a comparison of parametric and non parametric distance functions with application to european railways abstract in this paper we use multi output distance functions to investigate technical inefficiency in european railways the principle aim of the paper is to compare the results obtained from the three alternative methods of estimating multi output distance functions namely the construction of a parametric frontier using linear programming data envelopment analysis dea and corrected ordinary least squares cols input orientated output orientated and constant returns to scale crs distance functions are estimated and compared the results indicate a strong degree of correlation between the input and output orientated results for each of the three methods there are also significant correlations observed between the results obtained using the alternative estimation methods the strongest correlations being between the parametric linear programming and the cols methods finally the paper concludes with the suggestion that a combination of the technical efficiency scores obtained from the three different methods be used as the preferred set of scores this idea is borrowed from the time series forecasting literature

the laurent series approach to structural modeling abstract caves and christensen 1980 have provided a procedure for displaying the regular regions of a flexible functional form in the 2 good homothetic and nonhomothetic cases and in the 3 good homothetic case we extend the procedure to the nonhomothetic 3 good case and we apply the extended procedure to the translog generalized leontief and minflex laurent flexible functional forms in addition we acquire the regular regions for the minflex laurent model in the 2 good nonhomothetic case and superimpose the resulting regions on those already found by caves and christensen for the translog and generalized leontief models we find that the new minflex laurent model generally has the largest regular regions of the three flexible functional forms in addition the regular region of the minflex laurent model is found to expand as real income increases as a result that model is particularly well suited for use with time series data which typically is characterized by positive long term growth trends in real income in such applications all recent data and future forecasts can be expected to lie within the regular region of the minflex laurent model although it is possible for some of the earliest data to fall outside that regular region the model s regular region nevertheless is sufficiently large to hold even all of those earliest data points in many data sets the regular region of each of the three models moves when the model s parameters are changed with the generalized leontief or translog model the regular region s shape location and size are unpredictable without prior knowledge of the model s parameters with either of those models the intersection of the model s regular regions as the parameters are changed is contained within a very small neighborhood of the one point at which we require the model to be regular with the minflex laurent model the primary properties of the regular regions are invariant to the values of the parameters and the intersection of the displayed regular regions is a very large unbounded set the width of that intersection increases without limit as real income increases

robustness in quantum measurements conditions are formulated under which a representation of an intrinsic c algebra of often quasilocal observables of an infinite system is appropriate to describe measurement type processes such a representation should allow for the description of robust experiments it should be separable and the pointer observable should be in its weak closure if the pointer values are discrete the existence of such a measurement representation can be proven if the pointer can take continuously many values then the existence can only be proven under the additional assumptions of having an asymptotically abelian system or dealing with type i representations in the constructed measurement representations the pointer observable turns out to be classical the structure of the representation suggests that spontaneous symmetry breaking might be a physical explanation of the emergence of the classical pointer

on the existence of strong nash equilibria this paper investigates the existence of strong nash equilibria sne in continuous and convex games we show that the concavity and an additional condition on payoff functions together with the compactness of strategy space permit the existence of strong nash equilibria these conditions are satisfied in many economic games and are quite simple to check we also characterize the existence of sne by providing a necessary and sufficient condition moreover we suggest a procedure that can be used to efficiently compute strong nash equilibrium the result is illustrated with an application to an economy with multilateral environmental externalities and to the simple oligopoly static model

globally flexible functional forms the neural distance function the output distance function is a key concept in economics however its empirical estimation often violates properties dictated by neoclassical production theory in this paper we introduce the neural distance function ndf which constitutes a global approximation to any arbitrary production technology with multiple outputs given by a neural network nn specification the ndf imposes all theoretical properties such as monotonicity curvature and homogeneity for all economically admissible values of outputs and inputs fitted to a large data set for all us commercial banks 1989 2000 the ndf explains a very high proportion of the variance of output while keeping the number of parameters to a minimum and satisfying the relevant theoretical properties all measures such as total factor productivity tfp and technical efficiency te are computed routinely next the ndf is compared with the translog popular specification and is found to provide very satisfactory results as it possesses the properties thought as desirable in neoclassical production theory in a way not matched by its competing specification

existence of strong equilibrium in discontinuous games abstract in this paper we give necessary and sufficient conditions for the existence of strong equilibria in games with non ordered preferences our result does not require continuous preferences and in the case of normal form games quasi concavity of payoff functions is not needed the result has been obtained by using the ky fan minimax inequality examples illustrate our conditions in some economic situations and compare the result with the previous literature

