Measuring the Impact of Price-Induced Innovation on Technological Progress: Application to the U.S. Food Processing and Distribution Sector

A model of price-induced innovation is presented incorporating long-run prices as arguments in the production function serving the role of stimulating firms to seek innovations. The empirical application examines the production structure and technological progress of the U.S. food processing and distribution sector for the period 1948–1991. The empirical model separates scarcity, innovation, and exogenous technical change responses in analyzing the Morishima elasticities for input combinations and multifactor input biases. The results suggest significant structural changes occurring in the food processing and distribution sector since 1980. Focusing on multifactor input bias, results suggest that there are no wide changes in technical change patterns over the last forty years. However, Morishima elasticity results suggest a more varied pattern of technical change between inputs. The price-induced technical progress has a dominant contribution on input decisions compared with the exogenous technical change.     

Separating Technical Change from Time-Varying Technical Inefficiency in the Absence of Distributional Assumptions

This paper proposes an alternative model for separating technical change from time-varying technical inefficiency. The proposed formulation uses the general index, developed by Baltagi and Griffin (1988), to model technical change in the production frontier function and a quadratic function of time, as in Cornwell, Schmidt and Sickles (1990), to capture the temporal pattern of technical inefficiency. In such a setting, all parameters associated with the rate of technical change and the temporal pattern of technical inefficiency are identified separately. Moreover, the proposed formulation is independent of any distributional assumption concerning the one-sided error term associated with technical inefficiency, and it can be estimated in a single stage with non-linear FGLS. Empirical results based on a translog production frontier, and estimates of technical inefficiency and technical change are presented for the UK dairy sector over the period 1982–1992.     

Adapting Productivity Theory to the Quadratic Cost Function. An Application to the Spanish Electric Sector

In this article we have adapted productivity analysis to the case of a cost model using a quadratic cost function and discrete data. The main theoretical result is a productivity index that can be decomposed into modified versions of the contribution of technical change and the effect of the variations in the scale of production. This framework has been applied to the study of the Spanish electric sector from 1985 to 1996, during which relevant regulatory changes were introduced in order to increase productivity. For this, a normalized quadratic cost function was estimated. The results show important productivity gains with both technical change and scale effect playing important roles.     

Productivity accounting for separable technologies

This paper develops a method for decomposing total factor productivity growth in separable production technologies and uses it to examine the role of pest-damage prevention on agricultural productivity. The rate of technical change is decomposed into output-enhancing and damage-preventing components. Growth accounting cannot provide separate estimates of these two components of technical change, and instead a parametric model is developed based on the dual cost function. The proposed model captures both components of technical change, properly accounts for environmental effects, and also accommodates the presence of capacity utilization and scale biases. The empirical application of the model is to a sample of Cretan olive-oil producers, and the results show that output-enhancing technical change is more important than damage-preventing technical change in explaining observed total factor productivity (TFP) changes. The second largest source of TFP growth is due to the scale effect.     

A comment on gasoline prices and urban structure

The effect of higher gasoline prices on urban concentration and aggregate work travel is investigated with a simple closed-city general equilibrium model used by Robson and Scheffman. Their approximate solution is shown to be invalid at reasonable parameter values; for the case of a Cobb-Douglas utility function, numerical solution indicates a long-run reduction in average trip length of 1.4% to 2.9% from an increase in transportation cost of 0.5 cents per mile. It is noted that this is still much larger than estimates obtained by other means.     

