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Dangers of data-driven inference : the case of calendar effects in stock returns
Sullivan, Ryan; Timmermann, Allan; White, Halbert - 1998
Persistent link: https://www.econbiz.de/10000988757
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The dangers of data-driven inference : the case of calendar effects in stock returns
Sullivan, Ryan; Timmermann, Allan; White, Halbert - 1998
Persistent link: https://www.econbiz.de/10000994251
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The importance of sample attrition in life cycle labor supply estimation
Ziliak, James P.; Kniesner, Thomas J. - 1996
Persistent link: https://www.econbiz.de/10000935351
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Dealing with the common econometric problems of count data with excess zeros, endogenous treatment effects, and attrition bias
Freund, Deborah A. - In: Economics letters 62 (1999) 1, pp. 7-12
Persistent link: https://www.econbiz.de/10001256038
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Estimating labor supply with panel data
Conway, Karen Smith - In: Economics letters 44 (1994) 1, pp. 27-33
Persistent link: https://www.econbiz.de/10001164049
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Count data models with variance of unknown form : an application to a hedonic model of worker absenteeism
Delgado, Miguel A. - In: The review of economics and statistics 79 (1997) 1, pp. 41-49
Persistent link: https://www.econbiz.de/10001215966
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Estimating labour supply disequilibrium with fixed-effects random-coefficients regression
Conway, Karen Smith - In: Applied economics 24 (1992) 7, pp. 781-789
Persistent link: https://www.econbiz.de/10001133004
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How fragile are male labor supply function estimates?
Conway, Karen Smith - In: Empirical economics : a journal of the Institute for … 17 (1992) 1
Persistent link: https://www.econbiz.de/10001279132
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Cross-correlated random regression coefficients : a refinement and some supporting evidence
Smith, Karen Marie; Smith, Karen Marie; Kniesner, Thomas J. - 1989
Persistent link: https://www.econbiz.de/10000847870
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The important econometric features of a linear regression model with cross-correlated random coefficients
Conway, Karen Smith - In: Economics letters 35 (1991) 2, pp. 143-147
Persistent link: https://www.econbiz.de/10001102174