Differences In Labor Productivity Research Articles

Competitiveness of Superpowers: Impact of Education and Innovations

The impact of knowledge determinants on global competitiveness based on multiple criteria assessment methodology and their empirical expert assessment was evaluated taking the comparative expert data of the U.S., Japan, China, and India for a case study. The complex evaluations were determined with an account of the education, knowledge and innovation parameters published in the international reports of the WEF, INSEAD a/o experts. As result of author evaluations was found that differences between the USA and Japan, on the one side, China and India, on other, by GTCI and GII levels are lower than their differences in GDP per capita (PPP). The correlation between GTCI scores and GDP per capita, also between national economic competitiveness and GTC indices is weaker than expected by an approach based on GTCI model. The deep difference in labor productivity per employee was determined by the technical retardation of India and China compared with USA and Japan. At the same time, the differences of superpowers in educating the employable skills are not so significant.

The effects of industrial policy on regional development in Ukraine

The paper is based on an empirical analysis of industrial policy effects on regional development. It looks at the state of the Ukrainian industrial policy and proposes the basic measures for future structural adjustments in Ukraine. The analysis of two groups of factors includes general and specific sources of growth for Ukraine’s 27 regions and estimates the effects of regional industrial policy in Ukraine. The first group of indices comprises macroeconomic indicators. In the aggregate, transition-specific factors combine the indicators of success of reforms, including labour productivity, capital intensity, technological change and regional differences. The regional imbalance assessment is determined by the gross regional product per capita, regional employment and expenditures on education. The use of econometric modelling proves the division into industrial regions with a high urbanisation rate and backward agrarian regions in Ukraine. Different types of industrial policies of protection and production subsidies across industries are proposed for the reforming process within the regions.

International differences in labor productivity: Role of capital, technological level and resource rent

Using level accounting methodology this article examines sources of per capita GDP and labor productivity differences between Russia and developed and developing countries. It considers the role played by the following determinants in per capita GDP gap: per hour labor productivity, number of hours worked per worker and labor-population ratio. It is shown that labor productivity difference is the main reason of Russia’s lagging behind. Factors of Russia’s low labor productivity are then estimated. It is found that 33-39% of 2.5-5-times labor productivity gap (estimated for non-oil sector) between Russia and developed countries (US, Canada, Germany, Norway) is explained by lower capital-to-labor ratio and the latter 58-65% of the gap is due to lower technological level (multifactor productivity). Human capital level in Russia is almost the same as in developed countries, so it explains only 2-4% of labor productivity gap.

Learning-by-importing in emerging innovation systems: evidence from Ecuador

ABSTRACTUsing data from the population of Ecuadorian importers, we examine the extent to which the characteristics of their imports relate to their labor productivity. Results indicate that the technological intensity of imports does not explain differences in labor productivity, although the region of origin of imports explains differences in the manufacturing sector, as imported technologies from advanced regions are associated with superior labor productivity. Nevertheless, as technology intensive imports are not associated with superior performance, we argue that importers from developing countries may use foreign technology inexpertly due to the lack of absorptive capacity and the emerging nature of their national innovation system.

A multi-sectoral balance-of-payments-constrained growth model with sectoral heterogeneity

This study builds a multi-sectoral balance-of-payments-constrained growth model that incorporates structural heterogeneity between sectors and countries, such as differences in labor productivity, price competition, shares of exports and imports, and the quality of commodities. The model in the current paper generates more comprehensive results than those presented by Thirlwall (1979), Blecker (1998), and Araujo and Lima (2007), even though it contains their properties and reproduces their implications. Furthermore, compared with these existing works, the current model sheds more light on the relationship between the trade structure, international competition, productivity dynamics, and economic growth. It also shows the differences between industrial and macroeconomic phenomena, by presenting an example that illustrates how changes in nominal wages, the Kaldor–Verdoorn effect, and the degree of market competition in both countries affect economic growth in the home country.

Scientific Innovation and Knowledge Creation Can Drive Social Development: A Chinese Perspective

The rapid growth of economy in the 20th century is largely due to the accelerative development of scientific achievement and technology. Modern educational system–especially research universities–has played a key role. Today’s world is led by knowledge society. China developed her manufacture sector recently, but the difference in labour productivity between China and the US increased significantly during the same period. Therefore, in order to catch up with progress of western countries, improving their research universities and research culture are great challenges faced by both China and India.

