Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. We estimate the parameters of a production function for the equipment industry and then use those estimates to analyze the evolution of plant-level productivity over this period. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Since firms choices on whether to liquidate and the on the quantities of inputs demanded should they continue depend on their productivity, we develop an estimation algorithm that takes into account the relationship between productivity on the one hand, and both input demand and survival on the other. The algorithm is guided by a dynamic equilibrium model that generates the exit and input demand equations needed to correct for the simultaneity and selection problems. A fully parametric estimation algorithm based on these decision rules would be both computationally burdensome and require a host of auxiliary assumptions. So we develop a semiparametric technique which is both consistent with a quite general version of the theoretical framework and easy to use. The algorithm produces markedly different estimates of both production function parameters and of productivity movements than traditional estimation procedures. We find an increase in the rate of industry productivity growth after deregulation. This in spite of the fact that there was no increase in the average of the plants' rates of productivity growth, and there was actually a fall in our index of the efficiency of the allocation of variable factors conditional on the existing distribution of fixed factors. Deregulation was, however, followed by a reallocation of capital towards more productive establishments (by a down sizing, often shutdown, of unproductive plants and by a disproportionate growth of productive establishments) which more than offset the other factors' negative impacts on aggregate productivity.

The Dynamics Of Productivity In The Telecommunications Equipment Industry

This paper analyzes productivity growth in seventeen OECD countries over the period 1979-88. A nonparametric programming method (activity analysis) is used to compute Malmquist productivity indexes. These are decomposed into two component measures, namely, technical change and efficiency change. The authors find that U.S. productivity growth is slightly higher than average, all of which is due to technical change. Japan's productivity growth is the highest in the sample with almost half due to efficiency change. Copyright 1994 by American Economic Association.

Productivity growth, technical progress and efficiency change in industrial countries

Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. Our empirical focus is on estimating the parameters of a production function for the equipment industry, and then using those estimates to analyze the evolution of plant-level productivity. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Firms' choices on whether to liquidate, and on input quantities should they continue, depended on their productivity. This generates a selection and a simultaneity problem when estimating production functions. Our theoretical focus is on providing an estimation algorithm which takes explicit account of these issues. We find that our algorithm produces markedly different and more plausible estimates of production function coefficients than do traditional estimation procedures. Using our estimates we find increases in the rate of aggregate productivity growth after deregulation. Since we have plant-level data we can introduce indices which delve deeper into how this productivity growth occurred. These indices indicate that productivity increases were primarily a result of a reallocation of capital towards more productive establishments.

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The Dynamics of Productivity in the Telecommunications Equipment Industry

The economic theory of index numbers and the measurement of input, output, and productivity

This paper analyzes productivity growth in 17 OECD countries over the period 1979-1988. A nonparametric programming method (activity analysis) is used to compute Malmquist productivity indexes. These are decomposed into two component measures, namely, technical change and efficiency change. We find that U.S. productivity growth is slightly higher than average, all of which is due to technical change. Japan's productivity growth is the highest in the sample, with almost half due to efficiency change. (JEL C43, D24) In this paper we apply recently developed

Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries

Focuses on additive and homogeneous production possibility frontiers that have played an important role in formulating statistical tests of the theory of production. Characterization of the class of production possibility frontiers that are homogenous and additive; Representation of the production possibility frontier; Statistical tests of the theory of production. (Из Ebsco)

https://www.jstor.org/stable/pdfplus/1927992.pdf

Transcendental logarithmic production frontiers

Early in this century economists began to give serious attention to making comparisons using index number techniques. There was extensive debate as to which index number formulas were the most appropriate for carrying out comparisons.1 The debate was extensive in no small part due to the lack of agreement as to criteria for preferring one formula over another. In recent decades there has been a resurgence of interest in index numbers, resulting from discoveries that the properties of index numbers can be directly related to the properties of the underlying aggregator functions that they represent. The underlying functions - production functions, utility functions, etc. - are the building blocks of economic theory, and the study of relationships between these functions and index number formulas has been referred to by Samuelson and Swamy (I974) as the economic theory of index numbers.2 A key development in the economic theory of index numbers has been the demonstration that numerous index number formulas can be explicitly derived from particular aggregator functions. This development provides a powerful new basis for selecting an index number procedure. Rather than starting the selection process with a number of plausible index number formulas, one can specify an aggregator function with desirable properties and derive the corresponding index number procedure. The resulting index is termed exact for that particular aggregator function. Diewert (I976) makes a strong case for limiting the consideration of aggregator functions to those which are flexible, i.e. those which can provide a second order approximation to an arbitrary aggregator function. He has termed index numbers that are exact for flexible aggregator functions 'superlative '. There are two superlative index numbers that are of particular interest - the Fisher Ideal index and the Tornqvist-Theil-translog index. Fisher (I 922) dubbed the following index Ideal since it best satisfied his several criteria for choosing among index numbers:

Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers

The translog function and the substitution of equipment, structures, and labor in U.S. manufacturing 1929-68

There has been a perception that U.S. trunk airlines had an inherent cost advantage over smaller regional airlines because of economies of scale. We have formulated a general model of airline costs, which we estimate by using panel data on large and small airlines. Differences in scale are shown to have no role in explaining higher costs for small airlines. The primary factor explaining cost differences is density of traffic within an airline's network. Also of major importance is the average length of individual flights.

Laurits R. Christensen

Papers

The economic theory of index numbers and the measurement of input, output, and productivity

Transcendental logarithmic production frontiers

Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers

The translog function and the substitution of equipment, structures, and labor in U.S. manufacturing 1929-68

Economies of Density versus Economies of Scale: Why Trunk and Local Service Airline Costs Differ