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Optimal Experimental Design for Error Components Models

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  • Aigner, Dennis J
  • Balestra, Pietro

Abstract

Social experiments are characterized by their high cost. A tempting alternative to the establishment of a contemporaneous statistical control group is preexempt observat ion of the treatment group. In this paper, the authors analyze the tr ade-off between these two types of "con-trol" as functions of their relative cost and information content in a multiperiod error compone nts framework, where the allocation of observations across the two gr oups is always done in an optimal manner. Solutions for the optimal p roportion of the sample to be devoted to the contemporaneous control group are presented and their behavior as a function of relevant para meters is studied. Copyright 1988 by The Econometric Society.

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  • Aigner, Dennis J & Balestra, Pietro, 1988. "Optimal Experimental Design for Error Components Models," Econometrica, Econometric Society, vol. 56(4), pages 955-971, July.
    • Handle: RePEc:ecm:emetrp:v:56:y:1988:i:4:p:955-71
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    Cited by:

    1. Alfano, Vincenzo & Ercolano, Salvatore, 2021. "Social capital, quality of institutions and lockdown. Evidence from Italian provinces," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 31-41.
    2. Connelly, Luke B., 2003. "Balancing the Number and Size of Sites: An Economic Approach to the Optimal Design of Cluster Samples," MPRA Paper 14676, University Library of Munich, Germany.
    3. Vincenzo Alfano & Salvatore Ercolano, 2022. "Stay at Home! Governance Quality and Effectiveness of Lockdown," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 101-123, January.
    4. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    5. Alfano, Vincenzo & Ercolano, Salvatore, 2022. "Back to school or … back to lockdown? The effects of opening schools on the diffusion of COVID-19 in Italian regions," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    6. Verbeek, M.J.C.M. & Nijman, T.E., 1993. "Incomplete panels and selection bias : A survey," Other publications TiSEM 08061352-957b-4f56-b303-9, Tilburg University, School of Economics and Management.
    7. Alfano, Vincenzo & Ercolano, Salvatore, 2023. "Fear itself. Is fear a determinant of the efficacy oflockdowns?," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    8. Vincenzo Alfano & Salvatore Ercolano & Gaetano Vecchione, 2020. "Religious Attendance and Covid-19. Evidences from Italian Regions," CESifo Working Paper Series 8596, CESifo.
    9. Vincenzo Alfano & Giuseppe Lucio Gaeta, 2022. "The Environmental Impact of a Pro-Environment International Governmental Meeting: Evidence from Italy," CESifo Working Paper Series 10136, CESifo.
    10. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Experimental designs in triangular simultaneous equations models," Statistical Papers, Springer, vol. 56(2), pages 273-290, May.
    11. Aufenanger, Tobias, 2018. "Treatment allocation for linear models," FAU Discussion Papers in Economics 14/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2018.

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