Rational inefficiency, adjustment costs and sequential technologies

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In this paper we propose a novel approach to estimate the rational inefficiency of decision making units in the presence of adjustment costs. Using sequential definitions of the production technology, we show how cost inefficiency can be decomposed into rational and residual inefficiency as well as inefficiency caused by technical change. Furthermore, we estimate lower bounds for the unobserved adjustment costs based on unexploited cost reductions due to rational inefficiency. Terms of use: Documents in EconStor mayThese adjustment costs are used to evaluate the feasibility of exploiting cost reductions caused by residual inefficiency. We demonstrate the empirical applicability of our model by estimating and decomposing the cost inefficiency of U.S. coal-fired power plants using panel data which cover the period between 1994 and 2009.JEL classification: D24, L20, O33

Endogenous dynamic efficiency in the intertemporal optimization models of firm behavior

“…Rather, the popular go-to approach 1 Estimated using the (non-stochastic) data envelopment analysis. 2 The closely related literature includes studies of dynamic production systems in the presence of intertemporal inefficiency and the lagged effects (Chen & van Dalen, 2010;Cherchye, De Rock & Kerstens, 2018), studies of inefficiency under sequential technologies (Hampf, 2017) as well as the work that seeks to dynamize evolution of time-persistent inefficiency in a more reduced dynamic framework (Wang & Huang, 2007;Skevas, Emvalomatis & Brümmer, 2018).…”

“…is to estimate technical efficiency from Silva & Oude Lansink's (2013) dynamic directional distance function (oriented in the space of freely-varying inputs and investments into quasi-fixed dynamic factors) under its duality to the optimal current value function associated with the firm's intertemporal cost-minimization problem under the Hamilton-Jacobi-Bellman conditions (e.g., Serra et al, 2011;Kapelko et al, 2014;Oude Lansink et al, 2015;Kapelko, Oude Lansink & Stefanou, 2016, 2017Minviel & Sipiläinen, 2018). Thus, in practice, the strategy for a (primal) estimation of dynamic technical efficiency is effectively the same as that for the estimation of a more conventional static efficiency except that in the former case a distance to the frontier is measured in the space of variable inputs and investments as opposed to merely conditioning the distance function on quasi-fixed levels of dynamic inputs.…”