Federally subsidized occupational training and the employment and earnings of male trainees

The impact of MDTA training on the earnings and employment probabilities of male trainees are studied on the basis of a longitudinal data set on trainees and non-trainees. Econometric techniques which eliminate many of the ambiguities in interpreting previous estimates are used. It is found that the program had little or no effect on employment or earnings of trainees in the late sixties (relative to continued normal employment). It is suggested that the program be interpreted as a pure income-maintenance program rather than a subsidized skill-acquisition program.     

Reinterpreting the convict labour market

The convicts transported to NSW between 1817 and 1840 were young, fit, highly literate and brought occupational skills which were broadly representative of the British and Irish working classes. In the colonial labour market where convicts were coerced, more labour was forthcoming and at a lower wage than in a free labour market. The assignment of convict labour in the colony was efficient; skilled urban and construction tradesmen were employed in the same jobs in NSW as they had held in Britain. Domestic servants and unskilled urban workers whose skills were not suited to the needs of the colony experienced job restructuring. The organization of convict workers into teams and gangs in Australia was similar to the way work was organized in free labour Britain, and a mbc of incentives and rewards characterized the extraction of work from convicts. The human capital of the transportees and the labour system within which they worked help to explain the rapid growth of the colonial economy before 1840.     

Identifying restrictions in limited information analysis of the schooling coefficient in a wage equation

Identifying restrictions underlying limited information estimates of the coefficients of a wage equation are considered from a Bayesian point of view. Within this framework ‘exclusion’ restrictions need not be imposed exactly, and it becomes possible to consider the marginal densities of interesting coefficients as functions of the tightness of these restrictions. In the application considered here the posterior mean for the schooling and test-score coefficients in a wage equation are examined as identifying restrictions are relaxed. The paper also serves as an example of the feasibility of Bayesian limited information analysis of a current economic issue.     

Patterns and drivers of post-socialist farmland abandonment in Western Ukraine

Farmland abandonment restructures rural landscapes in many regions worldwide in response to gradual industrialization and urbanization. In contrast, the political breakdown in Eastern Europe and the former Soviet Union triggered rapid and widespread farmland abandonment, but the spatial patterns of abandonment and its drivers are not well understood. Our goal was to map post-socialist farmland abandonment in Western Ukraine using Landsat images from 1986 to 2008, and to identify spatial determinants of abandonment using a combination of best-subsets linear regression models and hierarchical partitioning. Our results suggest that farmland abandonment was widespread in the study region, with abandonment rates of up to 56%. In total, 6600 km² (30%) of the farmland used during socialism was abandoned after 1991. Topography, soil type, and population variables were the most important predictors to explain substantial spatial variation in abandonment rates. However, many of our a priori hypotheses about the direction of variable influence were rejected. Most importantly, abandonment rates were higher in the plains and lower in marginal areas. The growing importance of subsistence farming in the transition period, as well as off-farm income and remittances likely explain these patterns. The breakdown of socialism appears to have resulted in fundamentally different abandonment patterns in the Western Ukraine, where abandonment was a result of the institutional and economic shock, compared to those in Europe's West, where abandonment resulted from long-term socio-economic transformation such as urbanization and industrialization.     

Did bank distress stifle innovation during the Great Depression?

We find a negative relationship between bank distress and the level, quality and trajectory of firm-level innovation during the Great Depression, particularly for R&D firms operating in capital intensive industries. However, we also show that because a sufficient number of R&D intensive firms were located in counties with lower levels of bank distress, or were operating in less capital intensive industries, the negative effects were mitigated in aggregate. Although Depression era bank distress was associated with the stifling of innovation, our results also help to explain why technological development was still robust following one of the largest shocks in the history of the U.S. banking system.     

Facets of the digital divide in Europe: Determination and extent of internet use

The primary objective of this article is to identify, given Internet accessibility, the factors that shape the decisions of individuals for personal Internet usage and its extent. Cross-sectional data from the European Social Survey database were utilized and an ordered probit model with selectivity was employed. The hypothesized link between the decision to use the Internet and the extent of usage was confirmed by the data. Household income, cost of access, demographics, media use, regional characteristics and general skill acquisition by individuals appear to correlate with Internet use and the extent of usage. In addition, a non-linear decomposition analysis was applied in order to identify the causes of the observed south/north divide. The results indicate that the observed differences in the probability of Internet use constitute a structural problem.     

Renewable energy consumption and unemployment: evidence from a sample of 80 countries and nonlinear estimates

This article contributes to the discussion on the dynamic nexus of renewable energy consumption and unemployment by incorporating nonlinear cointegration and causality analysis. Using a sample of 80 countries spanning the period 1990–2013 and the advanced generation of unit root, cointegration and nonlinear Granger causality methodological approaches in panel data, we obtain mixed results about the impact of renewable energy consumption on unemployment. Although the total findings document a positive impact of renewable energy consumption on unemployment, disaggregated data across specific regions, such as Asia and Latin America, highlight the favourable effect on unemployment, implying that the effect of renewable energy consumption on jobs creation depends on the cost of adopting renewable energy technologies and energy efficiencies that seem to vary across the regions under investigation.