A Reexamination of Card and Krueger's State-Level Study of the Minimum Wage

Card and Krueger's (1995) difference-in-difference study of the 1990-1991 federal minimum wage hikes compared states by the proportion of workers directly affected by the minimum wage. They found "no evidence that the increase in the minimum wage significantly lowered teenage employment rates more in highly affected states" and they concluded the minimum wage did not reduce employment. Their paper was highly influential and convinced many that the minimum wage did not reduce employment. However, when I apply their model to the 1996-1997 federal minimum wage hike, I find that increases in the minimum wage significantly lowered teenage employment rates more in highly affected states. Using Card and Krueger's interpretation, this implies the minimum wage did reduce teenage employment.     

MINIMUM WAGES AND TIPPED SERVERS

Tips allow restaurants to pay servers lower wages. As more servers are hired, each serves fewer meals and earns less in tips. As a result, restaurants must pay a higher wage. This gives them monopsony power over wages. Over some range, a higher minimum wage should increase employment. Empirically, we found the full "reverse C" monopsony pattern of employment for restaurants, with employment first going up and then down as the minimum wage is increased.     

THE EFFECT OF MINIMUM WAGES IN THE PRESENCE OF FRINGE BENEFITS: AN EXPANDED MODEL

Firms may react to a minimum wage hike by reducing their expenditures on fringe benefits. This possibility is incorporated into an expanded model of minimum wages. A set of predictions that differentiate this expanded model from current minimum wage models is derived and tested. The expanded model is shown to better predict the effect of minimum wages on labor force participation, quit rates, and prices than previous models. An interesting result of the expanded model is that a covered worker may be worse off due to a minimum wage hike even if he retains his job.     

DIAGNOSING ORDER PLANNING PERFORMANCE AT A NAVY MAINTENANCE AND REPAIR ORGANIZATION,USING LOGISTIC REGRESSION

We present a tool to diagnose the behavior of planners in complex production processes and to establish improvement potential for the delivery performance by changing the planning behavior. Scientific literature on production control offers valuable knowledge, but the complexity of real‐life processes makes it impossible to directly apply this knowledge in real‐life. The presented tool identifies possible deficiencies in the current way of managing the business processes, by matching the scientific knowledge on order planning with data reflecting the real‐life processes via logistic regression. A case study at a maintenance organization illustrates the diagnosis tool.