Determinants of microregional agricultural labour productivity – Evidence from Czechia

In this paper we aimed to explain differences in agricultural labour productivity at microregional level. We tested the effects of three major independent variables – farmland fragmentation, urbanization economies and farm size structure with particular emphasis on the relationship between land-use fragmentation and microregional differences in agricultural labour productivity. Our principal question therefore was if higher agricultural labour productivity at microregional level is associated with internal scale economies resulting from large average farm size (in terms of employment), proximity to large cities as a proxy for urbanization economies and lower levels of land-use fragmentation. We also asked if productivity gains from large average size of plots is higher than potential losses resulting from land tenure (tenants are generally less productive than farmland owners). Drawing on a case study of Czechia – a country with extremely fragmented farmland ownership, but the largest average size of plots in the EU and a strong role of farmland rental market – we confirmed our initial expectation that land-use fragmentation affects negatively microregional agricultural labour productivity. Larger average size of plots is positively related to microregional agricultural labour productivity despite potentially negative effects of land tenure. At the same time, no significant effects of urbanization economies and farm size structure were documented.

The Significance of Farm Size in the Evaluation of Labour Productivity in Agriculture

The paper deal with the analysis of difference in labour productivity of farms categorised according to their size, to determine if the set subsidy system influences labour productivity in the size groups of the farms. The source of data for enterprises analysis was the firms database, which contains accounting data of 926 farms with at least one employee. The observed data were from the 6 year period (2007–2012). The farms were divided, according to their size into four categories defined by the European Commission: micro, small, medium and large enterprises. The analysis of the labour productivity I based on the added value and labour costs revealed that there are big differences of the labour productivity levels in particular size groups of farms. The further analysis revealed that an adjustment of the farm approach of the labour productivity, when the paid operation subsidies are added (labour productivity II), changes this conclusion and the differences between particular size groups of farms decreased. Using σ-convergence, it was proved that the relative variability of the labour productivity II values decreased significantly in the case of the medium-sized farms. We can say that subsidies significantly influence the labour productivity in farms. On one hand, there is decrease of differences between the level values of particular size groups of farms; on the other hand, there is no significant decrease its variability (except the medium-sized farms).

製造業の労働生産性の地域間格差とその構成要因分析

An interregional differential of economic activity has been a public policy issue in Japan since the 1960s. The government has designed, legislated and implemented various policies to cope with this issue under various titles.Interregional differentials of economic activity can be measured by various indices such as the size, growth rate or productivity of a regional economy. Also, the geographic coverage of “region” can vary. In this study, I used data from the Manufacturing Census to conduct an analysis of labor productivity differentials of the manufacturing industries of 47 prefectures in Japan using two different methods; production function analysis and shift-share analysis. The production function analysis, though under the assumption of the Cobb-Douglas production function, showed different levels of total factor productivity, TFP in each mid-level subcategory of the manufacturing industry for each prefecture as the departure ratio from the national value. However, it should be noted that TFP was calculated as the Solow residual in the production function with a constant capital/labor substitution ratio. The shift-share analysis divided γi, the departure ratio of labor productivity of the manufacturing total in prefecture i, from the national value into three components; μi: industry-mix component, πi: productivity-differential component, and their cross terms αi: allocative component for each of the mid-level sub-categories in the manufacturing industry. To calculate γi these three components were summed over all mid-level subcategories of the manufacturing industry for each prefecture. From this series, ECV 2: the employment-weighted coefficient of variation, sum of the squared coefficient for the variation in labor productivity weighted by the manufacturing employees’ share of each prefecture in the national total, was calculated for each calendar year. Overall, the productivity-differential component, πi, showed a higher weight than the industry-structure component, μi, in the labor productivity differentials of the manufacturing industries among prefectures. This means that the two approaches show consistent outcomes. JEL Classifications: C81, L60, R00, R32

Labour productivity of agricultural business companies and cooperatives in the Czech Republic: A micro-regional level analysis

Abstract Drawing on empirical evidence from the Czech Republic, differences in agricultural labour productivity at the micro-regional level are examined. The role of geographical factors: natural conditions, landscape fragmentation, localisation and urbanization economies, are discussed. In addition, we also test the effects of farm size structure to capture the results of internal scale economies. The key importance of natural conditions is confirmed: they were significantly more important than farm characteristics such as size structure, ownership status and mode of production. Regional agricultural labour productivity was positively influenced by the nominal price of agricultural land and population density. Surprisingly, micro-regions dominated by large farms performed at lower productivity levels than micro-regions with fragmented farm size structure in the Czech Republic.

