Description
Book SynopsisA systematic treatment of dynamic decision making and performance measurementModern business environments are dynamic. Yet, the models used to make decisions and quantify success within them are stuck in the past. In a world where demands, resources, and technology are interconnected and evolving, measures of efficiency need to reflect that environment.In Dynamic Efficiency and Productivity Measurement, Elvira Silva, Spiro E. Stefanou, and Alfons Oude Lansink look at the business process from a dynamic perspective. Their systematic study covers dynamic production environments where current production decisions impact future production possibilities. By considering practical factors like adjustments over time, this book offers an important lens for contemporary microeconomic analysis. Silva, Stefanou, and Lansink develop the analytical foundations of dynamic production technology in both primal and dual representations, with an emphasis on directional distance functions. They cover conc
Table of ContentsDedication Forward Introduction Chapter 1 Overview 1.1 What Is a Production Technology? 1.2 Production in the Context of Time 1.2.1 Short run versus long run and being in disequilibrium 1.2.2 Changing Capacity 1.3 Characterizing Adjustment 1.3.1 Adjustment Cost Hypothesis 1.3.2 Isoquants 1.3.3 Non-convex production relationships 1.4 Implications of Adjustment for Measuring Performance Chapter 2 Primal Analytical Foundations of Dynamic Production Analysis 2.1 Introduction 2.2 Set Representation of the Adjustment Cost Production Technology 2.2.1 Adjustment cost production possibilities set 2.2.2 Adjustment cost input requirement sets 2.2.3 Adjustment cost producible output sets 2.3 The Adjustment Cost Transformation Function 2.4 Remarks Chapter 3 Dynamic Economic Decision Making 3.1 Introduction 3.2 Bellman's Dynamic Programming Approach 3.2.1 Cost minimization: Two-period framework 3.2.2 Iso-cost analysis 3.2.3 Cost curves in the short run and long run 3.2.4 Profit maximization 3.3 Generalization to the Continuous Time Case 3.3.1 Cost minimization 3.3.2 Profit maximization 3.3.3 Dynamic duality implications 3.4 Formulating the Cost Minimization Problem in DEA 3.5 Remarks 3.5.1 Nonparametric approaches 3.5.2 Parametric approaches Chapter 4 Dynamic Decision Making, Distance Functions, and Productive Efficiency 4.1 Introduction 4.2 Adjustment-cost Directional Distance Functions 4.2.1 Directional technology distance function 4.2.2 Directional input distance function 4.2.3 Directional output distance function 4.3 Dynamic Duality and Measurement of Productive Efficiency 4.3.1 Intertemporal cost minimization and duality 4.3.2 Temporal cost inefficiency measures 4.3.3 Temporal profit inefficiency measures 4.4 Remarks 4.5 Appendix: Proof of Lemmas 4.6 Appendix: Proof of Properties DDT.1-DDT.8 4.7 Appendix: Proof of DDI.1-DDI.9 Chapter 5 Dynamic Structure of Production and Productivity Change 5.1 Introduction 5.2 Scale, Scope, and Capacity Utilization 5.2.1 Scale elasticity 5.2.2 Cost elasticities and economics of size 5.2.3 Economics of scope and cost concepts 5.2.4 Capacity utilization 5.3 Constructing Measures of Productivity 5.3.1 Structural approach 5.3.2 Luenberger indicator 5.4 Remarks Chapter 6 Econometric Approaches 6.1 Introduction 6.2 Functional Forms 6.3 Structural Parametric Approaches 6.3.1 Estimation of dynamic inefficiency 6.3.2 Estimation of Luenberger TFP growth 6.3.3 Results 6.4 Remarks Chapter 7 Nonparametric Approaches 7.1 Introduction 7.2 Empirical Nonparametric Construction of Dynamic Efficiency 7.2.1 Compute shadow value using the Linear Complementarity Problem 7.2.2 Compute shadow value from the dual problem 7.2.3 Compute shadow value from the directional distance function 7.2.4 Compute shadow value from a parametrically estimated value function 7.3 Empirical Construction the Inner-bound and Outer-bound Technologies 7.4 Remarks 7.5 Appendix: R Code for Estimating Dynamic Technical Inefficiency References .
