The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Estimating Vector Autoregressions with Panel Data
Abstract
This paper considers estimation and testing of vector autoregressio n coefficients in panel data, and applies the techniques to analyze the dynamic relationships between wages an d hours worked in two samples of American males. The model allows for nonstationary individual effects and is estimated by applying instrumental variables to the quasi-differenced autoregressive equations. The empirical results suggest the absence of lagged hours in the wage forecasting equation. The results also show that lagged hours is important in the hours equation. Copyright 1988 by The Econometric Society.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
Cited by
Arellano, M., & Bond, S. (1991) · The Review of Economic Studies · doi:10.2307/2297968 · Cited by 33,272
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571
Another look at the instrumental variable estimation of error-components models
Arellano, M., & Bover, O. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01642-d · Cited by 19,880
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1995) · Working Paper Series · doi:10.1920/wp.ifs.1995.9517 · Cited by 14,755
Unit root tests in panel data: asymptotic and finite-sample properties
Levin, A., Lin, C.-F., & James Chu, C.-S. (2002) · Journal of Econometrics · doi:10.1016/s0304-4076(01)00098-7 · Cited by 12,849
How to do Xtabond2: An Introduction to Difference and System GMM in Stata
Roodman, D. (2009) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0900900106 · Cited by 9,848
Mostly Harmless Econometrics: An Empiricist's Companion
Angrist, J. D., & Pischke, J.-S. (2009) · doi:10.1515/9781400829828 · Cited by 9,467
Testing for Granger non-causality in heterogeneous panels
Dumitrescu, E.-I., & Hurlin, C. (2012) · Economic Modelling · doi:10.1016/j.econmod.2012.02.014 · Cited by 5,922
Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure
Pesaran, M. H. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00692.x · Cited by 5,078
The analysis of household surveys: A microeconometric approach to development policy
Deaton, A. (1997) · doi:10.1596/0-8018-5254-4 · Cited by 4,877
Financial intermediation and growth: Causality and causes
Levine, R., Loayza, N., & Beck, T. (2000) · Journal of Monetary Economics · doi:10.1016/s0304-3932(00)00017-9 · Cited by 4,414
Finance and the sources of growth
Beck, T., Levine, R., & Loayza, N. (2000) · Journal of Financial Economics · doi:10.1016/s0304-405x(00)00072-6 · Cited by 3,711
Do institutional investors drive corporate social responsibility? International evidence
Dyck, A., Lins, K. V., Roth, L., & Wagner, H. F. (2019) · Journal of Financial Economics · doi:10.1016/j.jfineco.2018.08.013 · Cited by 2,547
Finance, inequality and the poor
Beck, T., Demirgüç-Kunt, A., & Levine, R. (2007) · Journal of Economic Growth · doi:10.1007/s10887-007-9010-6 · Cited by 2,377
Is Learning by Exporting Important? Micro-Dynamic Evidence from Colombia, Mexico, and Morocco
Clerides, S. K., Lach, S., & Tybout, J. R. (1998) · The Quarterly Journal of Economics · doi:10.1162/003355398555784 · Cited by 2,272
Estimating dynamic panel data models: a guide for macroeconomists
Judson, R. A., & Owen, A. L. (1999) · Economics Letters · doi:10.1016/s0165-1765(99)00130-5 · Cited by 2,171
Stock markets, banks, and growth: Panel evidence
Beck, T., & Levine, R. (2004) · Journal of Banking & Finance · doi:10.1016/s0378-4266(02)00408-9 · Cited by 2,067
Panel Data Models With Interactive Fixed Effects
(2009) · Econometrica · doi:10.3982/ecta6135 · Cited by 1,690
Bernard, A. B., & Jensen, J. B. (2004) · Review of Economics and Statistics · doi:10.1162/003465304323031111 · Cited by 1,591
Synthetic Difference-in-Differences
Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., & Wager, S. (2021) · American Economic Review · doi:10.1257/aer.20190159 · Cited by 1,518
Panel Data Econometrics in R : The plm Package
Croissant, Y., & Millo, G. (2008) · Journal of Statistical Software · doi:10.18637/jss.v027.i02 · Cited by 1,243
Equity markets and growth: Cross-country evidence on timing and outcomes, 1980–1995
Rousseau, P. L., & Wachtel, P. (2000) · Journal of Banking & Finance · doi:10.1016/s0378-4266(99)00123-5 · Cited by 772
Dynamic panels with threshold effect and endogeneity
Seo, M. H., & Shin, Y. (2016) · Journal of Econometrics · doi:10.1016/j.jeconom.2016.03.005 · Cited by 698
Venture Capital, Entrepreneurship, and Economic Growth
Samila, S., & Sorenson, O. (2011) · Review of Economics and Statistics · doi:10.1162/rest_a_00066 · Cited by 673
Blunt Instruments: Avoiding Common Pitfalls in Identifying the Causes of Economic Growth
Bazzi, S., & Clemens, M. A. (2013) · American Economic Journal: Macroeconomics · doi:10.1257/mac.5.2.152 · Cited by 640
Is working capital management value-enhancing? Evidence from firm performance and investments
Aktas, N., Croci, E., & Petmezas, D. (2015) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2014.12.008 · Cited by 534
A homogeneous approach to testing for Granger non-causality in heterogeneous panels
Juodis, A., Karavias, Y., & Sarafidis, V. (2021) · Empirical Economics · doi:10.1007/s00181-020-01970-9 · Cited by 487
Does Financial Liberalization Reduce Financing Constraints?
