Academic journal article Contemporary Economic Policy

A Note on the Nonlinear Effect of Minimum Wage Increases

Academic journal article Contemporary Economic Policy

A Note on the Nonlinear Effect of Minimum Wage Increases

Article excerpt

I. INTRODUCTION

President Obama called for an increase of the minimum wage from $7.25 to $9.00 per hour in 2013 and is now proposing an increase to $10.10. The Congressional Budget Office (CBO 2014) estimates that increasing the minimum wage to $9.00 and $ 10.10 would lead to a net loss of 100.000 and 500,000 jobs, respectively. The CBO estimates rely on past empirical studies that report an elasticity of employment with respect to changes in minimum wages. These elasticities are then adjusted to account for the fraction of young workers who earn less than the minimum wage and the average amount below the new minimum that workers earn. As their estimates rely on past empirical studies that occurred when the minimum wage was low relative to the median wage, the CBO projections may not be reliable for large policy changes due to the nonlinear effects of minimum wage changes that occur when greater numbers of workers are impacted. Scaling previously estimated elasticities for changes in overall youth employment does not necessarily predict future unemployment changes.

Increasing the minimum wage from $5.15 to $7.25 an hour will not have the same effect on unemployment as increasing the minimum wage from $7.25 per hour to $10.10 per hour even though the percentage changes in the wage levels are approximately equal. In a standard search model with minimum wages such as Flinn (2006), higher minimum wages have nonlinear effects on the unemployment rate. This occurs because higher minimum wages impact a greater fraction of workers as it cuts deeper into the underlying productivity distribution that is not uniform. Modeling the wage bargaining process between workers and firms allows the model to predict which workers will receive a raise to the level of the minimum wage and which affected workers will lose their jobs.

While the logic of unemployment in a search and matching model is clear, this article documents the pattern in the life cycle labor search model developed in Gorry (2013). The model provides an ideal framework to assess the impact of minimum wages on different age groups as it replicates observed age patterns of unemployment and accounts for the value of experience to workers as they search for jobs. (1) Minimum wages can have lasting impacts on individuals because workers with unemployment spells early in life accumulate less job experience, generating worse outcomes later in life. Minimum wages interact with a worker's ability to find employment leading to changes in job finding and separation rates. Due to these interactions, the CBO (2014) estimates do not capture the lull impact of minimum wages over the life cycle.

Finally, assessing the impact of the minimum wage by updating Gorry (2013) to match current economic conditions allows us to compare the effects of proposed minimum w age increases with those that occurred during the recent recession. Gorry (2013) finds that minimum wage increases account for about 25% of the increase in unemployment among young high school-educated workers during the recession. Clemens and Wither (2014) find similar sized effects using an empirical approach. In contrast, we find the proposed further increases can have much more damaging effects on employment outcomes of young workers. While the increase to $9.00 per hour has a moderate impact on youth unemployment, further increases can have an extreme impact on unemployment outcomes, further highlighting the nonlinear effect of the model. These increases are especially problematic as (hey can also cause worse employment outcomes for those workers later in life as workers are unable to gain as much experience when young.

While the wage distribution is an endogenous object in the model, the empirical plausibility of the results can be checked by looking at the empirical wage distribution in the data. To do this, we compute the fraction of hourly workers who earn less than $9.00 and $10. …

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