Mechanisms, Distribution, Mediators, and Policy Implications of Earnings Instability

The magnitude of month-to-month earnings volatility has proven difficult to measure systematically for a large and representative sample of workers. Economist Peter Ganong will combine paycheck, scheduling, and job title data to identify firm-level and managerial sources of pay volatility. He will also interview firm managers and analyze how changes in management or scheduling affect volatility. Ganong draws on two data sources. The first is from an anonymous payroll processing company, which issues paychecks to between two and four million employees each month at small firms. The data captures hours, earnings, wages, and paid leave at the paycheck level from 2010 to 2023. The second data source is bank account data from the JPMorgan Chase Institute. This dataset, which includes information on about 20 million households per month from 2012-2018, allows Ganong to link income and consumption to understand the welfare-relevant implications of earnings volatility.