Abstract

The curvature of the marginal revenue product curve plays an important role in most theoretic microeconomic models since it determines the size of profit contribution to an employer and optimality conditions of solutions. There are many well established introductory and intermediate microeconomic textbooks portray marginal revenue product curves as linear or concave to the origin. In nearly all cases, the MRP cannot be linear, nor can it be concave. In this analysis, most of the well-known production functions generate convex MRP curves.

Highlights

  • Input hiring decisions play an important role in microeconomic theory

  • The curvature of the marginal revenue product curve plays an important role in most theoretic microeconomic models since it determines the size of profit contribution to an employer and optimality conditions of solutions

  • In a competitive output market, it is known as the value of the marginal product (VMP), whereas in a monopoly market, the additional monetary contribution is often referred to as the marginal revenue product (MRP)

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Summary

Introduction

Input hiring decisions play an important role in microeconomic theory. These decisions are based on the monetary contribution of a variable input to the firm compared with its cost. In a competitive output market, it is known as the value of the marginal product (VMP), whereas in a monopoly market, the additional monetary contribution is often referred to as the marginal revenue product (MRP). These two concepts, VMP and MRP, are equal in the competitive output market as its output price equals marginal revenue. We analyze the shape of the MRP curve mathematically, present a set of simulations for a variety of well-known production functions frequently used in microeconomics textbooks. The curvature of the MRP curve plays an important role in most standard microeconomic models (see e.g. Takayama [2], Baumol and Klevorick [3]) in determining the characteristics of optimal solutions

Shapes of MRP Curves
Case I
Findings
Conclusions
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