Abstract
To estimate the model \({{\text{y}}_{\text{t}}} = \sum\nolimits_{{\text{i}} = 1}^{\text{k}} {{\beta _{\text{i}}}} {{\text{x}}_{{\text{ti}}}} + {\varepsilon _{\text{t}}}\) (t = 1,...T observations) by least squares, the T × k matrix of independent variables [xti] must be of full column rank. This requires that the number of observations T exceeds k, the number of independent variables. If this condition is not satisfied, the sample is said to be undersized.
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Dongling, C. (1995). Undersized Samples and Demand Analysis. In: Recent Developments in Applied Demand Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-85205-3_5
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