Sources of aggregate labour productivity growth in Canada and the United States

Abstract.  In this paper we propose a decomposition technique to examine the sources of industrial contribution to aggregate labour productivity growth. We show that in terms of pure labour productivity growth, the manufacturing and service sectors contributed equally to the aggregate Canada‐U.S. labour productivity growth gap during the 1987–98 period. But, in terms of total industrial contributions, which also take into account the contributions from a change in relative size, the service sector was the largest contributor. We also find that high labour productivity growth industries did not attract resources from stagnant industries – a phenomenon consistent with Baumol's cost disease of stagnant industries. JEL Classification: O47, C43     

Intangible Investment and Changing Sources of Growth in Korea

We examine how intangible investments change the sources of growth in the Korean economy. After constructing a novel industry‐level data set on intangibles, we estimate the contribution of intangible‐intensive industries and other industries to aggregate productivity growth in 1981–2008. The contribution of intangible‐intensive industries to aggregate labour productivity growth has significantly increased, whereas that of other industries has substantially decreased. The increased contribution of intangible‐intensive industries is mainly associated with total factor productivity growth rather than with input growth. This suggests that innovations related to intangible investments in these industries might become a new key source of productivity growth in Korea.     

Finance and sources of growth: evidence from the U.S. states

How does financial development affect economic growth: through its impact on accumulation of physical and human capital or by boosting total factor productivity (TFP) growth? We use a new data set on output, inputs, and total factor productivity for the US states to study this question. Unlike previous cross-country research that tries to disentangle the channels through which financial development impacts growth, we use a plausibly exogenous measure of financial development: the timing of banking deregulation across states during the period 1970–2000. At the same time our new data set allows us to go beyond what was previously done in the state banking deregulation literature and identify whether finance impacts states’ input accumulation or TFP growth. We find, in line with existing cross-country studies, that deregulation boosts growth by accelerating both TFP growth and the accumulation of physical capital without having any impact on human capital. In contrast to the cross-country studies, we also find that the effects of deregulation are largely independent of states’ initial level of development; both rich and poor states grow faster after deregulation. Additionally, since our data set breaks down aggregate output into three sectors: agriculture, manufacturing, and the remaining industries, we are able to show that deregulation accelerates the growth of productivity in manufacturing. This last finding answers an important critique of the banking deregulation studies which asserts that observed growth effects may be coming from the growth of financial industry itself and not from the beneficial effect of finance on other industries, such as manufacturing.     

POST-REFORM PRODUCTIVITY PERFORMANCE AND SOURCES OF GROWTH IN CHINESE INDUSTRY: 1980–85

This paper examines the productivity growth and its sources in 39 Chinese industries in the post-reform period 1980–85. We use both the gross-output and value-added models to isolate the contributions of labor, capital, materials and technical efficiency to growth in industrial output. Using new data from the National Industrial Census of China (1988) for large and medium-size enterprises, we find that Chinese industries, in particular, those in the manufacturing experienced sharp increases in total factor productivity growth in the 1984–85 period as compared to the 1980–84 period. Moreover, collective and private enterprises show higher output and total factor productivity gains than do state enterprises. Our regression results show that total factor productivity gains are closely tied to increases in retained profits and the proportion of total employees that are technical workers. However, labor bonuses have a negative effect on total factor productivity growth.     

Sources of the German Productivity Demise: Tracing the Effects of Industry-Level Information and Communication Technology Investment

Abstract. While the United States experienced two successive labor productivity surges in 1995 and 2000, Germany's productivity declined dramatically during the same period. We examine the sources of Germany's productivity demise using the ifo industry growth accounting database that provides detailed industry-level investment information. While much attention has focused on the reduction in German labor hours, our data show that information and communication technology (ICT) investment in Germany was deeply lacking in the mid-1990s as compared with the United States. The transition to the new economy mitigated the German productivity slowdown, but did not reverse it. After 2000, we find that a recovery in Non-ICT investment was offset by a widespread collapse in German total factor productivity. Over half of the German industries (accounting for almost 50 per cent of German output) experienced negative total factor productivity growth. This second major difference between the United States and German industry performance explains Germany's secular departure from the technological frontier.     