Laeven, L. (2003) · Financial Management · doi:10.2307/3666202 · Cited by 462
Effects of the minimum wage on employment dynamics
Meer, J., & West, J. (2016) · Journal of Human Resources · doi:10.3368/jhr.51.2.0414-6298r1 · Cited by 446
Colicev, A., Malshe, A., Pauwels, K., & O'Connor, P. (2018) · Journal of Marketing · doi:10.1509/jm.16.0055 · Cited by 370
Hakim, M. M., & Merkert, R. (2016) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2016.09.006 · Cited by 217
Information and Communication Technology Use and Economic Growth
Farhadi, M., Ismail, R., & Fooladi, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048903 · Cited by 212
Content marketing in e-commerce platforms in the internet celebrity economy
Geng, R., Wang, S., Chen, X., Song, D., & Yu, J. (2020) · Industrial Management & Data Systems · doi:10.1108/imds-05-2019-0270 · Cited by 205
Pradhan, R. P., Arvin, M. B., Hall, J. H., & Bahmani, S. (2014) · Review of Financial Economics · doi:10.1016/j.rfe.2014.07.002 · Cited by 184
Bank Regulations and Income Inequality: Empirical Evidence
Delis, M. D., Hasan, I., & Kazakis, P. (2014) · Review of Finance · doi:10.1093/rof/rft039 · Cited by 167
Biofuels, environmental sustainability and food security: A review of 51 countries
Subramaniam, Y., Masron, T. A., & Azman, N. H. N. (2020) · Energy Research & Social Science · doi:10.1016/j.erss.2020.101549 · Cited by 130
Institutions and the finance–growth nexus: Empirical evidence from MENA countries
Gazdar, K., & Cherif, M. (2015) · Borsa Istanbul Review · doi:10.1016/j.bir.2015.06.001 · Cited by 118
Financial intermediation and economic growth: Does income matter?
Seven, Ü., & Yetkiner, H. (2016) · Economic Systems · doi:10.1016/j.ecosys.2015.09.004 · Cited by 96
A New Look at Oligopoly: Implicit Collusion Through Portfolio Diversification
Azar, J. (2012) · doi:10.2139/ssrn.1993364 · Cited by 87
Alexiou, C., Vogiazas, S., & Nellis, J. G. (2018) · International Journal of Finance & Economics · doi:10.1002/ijfe.1609 · Cited by 68
Bonhomme, S., & Sauder, U. (2011) · Review of Economics and Statistics · doi:10.1162/rest_a_00164 · Cited by 58
Hollingsworth, A., & Wing, C. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3592088 · Cited by 53
Causal models for longitudinal and panel data: a survey
Arkhangelsky, D., & Imbens, G. (2024) · The Econometrics Journal · doi:10.1093/ectj/utae014 · Cited by 50
Can aging population affect economic growth through the channel of government spending?
Temsumrit, N. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e19521 · Cited by 44
Asteriou, D., Spanos, K., & Trachanas, E. (2024) · International Journal of Finance & Economics · doi:10.1002/ijfe.2793 · Cited by 37
“Following Holtz-Eakin et al. (1988), Arellano and Bond (1991) developed a GMM estimator that instruments the differenced variables with all their available lags in levels.”
MethodBond Market Development, Economic Growth and Other Macroeconomic Determinants: Panel VAR Evidence
Pradhan, R. P., Arvin, M. B., Bennett, S. E., Nair, M., & Hall, J. H. (2016) · Asia-Pacific Financial Markets · doi:10.1007/s10690-016-9214-x · Cited by 30
FinTech and financial inclusion in emerging and developing economies: a system GMM model
Mashoene, M., Tweneboah, G., & Schaling, E. (2025) · Cogent Social Sciences · doi:10.1080/23311886.2025.2491701 · Cited by 18
Metadata
- Authors
- Holtz-Eakin, D., Newey, W., & Rosen, H. S.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1988-11
- Volume
- 56
- Issue
- 6
- Pages
- 1371
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2092532477
- Cited by
- 4,239
- References
- 1
- FWCI
- 18.72
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.