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This paper aims to examine the long‐run and dynamic behaviors of real wage‐employment‐productivity relationship, using Malaysian manufacturing data, and to determine which related labor theories are supported.

Time‐series econometric techniques, which include stationarity and cointegration tests, vector error correction model, impulse response function and variance decomposition, are applied to analyze the relationships of real wages, employment and productivity.

A long run relationship exists between real wages, employment and real productivity, with real wages being the main variable that adjusts to maintain cointegration. The theory that real wages inversely affect employment is not supported, while the performance‐based pay scheme theory, and not the efficiency wage theory, is validated.

Although the data used to measure wages and employment account for most of the production in the various manufacturing sectors, they do not include all the manufacturing industries. The analysis is also limited in time span since data for earlier periods are not available.

The findings can provide assistance to policy makers in their implementation and evaluation of labor policies.

The real wage‐employment‐productivity relationship is examined in the framework of the Malaysian manufacturing sector, and the study includes both the long‐term and short‐run behaviors of the variables.

The purpose of this paper is to examine the relationships between foreign direct investment (FDI), wages and productivity in China. The direction of causality among these variables is also to be emphasized.

The authors develop a system of equations and test the relationships based on a vector autoregressive regression (VAR) model and two‐step generalized method of moments (GMM)‐type estimation approach. They use a panel data set of China's provinces for a 20‐year time period, 1988‐2007, and also distinguish between the coastal and inland provinces.

The result confirms the cheap labor argument for China, although this particularly true for inland provinces. In the coastal provinces, FDI inflow influences the wage rates upwards. FDI also has a positive effect on productivity, particularly in the coastal provinces, but does not act as a significant determinant of FDI.

Factors other than wage rates and labor productivity are also important determinants of FDI. This paper focuses on the interplay of these three variables, while assuming other factors constant.

Cheap labor as an attraction of FDI is a short term policy. Improvements in productivity should be the focus both in the coastal and the inland provinces. A conducive business environment, a suitable education policy and incentives for greater R&D contribute toward improving labor productivity, which in turn attracts greater FDI inflow.

The paper provides empirical evidence on the direction of causality between FDI inflow, wages rates and labor productivity in one system of equations.

The Saint Valentine's Decree (1984) and the ensuing hard‐fought referendum (1985), which reduced the automatisms of scala mobile, started a process of redefinition of wage fixing in Italy, which culminated with the final abolition of scala mobile (1992) and the approval of Protocollo d'intesa (1993). Since then, following new corporatist principles, a national system of centralised wage bargaining (concertazione) and so‐called “institutional indexation” have governed the determination of wages. Does incomes policy generate greater coordination in the process of wage formation? Does it cause greater co‐movement of wages, prices, labour productivity and unemployment? This paper aims to answer these questions with reference to one of the G8 economies.

After testing for unit root each component by using the ADF, Phillips and Perron, DF‐GLS and Zivot and Andrews statistics, the paper tests for co‐integration the so‐called WPYE model using different methods. The Engle and Granger approach is used to assess the impact of incomes policy on the speed of adjustment of real wages, productivity (and unemployment) to their equilibrium value, while the Gregory and Hansen procedure serves as a means to endogenously detect the presence of a regime shift. The paper estimates coefficients before and after the structural break.

Incomes policy based on the 1993 Protocol has caused a regime shift in the process of wage determination. The long‐run estimates of the WPYE model do not generate stationary residuals except when a dummy for 1993 is added. The share of wages over GDP reduces by about ten percentage points in the early 1990s and has stood at about 57 per cent since 1995. The link with productivity is close to one‐to‐one only before the break. The feedback mechanism, as measured by the coefficient of lagged residuals in short‐run estimates, is increased from −0.46 in the pre‐reform to −0.79 in the post‐reform period, suggesting that incomes policy has increased real wage flexibility indeed. In recent years the link between real wages and (very low) labour productivity growth has weakened. In a sense, incomes policy has introduced a new form of (upward) wage rigidity. Last but not least, incomes policy has changed the correlation with the unemployment rate from positive to not statistically significant.