Zasoby i produktywność pracy przemysłu spożywczego krajów członkowskich Unii Europejskiej w kontek- ście konkurencyjności sektora

Labour resources are an important factor in competitiveness of the sector. The aim of the study was to evaluate the spatial concentration of labour resources, performance advantages and cost-price advantages that are associated with the work factor in the food industry in the European Union in 2010-2012. The results indicate that the greatest concentration of labour resources exists in Germany, France, Italy and Poland. The biggest performance advantage was observed in the old EU countries, mainly in Ireland, the Netherlands, Belgium and Denmark. Diff erences in labour productivity in the food industry, the new EU countries, in relation to the old member states, are getting smaller. The most signifi cant cost-price advantage was observed in Ireland and the Netherlands, and many of the new EU countries, which compensated for the lack of performance advantages of lower labour costs. These include Poland, Bulgaria, Czech Republic, Latvia, Lithuania, Hungary and Romania.

Leverages for on-farm innovation from farm typologies? An illustration for family-based dairy farms in north-west Michoacán, Mexico

Knowledge on farm diversity provides insight into differences among farms, enables scaling from individual farm to farm population level and vice versa, and has been used in the definition of recommendation domains for introduction of novel technologies. Farm diversity can be broadly described in terms of resource endowment and resource use strategy, or in other words, in terms of scale and intensity of production. Measuring intensity of production requires much greater monitoring effort than measuring scale of production, and often only proxies of production intensity are used. Using data from a regional farm survey and from intensive on-farm monitoring the question addressed in this paper is to which extent results of farm surveys that measure primarily scale of production can inform on-farm interventions aimed at improving farm performance. The survey included a random sample of 97 out of 664 smallholder dairy farmers in a community in north-west Michoacán, Mexico. Farm types were identified by a combination of Principal Component Analysis to reduce the dimensionality of the dataset, followed by Cluster Analysis. The survey was complemented with detailed analyses of costs, revenues and productivity on 6 farms over the course of one year. Survey results revealed considerable variation among the dairy farms in land area, livestock units, amount of hired labour, and infrastructure and equipment, which led to the distinction of 4 farm types. Indicators for animal health management and feeding strategies were uniform across the 4 types. The farm types matched the distinction of family-based and semi-intensive farm types used in Mexico. The detailed analyses of the individual farms belonging to the different types, however, revealed differences in resource use strategies reflected in differences in animal productivity, labour productivity and return to labour. Differences in animal productivity and labour productivity were explained by stocking rate, albeit in different ways. Return to labour was strongly related to cost of feed. Profitability was negative for all farms and was on most farms related to high external feedstuff costs, which constituted 59–89% of the feed cost of the animal ration. The results indicate that in addition to variables reflecting resource endowment or scale of production, typologies that aim to inform on-farm interventions need to consider farm characteristics that reflect intensity of production. Which variables should be selected will need to be determined in a preliminary assessment. To enhance internal resource use efficiency as was the purpose in the current study, candidate variables expressing intensity could include the share of external feed in the ration and proxies of internal resource use, e.g. reflected in crop and milk yields. Opportunities for on-farm innovation arising from the analyses are discussed from the perspective of labour flexibility, low costs and use of internal resources.

Why Do South Korean Firms Produce so Much More Output Per Worker than Ghanaian Ones?

The labour productivity differentials between manufacturing firms in Ghana and South Korea exceed those implied by macro analysis. Median value-added per employee is nearly 40 times higher in South Korea than Ghana. The most important single factor in explaining this difference is the Mincerian return to skills which differ by a factor of three between Ghana and South Korea. There is no significant difference in total factor productivity across the countries once we allow for human capital. Our results are consistent with those who have argued that rises in the return to education within developed countries can be explained by skill-biased technical progress in those economies. They are also consistent with work in developing countries which finds a convex return to education based on individual labour market data. Allowing for differences in the shape of the relationship between productivity and human capital across countries is crucial for understanding the role of human capital in increasing productivity.

Zróżnicowanie regionalnej wydajności pracy w Polsce

Zróżnicowanie regionalnej wydajności pracy w Polsce

On the causes of economic growth in Europe: why did agricultural labour productivity not converge between 1950 and 2005?

The objective of this study is to make a further contribution to the debate on the causes of economic growth in the European Continent. It explains why agricultural labour productivity differences did not converge between 1950 and 2005 in Europe. We propose an econometric model, one combining both proximate and fundamental causes of economic growth. The results show that the continuous exit of labour power from the sector, coupled with the increased use of productive factors originating in other sectors of the economy, caused the efficiency of agricultural workers to rise. However, we offer a complete explanation of the role played by institutions and geographical factors. Thus, we detect a direct and inverse relation between membership of the EU and the Communist bloc and the productivity of agricultural labour. In addition, strong support for agriculture affected productivity negatively.

Assessing education’s contribution to productivity using firm-level evidence

Purpose– There is plenty of individual-level evidence, based on the estimation of Mincerian equations, showing that better-educated individuals earn more. This is usually interpreted as a proof that education raises labour productivity. Some macroeconomists, analysing cross-country time series, also support the idea that the continuous expansion of education has contributed positively to growth. Surprisingly, most economists with an interest in human capital have neglected the level of the firm to study the education-productivity-wage nexus. And the few published works considering firm-level evidence are lacking a proper strategy to cope with the endogeneity problem inherent to the estimation production and wage functions. The purpose of this paper is to aim at providing estimates of the causal effect of education on productivity and wage labour costs.Design/methodology/approach– This paper taps into a rich, firm-level, Belgian panel database that contains information on productivity, labour cost and the workforce’s educational attainment to deliver estimates of the causal effect of education on productivity and wage/labour costs. Therefore, it exclusively resorts to within firm changes to deal with time-invariant heterogeneity bias. What is more, it addresses the risk of simultaneity bias (endogeneity of firms’ education-mix choices in the short run) using the structural approach suggested by Ackerberget al. (2006), alongside more traditional system-GMM methods (Blundell and Bond, 1998) where lagged values of labour inputs are used as instruments.Findings– Results suggest that human capital, in particular larger shares of university-educated workers inside firms, translate into significantly higher firm-level labour productivity, and that labour costs are relatively well aligned on education-driven labour productivity differences. In other words, the authors find evidence that the Mincerian relationship between education and individual wages is driven by a strong positive link between education and firm-level productivity.Originality/value– Surprisingly, most economists with an interest in human capital have neglected the level of the firm to study the education-productivity-pay nexus. Other characteristics of the workforce, like gender or age have been much more investigated at the level of the firm by industrial or labour economists (Hellersteinet al., 1999; Aubert and Crépon, 2003; Hellerstein and Neumark, 2007; Vandenberghe, 2011a, b, 2012; Rigoet al., 2012; Dostie, 2011; van Ours and Stoeldraijer, 2011). At present, the small literature based on firm-level evidence provides some suggestive evidence of the link between education, productivity and pay at the level of firms. Examples are Hægeland and Klette (1999); Haltiwangeret al.(1999). Other notable papers examining a similar question are Galindo-Rueda and Haskel (2005), Prskawetzet al.(2007) and Turcotte and Whewell Rennison (2004). But, despite offering plausible and intuitive results, many of the above studies essentially rely on cross-sectional evidence and most of them do not tackle the two crucial aspects of the endogeneity problem affecting the estimation of production and wage functions (Griliches and Mairesse, 1995): first, heterogeneity bias (unobserved time-invariant determinants of firms’ productivity that may be correlated to the workforce structure) and second, simultaneity bias (endogeneity in input choice, in the short-run, that includes the workforce mix of the firm). While the authors know that labour productivity is highly heterogeneous across firms (Syverson, 2011), only Haltiwangeret al.(1999) control for firm level-unobservables using firm-fixed effects. The problem of simultaneity has also generally been overlooked. Certain short-term productivity shocks affecting the choice of labour inputs, can be anticipated by the firms and influence their employment decision and thus the workforce mix. Yet these shocks and the resulting decisions by firms’ manager are unobservable by the econometrician. Hægeland and Klette (1999) try to solve this problem by proxying productivity shocks with intermediate goods, but their methodology inspired by Levinsohn and Petrin (2003) suffers from serious identification issues due to collinearity between labour and intermediate goods (Ackerberget al., 2006).

An Analysis of Differences in Labour Productivity in Manufacturing: Spain and Germany, 1993-2007

L'objectiu d'aquest article es dur a terme una analisi comparativa de la productivitat del treball en el sector de les manufactures entre Espanya i Alemanya en el periode 1993-2007 amb la finalitat d'identificar els factors determinants que dificulten el creixement continu de la productivitat en la industria espanyola. La motivacio es esbrinar si les diferencies en la productivitat es deuen principalment a diferents estructures productives o si es deuen principalment a un problema intrinsec de la propia productivitat industrial o una combinacio de tots dos. Els resultats indiquen que les diferencies en l'estructura sectorial de la industria manufacturera no justifiquen en bona mesura la bretxa en la productivitat. Concloem que es mes un problema de velocitat de convergencia de les estructures de produccio, que no pas d'absencia de canvis.

