Dissecting Aggregate Output and Labour Productivity Change

This paper is about the relation between output and productivity measures for individual production units and those for aggregates such as industries, sectors, or economies. In the framework of discrete timeperiods several useful expressions are derived and confronted with results from the literature

The Many Decompositions of Total Factor Productivity Change

Total factor productivity change, here defined as output quantity change di- vided by input quantity change, is the combined result of (technical) efficiency change, technological change, a scale effect, and input and output mix ef- fects. Sometimes allocative efficiency change is supposed to also play a role. Given a certain functional form for the productivity index, the problem is how to decompose such an index into factors corresponding to these five or six components. A basic insight offered in the present paper is that mean- ingful decompositions of productivity indices can only be obtained for indices which are transitive in the main variables. Using a unified approach, we ob- tain decompositions for Malmquist, Moorsteen-Bjurek, price-weighted, and share-weighted productivity indices. A unique feature of this paper is that all the decompositions are applied to the same dataset of a real-life panel of decision-making units so that the extent of the differences between the various decompositions can be judged

A novel decomposition of aggregate total factor productivity change

An industry is an ensemble of individual firms (decision making units) which may or may not interact with each other. Similarly, an economy is an ensemble of industries. In National Accounts terms this is symbolized by the fact that the nominal value added produced by an industry or an economy is the simple sum of firm-, or industry-specific nominal value added. From this viewpoint it is natural to expect that there is a relation between (aggregate) industry or economy productivity and the (disaggregate) firm- or industry-specific productivities. In an earlier paper (Statistica Neerlandica 2015) three time-symmetric decompositions of aggregate value-added-based total factor productivity change were developed. In the present paper a fourth decomposition will be developed. A notable difference with the earlier paper is that the development is cast in terms of levels rather than indices. Various aspects of this new decomposition will be discussed and links with decompositions found in the literature unveiled. It turns out that one can dispense with the usual neo-classical assumptions

Measuring Productivity Change without Neoclassical Assumptions: A Conceptual Analysis

The measurement of productivity change (or difference) is usually based on models that make use of strong assumptions such as competitive behaviour and constant returns to scale. This survey discusses the basics of productivity measurement and shows that one can dispense with most if not all of the usual, neoclassical assumptions. By virtue of its structural features, the measurement model is applicable to individual establishments and aggregates such as industries, sectors, or economies

The Residual: On Monitoring and Benchmarking Firms, Industries, and Economies with respect to Productivity

Inaugural address given in shortened form at the occasion of accepting the appointment as professor of business administration, in particular the measurement of price, quantity, and productivity changes and economic-statistical research, supported by Statistics Netherlands, at the Rotterdam School of Management / Faculteit Bedrijfskunde of Erasmus University Rotterdam on Friday, November 9, 2001Productivity is an important component of profitability, and therefore an important variable for monitoring and benchmarking exercises. This paper discusses the necessary accounting model as well as the various measurement problems one gets involved in. By virtue of its structural features, this model is applicable to individual firms and aggregates such as industries or economies.Though the measurement of productivity change and productivity differences is important, more important is their explanation. Thus firstly, this paper reviews recent results relating to the decomposition of aggregate productivity change into components due to firm dynamics and intra-firm productivity change. All these results were obtained by studying longitudinal enterprise microdata sets. Secondly, this paper reviews a number of methods for decomposing productivity change and productivity differences, whether at the individual firm level or at aggregate level, into partial measures relating to technological change and efficiency change. The combination of both research strategies seems to be a promising undertaking

Aggregation Methods in International Comparisons

This paper reviews the progress that has been made over the past decade in understanding the nature of the various multilateral in- ternational comparison methods. Fifteen methods are discussed and subjected to a system of ten tests. In addition, attention is paid to recently developed methods based on the principle of chaining, model based approaches, and the economic approach to international com- parison

Symmetric decompositions of cost variation

In this paper a number of symmetric, empirically implementable decompositions of the cost variation (in difference and ratio form) of a production unit are developed. The components distinguished are price level change, technical efficiency change, allocative efficiency change, technological change, scale of activity change, and price structure change. Given data from a (balanced) panel of production units, all the necessary ingredients for the computation of the various decompositions can be obtained by using linear programming techniques (DEA). An application is provided

A Toolbox for Calculating and Decomposing Total Factor Productivity Indices

Total Factor Productivity Toolbox is a new set of functions to calculate the main Total Factor Productivity (TFP) indices and their decompositions, based on Shephard’s distance functions, and using Data Envelopment Analysis (DEA) programming techniques. The package includes code for the standard Malmquist, Moorsteen–Bjurek, price-weighted and share-weighted TFP indices, allowing for the choice of orientation (input or output), reference period (base, comparison, geometric mean), returns to scale (variable or constant), and specific decompositions (aggregate, or identifying scale effects, as well as input and output mix effects). Classic definitions of TFP corresponding to the Laspeyres, Paasche, Fisher, or Törnqvist formulas can also be calculated as particular cases. This paper describes the methodology and implementation of the productivity functions in MATLAB. We compare the results corresponding to the different definitions by studying productivity trends in the US agriculture at the individual state level

An Evaluation of Cross-Efficiency Methods, Applied to Measuring Warehouse Performance

In this paper method and practice of cross-efficiency calculation is discussed. The main methods proposed in the literature are tested not on a set of artificial data but on a realistic sample of input-output data of European ware- houses. The empirical results show the limited role which increasing automation investment and larger warehouse size have in increasing productive performance. The reason is the existence of decreasing returns to scale in the industry, resulting in sub-optimal scales and inefficiencies, regardless of the operational performance of the facilities. From the methodological perspective, and based on a multidimensional metric which considers the capability of the various methods to rank warehouses, their ease of implementation, and their robustness to sensitivity analyses, we conclude to the superiority of the classic Sexton et al. (1986) method over recently proposed, more sophisticated methods