Agglomeration Economies and Productivity Growth in Manufacturing Industry: Empirical Evidence from Indonesia

This study examines the effect of agglomeration economies on productivity growth in Indonesian manufacturing industries during the first decade of this century. Productivity growth is measured at the firm level using the Färe‐Primont Productivity Index. Each firm's productivity growth is then regressed against a set of firm and industry characteristics, including three measures of agglomeration representing the effects of specialisation, diversity and competition. The results show evidence of a positive specialisation effect and a negative diversity effect for aggregate manufacturing and sub‐sectors. Furthermore, there are mixed effects across industries, suggesting that Porter's competition externalities stimulate firm productivity growth under some conditions but not others.     

Declining output growth volatility: A sectoral decomposition

A decomposition of the U.S. aggregate output growth volatility using two-digit industry-level data shows that more than 60% of the post-1983 reduction in aggregate output growth volatility is attributed to the lowered comovement in total factor productivity (TFP) growth between industries. In contrast, stabilized input and TFP growths within an industry contribute little.     

A STATISTICAL ANALYSIS OF PRODUCTIVITY IN SELECTED SERVICE INDUSTRIES IN THE UNITED STATES, 1939–1963

This paper examines differentials in output, employment and productivity across seventeen service industries in the United States from 1939 to 1963. Included are 9 retail trades and 8 services mostly from the personal service group. The industries chosen were those for which it was possible to obtain from available data reasonably comparable measures of output and input for selected years since 1939. Also, they are industries for which it is possible to calculate a measure of real output that is not based on labor input.
Sixteen of the industries show positive rates of change of real output per man. Thus there appears to be no basis for assuming that productivity cannot or does not increase in industries providing services. However, the rate of increase for the group as a whole was not as rapid as in manufacturing or in goods production as a whole.
The data for the seventeen industries give strong support to the hypothesis of a positive correlation between industry rates of growth and rates of change of productivity. The correlations are of the same order of magnitude as those found by other investigators in studies of manufacturing industries.
The coefficient of correlation between growth of output per man and growth of output is .93; between growth of output per man and growth of employment it is .54 for 1939–1963. The comparable coefficients for the 1948–1963 period are .70 and .13.
The results also parallel those reported for manufacturing in one other respect, namely, the absence of any correlation between changes in output per man and changes in compensation per man.
The paper concludes with a discussion of the problems encountered in measuring changes in real output in these industries and presents some alternative estimates based on different concepts and different sources.     

Engine or drag: Can high energy consumption and CO2 emission drive the sustainable development of Chinese industry?

To analyze China industrial sustainable development featured with high energy consumption and high CO₂ emission, this paper constructs the input and output panel data of China’s 38 sub-industries, estimates their productivity and carries out the green growth accounting based on translog production function. This paper concludes that, as a whole, China industry has achieved the transformation from extensive to intensive growth, with the productivity to be the first driving force, that is necessary to sustainable development in the long run. In addition to technical progress, energy and capital have also been driving the industrial growth during the sample period, while labor and emission made less even negative contribution to it. Some heavy industries, however, are still characterized by extensive growth and must improve their energy-save and emission-abate technology to favor the sustainable development of overall Chinese industry.     

Information and Communications Technology as a General-Purpose Technology: Evidence from US Industry Data

Abstract. Many people point to information and communications technology (ICT) as the key for understanding the acceleration in productivity in the United States since the mid-1990s. Stories of ICT as a 'general-purpose technology' suggest that measured total factor productivity (TFP) should rise in ICT-using sectors (reflecting either unobserved accumulation of intangible organizational capital; spillovers; or both), but with a long lag. Contemporaneously, however, investments in ICT may be associated with lower TFP as resources are diverted to reorganization and learning. We find that US industry results are consistent with general-purpose technology (GPT) stories: the acceleration after the mid-1990s was broad-based – located primarily in ICT-using industries rather than ICT-producing industries. Furthermore, industry TFP accelerations in the 2000s are positively correlated with (appropriately weighted) industry ICT capital growth in the 1990s. Indeed, as GPT stories would suggest, after controlling for past ICT investment, industry TFP accelerations are negatively correlated with increases in ICT usage in the 2000s.     

