TY  - JOUR
A1  - Neumann, Anne
A1  - Nieswand, Maria
A1  - Schubert, Torben
T1  - Estimating alternative technology sets in nonparametric efficiency analysis: restriction tests for panel and clustered data
JF  - Journal of productivity analysis
N2  - Nonparametric efficiency analysis has become a widely applied technique to support industrial bench-marking as well as a variety of incentive-based regulation policies. In practice such exercises are often plagued by incomplete knowledge about the correct specifications of inputs and outputs. Simar and Wilson (Commun Stat Simul Comput 30(1): 159-184, 2001) and Schubert and Simar (J Prod Anal 36(1): 55-69, 2011) propose restriction tests to support such specification decisions for cross-section data. However, the typical oligopolized market structure pertinent to regulation contexts often leads to low numbers of cross-section observations, rendering reliable estimation based on these tests practically unfeasible. This small-sample problem could often be avoided with the use of panel data, which would in any case require an extension of the cross-section restriction tests to handle panel data. In this paper we derive these tests. We prove the consistency of the proposed method and apply it to a sample of US natural gas transmission companies from 2003 through 2007. We find that the total quantity of natural gas delivered and natural gas delivered in peak periods measure essentially the same output. Therefore only one needs to be included. We also show that the length of mains as a measure of transportation service is non-redundant and therefore must be included.
KW  - Benchmarking models
KW  - Network industries
KW  - Nonparametric efficiency estimation
KW  - Data envelopment analysis
KW  - Testing restrictions
KW  - Subsampling
KW  - Bootstrap
Y1  - 2016
U6  - https://doi.org/10.1007/s11123-015-0461-z
SN  - 0895-562X
SN  - 1573-0441
VL  - 45
SP  - 35
EP  - 51
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Zaklan, Aleksandar
A1  - Abrell, Jan
A1  - Neumann, Anne
T1  - Stationarity changes in long-run energy commodity prices
JF  - Energy economics
N2  - Situated at the intersection of the literatures on speculative storage and non-renewable commodity scarcity, this paper considers whether changes in persistence have occurred in long-run U.S. prices of the energy commodities crude oil, natural gas and bituminous coal. We allow for a structural break when testing for a break in persistence to avoid a change in the stochastic properties of prices being confounded by an unaccounted-for deterministic shift in the price series. We find that coal prices are trend stationary throughout their evolution and that oil prices change from stationarity to non-stationarity in the decade between the late 1960s to late 1970s. The result on gas prices is ambiguous. Our results demonstrate the importance of accounting for a possible structural shift when testing for breaks in persistence, while being robust to the exact date of the structural break. Based on our analysis we caution against viewing long-run energy commodity prices as being non-stationary and conclude in favor of modeling commodity market fundamentals as stationary, meaning that speculative storage will tend to have a dampening effect on prices. We also cannot reject that long-run prices of coal and, with some hesitation, gas follow a Hotelling-type rule. In contrast, we reject the Hotelling rule for oil prices since the late 1960s/early 1970s. (C) 2016 Elsevier B.V. All rights reserved.
KW  - Non-renewable commodity prices
KW  - Competitive storage
KW  - Resource scarcity
KW  - Stationarity
KW  - Structural breaks
Y1  - 2016
U6  - https://doi.org/10.1016/j.eneco.2016.07.022
SN  - 0140-9883
SN  - 1873-6181
VL  - 59
SP  - 96
EP  - 103
PB  - Elsevier
CY  - Amsterdam
ER  -