This paper considers identification and estimation of ceteris paribus effects of continuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We find that these derivatives are identified with two time periods for 'stayers', i.e. for individuals with the same regressor values in two time periods. We show that the identification results carry over to models that allow location and scale time effects. We propose nonparametric series methods and a weighted bootstrap scheme to estimate and make inference on the identified effects. The bootstrap proposed allows uniform inference for function-valued parameters such as quantile effects over a region of quantiles or regressor values. An empirical application to Engel curve estimation with panel data illustrates the results.
Authors
Whitney K. Newey
Associate Professor Boston College
Ivan Fernandez-Val
Hajo Holzmann
Working Paper details
- DOI
- 10.1920/wp.cem.2013.6613
- Publisher
- IFS
Suggested citation
Chernozhukov, V et al. (2013). Nonparametric identification in panels using quantiles. London: IFS. Available at: https://ifs.org.uk/publications/nonparametric-identification-panels-using-quantiles (accessed: 15 May 2024).
Related documents
More from IFS
Understand this issue
Where next for the state pension?
13 December 2023
Social mobility and wealth
12 December 2023
Autumn Statement 2023: IFS analysis
23 November 2023
Policy analysis
The past and future of UK health spending
14 May 2024
Recent trends in and the outlook for health-related benefits
19 April 2024
Progression of nurses within the NHS
12 April 2024
Academic research
The role of hospital networks in individual mortality
13 May 2024
Forced displacement, mental health, and child development: Evidence from Rohingya refugees
10 May 2024
Leveraging edutainment and social networks to foster interethnic harmony
10 May 2024