Effects of Public Infrastructure on Cost Structure and Productivity in the Private Sector

This paper examines the effects of public infrastructure on the cost structure and productivity in the private sector in Australia. Translog cost functions incorporating public capital infrastructure are estimated for the aggregate private sector as well as for seven broad industry groups using annual time series data for 1968/69–1995/96. The effects of public infrastructure on productivity are measured in terms of both cost-saving and output-augmenting measures. The empirical results suggest that public infrastructure has a positive and significant impact on productivity in private sector industries. Public capital serves as a substitute for both private capital and labour. The rates of return to public capital are significant and vary over the sample period.     

Export Growth,Capacity Utilization,and Productivity Growth: Evidence from the Canadian Manufacturing Plants

Aggregate labor and multifactor productivity growth slowed substantially post‐2000 in the Canadian manufacturing sector. To examine the source of the decline, this paper proposes a decomposition method that delves deeper into the two micro‐components of aggregate productivity growth: a within‐plant component and a between‐plant component. The decomposition builds on earlier work by Jorgenson and his collaborators that decomposes aggregate productivity growth into its industry components, but applies it to the plant level and introduces non‐neoclassical features of the plant‐level economic environment. It finds that the preponderance of the aggregate labor and multifactor productivity growth slowdown is due to the pro‐cyclical nature of productivity growth arising from capacity utilization. Almost all of the aggregate productivity growth slowdown is driven by exporters, as exporters experienced large declines in labor productivity growth in the post‐2000 period as a result of large declines in their capacity utilization.     

EFFECTS OF PATENTS ON PRODUCTIVITY GROWTH IN KOREAN MANUFACTURING: A PANEL DATA ANALYSIS*

Abstract.  We analyse the contributions of patents to total factor productivity (TFP) performance in Korean manufacturing industries during the period 1981–1999. This paper treats potential autocorrelation problems seriously and uses recent panel cointegration approaches to investigate the robustness of the patent-TFP relationship. The results show that both domestic and foreign-resident patent applications have significant positive effects on productivity and that foreign-resident patent applications have a larger effect than domestic patents in improving TFP in Korean manufacturing. We also find evidence of knowledge spillovers among industries, in that the patent applications of other industries increase TFP in any single industry.     

Structural Change,Expanding Informality and Labor Productivity Growth in Russia

Strong growth, intensive structural change, and expanding informality have characterized many developing and emerging economies in recent decades. Yet most empirical investigations into the relationship between structural change and productivity growth overlook informality. This paper includes the informal sector in an analysis of the effects of structural changes in the Russian economy on aggregate labor productivity growth. Using a newly developed dataset for 34 industries covering the period 1995–2012 and applying three alternative approaches, aggregate labor productivity growth is decomposed into intra-industry and inter-industry contributions. All three approaches show that the overall contribution of structural change is growth enhancing, significant, and decreasing over time. Labor reallocation from the formal sector to the informal sector tends to reduce growth through the extension of informal activities with low productivity levels. Sectoral labor reallocation effects are found to be highly sensitive to the methods applied.     

可标准化服务行业对服务业发展的影响——基于两部门模型的分析

从理论上探讨了标准化促进服务业发展的内在机制。构建了两部门模型,分析了可标准化服务部门对服务业发展的影响。利用2003—2012年中国服务业的省际数据,运用面板模型对可标准化服务部门的溢出效应进行了估算,利用DEA方法对服务业各行业的全要素生产率进行了测算和分解。结果表明:可标准化服务部门要素的边际产出高于不可标准化服务部门,发展可标准化服务部门有利于服务业增长;可标准化服务行业对不可标准化服务行业的溢出效应为负,原因在于可标准化服务行业的全要素生产率较低,因此在当前发展阶段需要进一步对可标准化服务行业内部进行优化整合。     

