Two-stage DEA: <Emphasis Type=Italic>caveat emptor</Emphasis>

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a second-stage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (J Prod Anal 13:49–78, 2007), truncated regression provides consistent estimation in the second stage, where as in the model proposed by Banker and Natarajan (Oper Res 56: 48–58, 2008a), ordinary least squares (OLS) provides consistent estimation. This paper examines, compares, and contrasts the very different assumptions underlying these two models, and makes clear that second-stage OLS estimation is consistent only under very peculiar and unusual assumptions on the data-generating process that limit its applicability. In addition, we show that in either case, bootstrap methods provide the only feasible means for inference in the second stage. We also comment on ad hoc specifications of second-stage regression equations that ignore the part of the data-generating process that yields data used to obtain the initial DEA estimates.     

One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient,root-<Emphasis Type="Italic">n</Emphasis> consistent StoNEZD method

Understanding the effects of operational conditions and practices on productive efficiency can provide valuable economic and managerial insights. The conventional approach is to use a two-stage method where the efficiency estimates are regressed on contextual variables representing the operational conditions. The main problem of the two-stage approach is that it ignores the correlations between inputs and contextual variables. To address this shortcoming, we build on the recently developed regression interpretation of data envelopment analysis (DEA) to develop a new one-stage semi-nonparametric estimator that combines the nonparametric DEA-style frontier with a regression model of the contextual variables. The new method is referred to as stochastic semi-nonparametric envelopment of z variables data (StoNEZD). The StoNEZD estimator for the contextual variables is shown to be statistically consistent under less restrictive assumptions than those required by the two-stage DEA estimator. Further, the StoNEZD estimator is shown to be unbiased, asymptotically efficient, asymptotically normally distributed, and converge at the standard parametric rate of order n ^−1/2. Therefore, the conventional methods of statistical testing and confidence intervals apply for asymptotic inference. Finite sample performance of the proposed estimators is examined through Monte Carlo simulations.     

Endogenous elites: power structure and patron-client relationships

In weak institutional settings, autocrats barter political and economic concessions for support to remain in power and extract rents. Instead of viewing the favors’ beneficiaries, i.e. the elites, as an exogenous entity, we allow the king to decide whom to coopt provided the subjects are heterogeneous in the potential support—their strength—they could bring to the regime. While the ruler can select the elites on the basis of their personal characteristics, an alternative strategy consists in introducing some uncertainty in the cooptation process. The latter strategy allows the king to reduce the clients’ cooptation price since in the event of a revolution the likelihood of being included in the future body of elites is lower. We show that weak rulers are more likely to coopt the society’s strongest individuals, while powerful rulers diversify the composition of their clientele. Moreover, when agents value more future discounted outcomes, the king is more likely to randomly coopt subjects.     

Bounds for the mean residual life function of a <Emphasis Type="Italic">k</Emphasis>-out-of-<Emphasis Type="Italic">n</Emphasis> system

In the reliability studies, k-out-of-n systems play an important role. In this paper, we consider sharp bounds for the mean residual life function of a k-out-of-n system consisting of n identical components with independent lifetimes having a common distribution function F, measured in location and scale units of the residual life random variable X _t  = (X−t|X > t). We characterize the probability distributions for which the bounds are attained. We also evaluate the so obtained bounds numerically for various choices of k and n.     

A Cramér-type large deviation theorem for sums of functions of higher order non-overlapping spacings

Let U ₁, U ₂, . . . , U _n–1 be an ordered sample from a Uniform [0,1] distribution. The non-overlapping uniform spacings of order s are defined as \({G_{i}^{(s)} =U_{is} -U_{(i-1)s}, i=1,2,\ldots,N^\prime, G_{N^\prime+1}^{(s)} =1-U_{N^\prime s}}\) with notation U ₀ = 0, U _n = 1, where \({N^\prime=\left\lfloor n/s\right\rfloor}\) is the integer part of n/s. Let \({ N=\left\lceil n/s\right\rceil}\) be the smallest integer greater than or equal to n/s, f _m (u), m = 1, 2, . . . , N, be a sequence of real-valued Borel-measurable functions. In this article a Cramér type large deviation theorem for the statistic \({f_{1,n} (nG_{1}^{(s)})+\cdots+f_{N,n} (nG_{N}^{(s)} )}\) is proved.     

Accuracy of self-reports on donations to charitable organizations

In this paper we assess overall accuracy in survey self-reports on giving to charitable organizations, direction of bias in self-reports, and the influence of this bias on relationships. We compare donations to one specific health charity reported in the Giving in the Netherlands Panel Study 2003 with donations recorded in the database (n =  191). We find that (a) reported donations are significantly higher than recorded donations; (b) reported amounts contributed are correlated very strongly with recorded contributions; (c) differences between amounts reported and amounts recorded are positively related to education, religious affiliation, and the tendency to social desirability, and negatively to household income. This suggests that effects of education are overestimated and effects of income and religious affiliation are underestimated using self-reports on donations rather than archival records.     

Mixing process-generated data in market sociology

Mixed methods researchers often neglect the methodological discussion on data in general and process-generated data specifically. Assuming that the advantages and disadvantages of surveys, interviews and observations are well-known, the author discusses when and why researchers should prefer process-generated data to research-elicited data in market sociology. The author then compares four different types of process-generated data (aggregated statistical data, business directories, newspaper articles, engineering literature). For each data type, the author (a) describes the data type, (b) illustrates what kind of information researchers can gain from this data type and (c) discusses the draw-backs and limits of the data. The article concludes with a discussion of what one can learn for mixing methods and market sociology from this example and why primary data might be useful as an alternative data source after all.     

Competition for private capital and central grants: the case of Japanese industrial parks

Local governments invest in public infrastructure to develop their regions. When they depend on intergovernmental grants for local development and have opportunities to lobby upper-level governments for such grants, horizontal intergovernmental competition in lobbying activity may emerge in addition to competition over public infrastructure. This paper empirically examines the existence of these interactions between Japanese localities, by using data on the value of industrial parks as infrastructure provisions and on personnel interchanges between the central and local governments as a measure of lobbying activity. Our results suggest that a Japanese local government’s choice of the size of industrial parks and its invitation to central officers to act as a director on loan are positive responses to the neighboring local government’s policy choices. As the value of the industrial parks in a district is affected by the neighboring districts’ lobby activities and their industrial park values, we can interpret these results as evidence of inter-regional competition in these two dimensions, rather than control by the central government in this unitary state.