Utilization of fixed capital and Soviet industrial growth

Growth rates of output and factor productivity in Soviet industry fluctuate around a long-term downward trend. These fluctuations can be partially explained by fluctuations in the growth of services of capital. The capacity utilization rate is taken as a proxy for the extent of utilization of capital stock. Variations in the capacity utilization rate explain a significant part of the changes in the rate of growth of total factor productivity between 1970–1983. Declines in the capacity utilization rate are caused by errors in the allocation of investment, which create an imbalance of capacities between raw-materials and manufacturing sectors.Useful suggestions by Emil Bej, Robert Cambell, Richard Harmstone, Kenneth Gray, and Josef Brada are grateful acknowledged     

Intangible investment in people and productivity

Organizational activity, information and communication technology work, and research and development (R&D) can be classified as work that creates intangible capital. We measure the returns to these three types of labor input by accounting for differences in their productivity compared with other labor inputs using Finnish firm-level data from 1998 to 2008. We apply a novel idea to use hiring as one proxy for productivity and demand shocks. We find that organizational workers increase total factor productivity and improve the profitability of high-productivity firms. R&D workers account for a large share of intangible capital; however, the returns to R&D are low. Investments in organizational competence are more likely to result in more rapid productivity growth. Firms with performance-related pay or domestically owned firms with extensive foreign activities have been among the highest performers with respect to the use of organizational work.     

Analysis of regional productivity with capital as a quasi-fixed factor

Most existing studies of regional productivity growth do not incorporate the effect of variations in capacity utilization on changes in output. By failing to do so, their factor productivity estimates are biased. To overcome this shortcoming, we adjust multifactor productivity growth measure for changes in capacity utilization. Our technique recognizes that capital is a quasi-fixed factor which implies that capital in the short run can be either under- or over-utilized by a firm. Our results from 1974 to 1978 show that capacity adjusted multifactor productivity growth measure exceeds capacity unadjusted multifactor productivity growth measure for the nine census divisions. The bias in the capacity unadjusted measure of multifactor productivity growth is approximately 8 percent in East North Central and over 33 percent in Mountain. We find that the aggregate factor productivity growth is slowest in the traditional manufacturing belt (Middle Atlantic and East North Central divisions). The level of aggregate factor productivity in the manufacturing belt, however, is almost 33 percent higher than in regions in the south.     

Returns to scale effect in labour productivity growth

Economists acknowledge that technical progress and growth in capital inputs increase labour productivity (LP). However, less focus is given to the realization that changes in labour input alone could also affect LP. Because this effect disappears when the short-run technology exhibits constant returns to scale, we call it the returns to scale effect. We decompose growth in LP into three contributing factors: (1) technical progress, (2) capital input growth and the (3) returns to scale effect. We propose theoretical measures for these three components and show that they coincide with the index number formulae consisting of prices and quantities of inputs and outputs. Subsequently, we apply the results of our decomposition to US industry data for 1987–2009. LP in the services sector is shown to grow much slower than that in the goods sector during the 1987–1995 productivity slowdown period. We conclude that the returns to scale effect can considerably explain the gap in LP growth between the two industry groups.     

Errors of measurement and the recent acceleration in manufacturing productivity growth

Using detailed (4-digit SIC) industry data for the years 1958–1989, I examine whether the recent acceleration in manufacturing productivity can be attributed to the effects of mismeasurement of the prices of inputs and output, by testing a model linking a set of proxy variables for measurement error to a series of measures of acceleration in total factor productivity (TFP). Alternative TFP estimates are presented in order to determine if the findings are sensitive to the method of TFP calculation. The results are inconsistent with the measurement error hypothesis and invariant to the specification of the TFP equation.     

Public infrastructure,input efficiency and productivity growth in the Canadian food processing industry

Canadian food processing is an important manufacturing industry, accounting for 13 percent of shipments. By its nature food processing depends on infrastructure capital. Our objective is to estimate infrastructure’s effects on input requirements, cost and productivity. The increase in capital and decrease in materials were respectively 2.5 and 3 times greater than the −0.07 infrastructure elasticity of labor. Infrastructure investment was cost-reducing by inducing reductions in employment and intermediate inputs. A 1 percent increase caused cost to decline by 0.16 percent. Infrastructure capital was a major contributor to productivity, annually contributing 0.5 percentage points. This was nearly double TFP growth.      