ICT growth effects at the industry level: A comparison between the US and the EU

This is an empirical study on the growth impact of Information and Communication Technologies using industry-level data for the US and the EU industries over the period 1980-2000. A panel data approach is employed to estimate the ICT effect using the system GMM and the pooled mean group panel data estimators. The results vary depending on the period, the region, and the type of industry considered. The GMM estimates suggest a significant ICT effect on growth during the 90s both in the US and in the EU. This effect for the EU was strong in the early 90s and weakened afterwards, as opposed to the US where it strengthened in the late 90s. The results of the pooled mean group estimator confirm that the long run growth contribution of ICT was significantly positive in the industries of both regions and over the entire period 1980-2000. However, it seems that the productivity effects of ICT are mainly present in the industries which are either ICT producers or heavy ICT users.     

Convergence in Productivity Across Industries: Some Results for New Zealand and Australia

New Zealand shares a wealth of common interests and experiences with Australia. This has tempted some to assume that these economies form an ‘Economic Club’, in which one would expect to identify common aggregate trends and growth experiences. In this paper we present results that test, and generally reject, convergence in labour productivity across Australia and New Zealand, using both aggregate and disaggregate, industry‐level data. We find that only two industries satisfy our definition of Conditional Convergence (Agriculture, Forestry and Fishing and Cultural and Recreational Services), and that the Mining and Wholesale Trade industries have particularly important roles to play in explaining the measured divergence. Cointegration‐based tests reveal more stochastic trends governing Australian productivity than in New Zealand. The evidence suggests, therefore, that the underlying growth processes of the two economies are fundamentally different, thereby questioning the relevance of aggregate comparisons between them. New evidence using industry‐level data does not, therefore, resolve the aggregate‐level ‘non‐convergence puzzle’ identified here, and elsewhere.     

ICT and Productivity in Europe and the United States Where Do the Differences Come From?

In this paper we analyse labour productivity growth in 51 industriesin European countries and the United States. Using shift-sharetechniques we identify the industries in which the U.S. is leadingmost strongly. With a detailed decomposition analysis we identifywhether the sources of the U.S. advantage are due to fasterproductivity growth, higher industry productivity levels relativeto the country aggregate, different employment shares or fasterchange in employment shares of rapidly growing industries. Theresults show that U.S. productivity has grown faster than inthe EU because of a larger employment share in the ICT producingsector and faster productivity growth in services industriesthat make intensive use of ICT. Wholesale and retail trade andthe financial securities industry account for most of the differencein aggregate productivity growth between the EU and the U.S.(JEL N10, O47, O57)     

The effect of structural change on the self-reliance and interdependence of aggregate sectors: the case of Spain, 1980–1994

The objective of this paper is to analyse structural and technological change in the Spanish economy between 1980 and 1994 using the input–output tables of 1980, 1986, 1990 and 1994. First we obtain and compare four linkage components throughout the period for each of the nine aggregate sectors in which the industries are grouped. Second, using Structural Decomposition Analysis, we obtain a technological effect and a demand effect for each of the previous components. These pressures show that the process of the technological modernisation of the Spanish economy is strongly linked to the growth of the high- and medium-technology industries and the service industries, and the different contribution of these industries to the improvement of productivity. On the one hand, the technology industries increase productivity by using better technologies. On the other hand, the service industries do not raise it significantly and even reduce it by increasing their unit costs.     

Link between innovation and productivity in Canadian manufacturing industries

Empirical studies commonly use research and development (R&D) to measure innovation and often find, especially in Canada, no strong link between productivity and innovation. In this article, we model innovation as an unobservable latent variable that underlies four indicators: R&D, patents, technology adoption, and skills. We find that these indicators are reasonably good measures of innovation for aggregate manufacturing. However, except for skills, the reliability of the indicators for innovation differs among individual industries. Our innovation indexes, based on the latent variable model, show that most manufacturing industries became more innovative over the 1980–1997 period. The pace of innovation in the electrical and electronic products industry accelerated during the 1990s. In addition, we show that the new measure of innovation has a positive and statistically significant impact on productivity. It takes from 1 to 3 years, depending on the industry, for innovation to generate an impact on productivity.