a system performance approach to osnr optimization in optical networks this paper studies a constrained optical signal to noise ratio osnr optimization problem in optical networks from the perspective of system performance a system optimization problem is formulated with the objective of achieving an osnr target for each channel while satisfying the total power constraint in order to establish existence of a unique optimal solution the conditions are derived which can be used as a basis for an admission control scheme the original problem is then converted to a relaxed system problem by using a barrier function and solved by a distributed iterative algorithm next the system optimization framework developed is compared to the game theoretic one in 1 the effects of parameters in both formulations are investigated to study efficiency of nash equilibria in the osnr game and pricing mechanisms affecting overall system performance the theoretical analysis is supported by numerical simulations and experiments conducted on an optical fiber link

consistent estimation of the fixed effects stochastic frontier model abstract in this paper we consider a fixed effects stochastic frontier model that is we have panel data fixed individual firm effects and the usual stochastic frontier analysis sfa composed error maximum likelihood estimation mle of this model has been considered by greene 2005a greene 2005b it is subject to the incidental parameters problem that is to possible inconsistency due to the number of parameters growing with the number of firms in the linear regression model with normal errors it is known that the mle of the regression coefficients is consistent and the inconsistency due to the incidental parameters problem applies only to the error variance greene s simulations suggest that the same is true in the fixed effects sfa model in this paper we take a somewhat different approach we consider mle based only on the joint density of the deviations from means in the linear regression model with normal errors this estimator is the same as the full mle for the regression coefficients but it yields a consistent estimator of the error variance for the sfa model the mle based on the deviations from means is not the same as the full mle and it has the advantage of not being subject to the incidental parameters problem the derivation of the joint density of the deviations from means is made possible by results in the statistical literature on the closed skew normal family of distributions these results may be of independent interest to researchers in this area simulations indicate that our within mle estimator performs quite well in finite samples we also present an empirical example

the global properties of the minflex laurent generalized leontief and translog flexible functional forms caves and christensen 16 have provided a procedure for displaying the regular regions of a flexible functional form in the 2 good homothetic and nonhomothetic cases and in the 3 good homothetic case we extend the procedure to the nonhomothetic 3 good case and we apply the extended procedure to the translog generalized leontief and minflex laurent flexible functional forms in addition we acquire the regular regions for the minflex laurent model in the 2 good nonhomothetic case and superimpose the resulting regions on those already found by caves and christensen for the translog and generalized leontief models we find that the new minflex laurent model generally has the largest regular regions of the three fiexible functional forms in addition the regular region of the minflex laurent model is found to expand as real income increases as a result that model is particularly well suited for use with time series data which typically is characterized by positive long term growth trends in real income in such applications all recent data and future forecasts can be expected to lie within the regular region of the minflex laurent model although it is possible for some of the earliest data to fall outside that regular region the model s regular region nevertheless is sufficiently large to hold even all of those earliest data points in many data sets the regular region of each of three models moves when the model s parameters are changed with the generalized leontief or translog model the regular region s shape location and size are unpredictable without prior knowledge of the model s parameters with either of those two models the intersection of the model s regular regions as the parameters are changed is contained within a very small neighborhood of the one point at which we require the model to be regular with the minflex laurent model the primary properties of the regular regions are invariant to the values of the parameters and the intersection of the displayed regular regions is a very large unbounded set the width of that intersection increases without limit as real income increases

virtual implementation in nash equilibrium the two person case needs to be considered separately we provide a complete characterization of virtually implementable two person social choice functions while not all two person social choice functions are virtually implementable our necessary and sufficient condition is simple this contrasts with the rather complex necessary and sufficient conditions for exact implementation we show how our results can be extended to implementation in strict nash equilibrium and coalition proof nash equilibrium to social choice correspondences which map from cardinal preference profiles to lotteries and to environments with a continuum of pure alternatives

specification and estimation of multiple output technologies a primal approach abstract this paper addresses specification and estimation of multiple outputs and multiple inputs production technology in the presence of technical inefficiency the primary focus is on the primal formulations several competing specifications such as production function input output distance function input requirement function are considered we show that all these specifications come from the same transformation function and are algebraically identical we also show that i unless the transformation function is separable i e outputs are separable from inputs the input output ratios in the input output distance function can not be treated as exogenous uncorrelated with technical inefficiency resulting inconsistent estimates of the input output distance function parameters ii even if input output ratios are exogenous estimation of the input output distance function will result in inconsistent parameter estimates if outputs inputs are endogenous we address endogeneity and instrumental variable issues in details in the context of flexible translog functional forms estimation of several specifications using both single and system approaches are discussed using norwegian dairy farming data

