Pooled Time Series Analysis, Issue 70

Front Cover
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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Contents

Series Editors Introduction
5
The Structural Equation Model 52
15
The Constant Coefficients Model
19
The LSDV Model
26
The Random Coefficient Model
32
How Good Are These
62
Conclusions on Pooled Time Series
70
References
77
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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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