Jiti Gao, Guangming Pan, Yanrong Yang, Bo Zhang
arXiv 15 Apr 2019 · Econometrics · 1 citations (OpenAlex)
arXiv:1904.06843 · PDF · DOI · OpenAlex · Extracted main text
Accurate estimation for extent of cross{sectional dependence in large panel data analysis is paramount to further statistical analysis on the data under study. Grouping more data with weak relations (cross{sectional dependence) together often results in less efficient dimension reduction and worse forecasting. This paper describes cross-sectional dependence among a large number of objects (time series) via a factor model and parameterizes its extent in terms of strength of factor loadings. A new joint estimation method, benefiting from unique feature of dimension reduction for high dimensional time series, is proposed for the parameter representing the extent and some other parameters involved in the estimation procedure. Moreover, a joint asymptotic distribution for a pair of estimators is established. Simulations illustrate the effectiveness of the proposed estimation method in the finite sample performance. Applications in cross-country macro-variables and stock returns from S&P 500 are studied.
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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 | N. Bailey, G. Kapetanios, M.H. Pesaran (2015) Exponent of cross-sectional dependence: estimation and inference | 1.000 | 16 | 7 | 100% |
| 2 | J. S. Bai, S. Ng (2002) Determine the number of factors in approximate factor models | 0.843 | 3 | 3 | 100% |
| 3 | J. Fan, Y. Liao, M. Mincheva (2011) Large covariance estimation by thresholding principal orthogonal complements | 0.585 | 3 | 1 | 100% |
| 4 | J. Q. Fan, Y. Y. Fan, J. C. Lv (2008) High dimensional covariance matrix estimation using a factor model | 0.511 | 2 | 1 | 100% |
| 5 | V. Sarafidis, T. Wansbeek (2012) Cross-sectional dependence in panel data analysis | 0.511 | 2 | 1 | 100% |
| 6 | L. Alessi, M. Barigozzi, M. Capasso (2010) Improved penalization for determining the number of factors in approximate static factor models | 0.405 | 1 | 1 | 100% |
| 7 | S.C. Ahn, A.R. Horenstein (2013) Eigenvalue ratio test for the number of factors | 0.405 | 1 | 1 | 100% |
| 8 | B.H. Baltagi, Q. Feng, C. Kao (2012) A large multiplier test for cross-sectional dependence in a fixed effects panel data model | 0.405 | 1 | 1 | 100% |
| 9 | J. Boivin, S. Ng (2006) Are more data always better for factor analysis? | 0.405 | 1 | 1 | 100% |
| 10 | G. Chamberlain (1983) Funds, factors and diversification in arbitrage pricing theory | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 24 scored citations.