Productivity,efficiency and technical change: measuring the performance of China’s transforming agriculture

As China enters the twenty-first century the health of the agricultural economy will increasingly rely, not on the growth of inputs, but on the growth of total factor productivity (TFP). However, the tremendous changes in the sector—sometimes back and sometimes forwards—as well as evolving institutions make it difficult to gauge from casual observation if the sector is healthy or not. Research spending has waxed and waned. Policies to encourage the import of foreign technologies have been applied unevenly. Structural adjustment policies also triggered wrenching changes in the sector. Horticulture and livestock production has boomed; while the output of other crops, such as rice, wheat and soybeans, has stagnated or fallen. At a time when China’s millions of producers are faced with complex decisions, the extension system is crumbling and farmer professional associations remain in their infancy. In short, there are just as many reasons to be optimistic about the productivity trends in agriculture as to be pessimistic. In this paper, we pursue one overall goal: to better understand the productivity trends in China’s agricultural sector during the reform era—with an emphasis on the 1990–2004 period. To do so, we pursue three specific objectives. First, relying on the National Cost of Production Data Set—China’s most complete set of farm input and output data—we chart the input and output trends for 23 of China’s main farm commodities. Second, using a stochastic production frontier function approach we estimate the rate of change in TFP for each commodity. Finally, we decompose the changes in TFP into two components: changes in efficiency and changes in technical change. Our findings—especially after the early 1990s are remarkably consistent. China’s agricultural TFP has grown at a healthy rate for all 23 commodities. TFP growth for the staple commodities generally rose around 2% annually; TFP growth for most horticulture and livestock commodities was even higher (between 3 and 5%). Equally consistent, we find that most of the change is accounted for by technical change. The analysis is consistent with the conclusion that new technologies have pushed out the production functions, since technical change accounts for most of the rise in TFP. In the case of many of the commodities, however, the efficiency of producers—that is, the average distance of producers from the production frontier—has fallen. In other words, China’s TFP growth would have been even higher had the efficiency of production not eroded the gains of technical change. Although we do not pinpoint the source of rising inefficiency, the results are consistent with a story that there is considerable disequilibrium in the farm economy during this period of rapid structural change and farmers are getting little help in making these adjustments from the extension system.     

Estimation of stochastic frontier production functions with input-oriented technical efficiency

This paper deals with estimation of input-oriented (IO) technical inefficiency using a stochastic production frontier model. Econometrically the model is similar to a class of models that arise in specifying technical inefficiency in cost-minimizing and profit-maximizing frameworks. The standard maximum likelihood (ML) method that is used to estimate output-oriented (OO) technical efficiency cannot be applied to estimate these models. We use a simulated ML approach to estimate the IO production function and compare results from the IO and OO models, mainly to emphasize the point that estimated efficiency, returns to scale, technical change, etc., differ depending on whether one uses the model with IO or OO technical inefficiency.     

Some Applications of Input–Output Analysis in a Gold Mine

In this paper, some applications of a mixed physical-financial input–output model for a large gold mine in China are described. This mixed input–output model is a basic part of the mine's decision-making system, called an interactive and hierarchical multi-objective feedback decision-making system of the gold mine's production and management. The model is used for the following: (1) to analyze quantitatively how the changes in the economic, technical and geological factors affect the mine's production and management; (2) to search for a series of bottleneck components in the mine when the capacities of some components of the mine change; (3) to optimize mine planning with the help of mathematical programming (linear programming, 0–1 programming) and computer simulation.     

An industrial network flow information integration model for supply chain management and intelligent transportation

Industrial network flow involves three domains: infrastructure, individual subjects of movement, and planning and control of the movement. Examples include supply chain and intelligent transportation. These traditionally isolated domains can be digitally connected to enhance their performance. Digitization of the infrastructure provides real-time data to facilitate its operation, while digitally connecting the subjects to the infrastructure allows for tailored services and support to particular subjects. Connection of both to the enterprise information systems enables adaptive control for the application (e.g. logistics) at a global optimization level. Previous results in the field cover separate aspects of planning/routing, real-time monitoring, and trip support. Toward this end, a new highway-based subject-infrastructure-enterprise (SIE) information integration model using digital connection is proposed to the field of industrial network flow control for application to intelligent transportation and supply chain management. The SIE model supports industrial network flow control in a way comparable to an adaptive control panel administering an automated material handling system. In this metaphor, the global infrastructure becomes ‘controllable’ similar to factory conveyors and automated guided vehicles. This paper presents a conceptual design substantiated with information requirements analysis. An empirical experiment at locations in New York State shows the technical feasibility of the digital connection envisioned.     

