Heterogeneous autoregressions in short T panel data models
Bibliographic Data
| ID | 21653574 |
|---|---|
| Authors | M Hashem Pesaran (0000-0001-5936-363X, Department of Economics University of Southern California Los Angeles California USA), Liying Yang (0000-0001-9211-0685, University of British Columbia, corresponding author), L T Yang (0000-0002-4570-8243, Sauder School of Business University of British Columbia Vancouver British Columbia Canada) |
| Year | 2024 |
| Volume | 39 |
| Issue | 7 |
| Pages | 1359-1378 |
| Publication date | 2024-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Applied Econometrics (JOURNAL) |
| Journal identifiers | ISSN: 1099-1255 • E-ISSN: 0883-7252 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/jae.3085 |
| OpenAlex | W4401467573 |
| Language | EN |
| Citations received | 1 |
| References cited | 35 |
This paper considers a first‐order autoregressive (AR) panel data model with individual‐specific effects and heterogeneous AR coefficients defined on the interval , thus allowing for some of the individual processes to have unit roots. It proposes estimators for the moments of the cross‐sectional distribution of the AR coefficients, assuming a random coefficient model for the AR coefficients without imposing any restrictions on the fixed effects. It is shown that the standard generalized method of moments estimators obtained under homogeneous slopes are biased. Small sample properties of the proposed estimators are investigated by Monte Carlo experiments and compared with a number of alternatives, both under homogeneous and heterogeneous slopes. It is found that a simple moment estimator of the mean of heterogeneous AR coefficients performs very well even for moderate sample sizes, but to reliably estimate the variance of AR coefficients, much larger samples are required. It is also required that the true value of this variance is not too close to zero. The utility of the heterogeneous approach is illustrated in the context of earnings dynamics
Autoregressive model · Econometrics · Economics · Estimator · Monte Carlo method · Panel data · Statistics · Fiscal Policy and Economic Growth · Housing Market and Economics · Mathematics · Spatial and Panel Data Analysis · Applied Mathematics
Estimating long-run relationships from dynamic heterogeneous panels
The use of time series processes to model the error structure of earnings in a longitudinal data analysis
On the Covariance Structure of Earnings and Hours Changes
Estimation of Dynamic Models with Error Components
The nature of precautionary wealth
Formulation and estimation of dynamic models using panel data
Income Variance Dynamics and Heterogeneity
Biases in Dynamic Models with Fixed Effects
Some Tests of Specification for Panel Data
Initial conditions and moment restrictions in dynamic panel data models
Dynamic Aspects of Earning Mobility
Unobserved Heterogeneity in Income Dynamics
Density Forecasts in Panel Data Models
Fixed-Effects and Related Estimators for Correlated Random-Coefficient and Treatment-Effect Panel Data Models
Precautionary Saving and Social Insurance
Income and Consumption
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |