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.     

Schooling and productivity growth: evidence from a dual growth accounting application to U.S. states

This paper exploits the dual growth accounting framework to determine the effect of schooling on total-factor productivity (TFP) growth for U.S. states over 1980–2010. The paper contributes to the literature by constructing TFP growth measures, in the process, both real wage growth and real user cost growth measures at the state level. The growth accounting exercise reveals that states display considerable heterogeneity in TFP growth with both real wage growth and real user cost growth equally contributing to it. While our econometric estimates reveal significant TFP growth effects associated with college education, they are considerably lower in magnitude when compared to the earlier studies. Productivity growth effects associated with high school education remain insignificant. Our empirical findings are further validated by the use of instrumental variable estimation to address the endogeneity of the schooling variables and are also robust to the inclusion of a rich set of control variables, alternative TFP growth measures as well as to the tests to draw robust inferences in the presence of weak instruments.     

Limited information Bayesian analysis of a simultaneous equation with an autocorrelated error term and its application to the U.S. gasoline market

Using Markov Chain Monte Carlo algorithms within the limited information Bayesian framework, we estimate the parameters of the structural equation of interest and test weak exogeneity in a simultaneous equation model with white noise as well as autocorrelated error terms. A numerical example and an estimation of the supply and demand equations of the U.S. gasoline market show that if we ignore autocorrelation we obtain unreasonable posterior distributions of the parameters of interest. Also we find that the hypothesis of the asymmetric effect of the changes in oil price on the changes in gasoline price is rejected. Oil inventory has a significant negative effect on the gasoline price.     

On the Technically Efficient Organization of an Industry: A Study of U.S. Airlines

In nonparametric analysis of production efficiency, the focus of attention is typically on the individual firm. In this article, we evaluate efficiency in resource utilization at the industry level. We propose an integer programming model to measure the extent of input saving possible if the observed output level of the industry is allocated to an optimal number of identical firms. This approach is applied to data for U.S. airlines covering the period 1970–84. Our results confirm that there were too few airlines prior to deregulation and suggest that there were too many firms during the early years of the post-deregulation era.     

Information technology and U.S. productivity growth: evidence from a prototype industry production account

The rapid productivity growth in the US during the Information Age, prior to the dot-com bust in 2000, and the large contribution of the IT producing sector, is well known. Less known are the sources of the surprisingly rapid TFP growth during the slow growth period after 2000. We construct an account of US economic growth by aggregating over detailed industries using a new data set based on the NAICS classification. We find that, post 2000, TFP originating from the IT-Producing sector decelerated relative to the IT boom, but still accounted for 40% of aggregate productivity growth. This deceleration was counterbalanced by the contribution from IT-Using sectors, which buoyed aggregate TFP growth to almost the same rate as the 1995–2000 period. For aggregate GDP, the contributions to the growth rate of 2.8% during 2000–2007 were: capital input (1.7% points), labor input (0.4) and TFP (0.7).     

Panel data analysis of U.S. coal productivity

We analyze labor productivity in coal mining in the United States using indices of productivity change associated with the concepts of panel data modeling. This approach is valuable when there is extensive heterogeneity in production units, as with coal mines. We find substantial returns to scale for coal mining in all geographical regions, and find that smooth technical progress is exhibited by estimates of the fixed effects for coal mining. We carry out a variety of diagnostic analyses of our basic model and primary modeling assumptions, using recently proposed methods for addressing ‘errors-in-variables’ and ‘weak instrument bias’ problems in linear and nonlinear models.     

A profit function approach to measuring productivity growth: The case of U.S. manufacturing

This article proposes a method of estimating productivity growth using an estimated profit function. The approach has the advantage of incorporating endogenous changes in profit-maximizing output levels that would result from productivity changes. As with the cost function, it can be easily adapted to accomodate the presence of quasi-fixed factors. The article first develops the methodology and shows the equivalence between the proposed measure and other measures of productivity based on cost or production functions. An empirical application to the measurement of productivity changes in the U.S. manufacturing industry is presented next. The profit-function measure is compared to a nonparametric measure based on the same data and to the results of other studies of U.S. manufacturing.The refereeing process of this paper was handled through J. deMelo.     

