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Functional instrumental variable regression with an application to estimating the impact of immigration on native wages

Dakyung Seong, Won-Ki Seo

arXiv 25 Oct 2021 · Econometrics · publishedEconometric Theory (2024) · 2 citations (OpenAlex)

arXiv:2110.12722 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Functional linear regression gets its popularity as a statistical tool to study the relationship between function-valued response and exogenous explanatory variables. However, in practice, it is hard to expect that the explanatory variables of interest are perfectly exogenous, due to, for example, the presence of omitted variables and measurement error. Despite its empirical relevance, it was not until recently that this issue of endogeneity was studied in the literature on functional regression, and the development in this direction does not seem to sufficiently meet practitioners' needs; for example, this issue has been discussed with paying particular attention on consistent estimation and thus distributional properties of the proposed estimators still remain to be further explored. To fill this gap, this paper proposes new consistent FPCA-based instrumental variable estimators and develops their asymptotic properties in detail. Simulation experiments under a wide range of settings show that the proposed estimators perform considerably well. We apply our methodology to estimate the impact of immigration on native wages.

Citation extraction

53
references
164
in-text mentions
53
distinct cited
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self-citations
21,330
main-text words

appendix boundary found by appendix_titled_section at “Appendix to Section \ref{sec:estimators} on ``Functional IV estimator" \label{sec:pf}” · 44% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chen, C., S. Guo, and X. Qiao (2022) Functional linear regression: Dependence and error contamination1.00093100%
2Hall, P. and J. L. Horowitz (2007) Methodology and convergence rates for functional linear regression1.00083100%
3Benatia, D., M. Carrasco, and J.-P. Florens (2017) Functional linear regression with functional response0.96721690%
4Park, J. Y. and J. Qian (2012) Functional regression of continuous state distributions0.96510590%
5Florens, J.-P. and S. Van Bellegem (2015) Instrumental variable estimation in functional linear models0.92843100%
6Mas, A (2007) Weak convergence in the functional autoregressive model0.87492100%
7Imaizumi, M. and K. Kato (2018) PCA-based estimation for functional linear regression with functional responses0.8558362%
8Horváth, L. and P. Kokoszka (2012) Inference for Functional Data with Applications0.7373367%
9Ramsay, J. O. and B. W. Silverman (2005) Functional Data Analysis0.7373367%
10Card, D (2009) Immigration and inequality0.73732100%

Showing the top 10 of 53 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Binary response model with many weak instruments0.92843
2Functional Regression with Nonstationarity and Error Contamination: Application to the Economic Impact of Climate Change0.862255
3Nonlinear Temperature Sensitivity of Residential Electricity Demand: Evidence from a Distributional Regression Approach0.679323
4Functional Linear Projection and Impulse Response Analysis0.610225