virtual bayesian implementation allowing for incomplete information this paper characterizes the social choice functions that can be approximated by the equilibrium outcomes of a mechanism incentive compatibility is necessary and almost sufficient for virtual bayesian implementability in conjunction with a second condition bayesian incentive consistency incentive compatibility is also sufficient this new condition is weak under standard topological and informational assumptions it is satisfied by every social choice function the type sets of the agents are taken to be arbitrary possibly infinite measurable spaces an example shows that there are virtually in fact exactly bayesian implementable social choice functions that are not virtually implementable in iteratively undominated strategies

the price of anarchy under nonlinear and asymmetric costs in this paper we characterize the price of anarchy i e the inefficiency between user and system optimal solutions when costs are nonseparable asymmetric and nonlinear generalizing earlier work that has addressed the price of anarchy under separable costs the results in this paper apply primarily to nonatomic games such as the traffic equilibrium problem but also in competitive multiperiod pricing and competitive supply chain settings the bounds established in this paper are tight and explicitly account for the degree of asymmetry and nonlinearity of the cost function we first provide a proof method for problems with a positive definite jacobian matrix subsequently we use ideas from semidefinite optimization in order to account for problems with a positive semidefinite jacobian matrix where the first approach does not apply this latter connection also provides a different application of semidefinite optimization

α returns to scale and multi output production technologies abstract this contribution proposes a specification of strictly increasing and decreasing returns to scale in multi output technologies along this line a notion of returns to scale is derived from that of homogeneous multi output technology for a large class of technologies we establish necessary and sufficient conditions characterizing strictly increasing and strictly decreasing returns to scale to scale furthermore a relationship between input output and graph distance functions is established these connections lead naturally to a link between the various malmquist indexes and the chavas cox productivity index finally we show that these concepts can be implemented in a dea context using a piecewise homogeneous constant elasticity substitution transformation model due to fare r grosskopf s njinkeu d 1988b on piecewise reference technologies management science 34 1507 1511

scheduling selfish jobs on multidimensional parallel machines abstract we study the multidimensional vector scheduling problem with selfish jobs both in non cooperative and in cooperative versions in two variants these variants differ in the private costs of the jobs in the first variant the cost is the l norm maximum over components while in the second variant it is the l 1 norm sum of components of the load we show existence of assignments that are nash strong nash weakly and strictly pareto optimal nash equilibria in these settings for the first variant we improve upon the previous bounds on the price of anarchy for the non cooperative case and find tight bounds for every number of machines and dimension for the cooperative case we provide tight bounds on the strong prices of anarchy and stability as well as tight bounds on weakly and strictly pareto optimal prices of anarchy and stability for every number of machines and dimension for the second variant which was not considered before we again consider all the aforementioned measures and find tight bounds each of which being a function of the number of machines and the dimension showing cardinal differences in the behavior of these measures both between the two variants and in comparison to the one dimensional case

virtual implementation in iteratively undominated strategies complete information we investigate the implementation of social choice functions in complete information environments we consider social choice functions scf s which map from a finite set of preference profiles to lotteries over alternatives and require virtual implementation in iteratively undominated strategies an scf x is virtually implementable in iteratively undominated strategies if for all e 0 there exists an scf y which is e close to x that is for all preference profiles x and y map to lotteries which are within e of one another and which is exactly implementable in iteratively undominated strategies under very weak domain restrictions we show that if there are three or more players any scf is virtually implementable in iteratively undominated strategies a noteworthy feature of our constructions is that we only employ finite mechanisms as a corollary we obtain virtual implementation in pure and mixed strategy nash equilibrium using well behaved in particular finite mechanisms the literature on implementation in nash equilibrium and its refinements is compromised by its reliance on game forms with unnatural features for example integer games or modulo constructions with mixed strategies arbitrarily excluded in contrast our results allow for mixed strategies and do not rely on mechanisms with obviously suspicious features

estimation and inference in two stage semi parametric models of production processes many papers have regressed non parametric estimates of productive efficiency on environmental variables in two stage procedures to account for exogenous factors that might affect firms performance none of these have described a coherent data generating process dgp moreover conventional approaches to inference employed in these papers are invalid due to complicated unknown serial correlation among the estimated efficiencies we first describe a sensible dgp for such models we propose single and double bootstrap procedures both permit valid inference and the double bootstrap procedure improves statistical efficiency in the second stage regression we examine the statistical performance of our estimators using monte carlo experiments

flexible functional forms and global curvature conditions empirically estimated flexible functional forms frequently fail to satisfy the appropriate theoretical curvature conditions lau and gallant and golub have worked out methods for imposing the appropriate curvature conditions locally but those local techniques frequently fail to yield satisfactory results we develop two methods for imposing curvature conditions globally in the context of cost function estimation the first method adopts lau s technique to a generalization of a functional form first proposed by mcfadden using this generalized mcfadden functional form it turns out that imposing the appropriate curvature conditions at one data point imposes the conditions globally the second method adopts a technique used by mcfadden and barnett which is based on the fact that a non negative sum of concave functions will be concave our various suggested techniques are illustrated using the u s manufacturing data utilized by berndt and khaled

