Journal ArticleDOI
Testing for unit roots in panel data: are wages on different bargaining levels cointegrated?
Jörg Breitung,Wolfgang Meyer +1 more
TLDR
This paper applied various unit root tests to a panel of wage data and found that firm and industry wages both possess a unit root in the autoregressive representation of the distribution of hourly wages.Abstract:
Theoritical considerations suggest that spillover forces equalize wages for similar jobs Thus, it is expected that firm wages are cointegrated with the corresponding wage rates on an industrial level In this paper we apply various unit root tests to a panel of wage data We show that the familiar techniques can be adopted to this type of data allowing for unobserved heterogeneity and common time effects Our results suggest that firm and industry wages both possess a unit root in the autoregressive representation However, ther is only weak evidence for a cointegration realtionshipread more
Citations
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Journal ArticleDOI
Unit root tests in panel data: asymptotic and finite-sample properties
TL;DR: In this article, the authors consider pooling cross-section time series data for testing the unit root hypothesis, and they show that the power of the panel-based unit root test is dramatically higher, compared to performing a separate unit-root test for each individual time series.
Book
Econometric Analysis of Panel Data
TL;DR: In this article, the authors proposed a two-way error component regression model for estimating the likelihood of a particular item in a set of data points in a single-dimensional graph.
Journal ArticleDOI
A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test
G. S. Maddala,Shaowen Wu +1 more
TL;DR: The Im-Pesaran-Shin (IPS) test as discussed by the authors relaxes the restrictive assumption of the LL test and is best viewed as a test for summarizing the evidence from independent tests of the sample hypothesis.
Journal ArticleDOI
Spurious regression and residual-based tests for cointegration in panel data
TL;DR: In this paper, the null distribution of residual-based cointegration tests depends on the asymptotics of the least-squares dummy variable (LSDV) estimator and other conventional statistics.
Journal ArticleDOI
Testing for Stationarity in Heterogeneous Panel Data
TL;DR: In this article, a residual-based Lagrange multiplier (LM) test for a null that the individual observed series are stationary around a deterministic level or around deterministic trend against the alternative of a unit root in panel data is proposed.
References
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Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI
Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations.
Manuel Arellano,Stephen Bond +1 more
TL;DR: In this article, the generalized method of moments (GMM) estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables.
Journal ArticleDOI
The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics
Trevor Breusch,Adrian Pagan +1 more
TL;DR: The Lagrange multiplier (LM) statistic as mentioned in this paper is based on the maximum likelihood ratio (LR) procedure and is used to test the effect on the first order conditions for a maximum of the likelihood of imposing the hypothesis.
Journal ArticleDOI
Trends and random walks in macroeconmic time series: Some evidence and implications
TL;DR: In this paper, the authors investigate whether macroeconomic time series are better characterized as stationary fluctuations around a deterministic trend or as non-stationary processes that have no tendency to return to the deterministic path, and conclude that macroeconomic models that focus on monetary disturbances as a source of purely transitory fluctuations may not be successful in explaining a large fraction of output variation.