Pooled Time Series Analysis, Issue 70

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SAGE, May 1, 1989 - Mathematics - 79 pages
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Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross-sections). Pooled Time Series Analysis combines time series and cross-sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied. In addition, with more relevant data available this analysis technique allows the sample size to be increased, which ultimately yields a more effective study.

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Series Editors Introduction
The Structural Equation Model 52
The Constant Coefficients Model
The LSDV Model
The Random Coefficient Model
How Good Are These
Conclusions on Pooled Time Series

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Page 77 - Methods. 3rd ed. New York: McGraw-Hill. Judge, GG, WE Griffiths, RC Hill, H. Lutkepohl, and TC. Lee. 1985. The Theory and Practice of Econometrics. New York: Wiley.
Page 77 - Combining cross-section data and time series." Cowles Commission Discussion Paper. Statistics No 347. HSAIO, C. (t975l "Some estimation methods for a random coefficient model.
Page 78 - A pooled cross-sectional analysis." Paper presented at the Third Annual Methodology Conference, Harvard University, Cambridge. MA, August 7-t0, t986. MUNDLAK, Y. (t978l "On the pooling of lime scries and cross-section data.

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