Agricultural Productivity Differences across Countries

Recent studies argue that cross-country labor productivity differences are much larger in agriculture than in the aggregate. We reexamine the agricultural productivity data underlying this conclusion using new evidence from disaggregate sources. We find that for the world's staple grains-maize, rice, and wheat-cross-country differences in the quantity of grain produced per worker are enormous according to both micro- and macrosources. Our findings validate the idea that understanding agricultural productivity is at the heart of understanding world income inequality.

Productivity of Dairy Supply Chains: A Comparative Analysis Across the Countries of the Baltic Sea Region

To explore the competitiveness of the Finnish dairy chain, we analysed its productivity performance relative to that of other Baltic countries: Sweden, Denmark, Germany, Poland, and the three Baltic states. We used partial productivity indicators and indices of total factor productivity (TFP) to investigate productivity growth and productivity levels in both dairy farming and dairy manufacturing, using data from the Farm Accountancy Data Network as well as national industrial statistics. At farm level, there are enormous differences in the level of labour productivity across the eight countries: a dairy farmer in Denmark produces 13 times more milk than one in Latvia or Lithuania. Labour productivity in Finland is also significantly lower than in the other old EU countries – not only Denmark, the clear leader, but also Germany and Sweden. Further, there is evidence that Estonia is catching up with Finland in terms of labour productivity. A decomposition analysis then shows that the cross-country differences in labour productivity on farms are driven primarily by differences in labour requirements per cow, while differences in milk yields account for a much smaller share of the difference. Thus, the key to high labour productivity in dairy is the farm structure and the adoption of mechanical innovations, while differences in adoption of biological innovations (e.g., genetic improvement, feeds) are relatively less important. In a second step, a growth accounting exercise indicates that growth in farm-level production in the four older EU members has occurred through different channels, but that TFP growth rates have been roughly comparable from 1995 to 2010. Thus, the competitive position of Finnish dairy farms relative to those in Sweden, Germany and Denmark has not changed greatly over the last two decades. More positively, we find that in recent years (i.e., since 2004), TFP on Finnish farms has grown much faster than on German and Swedish farms. Altogether, Finnish farms appear in the process of raising their productivity to the level achieved by German and Swedish farms, while Danish farms are probably out of reach. Extending the comparison to include the new EU members reveals that dairy farms in those countries are lagging behind Finnish ones in terms of productivity and are not catching up. Although Estonian farms, which are on average relatively large, have recorded impressive increases in yields and labour productivity, this has been achieved more by substitutions of other production factors for labour than real efficiency gains. The processing level of the Finnish dairy supply chain appears more competitive when benchmarked against the processing sectors of the old EU members, although TFP growth has been slow in absolute terms. However, the productivity of dairy manufacturing in Poland and Lithuania is increasing rapidly and converging towards the levels observed in the older EU countries. Overall, the evolution documented in the paper is consistent with the view that transferring technologies and organisational forms from the productivity leaders to the productivity “laggards” is easier in the manufacturing sector than in primary production, due to the typical difference in the size of firms as well as the more pronounced reliance of the primary sector on country-specific agro-ecological conditions.

Making the Construction Industry Resilient to Extreme Weather: Lessons from Construction in Hot Weather Conditions

The construction industry is susceptible to extreme weather events (EWEs) due to most of its activities being conducted by manual workers outdoors. Although research has been conducted on the effects of EWEs, such as flooding and snowfall, limited research has been conducted on the effects of heatwaves and hot weather conditions. Heatwaves present a somewhat different risk profile to construction, unlike EWEs such as flooding and heavy snowfall that present physical obstacles to work onsite. However, heatwaves have affected the construction industry in the UK, and construction claims have been made due to adverse weather conditions. With heatwaves being expected to occur more frequently in the coming years, the construction industry may suffer unlike any other industry during the summer months. This creates the need to investigate methods that would allow construction activities to progress during hot summer months with minimal effect on construction projects. Hence, the purpose of this paper. Regions such as the Middle East and the UAE in particular flourish with mega projects, although temperatures soar to above 40̊C in the summer months. Lessons could be learnt from such countries and adapted in the UK. Interviews have been conducted with a lead representative of a client, a consultant and a contractor, all of which currently operate on UAE projects. The key findings include one of the preliminary steps taken by international construction companies operating in the UAE. This involves restructuring their entire regional team by employing management staff from countries such as Lebanon, Palestine, Iraq, and their labour force from the sub-continent such as India and Pakistan. This is not only due to the cheap wage rate but also to the ability to cope and work in such extreme hot weather conditions. The experience of individuals working in the region allows for future planning, where the difference in labour productivity during the extreme hot weather conditions is known, allowing precautionary measures to be put in place.