Multi-modal,multi-output,multiregional variable input-output model

A multi-modal, multi-output, multiregional variable input-output (MMMVIO) model is introduced to evaluate the economic impact of a transportation system. The MMVIO model differs from the conventional input-output models by being price and cost sensitive. The regional technical coefficients, trade coefficients, modal choice of shipment, input mix and output composition are determined by the price and cost variables, a property not shared by the conventional input-output models.The transportation system reduces shipping cost of delivering commodities between regions, thereby stimulating economy of trading regions. The MMMVIO model captures the development impact incident to the transportation system.     

Estimation of technical and allocative inefficiency: A primal system approach

The estimation of technical and allocative inefficiencies using a flexible (translog) cost system is found to be quite difficult, especially when both the inefficiencies are random. In this paper we use the alternative primal system consisting of the production function (translog) and the first-order conditions of cost minimization. The estimation of the primal system is more straightforward and it enables us to estimate observation-specific technical and allocative inefficiencies, and their impact on input demand and cost. We use data on steam-electric generating plants from the U.S. to estimate the model using both Cobb–Douglas and translog production functions.     

Analyzing China's productivity growth: Evidence from manufacturing industries

This article examines the growth attributes of manufacturing industries in China for the sample period of 1999–2007. The output growth of manufacturing industries classified under four groups and four regions is decomposed into four components of input growth, scale effect, technical progress, and technical efficiency change. A stochastic frontier model is applied to the translog production function to estimate technical efficiency. Despite the conventional argument that input growth and technical progress are important factors to output growth, the empirical findings show a significant scale effect but a weak technical efficiency change. The contribution to growth from labor has been replaced by human and physical capitals. Structural transformation in the industrial sector is evident, so as regional imbalances.     

Learning-by-doing and the sources of productivity growth: A dynamic model with application to U.S. agriculture

The significance of learning to productivity growth is formulated within a dynamic adjustment-cost framework. Explicitly treating the acquisition of knowledge as a firm-specific capital good entering the production function along with other conventional inputs, the dynamic optimization model integrates the learning-by-doing hypothesis with technical change, scale, and disequilibrium input use effects in the aggregate productivity analysis. The theoretical framework is applied to examining the dynamic components accounting for the growth of U.S. production agriculture over the 1950–82 period. The results imply a less important role for technical change and assign a substantial role to the previously unmeasured contribution of learning-by-doing to the growth of aggregate agriculture industry.The editor for this paper was Melvyn Fuss.     

Estimating Technological Change Using a Stochastic Frontier Production Function Framework: Evidence from U.S. Firm-Level Data

This paper presents a methodology for estimating an index of technological change using firm-level data in a stochastic frontier production function model that takes into account time-varying technical inefficiency. In contrast to the Solow divisia index approach, econometric estimation of the index with panel data allows the researcher to separate technical progress from the stochastic measurement error. Applying the econometric methodology to a panel of 908 publicly-traded U.S. firms from the COMPUSTAT database, we find evidence of a significant downturn in general technological change for the period, 1970– 1989, whereas the divisia index methodology applied to the same data shows stagnation. When the sample is divided into Manufacturing, Services, and Miscellaneous categories we find that estimates of technological change for the three groups display markedly different stochastic behavior and that the Services group is the source of the downturn.     