nonparametric stochastic frontiers a local maximum likelihood approach this paper proposes a new approach to handle nonparametric stochastic frontier sf models it is based on local maximum likelihood techniques the model is presented as encompassing some anchorage parametric model in a nonparametric way first we derive asymptotic properties of the estimator for the general case local linear approximations then the results are tailored to a sf model where the convoluted error term efficiency plus noise is the sum of a half normal and a normal random variable the parametric anchorage model is a linear production function with a homoscedastic error term the local approximation is linear for both the production function and the parameters of the error terms the performance of our estimator is then established in finite samples using simulated data sets as well as with a cross sectional data on us commercial banks the methods appear to be robust numerically stable and particularly useful for investigating a production process and the derived efficiency scores

global approximation to arbitrary cost functions a bayesian approach with application to us banking this paper proposes and estimates a globally flexible functional form for the cost function which we call neural cost function ncf the proposed specification imposes a priori and satisfies globally all the properties that economic theory dictates the functional form can be estimated easily using markov chain monte carlo mcmc techniques or standard iterative sure we use a large panel of u s banks to illustrate our approach the results are consistent with previous knowledge about the sector and in accordance with mathematical production theory

how to generate regularly behaved production data a monte carlo experimentation on dea scale efficiency measurement abstract monte carlo experimentation is a well known approach used to test the performance of alternative methodologies under different hypotheses in the frontier analysis framework whatever the parametric or non parametric methods tested experiments to date have been developed assuming single output multi input production functions the data generated have mostly assumed a cobb douglas technology among other drawbacks this simple framework does not allow the evaluation of dea performance on scale efficiency measurement the aim of this paper is twofold on the one hand we show how reliable two output two input production data can be generated using a parametric output distance function approach a variable returns to scale translog technology satisfying regularity conditions is used for this purpose on the other hand we evaluate the accuracy of dea technical and scale efficiency measurement when sample size and output ratios vary our monte carlo experiment shows that the correlation between true and estimated scale efficiency is dramatically low when dea analysis is performed with small samples and wide output ratio variations

on the bias in flexible functional forms and an essentially unbiased form the fourier flexible form abstract the fourier flexible form and its derived expenditure system are introduced subject to smoothness conditions on the consumer s true indirect utility function the consumer s true expenditure system must be of the fourier form over the region of interest in an empirical investigation arbitrarily accurate finite parameter approximations of the consumer s true expenditure system are obtained by dropping all high order terms of the fourier expenditure system past an appropriate truncation point the resulting finite parametersystem is tractable in empirical studies the reader who is primarily interested in applications need only read the second and fifth sections the remainder of the article is concerned with the verification of these claims and an investigation of some aspects of the bias in translog specifications

necessary and sufficient karush kuhn tucker conditions for multiobjective markov chains optimality the solution concepts proposed in this paper follow the karush kuhn tucker kkt conditions for a pareto optimal solution in finite time ergodic and controllable markov chains multi objective programming problems in order to solve the problem we introduce the tikhonov s regularizator for ensuring the objective function is strict convex then we consider the c variable method for introducing equality constraints that guarantee the result belongs to the simplex and satisfies ergodicity constraints lastly we restrict the cost functions allowing points in the pareto front to have a small distance from one another the computed image points give a continuous approximation of the whole pareto surface the constraints imposed by the c variable method make the problem computationally tractable and the restriction imposed by the small distance change ensures the continuation of the pareto front we transform the multi objective nonlinear problem into an equivalent nonlinear programming problem by introducing the lagrange function multipliers as a result we obtain that the objective function is strict convex the inequality constraints are continuously differentiable and the equality constraint is an affine function under these settings the kkt optimality necessary and sufficient conditions are elicited naturally a numerical example is solved for providing the basic techniques to compute the pareto optimal solutions by resorting to kkt conditions

inefficiency of nash equilibria it is shown that nash equilibria of smooth games generally tend to be inefficient in the pareto sense

on a high dimensional model representation method based on copulas abstract this article provides an alternative to high dimensional model representation using a copula approximation of an unknown functional form we apply our methodology in the context of an extensive monte carlo study and to a sample of large us commercial banks in the monte carlo experiment the approximations errors of the copula approach are small and behave randomly in our empirical application we find that the copula approximation performs much better in terms of bayes factors for model comparison compared to high dimensional model representation which in turn provides better results when compared with standard flexible functional forms like the translog the minflex laurent and the generalized leontief or a multilayer perceptron moreover the choice of approximation has significant implications for productivity and its components returns to scale technical inefficiency technical change and efficiency change

