Jinyuan Chang, Qiao Hu, Zhentao Shi, Jia Zhang
arXiv 26 Feb 2025 · Econometrics
arXiv:2502.18970 · PDF · DOI · OpenAlex · Extracted main text
Economic and financial models -- such as vector autoregressions, local projections, and multivariate volatility models -- feature complex dynamic interactions and spillovers across many time series. These models can be integrated into a unified framework, with high-dimensional parameters identified by moment conditions. As the number of parameters and moment conditions may surpass the sample size, we propose adding a double penalty to the empirical likelihood criterion to induce sparsity and facilitate dimension reduction. Notably, we utilize a marginal empirical likelihood approach despite temporal dependence in the data. Under regularity conditions, we provide asymptotic guarantees for our method, making it an attractive option for estimating large-scale multivariate time series models. We demonstrate the versatility of our procedure through extensive Monte Carlo simulations and three empirical applications, including analyses of US sectoral inflation rates, fiscal multipliers, and volatility spillover in China's banking sector.
appendix boundary found by appendix_command · 28% of the source is main text. Read the extracted text to check this.
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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Ramey \ Zubairy (2018) `Government spending multipliers in good times and in bad: Evidence from us historical data', Journal of Political Economy 126(2… | 0.874 | 6 | 2 | 100% |
| 2 | Chang, Tang \ Wu (2018) `A new scope of penalized empirical likelihood with high-dimensional estimating equations', The Annals of Statistics 46(6B), 318… | 0.843 | 4 | 3 | 75% |
| 3 | Kitamura (1997) `Empirical likelihood methods with weakly dependent processes', The Annals of Statistics 25(5), 2084–2102 | 0.737 | 3 | 2 | 100% |
| 4 | Chang, Chen, Tang \ Wu (2021) `High-dimensional empirical likelihood inference', Biometrika 108(1), 127–147 | 0.644 | 4 | 2 | 50% |
| 5 | Chang, Chen \ Chen (2015) `High dimensional generalized empirical likelihood for moment restrictions with dependent data', Journal of Econometrics 185(1),… | 0.644 | 2 | 2 | 100% |
| 6 | Engle \ Kroner (1995) `Multivariate simultaneous generalized ARCH', Econometric Theory 11(1), 122–150 | 0.644 | 2 | 2 | 100% |
| 7 | Jordà (2005) `Estimation and inference of impulse responses by local projections', American Economic Review 95(1), 161–182 | 0.644 | 2 | 2 | 100% |
| 8 | Owen (1988) `Empirical likelihood ratio confidence intervals for a single functional', Biometrika 75(2), 237–249 | 0.644 | 2 | 2 | 100% |
| 9 | Qin \ Lawless (1994) `Empirical likelihood and general estimating equations', The Annals of Statistics 22(1), 300–325 | 0.644 | 2 | 2 | 100% |
| 10 | Chang, Shi \ Zhang (2023) `Culling the herd of moments with penalized empirical likelihood', Journal of Business & Economic Statistics 41(3), 791–805 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 76 scored citations.