两种等效益面生产函数与全要素生产率变化率的分解

本文根据规模报酬可变还是规模报酬不变，分别定义了一般等效益面生产函数和典型等效益面生产函数。由一般等效益面生产函数的离散型分解式可以测算一个生产单元的纯技术进步，以及纯技术效率变化对经济增长的贡献；而由典型等效益面生产函数可以将全要素生产率的变化率分解为典型技术进步率、纯技术效率和规模效率的变化率之和。进而由具有明确几何意义的离散型分解式分别测算典型技术进步和规模效率对经济增长的贡献。等效益面生产函数与分解式的几何意义还说明，全要素生产率的改变最终是由技术创新、制度创新和管理创新共同推动的。     

The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach

This study measures productivity growth on Irish dairy farms over the period 1984–2000. A total factor productivity index is constructed for the dairy system and is decomposed into technical change, efficiency change, and changes in scale efficiency. This is achieved by estimating a stochastic output distance function model of the production technology in use on Irish dairy farms. Overall, productivity on Irish dairy farms grew by 1.2% per annum over the sample period.

物流系统的数学模型

作为企业“第三利润源泉”的物流,对其成本的控制目前已经成为物流合理化进程中的热点问题。文章把物流系统看成是一个特殊的生产系统,用柯布一道格拉斯生产函数方程对其进行建模。把物流系统的产出——满足服务需求看成是此方程的产出,把运输费用、储存费用和管理费用看戍是投入．对物流系统的数学建模提供了一个新的方法。最后用这个物流系统模型对社会物流系统进行了实例验证。     

Estimating demand systems when outcomes are correlated counts

We describe and employ a Bayesian posterior simulator for fitting a high-dimensional system of ordinal or count outcome equations. The model is then applied to describe the multiple site recreation demands of individual agents, and we argue that our approach provides advantages relative to existing methods commonly applied in this area. In particular, our model flexibly adjusts to match observed frequencies in trip outcomes, permits a flexible correlation pattern among the sites visited by individuals, and the posterior simulator for fitting this model is relatively easy to implement in practice. We also describe how the posterior simulations produced from the model can be used to conduct a variety of counterfactual experiments, including predicting behavioral changes and describing welfare implications resulting from shifts in exogenous demographic and site characteristics. We illustrate our method using data from the Iowa Lakes Project by modeling the visitation patterns of individuals to a set of twenty-nine large Iowa lakes. Consistent with previous findings in the literature, we see strong evidence that own and cross-price effects on trip demand are negative and positive, respectively, that higher income increases the likelihood of visiting most sites, and that a commonly used indicator of water quality, Secchi transparency, is positively correlated with the number of trips taken. In addition, the correlation structure among the errors reveals a complex pattern in which unobserved factors affecting trip demand are generally (though not strictly) positively correlated across sites. The flexibility and richness with which we are able to characterize the demand system provides a solid platform for counterfactual analysis, where we find significant behavioral and welfare effects from changes in site availability, water quality, and travel costs.     

Is technical change embodied in the capital stock or new investment?

The question of technical change and productivity growth is one of the fundamental empirical issues of our time. Surprisingly, Solow's original question of whether technical change is embodied in investment or the entire capital stock has been largely neglected. This paper seeks to bridge the early work of Solow and others on the extent of embodiment of technical change with the more modern approach to estimating the structure of production and technical change using multifactor cost functions. We also attempted to identify the source and structural nature of embodied technical change by decomposing it. Our theoretical model is applied to a pooled cross-section of six OECD countries for the 1965–1989 period. Our preferred model is one of full factor-augmenting embodied technical change because technical change augmenting the entire capital stock tends to overstate quality change in the aggregate capital stock more than that embodied in new investment. This model specification supports the view that technical change is embodied in the stock of capital structure and is embodied in new investment of capital equipment.     

A Decomposition of Total Factor Productivity Growth in Korean Manufacturing Industries: A Stochastic Frontier Approach

This paper applies a stochastic frontier production model to Korean manufacturing industries, to decompose the sources of total factor productivity (TFP) growth into technical progress, changes in technical efficiency, changes in allocative efficiency, and scale effects. Empirical results based on data from 1980–1994 show that productivity growth was driven mainly by technical progress, that changes in technical efficiency had a significant positive effect, and that allocative efficiency had a negative effect. This study suggests that specific guidelines are required to promote productivity in each industry, and provides additional insight into understanding the recent debate on TFP growth in Korean manufacturing.