Future developments will focus on disentangling the impact of incomes policy vis‐à‐vis other policy interventions on WPYE and on unemployment.

The analysis calls for a careful revision of the 1993 Protocol aimed at better protecting the purchasing power of real wages without losing control on inflation, and introducing growth‐generating mechanisms.

The paper studies the impact of incomes policy on WPYE and the Phillips curve by means of co‐integration and structural break analysis. It proposes to interpret the effect of incomes policy on the Phillips curve as changing the coefficient of the error correction mechanism that leads real wages to their long‐run equilibrium value.

Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.

The aim of this study is to empirically investigate the effect of real wages on labour productivity in Malaysia's manufacturing sector using annual data from 1980 to 2009.

This study uses the Johansen cointegration test to examine the presence of long‐run equilibrium relationship between labour productivity and real wages in Malaysia. In addition, the Granger causality test within the vector error‐correction model (VECM) is used to ascertain the direction of causality between the variables of interest.

The Johansen test suggests that real wages and labour productivity are cointegrated. Moreover, labour productivity and real wages have a quadratic relationship (i.e. inverted U‐shaped curve) instead of linear relationship. Hence, the effect of real wages on labour productivity is non‐monotonic. Furthermore, the Granger causality test indicates that real wages and labour productivity are bilateral causality in nature.

This study is limited to the labour productivity in the manufacturing sector only.

This study demonstrates that the effect of real wages on labour productivity is non‐monotonic; hence increase in real wages alone does not always enhance labour productivity. Thus, other incentives should be offered to stimulate long‐term labour productivity growth in Malaysia.

This paper looks at the convergence of CEE economies to North-western Europe (Austria, Belgium, Denmark, France, Germany, Ireland, Netherlands, Norway, the United Kingdom, Sweden, and Switzerland, simplified in this study as ‘Western Europe’) in terms of indicators other than GDP, which are more relevant reflections of the welfare level of everyday citizens. It finds that contrary to the results of studies concentrating solely on GDP, a multi indicator analysis reveals a slow but definite divergence rather than convergence.

The purpose of this paper is to provide an analysis of regional concentration patterns within ten new European Union (EU) member states, EU10, and make comparisons with EU15 and the US economy.

Industrial specialization and clusters are measured as employment in the intersection between a sector (three‐digit NACE data) and a particular region (NUTS 2 level), with a total of 38 sectors and 41 regions within EU10. Regional cluster size and degree of specialization is measured along 3D: absolute number of employees (>10,000 jobs is used as cut‐off for a regional cluster), degree of specialization (regional sector employment is at least two times expected levels) and degree of regional market labor dominance (>3 per cent of total employment in a particular sector). Each of these three measures of cluster size, specialization and labor market focus are classified with a “star”. The largest and most specialized clusters receive three stars.

EU10 exhibits 19 three‐star regional clusters, which display high values for each of the three measured parameters. In addition, there are 92 two‐star regional clusters and 313 one‐star regional clusters. The analysis also suggests that regional concentration in EU10 is clearly lower than in the USA, and slightly lower than in the old EU member states. In a few cases – IT, biopharmaceuticals and communications equipment – where the total size of the cluster is small, and there is little historical legacy in Eastern Europe, the EU10 exhibits higher geographical concentration than EU15.

Overall, the economies of EU10 exhibit a pattern of geographical concentration close to a random distribution, i.e. the process of regional concentration and redistribution of industry is in a very early phase. If Europe is to build a more competitive economy, industrial restructuring towards larger clusters must be allowed and pushed by policy makers both at the national and EU levels.

Policymakers must be well informed about geographical concentration patterns of industry. The research offers a consistent methodology of mapping regional clusters and geographical concentration patterns across sectors.

This paper is the first in measuring regional concentration patterns in Europe at this fine level, and is based on a new methodology developed by Professor Michael E. Porter at Harvard University. The paper has also introduced a new method of ranking clusters according to the star model.