stochastic frontier models with time varying conditional variances abstract in this paper we introduce stochastic frontier models in which either the inefficiency or the noise component or both the components follow generalized autoregressive conditional heteroskedasticity garch 1 1 process bayesian estimation of the technology parameters are proposed using a half normal exponential distribution for the inefficiency component and a normal distribution for the noise component we show in simulations that predictions of inefficiency ignoring the garch 1 1 process are not aligned with their true values we use real panel data on electricity distribution and show how to estimate our proposed model and predict inefficiency moreover we examine the effect of ignoring garch specification on economic measures like input elasticities technical change and returns to scale we also provide test for garch vs no garch models using bayes factors finally we examine variants of the garch family such as the arch and egarch models and we compared garch models of different orders

hadamard well posedness in discontinuous non cooperative games abstract we consider some recent classes of discontinuous games with nash equilibria and we prove that such classes have the hadamard well posedness property this means that given a game y a net y of games converging to y and a net x such that x is a nash equilibrium of any y then at least a cluster point of x is a nash equilibrium of y in order to obtain this property we prove that the map of nash equilibria is upper semicontinuous using the pseudocontinuity a generalization of the continuity we improve previous results obtained with continuous functions

new results on equilibria of abstract fuzzy economies abstract in this paper we consider the model of an abstract fuzzy economy and we obtain new equilibrium theorems for the situations when the involved correspondences satisfy properties which are weaker than upper semicontinuity in our case the constraint or preference correspondences are almost weakly upper semicontinuous or have the e upper semicontinuous selection property the obtained results either generalize or improve corresponding ones present in the literature

computing the strong nash equilibrium for markov chains games present a novel method for finding the strong nash equilibriumintroduce tikhonov s regularization method to guarantee convergence to a single equilibriumprove the existence of a unique strong nash equilibriumpropose the euler method with penalty function for converging to the strong nash equilibriumpresent the convergence conditions of the step size parameter and tikhonov s regularizator in this paper we present a novel method for finding the strong nash equilibrium the approach consists on determining a scalar and the corresponding strategies d fixing specific bounds min and max that belong to the pareto front bounds correspond to restrictions imposed by the player over the pareto front that establish a specific decision area where the strategies can be selected we first exemplify the pareto front of the game in terms of a nonlinear programming problem adding a set of linear constraints for the markov chain game based on the c variable method for solving the strong nash equilibrium problem we propose to employ the euler method and a penalty function with regularization the tikhonov s regularization method is used to guarantee the convergence to a single strong equilibrium point then we established a nonlinear programming method to solve the successive single objective constrained problems that arise from taking the regularized functional of the game to achieve the goal we implement the gradient method to solve the first order optimality conditions starting from an utopia point pareto optimal point given an initial of the individual objectives the method solves an optimization problem adding linear constraints required to find the optimal strong strategy d we show that in the regularized problem the functional of the game decrease and finally converges proving the existence and uniqueness of strong nash equilibrium pareto optimal nash equilibrium in addition we present the convergence conditions and compute the estimated rate of convergence of variables and corresponding to the step size parameter of the gradient method and the tikhonov s regularization respectively moreover we provide all the details needed to implement the method in an efficient and numerically stable way the usefulness of the method is successfully demonstrated by a numerical example

a note on the equilibrium existence problem in discontinuous games in this note we prove an equilibrium existence theorem for games with discontinuous payoffs and convex and compact strategy spaces it generalizes the classical result of reny 1999 as well as the recent paper of mclennan monteiro and tourky 2011 our conditions are simple and easy to verify importantly examples of spatial location models show that our conditions allow for economically meaningful payoff discontinuities that are not covered by other conditions in the literature

on the existence of maximal elements fixed points and equilibria of generalized games in a fuzzy environment we give new sufficient conditions for the existence of fuzzy maximal elements fuzzy fixed points and equilibria of generalized fuzzy games in our results a key role is played by the existence of upper semicontinuous selection maps of set valued functions that we obtain for the class of generalized transfer open lower sections maps

continuity properties of the nash equilibrium correspondence in a discontinuous setting abstract we introduce a new complete metric space of discontinuous normal form games and prove that the nash equilibrium correspondence is upper semicontinuous with non empty and compact values so using the theorem of fort 1949 we obtain that the correspondence is also lower semicontinuous in a dense subset we introduce new topological assumptions on the payoff functions and a strengthening of standard quasi concavity properties examples show that our results cannot be obtained from the previous ones