江苏省工业企业社会劳动生产率增长效应分析

本文基于LMDI指数分解方法,建立社会劳动生产率增长效应分析模型,并以江苏省工业企业为例,实证分析社会劳动生产率增长效应。首先,分析生产要素流动对部门资本利用效率、部门资本深化以及部门劳动力转移的影响;其次,分析社会劳动生产率增长效应;最后分析各类型企业的资本利用效应、资本深化效应以及劳动力转移效应对社会劳动生产率增长的贡献。实证分析表明,加快生产要素转移,既有利于提高各类型企业的资本利用效应与资本深化效应,又有利于提高劳动力转移效应,从而有利于加快社会劳动生产率增长。     

Measuring total factor productivity,technical change and the rate of returns to research and development

This paper examines the relationship between research and development expenditures and total factor productivity using establishment level (or micro) data. The confidential data are taken from the U.S. Bureau of the Census Annual Survey of Manufacturers and other Census surveys. Several measures of total factor productivity are considered as are several variables that proxy for technical knowledge. The latter include research and development expenditures by the firm, the accumulated research expenditures of the industry, and new equipment purchases. We find that there is a statistically significant relationship among above measures of technical expertise and a broad measure of total factor productivity.The refereeing process of this paper was handled through N.R. Adam.     

Roles of Public Capital in Pakistan's Economy: Productivity, Investment and Growth Analysis

This study analyzes the role of public capital in Pakistan's economy, tracing the relationship between productivity of public capital and economic growth. We estimate a production function, with public capital as an inputs. The results indicate that the productivity (output elasticity) of aggregate as well as different components of public capital are sufficiently high. We also analyze substitutability and complementarity between public and private capital by estimating investment functions, revealing that public capital has worked as a substitute for private investment. The net effect of public capital on the national economy is analyzed by estimating reduced forms, with the result that public capital has a positive net effect on national product. The growth analysis shows that the contribution of public capital is declining over time.     

Tenure and output

A key tenet of the theory of human capital is that investment in skills results in higher productivity. The previous literature has estimated the degree of investment in human capital for individuals by looking at individual wage growth as a proxy for productivity growth. In this paper, we have both wage and personal productivity data, and thus are able to measure of the increase in workers' output with tenure as evidence of the degree of learning on the job. The data is from an autoglass company. Most of production occurs at the individual level so measures of output are clear. We find a very steep learning curve in the first eight months on the job: output is 53 percent higher after eight months than it is initially. Our data show that these output gains with tenure are not reflected in equal percentage pay gains: pay profiles are much flatter than output profiles in the first year and a half on the job. For these data, using wage profiles significantly underestimates the amount of investment compared to the gains evident in output-tenure profiles. The pattern of productivity rising more rapidly than pay reverses after two years of tenure, although our evidence on this point is less reliable. Worker selection is also important. Workers who stay longer have higher output levels and faster early learning.     

Technical efficiency and region The U.S. manufacturing sector 1972–1977

In this paper we estimate the extent of technological bias in an interregional context for U.S. manufacturing during the period 1972–1977 using a factor augmenting production function approach. We present estimates of the elasticity of factor substitution for each of the 48 states in the sample using a variable elasticity of substitution production function. Next, we use these estimates to generate estimates of the rates of change in the efficiencies of capital and labor inputs and compare these estimates across states and census regions. We also examine and compare estimates of total factor productivity across states and regions. We ,find that the average annual rates of growth of capital efficiency during the period are 5.5 percent in the Northeast, 5.3 percent in the Northcentral, 5.6 percent in the West and 3.1 percent in the South. The rates of change of the efficiencies of labor are found to be negative across all regions except the South. The rates of change of total factor productivity are found to be 1.7 percent in the Northeast, 2.3 percent in the Northcentral, 2.4 percent in the West and 1.7 percent in the South. We also find that between 33 percent and 56 percent of the growth of output across regions is due to technical progress.     

Sources of growth in Indonesian agriculture

Indonesia sustained an average increase in agricultural output of 3.6% per year between 1961 and 2006, resulting in a more than fivefold increase in real output. This paper constructs Tornqvist-Thiel indices of agricultural outputs, inputs and total factor productivity (TFP) to examine the sources of growth in Indonesian agriculture over this period. The paper extends previous work on measuring productivity change in Indonesian agriculture by assembling more complete data on cropland and expanding the commodity coverage to include cultured fisheries in addition to crops and livestock. It also accounts for the contribution of the spread of rural education and literacy to agricultural growth. Results show that Indonesia pursued both agricultural intensification to raise yield, especially for food crops, and extensification to expand crop area and absorb more labor. Productivity growth accelerated in the 1970s and 1980s but stagnated in the 1990s once “Green Revolution” food crop varieties had become widely adopted. TFP growth resumed in the early 2000s led by diversification into non-staple commodities such as tropical perennials, horticulture, livestock and aquaculture. Agricultural extensification continued to be an important source of growth in many of parts of the archipelago where previously forested areas were converted to cropland. Human capital deepening, in the form of the spread of literacy and education in the farm labor force, made a modest but sustained contribution to agricultural productivity growth.     