A primal-dual approach to nonparametric productivity analysis: The case of U.S. agriculture

Nonparametric methods for measuring productivity indexes based on bounds for the underlying production technology are presented. Following Banker and Maindiratta, the lower bound is obtained from a primal approach while the upper bound corresponds to a dual approach to nonparametric production analysis. These nonparametric bounds are then used to estimate input-based and output-based distance functions. These radial measures provide the basis for measuring productivity indexes. Application to times series data on U.S. agriculture indicates a large gap between the primal lower bound and the dual upper bound. This generates striking differences between the primal and dual nonparametric productivity indexes.Respectively, professor and associate professor of Agricultural Economics, University of Wisconsin-Madison. Seniority of authorship is equally shared. We would like to thank Rolf Färe and an anonymous reviewer for useful comments on an earlier draft of the paper. This research was supported in part by a Hatch grant from the College of Agriculture and Life Sciences, University of Wisconsin-Madison.     

The dynamics of efficiency and productivity growth in U.S. electric utilities

This study recognizes explicitly the efficiency gain or loss as a source in explaining the growth. A theoretically consistent method to estimate the decomposition of dynamic total factor productivity growth (TFP) in the presence of inefficiency is developed which is constructed from an extension of the dynamic TFP growth, adjusted for deviations from the long-run equilibrium within an adjustment-cost framework. The empirical case study is to U.S. electric utilities, which provides a measure to evaluate how different electric utilities participate in the deregulation of electricity generation. TFP grew by 2.26% per annum with growth attributed to the combined scale effects of 0.34%, the combined efficiency effects of 0.69%, and the technical change effect of 1.22%. The dynamic TFP grew by 1.66% per annum for electric utilities located within states with the deregulation plan and 3.30% per annum for those located outside. Electric utilities located within states with the deregulation plan increased the outputs by improving technical and input allocative efficiencies more than those located outside of states with deregulation plans.

Efficiency and productivity growth comparisons of European and U.S. Air carriers: A first look at the data

In this paper we carry out technical efficiency and productivity growth comparisons among the four largest European carriers and eight of their American counterparts. The time period of our comparisons is 1976 through 1986. This is a particularly interesting period since it begins just after the informal steps toward deregulation in the United States and ends just prior to the introduction of the first wave of reforms by the Council of Ministers in Europe. We also identify the potential efficiency gains of the European liberalization by comparing efficiency differences between the two carrier groups. The reductions in inefficiency describe the amount that inputs can be decreased without altering output.     

A comparison of multifactor productivity calculations of the U.S. agricultural sector

Since the late 1970s, there have been fourteen studies that have estimated multifactor productivity (MFP) growth rates for the U.S. agricultural sector. The estimates of average annual MFP growth rates have ranged from 1.15 to 1.94 percent per year for studies using the gross productivity approach. The purpose of this paper is to identify the reasons for these different estimates. We consider theoretical and empirical factors and do not find any single reason that satisfactory explains the variation. The alternative estimates appear to be most sensitive to the coverage of years.     

Externalities, efficiency, regulation, and productivity growth in the U.S. electric utility industry

This paper examines the decomposition of total factor productivity growth for firms subject to regulation, given the production of a bad output. The production of good and bad outputs provides benefits and costs to society. Corporate socially responsible firms recognize the cost to society of producing the bad output. The paper separates the production technology and regulation effects from both the scale and technical change components. The paper also examines the measurement and decomposition of productivity growth when not accounting for production of the bad output. Using a 1992–2000 panel of 34 U.S. investor-owned electric utilities, results indicate that improvements in the scale, efficiency change, and technical change components contributed to positive growth. Not accounting for production of the bad output led to, on average, an overestimation of both the rate of productivity growth, and the contributions of scale economies and technical change to changes in productivity growth.

