Publication Type
Working Paper
Version
publishedVersion
Publication Date
4-2013
Abstract
Monotonicity in a scalar unobservable is a crucial identifying assumption for an important class of nonparametric structural models accommodating unobserved heterogeneity. Tests for this monotonicity have previously been unavailable. This paper proposes and analyzes tests for scalar monotonicity using panel data for structures with and without time-varying unobservables, either partially or fully nonseparable between observables and unobservables. Our nonparametric tests are computationally straightforward, have well behaved limiting distributions under the null, are consistent against precisely specified alternatives, and have standard local power properties. We provide straightforward bootstrap methods for inference. Some Monte Carlo experiments show that, for empirically relevant sample sizes, these reasonably control the level of the test, and that our tests have useful power. We apply our tests to study asset returns and demand for ready-to-eat cereals.
Keywords
monotonicity, nonparametric, nonseparable, specification test, unobserved heterogeneity
Discipline
Econometrics | Economics
Research Areas
Econometrics
First Page
1
Last Page
43
Citation
SU, Liangjun; HODERLEIN, Stefan; and WHITE, Halbert.
Testing Monotonicity in Unobservables with Panel Data. (2013). 1-43.
Available at: https://ink.library.smu.edu.sg/soe_research/1717
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.