TY - JOUR
T1 - Intriguing yet simple skewness: kurtosis relation in economic and demographic data distributions, pointing to preferential attachment processes
AU - Cerqueti, Roy
PY - 2018/9/10
Y1 - 2018/9/10
N2 - In this paper, we propose that relations between high-order moments of data distributions, for example, between the skewness (S) and kurtosis (K), allow to point to theoretical models with understandable structural parameters. The illustrative data concern two cases: (i) the distribution of income taxes and (ii) that of inhabitants, after aggregation over each city in each province of Italy in 2011. Moreover, from the rank-size relationship, for either S or K, in both cases, it is shown that one obtains the parameters of the underlying (hypothetical) modeling distribution: in the present cases, the 2-parameter Beta function, itself related to the Yule–Simon distribution function, whence suggesting a growth model based on the preferential attachment process.
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Applied Statistics on [date of publication], available online: http://www.tandfonline.com/10.1080/02664763.2017.1413077.
AB - In this paper, we propose that relations between high-order moments of data distributions, for example, between the skewness (S) and kurtosis (K), allow to point to theoretical models with understandable structural parameters. The illustrative data concern two cases: (i) the distribution of income taxes and (ii) that of inhabitants, after aggregation over each city in each province of Italy in 2011. Moreover, from the rank-size relationship, for either S or K, in both cases, it is shown that one obtains the parameters of the underlying (hypothetical) modeling distribution: in the present cases, the 2-parameter Beta function, itself related to the Yule–Simon distribution function, whence suggesting a growth model based on the preferential attachment process.
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Applied Statistics on [date of publication], available online: http://www.tandfonline.com/10.1080/02664763.2017.1413077.
U2 - 10.1080/02664763.2017.1413077
DO - 10.1080/02664763.2017.1413077
M3 - Article
SN - 0266-4763
SP - 2202
EP - 2218
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
ER -