A cross-country comparison of productivity growth using the generalised metafrontier Malmquist productivity index: with application to banking industries in Taiwan and China

This paper is an extension of the metafrontier Malmquist productivity index, which takes into account the effect of scale efficiency change in its decomposition for both the non-parametric and parametric frameworks. Meanwhile, the ‘catch-up’ in the index is also disintegrated as two components: pure technological catch-up and frontier catch-up. An empirical application that uses unbalanced panel data of the Taiwanese and Chinese commercial banking industry is also conducted under a parametric framework. The results reveal that the adverse scale efficiency change is the key factor to inducing the inferior productivity growth seen in Chinese banks compared with Taiwanese banks, which spotlights the importance of the scale efficiency change term on productivity measures. It also provides one possible explanation for the recent hot issue about the motives for the two shores of the Taiwan Straits advancing financial openness to each other and mutually signing a banking Memorandum of Understanding.     

美国城市增长管理的方法与启示

介绍美国主要的三类城市增长管理方法,即管理和控制城市增长区间和特点的方法;保护自然资源、环境质量和生态特征的方法;提供有效的公共基础设施的方法.分别对每一类方法进行了系统的介绍,进而指出对中国城市增长管理和土地利用管制的启示.     

A nonlinear long memory model, with an application to US unemployment

Two important empirical features of US unemployment are that shocks to the series seem rather persistent and that it seems to rise faster during recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, we put forward a new time series model and evaluate its empirical performance. We find that the model describes the data rather well and that it outperforms related competitive models on various measures of fit.     

Does pay affect productivity or react to it?: Examination of U.S. manufacturing

There may be a bi-directional relationship between wages and labor productivity. According to conventional theory, employers reward improvements in productivity by raising pay. It also has been argued that wage increases can provide an incentive to improve productivity. This study applies a technique by Geweke to identify the feedback between pay and productivity in U.S. manufacturing. For the 1949–1998 period, measures of directional feedback indicate that both “pay as reward” and “pay as incentive” behaviors have occurred, but the results vary across manufacturing subsectors.     

Efficiency, productivity, and scale economies in the U.S. property-liability insurance industry

The paper examines efficiency, productivity and scale economies in the U.S. property-liability insurance industry. Productivity change is analyzed using Malmquist indices, and efficiency is estimated using data envelopment analysis. The results indicate that the majority of firms below median size in the industry are operating with increasing returns to scale, and the majority of firms above median size are operating with decreasing returns to scale. However, a significant number of firms in each size decile have achieved constant returns to scale. Over the sample period, the industry experienced significant gains in total factor productivity, and there is an upward trend in scale and allocative efficiency. More diversified firms and insurance groups were more likely to achieve efficiency and productivity gains. Higher technology investment is positively related to efficiency and productivity improvements.     

A structural equation approach to measuring technological change: An application to Southeastern U.S. Agriculture

The study demonstrates a method of obtaining consistent estimates of technological change. This was accomplished by extending Theil's differential input demand system into a Multiple Indicator, Multiple Cause (MIMIC) structural equation latent variable model which explicitly accounts for the fact that technological progress is not directly observed and therefore is invariably measured with error. Results obtained for the agricultural sector of the Southeastern states suggest that technological change has been an important determinant of agricultural production and is bias towards the use of capital and against the use of land and labor.This research was partially supported by the McKethan-Matherly Eminent Scholar Chair, graduate school of Business Administration, University of Florida.     

The fountain of knowledge: an epistemological perspective on the growth of U.S. SBIR-funded firms

The premise of this paper is that a basis for firms receiving Small Business Innovation Research (SBIR) research awards to develop commercializable technologies is not only their proposed creative ideas but also their endowment of attendant knowledge necessary to develop the technology being proposed. Based on this premise, we propose that those firms that have higher growth rates attributable to their SBIR awards are also those firms that are more creative and have more knowledge endowments. Empirically, we quantify a firms creativity and its sources of research knowledge in terms of its past experiences, and we find that firms with more technical experience and sector experience are those that have realized higher growth rates from their SBIR-funded research.