measurement of technical inefficiency and total factor productivity growth a semiparametric stochastic input distance frontier approach and the case of lithuanian dairy farms abstract this paper presents a four component stochastic frontier model in which the frontier function is represented by an unknown smooth input distance function and inefficiency is decomposed into persistent and transient inefficiencies furthermore the pre truncation mean and variance of the transient inefficiency are functions of the environmental variables by differentiating the four component input distance frontier with respect to the time trend total factor productivity tfp growth is estimated under the semiparametric smooth coefficient framework and is decomposed into six components i e technical change scale component allocative component external component efficiency change and residual component the empirical example focuses on the lithuanian dairy sector with multiple outputs our results show that there are some persistent and transient inefficiencies in lithuanian dairy farms however these farms maintained tfp growth of 2 per annum on average during 2004 2016 and much of it is attributed to the technical change and scale components

collusive game solutions via optimization a nash based collusive game among a finite set of players is one in which the players coordinate in order for each to gain higher payoffs than those prescribed by the nash equilibrium solution in this paper we study the optimization problem of such a collusive game in which the players collectively maximize the nash bargaining objective subject to a set of incentive compatibility constraints we present a smooth reformulation of this optimization problem in terms of a nonlinear complementarity problem we establish the convexity of the optimization problem in the case where each player s strategy set is unidimensional in the multivariate case we propose upper and lower bounding procedures for the collusive optimization problem and establish convergence properties of these procedures computational results with these procedures for solving some test problems are reported

on the estimation of technical inefficiency in the stochastic frontier production function model abstract the error term in the stochastic frontier model is of the form v u where v is a normal error term representing pure randomness and u is a non negative error term representing technical inefficiency the entire v u is easily estimated for each observation but a previously unsolved problem is how to separate it into its two components v and u this paper suggests a solution to this problem by considering the expected value of u conditional on v u an explicit formula is given for the half normal and exponential cases

technical and allocative efficiency in a panel stochastic production frontier system model abstract in this paper we consider a state of the art panel stochastic production frontier model and estimate it using a system that includes both technical and allocative inefficiency the system consists of the optimal input choice rule the first order conditions focs under cost minimization together with the production function the focs are used to take care of endogeneity of inputs allocative inefficiency is modeled as non fulfillment of the focs we use distributional assumptions on the noise and inefficiency components and estimate the model parameters using the maximum likelihood method in estimating technical and allocative inefficiency components and costs therefrom we control for fixed firm effects in each equation of the system we also correct for the incidental parameter bias by using the half panel jackknife estimator

jauch piron states in w algebraic quantum mechanics a state on a w algebra m is said to fulfill the jauch piron condition if p q 1 for projections p q m implies p q 1 here p q denotes the infimum of p and q in the projection lattice of m the jauch piron condition is a compatibility condition between the algebraic and the lattice theoretic approach for the description of physical systems normal i e weakly continuous states always fulfill the jauch piron condition it is argued that states not fulfilling this condition should be regarded as unphysical it is shown that a state on a finite factor m is singular if and only if projections e f m exist such that e f 1 and e f 0 in particular any pure state on m fulfilling the jauch piron condition is normal which implies that the underlying factor m is of type i furthermore the following result is proved let be a pure jauch piron state on w algebra m with separable predual and without any commutative summand then is normal and a central projection z0 m exists such

specification and estimation of primal production models abstract while estimating production technology in a primal framework production function input and output distance functions and input requirement functions are widely used in the empirical literature this paper shows that these popular primal based models are algebraically equivalent in the sense that they can be derived from the same underlying transformation production possibility function by assuming that producers maximize profit we show that in all cases except one the use of ordinary least squares ols gives inconsistent estimates irrespective of whether the production input distance and input requirement functions are used based on several specifications of the production and input distance function models we conclude that one can estimate the input elasticities and returns to scale consistently using instruments on only one regressor no instruments are needed if either it is assumed that producers know the technology entirely including the so called error term or a system approach is used we used norwegian timber harvesting data to illustrate workings of various model specifications

elicitation of multiattribute value functions through high dimensional model representations monotonicity and interactions abstract this work addresses the early phases of the elicitation of multiattribute value functions proposing a practical method for assessing interactions and monotonicity we exploit the link between multiattribute value functions and the theory of high dimensional model representations the resulting elicitation method does not state any a priori assumption on an individual s preference structure we test the approach via an experiment in a riskless context in which subjects are asked to evaluate mobile phone packages that differ on three attributes

