Homogeneity pursuit in panel data models: Theory and application

By Wuyi Wang, Peter C. B. Phillips, Liangjun Su. Journal of applied econometrics, 2018

68 citations recorded by the source corpus.

This paper studies estimation of a panel data model with latent structures where individuals can be classified into different groups where slope parameters are homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS which is a systematic extension of the CARDS procedure proposed by Ke, Fan, and Wu (2015) in a cross section framework. The extension addresses the problem of comparing vector coefficients in a panel model for homogeneity and introduces a new concept of controlled classification of multidimensional quantities called the segmentation net. We show that the Panel-CARDS method identifies group structure asymptotically and consistently estimates model parameters at the same time. External information on the minimum number of elements within each group is not required but can be used to improve the accuracy of classification and estimation in finite samples. Simulations evaluate performance and corroborate the asymptotic theory in several practical design settings. Two empirical economic applications are considered: one explores the effect of income on democracy by using cross-country data over the period 1961-2000; the other examines the effect of minimum wage legislation on unemployment in 50 states of the United States over the period 1988-2014. Both applications reveal the presence of latent groupings in these panel data.

Subfields: Economics and Econometrics, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/42a7bc216b081b25837d4e4b707f7216e3b606eb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Liangjun Su
2. Xia Wang
3. Sainan Jin
4. Yiguo Sun
5. Xun Lu
6. Yixiao Sun
7. Emir Malikov
8. Peter C. B. Phillips

In Sociology and Political Science

1. Sainan Jin
2. Xia Wang
3. Liangjun Su

In Statistics and Probability

1. Liangjun Su
2. Xia Wang
3. Sainan Jin
4. Halbert White
5. Xun Lu
6. Tzee-Ming Huang
7. Yixiao Sun
8. Xiaofeng Shao

Citations in the corpus

• Sieve Estimation of Time-Varying Panel Data Models With Latent Structures (2019, methodology): “To explore homogeneity of coefficients, Ke, Fan, and Wu (2015) proposed a new method called clustering algorithm in regression via data-driven segmentation (CARDS), which is extended to the panel setup by Wang, Phillips, and Su (2017).”