Taxes and Mistakes: What's in a Sufficient Statistic?

Author(s):  
Daniel H. Reck
Keyword(s):  

1997 ◽  
Vol 13 (6) ◽  
pp. 771-790 ◽  
Author(s):  
Kees Jan van Garderen

Curved exponential models have the property that the dimension of the minimal sufficient statistic is larger than the number of parameters in the model. Many econometric models share this feature. The first part of the paper shows that, in fact, econometric models with this property are necessarily curved exponential. A method for constructing an explicit set of minimal sufficient statistics, based on partial scores and likelihood ratios, is given. The difference in dimension between parameterand statistic and the curvature of these models have important consequences for inference. It is not the purpose of this paper to contribute significantly to the theory of curved exponential models, other than to show that the theory applies to many econometric models and to highlight some multivariate aspects. Using the methods developed in the first part, we show that demand systems, the single structural equation model, the seemingly unrelated regressions, and autoregressive models are all curved exponential models.



2021 ◽  
Author(s):  
Fernando Alvarez ◽  
Andrea Ferrara ◽  
Erwan Gautier ◽  
Herve Le Bihan ◽  
Francesco Lippi




2019 ◽  
Vol 109 (1) ◽  
pp. 271-313 ◽  
Author(s):  
Sebastian Di Tella

I characterize the optimal financial regulation policy in an economy where financial intermediaries trade capital assets on behalf of households, but must retain an equity stake to align incentives. Financial regulation is necessary because intermediaries cannot be excluded from privately trading in capital markets. They don’t internalize that high asset prices force everyone to bear more risk. The socially optimal allocation can be implemented with a tax on asset holdings. I derive a sufficient statistic for the externality and use market data on leverage and volatility of intermediaries’ equity to measure it. (JEL D82, G01, G12, G20, G31, H25)





Author(s):  
William E. Strawderman
Keyword(s):  


1974 ◽  
Vol 8 (1) ◽  
pp. 77-90 ◽  
Author(s):  
William S. Jewell

AbstractThe credibility formula used in casualty insurance experience rating is known to be exact for certain prior-likelihood distributions, and is the minimum least-squares unbiased estimator for all others. We show that credibility is, in fact, exact for all simple exponential families where the mean is the sufficient statistic, and is also exact in an extended sense for all regular distributions with their natural conjugate priors where there is a fixed-dimensional sufficient statistic.



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