Estimating production functions with control functions when capital is measured with error

被引:14
|
作者
Kim, Kyoo Il [1 ]
Petrin, Amil [2 ,3 ]
Song, Suyong [4 ]
机构
[1] Michigan State Univ, E Lansing, MI 48824 USA
[2] Univ Minnesota, Minneapolis, MN 55455 USA
[3] NBER, Cambridge, MA 02138 USA
[4] Univ Iowa, Iowa City, IA 52242 USA
关键词
Production function; Unobserved productivity; Measurement error; Nonparametric estimation; Control variate; CONDITIONAL MOMENT RESTRICTIONS; MODELS;
D O I
10.1016/j.jeconom.2015.06.016
中图分类号
F [经济];
学科分类号
02 ;
摘要
We revisit the production function estimators of Olley and Pakes (1996) and Levinsohn and Petrin (2003). They use control functions to address the simultaneous determination of inputs and productivity. Both assume that input demand is a monotonic function of productivity holding capital constant and then invert this function to condition on productivity during estimation. If the observed capital variable is measured with error, input demand will not generally be monotonic in the productivity shock holding observed capital constant. We develop consistent estimators of production function parameters in the face of this measurement error. Our identification and estimation results combine the nonlinear measurement error literature with Wooldridge's (2009) joint estimation method to construct a proxy for productivity that addresses simultaneity. Our approach directly extends to the case where other inputs like intermediates or labor are observed with error. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:267 / 279
页数:13
相关论文
共 50 条