convergence results for patchwork copulas abstract we present a general construction that allows to extend a given subcopula to a copula in such a way that the extension is affine on some specific segments of the copula domain this construction is hence applied to provide convergence theorems for approximating a copula in strong convergence and in d 1 metric related to the markov kernel representation of a copula

robust distributed routing in dynamical networks part ii strong resilience equilibrium selection and cascaded failures strong resilience properties of dynamical networks are analyzed for distributed routing policies the latter are characterized by the property that the way the outflow at a non destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links the strong resilience of the network is defined as the infimum sum of link wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin a class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin destination pair the maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network the latter depends on the limit flow of the unperturbed network and is defined as the minimum among all the non destination nodes of the sum over all the links outgoing from the node of the differences between the maximum flow capacity and the limit flow of the unperturbed network we propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees and discuss the use of tolls to induce such an equilibrium flow in traffic networks finally we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network

optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria in this two part paper we propose a decentralized strategy based on a game theoretic formulation to find out the optimal precoding multiplexing matrices for a multipoint to multipoint communication system composed of a set of wideband links sharing the same physical resources i e time and bandwidth we assume as optimality criterion the achievement of a nash equilibrium and consider two alternative optimization problems 1 the competitive maximization of mutual information on each link given constraints on the transmit power and on the spectral mask imposed by the radio spectrum regulatory bodies and 2 the competitive maximization of the transmission rate using finite order constellations under the same constraints as above plus a constraint on the average error probability in this first part of the paper we start by showing that the solution set of both noncooperative games is always nonempty and contains only pure strategies then we prove that the optimal precoding multiplexing scheme for both games leads to a channel diagonalizing structure so that both matrix valued problems can be recast in a simpler unified vector power control game with no performance penalty thus we study this simpler game and derive sufficient conditions ensuring the uniqueness of the nash equilibrium interestingly although derived under stronger constraints incorporating for example spectral mask constraints our uniqueness conditions have broader validity than previously known conditions finally we assess the goodness of the proposed decentralized strategy by comparing its performance with the performance of a pareto optimal centralized scheme to reach the nash equilibria of the game in part ii we propose alternative distributed algorithms along with their convergence conditions

magnitude of inefficiency abstract various types of inefficiencies of a system state like the nash equilibrium ne exist such as social inefficiency pareto inefficiency etc a system state is inefficient if it is inferior to another realizable state firstly this article presents a general procedure to obtain each inefficiency measure the procedure brings as each inefficiency measure the maximum degree of corresponding inferiority of the state to some other we examine the procedure in the game theory context vastly many people use the social inefficiency measure represented by the price of anarchy poa however it cannot always serve as a pareto inefficiency measure contrarily the pareto inefficiency measures are yet to establish secondly we follow the procedure to which poa also conforms and obtain pareto inefficiency measures we confirm that they distinguish pareto inefficiencies that poa cannot always distinguish we show a fixed relation between the values of the measures further if a state is proportional to a pareto optimal state proposed measures of strict pareto inefficiency and pareto inefficiency behave in identical and straightforward ways then their value is the proportionality constant using examples we examine the measures

the calculation of posterior distributions by data augmentation comment a noniterative sampling importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest the sir algorithm

a coalitional extension of generalized fuzzy games abstract in this paper we give a coalitional extension of generalized fuzzy games and introduce the notion of coalitional fuzzy equilibria we first prove the existence of coalitional fuzzy equilibria in our model as an application we further show the existence theorem of strong fuzzy equilibria for fuzzy games

the three dimensional global properties of the minflex laurent generalized leontief and translog flexible functional forms abstract we use the caves and christensen procedure to produce the regular regions of three flexible functional forms generalized leontief translog and barnett s new minflexlaurent model we display the regular regions in six cases with three goods using both three dimensional color graphics and two dimensional sections we find that minflex laurent generally has the largest regular region in addition the regular regions of that model are the most stable in shape across the six cases and always expand as real income increases consequently that model is especially well suited for use with income trended time series data

riemann manifold langevin and hamiltonian monte carlo methods the paper proposes metropolis adjusted langevin and hamiltonian monte carlo sampling methods defined on the riemann manifold to resolve the shortcomings of existing monte carlo algorithms when sampling from target densities that may be high dimensional and exhibit strong correlations the methods provide fully automated adaptation mechanisms that circumvent the costly pilot runs that are required to tune proposal densities for metropolis hastings or indeed hamiltonian monte carlo and metropolis adjusted langevin algorithms this allows for highly efficient sampling even in very high dimensions where different scalings may be required for the transient and stationary phases of the markov chain the methodology proposed exploits the riemann geometry of the parameter space of statistical models and thus automatically adapts to the local structure when simulating paths across this manifold providing highly efficient convergence and exploration of the target density the performance of these riemann manifold monte carlo methods is rigorously assessed by performing inference on logistic regression models log gaussian cox point processes stochastic volatility models and bayesian estimation of dynamic systems described by non linear differential equations substantial improvements in the time normalized effective sample size are reported when compared with alternative sampling approaches matlab code that is available from http www ucl ac uk statistics research rmhmc allows replication of all the results reported