United States digital divide: State level analysis of spatial clustering and multivariate determinants of ICT utilization

This study analyzes factors associated with availability and utilization of information and communication technologies (ICTs) for U.S. states. We construct an exploratory conceptual model of technology utilization in which eight dependent ICT availability and utilization factors are posited to be associated with fourteen independent socio-economic, demographic, innovation, social capital, and societal openness factors. Technology utilization variables are spatially analyzed to determine extent of agglomeration, and regression residuals are examined to eliminate spatial bias. Findings indicate social capital, education, societal openness, urbanization, and ethnicities are significantly associated with ICT utilization. We suggest important implications for policymakers at state and federal levels.     

Exploring reallocation’s apparent weak contribution to growth

Two recent meta-analyses use variants of the Baily et al. (Brookings Papers Econ Act Microecon 1:187–267, 1992) (BHC) decompositions to ask whether recent robust growth in aggregate labor productivity (ALP) across 25 countries is due to lower barriers to input reallocation. They find weak gains from measured reallocation and strong within-plant productivity gains. We show these findings may be because BHC indices decompose ALP growth using plant-level output-per-labor (OL) as a proxy for the marginal product of labor and changes in OL as a proxy for changes in plant-level productivity. We provide simple examples to show that (1) reallocation growth from labor should track marginal changes in labor weighted by the marginal product of labor, (2) BHC reallocation growth can be positively correlated, negatively correlated, or uncorrelated with actual growth arising from the reallocation of inputs, and that (3) BHC indices can mistake growth from reallocation as growth from productivity, principally because OL is neither a perfect index of marginal products nor plant-level productivity. We then turn to micro-level data from Chile, Colombia, and Slovenia, and we find for the first two that BHC indices report weak or negative growth from labor reallocation. Using the reallocation definition based on marginal products we find a positive and robust role for labor reallocation in all three countries and a reduced role of plant-level technical efficiency in growth. We close by exploring potential corrections to the BHC decompositions but here we have limited success.     

Firms' human capital,R&D and performance: a study on French and Swedish firms

This paper studies the effects of human and technological capital on productivity in a sample of large French and Swedish firms. While the role of technological capital as measured by R&D has been intensively investigated, almost no work has been done on the role of human capital as measured by firm-sponsored training and even less its interaction with technological capital. The level of intangible capital may also have a lasting effect on productivity growth, as emphasised by some endogenous growth models in a macroeconomic setting.The study uses data from two panels of large French and Swedish firms for the same period (1987–1993). It constructs measures of a firm's human capital stock, based on their past and present training expenditures. The results confirm that firm-sponsored training and R&D are significant inputs in the two countries, although to a different extent, and have high returns. However, except for managers and engineers in France, we do not find evidence of positive interactions between these two types of capital. Finally, growth effects at the firm level do not appear.     

Economic development and the return to human capital: a smooth coefficient semiparametric approach

This paper investigates the impact of human capital on the process of economic growth by allowing the contribution of traditional inputs (capital and labour) as well as that of human capital to vary both across countries and time. The former is accomplished by constructing an index of TFP growth for traditional inputs, while the latter through semiparametric methods. We derive estimates of the output elasticity and social return to human capital for 51 countries at various stages of economic development. Copyright © 2005 John Wiley & Sons, Ltd.     

Australia’s mining productivity decline: implications for MFP measurement

This paper investigates the mining sector’s poor productivity performance as measured by the growth accounting formula for multifactor productivity (MFP) index during the recent mining boom in Australia. We provide an alternative measure of productivity growth by estimating a translog variable cost function, with parameters that separate productivity growth due to technical change from that due to the effects of returns to scale, capacity utilisation and natural resource inputs. The results show that the average MFP growth in Australian mining based on the dual cost-function measure of technical change is 2 % over the sample period 1974–1975 to 2007–2008, rather than ?0.2 % from the published index. The difference arises because declining natural resource inputs, the effects of capacity utilisation and returns to scale have all reduced the ‘true’ MFP growth.     

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.     

Knowledge Spillovers,ICT and Productivity Growth

This paper looks at the channels through which intangible assets affect productivity growth. The econometric analysis exploits a new data set on intangible investment (INTAN‐Invest) in conjunction with EUKLEMS productivity estimates for 10 EU member states from 1998 to 2007. We find that (a) the output elasticity of intangible capital depends upon ICT intensity, consistent with complementarities between ICT and intangible capital; (b) non‐R&D intangible capital has a higher estimated output elasticity than its factor share, as does (c) an index of labour composition. The last two findings are consistent with growth spillovers from investments in knowledge‐based/intangible capital and skills.