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On the Interpolation of Missing Dependent Variable Observations

Medvedeff, Alexander Mark
http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971

Abstract Details

2008, Master of Arts, University of Akron, Economics.
This paper utilizes a Monte Carlo experiment to simulate random missing observations in a dataset in order to analyze the effects of how various techniques to compensate for missing dependent variable observations behave in time series regression analysis. Reduced Sample, Modified Zero Order, and First Order techniques are tested with authentic data and simulated population datasets. The size of the datasets and the relative percentage of observations simulated as missing are changed in order to investigate the sensitivity of results to different dataset conditions. Each combination of data-type, size of dataset, percentage of missing observations, and model specification are regressed 1,000 times. Results are compared to a control or "full information" regression in order to analyze the bias and efficiency of each method tested. Results indicate that the Reduced Sample method should be the preferred solution for dealing with missing dependent variables in time series regression, as it consistently produces the least biased and most efficient estimates. The results also indicate a small degree of sensitivity to model specification, size of dataset and the percentage of observation simulated as missing.
Steven Myers, PhD (Advisor)
Gasper Garofalo, PhD (Advisor)
77 p.
Economics; Statistics
Interpolation; Missing Data; Missing Observations; Econometrics; Monte Carlo

Recommended Citations

Citations

  • Medvedeff, A. M. (2008). On the Interpolation of Missing Dependent Variable Observations [Master's thesis, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971

    APA Style (7th edition)

  • Medvedeff, Alexander. On the Interpolation of Missing Dependent Variable Observations. 2008. University of Akron, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971.

    MLA Style (8th edition)

  • Medvedeff, Alexander. "On the Interpolation of Missing Dependent Variable Observations." Master's thesis, University of Akron, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971

    Chicago Manual of Style (17th edition)

akron1208185971
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© 2008, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.