پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 636 |
| تعداد مقالات | 9,327 |
| تعداد مشاهده مقاله | 67,937,155 |
| تعداد دریافت فایل اصل مقاله | 21,912,370 |
Small area estimation of labor force indicators using the multinomial logit mixed model | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 16، دوره 15، شماره 1، فروردین 2024، صفحه 191-198 اصل مقاله (343.45 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.29180.4080 | ||
| نویسندگان | ||
| Anita Abounoori* ؛ Mohammadreza Faghihi Habibabadi | ||
| Department of Statistics, Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran | ||
| تاریخ دریافت: 12 آبان 1401، تاریخ بازنگری: 28 آذر 1401، تاریخ پذیرش: 19 دی 1401 | ||
| چکیده | ||
| Small area estimation methods have been considered in various fields, especially medicine, agriculture, economics, social sciences, and political Science. These methods have many applications in providing reliable statistics for small-sample or non-sample statistical areas. In estimating the small area, there are two approaches: the basic design and the basic model. In this paper, a model-based approach to labor force indicators is considered using a multinomial mixed Logit model. The practical application of the method proposed in this article is to estimate the total number of employees, unemployed and unemployment rate using household income and expenditure data for Semnan province by cities; Semnan, Shahroud, Damghan and Garmsar concerning the period 2011-2016. Finally, we have found the estimates of unemployment rate for Garmsar (9.14), Semnan (9.84), Damghan (11.29), and Shahroud (12.40) in 2016. The more distance from Tehran (the Iranian Capital), the more is the unemployment rate! | ||
| کلیدواژه‌ها | ||
| Small Area Estimation؛ Labor Force؛ Logit Mixed Model؛ Iran | ||
| مراجع | ||
|
[1] G.S. Datta, P. Lahiri and T. Maiti, Empirical Bayes estimation of median income of four-person families by state using time series and cross-sectional data, J. Statist. Plann. Inference 102 (2002), no. 1, 83–97. [2] G.S. Datta, P. Lahiri, T. Maiti and K.L. Lu, Hierarchical Bayes estimation of unemployment rates for the states of the US, J. Amer. Statist. Associat. 94 (1999), no. 448, 1074–1082. [3] M.D. Esteban, D. Morales, A. P´erez and L. Santamarıa, Small area estimation of poverty proportions under area-level time models, Comput. Statist. Data Anal. 56 (2012), no. 10, 2840–2855. [4] R.E. Fay III and R.A. Herriot, Estimates of income for small places: an application of James-Stein procedures to census data, J. Amer. Statist. Associat. 74 (1979), no. 366a, 269–277. [5] M. Ghosh, N. Nangia and D.H. Kim, Estimation of median income of four-person families: A Bayesian time series approach, J. Amer. Statist. 91 (1996), no. 436, 1423–1431. [6] M. Ghosh, J.N.K. Rao, Small area estimation: an appraisal, Statist. Sci. 9 (1994), no. 1, 55–76. [7] J. Jiang and P. Lahiri, Mixed model prediction and small area estimation, Test: Offic. J. Spanish Soc. Statist. Operat. Res. 15 (2006), no. 1, 96. [8] C. Jones, The estimation of rates of unemployment for small spatial units, Local Econ. 15 (2000), no. 2, 144–158. [9] Y. Marhuenda, I. Molina and D. Morales, Small area estimation with spatiotemporal Day–Herriot models, Comput. Statist. Data Anal. 58 (2013), 308–325. [10] D. Pfeffermann, Small area estimation-new developments and directions, Int. Statist. Rev. 70 (2002), no. 1, 125–143. [11] D. Pfeffermann, New important developments in small area estimation, Statist. Sci. 28 (2013), no. 1, 40–68. [12] D. Pfeffermann and L. Burck, Robust small area estimation combining time series and cross-sectional data, Survey Methodol. 16 (1990), 217–237. [13] J.N.K. Rao, Some new developments in small area estimation, J. e Iranian Statist. Soc. 2 (2003), no. 2, 145–169. [14] J.N.K. Rao and M. Yu, Small-area estimation by combining time-series and cross-sectional data, Canad. J. Statist. 22 (1994), no. 4, 511–528. [15] W. Rudin, Principles of Mathematical Analysis, McGraw-Hill Inc, 1976. [16] A. Saei and R. Chambers, Small area estimation under linear and generalized linear mixed models with time and area effects, Methodol. Work. Paper no M03/15 Southampton Statistical Sciences Research Institute, University of Southampton, UK, 2003. [17] N. Salvati, E. Fabrizi, M.G. Ranalli and R.L. Chambers, Small area estimation with linked data, J. Royal Statist. Soc. Ser. B 83 (2021), no. 1, 78–107. [18] M.D. Ugarte, T. Goicoa, A.F. Militino and M. Durban, Spline smoothing in small area trend estimation and forecasting, Comput. Statist. Data Anal. 53 (2009), no. 10, 3616–3629. [19] X. Wang and Z. Zhu, Small area estimation with subgroup analysis, Statist. Theory Related Fields 3 (2019), no. 2, 129–135. [20] Y. You, J.N.K. Rao and J. Gambino, Model-based unemployment rate estimation for the Canadian labour force survey: a hierarchical Bayes approach, Survey Methodol. 29 (2001), no. 1, 25–32. | ||
|
آمار تعداد مشاهده مقاله: 25,940 تعداد دریافت فایل اصل مقاله: 4,996 |
||