MULTIPLE COMPARISONS WITH THE BEST: BAYESIAN PRECISION MEASURES OF EFFICIENCY RANKINGS



Prior to estimation, several sets of parametric restrictions are imposed on (4.9). We
impose symmetry, linear homogeneity in input quantities, and constrain
βfq , q, to equal
zero for one firm in order to achieve identification. Symmetry requires that

Ymm' = Ym'm, m, m', m = m'

Yzz' = Yz'z, z,z', z = z'

Ynn' = Yn'n, n,n', n = n.                            (4.14)

In addition, linear homogeneity in input quantities implies

Yn=1,
n

£ Ynn' = £ Ynn' =£ £ Ynn' =0,

Ymn = 0, m,
n

Yzn = 0, z, and
n

Ynt =0.

(4.15)


n

Finally, identification requires that βfq, q, must be constrained for one firm in (4.11).

4.2 Data

Our dataset is an updated and refined version of the panel of utilities originally an-
alyzed by Nelson (1984).
3 Subsets of that data were used by Baltagi and Griffin (1988)
and Callan (1991). The sample used here is comprised of 43 privately owned U.S. electric

3 We are grateful to Professor Nelson for making his data available to us.

14



More intriguing information

1. The name is absent
2. Feeling Good about Giving: The Benefits (and Costs) of Self-Interested Charitable Behavior
3. Fiscal Insurance and Debt Management in OECD Economies
4. The value-added of primary schools: what is it really measuring?
5. Retirement and the Poverty of the Elderly in Portugal
6. Skill and work experience in the European knowledge economy
7. A Bayesian approach to analyze regional elasticities
8. LAND-USE EVALUATION OF KOCAELI UNIVERSITY MAIN CAMPUS AREA
9. The name is absent
10. The demand for urban transport: An application of discrete choice model for Cadiz