computing pure nash and strong equilibria in bottleneck congestion games bottleneck congestion games properly model the properties of many real world network routing applications they are known to possess strong equilibria a strengthening of nash equilibrium to resilience against coalitional deviations in this paper we study the computational complexity of pure nash and strong equilibria in these games we provide a generic centralized algorithm to compute strong equilibria which has polynomial running time for many interesting classes of games such as e g matroid or single commodity bottleneck congestion games in addition we examine the more demanding goal to reach equilibria in polynomial time using natural improvement dynamics using unilateral improvement dynamics in matroid games pure nash equilibria can be reached efficiently in contrast computing even a single coalitional improvement move in matroid and single commodity games is strongly np hard in addition we establish a variety of hardness results and lower bounds regarding the duration of unilateral and coalitional improvement dynamics they continue to hold even for convergence to approximate equilibria

prediction of firm level technical efficiencies with a generalized frontier production function and panel data abstract a stochastic frontier production function is defined for panel data on sample firms such that the disturbances associated with observations for a given firm involve the differences between traditional symmetric random errors and a non negative random variable which is associated with the technical efficiency of the firm given that the non negative firm effects are time invariant and have a general truncated normal distribution we obtain the best predictor for the firm effect random variable and the appropriate technical efficiency of an individual firm given the values of the disturbances in the model the results obtained are a generalization of those presented by jondrow et al 1982 for a cross sectional model in which the firm effects have half normal distribution the model is applied in the analysis of three years of data for dairy farms in australia

stackelberg routing in arbitrary networks we investigate the impact of stackelberg routing to reduce the price of anarchy in network routing games in this setting an fraction of the entire demand is first routed centrally according to a predefined stackelberg strategy and the remaining demand is then routed selfishly by nonatomic players although several advances have been made recently in proving that stackelberg routing can in fact significantly reduce the price of anarchy for certain network topologies the central question of whether this holds true in general is still open we answer this question negatively by constructing a family of single commodity instances such that every stackelberg strategy induces a price of anarchy that grows linearly with the size of the network moreover we prove upper bounds on the price of anarchy of the largest latency first llf strategy that only depend on the size of the network besides other implications this rules out the possibility to construct constant size networks to prove an unbounded price of anarchy in light of this negative result we consider bicriteria bounds we develop an efficiently computable stackelberg strategy that induces a flow whose cost is at most the cost of an optimal flow with respect to demands scaled by a factor of 1 1 finally we analyze the effectiveness of an easy to implement stackelberg strategy called scale we prove bounds for a general class of latency functions that includes polynomial latency functions as a special case our analysis is based on an approach that is simple yet powerful enough to obtain almost tight bounds for scale in general networks

efficiency loss in a network resource allocation game we explore the properties of a congestion game in which users of a congested resource anticipate the effect of their actions on the price of the resource when users are sharing a single resource we establish that the aggregate utility received by the users is at least 3 4 of the maximum possible aggregate utility we also consider extensions to a network context where users submit individual payments for each link in the network they may wish to use in this network model we again show that the selfish behavior of the users leads to an aggregate utility that is no worse than 3 4 of the maximum possible aggregate utility we also show that the same analysis extends to a wide class of resource allocation systems where end users simultaneously require multiple scarce resources these results form part of a growing literature on the price of anarchy i e the extent to which selfish behavior affects system efficiency

distributed seeking of nash equilibria with applications to mobile sensor networks we consider the problem of distributed convergence to a nash equilibrium in a noncooperative game where the players generate their actions based only on online measurements of their individual cost functions corrupted with additive measurement noise exact analytical forms and or parameters of the cost functions as well as the current actions of the players may be unknown additionally the players actions are subject to linear dynamic constraints we propose an algorithm based on discrete time stochastic extremum seeking using sinusoidal perturbations and prove its almost sure convergence to a nash equilibrium we show how the proposed algorithm can be applied to solving coordination problems in mobile sensor networks where motion dynamics of the players can be modeled as 1 single integrators velocity actuated vehicles 2 double integrators force actuated vehicles and 3 unicycles a kinematic model with nonholonomic constraints examples are given in which the cost functions are selected such that the problems of connectivity control formation control rendezvous and coverage control are solved in an adaptive and distributed way the methodology is illustrated through simulations