# Journal of the Royal Statistical Society: Series A (Statistics in Society)

© Royal Statistical Society

Edited By: J. Carpenter and H. Goldstein

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ISI Journal Citation Reports © Ranking: 2016: 11/49 (Social Sciences Mathematical Methods); 21/124 (Statistics & Probability)

Online ISSN: 1467-985X

Associated Title(s): Journal of the Royal Statistical Society: Series B (Statistical Methodology), Journal of the Royal Statistical Society: Series C (Applied Statistics), Significance

#### 175:4

**When, where and how to perform efficiency estimation****, by O. Badunenko, D. J. Henderson and S. C. Kumbhakar, Journal of the Royal Statistical Society, Series A, Statistics in Society, Volume 175, (2012), part 4, pages 863 – 892.**

Data:

kt.csv contains data for 72 fossil fuel-fired steam electric power generating plants in the United States for year 1998. ``y'', (the output) is net steam electric power generation in megawatt-hours. ``x_l'' is the labor, calculated by diving the aggregate costs of labor by a cost-share weighted price for labor. ``x_f'' is fuel, calculated by dividing the fuel expenses by the Tornqvist price of fuel aggregate. ``x_k'' is the capital stock, calculated by the valuation of base and peak load capacity at replacement cost to estimate capital stocks in a base year and then updating it in the subsequent years based upon the value of additions and retirements to steam power plants.

usmanuf.csv contains data from the NBER-CES Manufacturing Industry Database (May, 2009), which is compiled by Randy A. Becker, and Wayne B. Gray. Y is defined as the total value of shipments divided by a respective deflator, K is the total real capital stock, L is the total employment, and M is the total cost of materials, electric and fuels divided by a respective deflator. We consider the year 2004 for our analysis.

forest.csv contains data from the Sample Survey of Agriculture and Forestry, compiled by Statistics Norway in 2004. All data are for the year 2003 and the sample consists of n = 3249 active forest owners. Output is measured as the annual timber sales from the forest. Labor is obtained as the hours worked by the owner, his/her family or hired labor plus the hours worked by contractors. Forest area cut is measured in hectares. This variable only includes the total hectares cut, not the total number of hectares the owner possesses. Finally, capital is an estimate of the value of the increment from the forest.

Estimation code: Estimate_real_data.R file contains R code to replicate the empirical part (real life data) of the paper. It contains functions ``flw96'' and ``ksw08'' to get FLW and KSW estimates. To use any of above described datasets, uncomment (by deleting # in the front of the line) respective lines.

Object flw.1 contains FLW estimates of lambda, sigmas and efficiencies along with confidence intervals. Object ksw.1 contains KSW estimates of efficiencies, bias-corrected efficiencies along with confidence intervals.

Daniel J. Henderson

Department of Economics

State University of New York

Binghamton

NY 13902-6000

USA

E-mail: djhender@binghamton.edu

**Dataset** (59KB)

**The synoptic problem: on Matthew's and Luke's use of Mark****, by A. Abakuks, Journal of the Royal Statistical Society, Series A, Statistics in Society, Volume 175, (2012), part 4, pages 959 – 975**

The accompanying file contains the data set that is analysed in the paper. There are 11078 rows and 9 columns:

- index t
- Number of chapter in Mark
- Number of verse in chapter
- Number of word in verse
- x_{t}, binary variable for Matthew's use of Mark
- y_{t}, binary variable for Luke's use of Mark.
- z_{t}, binary variable for direct speech, 'sayings' material
- Number of pericope in the Huck classification
- Number of pericope in the Aland classification

Andris Ababkuks

Department of Economics, Mathematics and Statistics

Birkbeck College

Malet Street

London WC1E 7HX

UK

E-mail: a.abakuks@bbk.ac.uk

**Dataset** (55KB)