment rate is likely to decline to 5.4 percent by the end of 2021. The predictive power of the methodology comes from its combined use of real-time data with the flow approach.

We read search theory's unemployment equilibrium condition as an Iso-Unemployment Curve(IUC).The IUC is the locus of job destruction rates and expected unemployment durations rendering the same unemployment level. A country's position along the curve reveals its preferences over the destruction-duration mix, while its distance from the origin indicates the unemployment level at which such preferences are satisfied Using a panel of 20 OECD countries over 1985-2008, we find employment protection legislation to have opposing efects on destructions and durations, while the effects of the remaining key institutional factors on both variables tend to reinforce each other. Implementing the right reforms could reduce job destruction rates by about 0.05 to 0.25 percentage points and shorten unemployment spells by around 10 to 60 days. Consistent with this, unemployment rates would decline by between 0.75 and 5.5 percentage points, depending on a country's starting position.

Based on a sample of unemployed men taken from the Spanish Labour Force Survey during the period 1987-1994.

The aim of the research is to determine whether recent high unemployment rates for youths, the aged, or minorities have been due to structural changes in the US economy or to high general unemployment rates. The focus of this paper is on groups classified by age, sex, and race. For each group, regression analysis was used to estimate the effect of a linear time trend and the overall unemployment rate on the unemployment rate for a specific group of workers. A significant time trend would support the hypothesis of a structural increase in unemployment. (Author).