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We first estimate the sample mean, autocovariances, and autocorrelations for each unit and then apply kernel smoothing to compute their density functions. The dependence of the kernel estimator on bandwidth makes asymptotic bias of very high order affect the required condition on the relative magnitudes of the cross-sectional sample size (N) and the time-series length (T). In particular, it makes the condition on N and T stronger and more complicated than those typically observed in the long-panel literature without kernel smoothing. We also consider a split-panel jackknife method to correct bias and construction of confidence intervals. An empirical application illustrates our procedure.<\/jats:p>","DOI":"10.1093\/ectj\/utz019","type":"journal-article","created":{"date-parts":[[2019,10,30]],"date-time":"2019-10-30T18:51:48Z","timestamp":1572461508000},"page":"156-175","source":"Crossref","is-referenced-by-count":17,"title":["Kernel estimation for panel data with heterogeneous dynamics"],"prefix":"10.1093","volume":"23","author":[{"given":"Ryo","family":"Okui","sequence":"first","affiliation":[{"name":"Department of Economics and the Institute of Economic Research, Seoul National University, Building 16, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takahide","family":"Yanagi","sequence":"additional","affiliation":[{"name":"Graduate School of Economics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, 606-8501, 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