The Study of Small Area Estimation Using Oversampling and M-Quantile Robust Regression Approach

Nia Aprillyana, Kusman Sadik, Indahwati Indahwati

Abstract


Statistics Indonesia (BPS) calculates poverty indicators (Head Count Ratio, Poverty Gap, and Poverty Severity) using National Socio-Economic Survey (Susenas). Susenas is only designed to estimate province and municipality/regency area level, whereas the government requires estimation until smaller area level (sub-district and village). Estimating poverty indicators directly from Susenas for the smaller area often leads to inaccurate estimates. To solve this problem, BPS usually conduct additional survey called Regional Socio-Economic Survey (Suseda) by increasing number to the original sample (called oversampling) but with the very high cost. Therefore, we proposed small area estimation technique which based on the unit level model using Population Census 2010 (SP2010) as the population auxiliary variables and household per-capita expenditure (Susenas 2015) as the response variable. We utilized robust M-quantile regression model which robust to the outlier using three weight functions (Huber, Hampel, and Tukey Bisquare). Our results provide evidence that M-quantile model is more accurate than direct estimates with oversampling.


Keywords


M-quantile; oversampling; small area estimation; weight function.

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References


I. Molina, J.N.K. Rao. (2010). “Small area estimation of poverty indicators”, The Canadian Journal of Statistics. .38(3),pp.369-385.

C. Giusti, S. Marchetti, M. Pratesi, N. Salvati. 2012. “Robust small area estimation and oversampling in the estimation of poverty indicators”, Survey Research Methods. 6(3),pp.155-163.

A.B. Kennickell, “The Role of Over-sampling of the Wealthy in the Survey of Consumer Finances”. In ISI 56th conference. 2007.

J.N.K. Rao. Small Area Estimation. New York, US: John Wiley and Sons. 2003.

Badan Pusat Statistik. Data dan Informasi Kemiskinan Ka-bupaten/ Kota 2015. Jakarta: Badan Pusat Statistik. 2016.

R. Chambers, N. Tzavidis. 2006. “M-Quantile Models for small area estimation”, Biometrika. 93(2),pp.255-268.

N. Tzavidis, S. Marchetti, R. Chambers. 2010. “Robust Estimation of Small Area Means and Quantiles”. Australian and New Zealand Journal of Statistics. 52(2),pp.167-186.

S. Marchetti, N. Tzavidis, M. Pratesi. 2012. ”Non-parametric bootstrap mean squared error estimation for M-quantile estimators of small area averages, quantiles and poverty indicators”, Computational Statstics and Data Analysis, 56,pp.2889-2902.

Girinoto. “Kajian pendugaan area kecil untuk indikator kem-iskinan melalui pendekatan regresi kekar M-kuantil (studi kasus: tingkat kecamatan pada Kabupaten Bogor) “ M.Si thesis. Institut Pertanian Bogor, Bogor. 2017.

J. Foster, J. Greer, E. Thorbecke. 1984 “A class of decomposable poverty measures”, Econometrica, 52(3), pp.761-766.


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