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The purpose of this paper is to examine the time series behavior of Greek labor market series by providing an empirical perspective on trend breaks and unit roots. Trend breaks represent aggregate behavior responses to “infrequent” changes in economic fundamentals, including changes in fiscal or labor market conditions, as have been perceived in Greece during the last years. Unit roots reveal whether “regular” shocks have significant effects on the level of the series over a specified finite horizon.

The authors employ recent procedures that deal with the “circular testing problem” between tests on the parameters of the trend function and unit root tests that often arises in empirical applications. These techniques assess trend function stability and are robust regardless of whether the noise component is stationary or having a unit root. Then, conditional on the presence of breaks, the authors test whether the series can be characterized by a stochastic trend.

The analysis provides evidence of “infrequent” trend breaks that appear to coincide with the recent global economic crisis and the implementation of the counteraction (fiscal) measures to the Greek debt crisis. Allowing for trend breaks does not lead to a rejection of the unit root hypothesis, which might reflect the low flexibility of the country’s labor market operation.

The procedures employed can be viewed as new tools that might help empirical researchers to explore more accurately the characteristics of individual time series and to find reasonable approximations to the true processes of the time series examined.

The paper provides new information on the presence of structural changes in the Greek labor market, and on whether the “aggressive” and “occasional” nature of fiscal measures can be approximated by infrequent changes in the slope of the trend function.

Internationalisation of the Australian economy is profoundly changing the macroeconomic fabric of the Australian labour market. This study aims to shed light on both trade and technology effects on the Australian labour market during the study period 1983(4)‐1995(3). The study uses unit root and multicointegration econometrics, general to specific modelling and encompassing tests to test how trade liberalisation and technical progress have immiserised Australian labour by increasing unemployment or through the widening of skill differentiated wage disparity. The study concludes with some policy perspectives on labour market deregulation in Australia.

Carbon dioxide emissions affect the environment, presenting major implications for sustainable development and consequently model climate change policies. The main aim of the paper is to highlight the factors leading to CO2 emissions in Latin America.

The analysis was performed using data for 1990–2020 and panel regression and STATA software.

The results highlighted that the variables have significantly influence CO2 emissions in case of the countries in the sample.

The novelty of the paper consists in using all financial inflows of together (foreign direct investment, official development assistance and remittences), Latin America heavily in-flowed with remittances from the USA. Since Latin America is enriched with forest areas, the authors also covered this variable in the estimations. Urbanization and transportation are induced by remittance inflows, thus wellbeing was incorporated in the model. The conclusion of the study demonstrates the need for complex measures involving public-private partnerships, public awareness of the need for energy transition and the involvement of foreign-owned companies that must not only pursue their own interests but also generate positive economic, environmental, and social externalities in host countries.

For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

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.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.