Adult Training in Canada - Article Example

? Economic activity was uneven during the nineties in Canada which prompted the to conduct a study. The decade had begun with a brief recession in 1991 but thereafter output and employment expanded. Low economic activity implies low productivity and this influences the standard of living. Standard of living depends on the skills of the labor force. Thus, any nation’s economy depends upon the skills that the labor force possesses. Education and training are lifetime activities related to the working career but it is difficult to evaluate the training decisions based on the business cycle as there are many other factors that influence the training decisions. As labour market conditions improve it becomes essential to train the workforce. Training is influenced by the ‘business cycle’. As business activity increases hiring too has to increase because businesses require more staff. The staff also needs to be trained and hence as employers add staff they also undertake to train the staff. However, the ‘opportunity cost’ in training the staff is higher in a robust economy and this can reduce the incidence of training. However these are counterbalancing influences which make it difficult to relate training to business cycle. A thorough study would entail examining the entire workings of the Canadian economy which is a long-drawn process. The authors decided to restrict their query to evaluate whether the AETS instruments provide a consistent explanation of training incidence and duration for both men and women. Overall education level increased between 1992 and 1998 and more women opted for university degree. Several factors suggest that training too should have increased during this period. Based on the human capital model training should increase. Besides, between 1994 and 1998 business activity and employment rose, and this also is an indicator of rise in training. However, an aging population would imply reduced training levels. Besides, data analysis revealed changes in several factors that influence training levels. As the education level rose, people became more urban. Lifestyle changed resulting in delayed marriages and late children; men keeping out of unionism and preferring to be in employment rather than be self-employed. Men preferred to work for larger but private firms while women preferred the public sector. All these make it difficult to deduce the training duration and incidence based on the economy and business cycles. This gives rise to the query as to what factors influence an individual to undertake training. The authors draw a parallel between the human capital and the physical capital. Just as the stock and quality of physical capital comprising of machinery, equipment and computers can be augmented through investments, human capital too can be upgraded through training activities. Adults may undertake training for various reasons. This could range from a simple desire to upgrade skills after an absence from job market to desire for career advancement. Participation in training can occur at all stages in the life cycle of an individual. Thus, based on these probabilities, this study evaluated the factors that influence training decision. It further describes the incidence of training activity during the 1990s among adult Canadians who were not part- or full-time students in any education program. The study is based on a core model of human capital accumulation over the life cycle. Various factors that influence training participation and duration were taken as the variables in this study. These include age, job tenure, hours worked and past education level. The control variables included in the study were sex, family circumstances, region of residence and firm size. Data pooled from 1992, 1994 and 1998 Adult Education and Training Surveys (AETS) were statistically analyzed. The AETS survey (1998) was the sixth in the series but for this study only the data from three surveys were compiled. The purpose of AETS was to measure participation rates for learning and training among adults over 17. Basically it was meant to determine the percentage of adults who undertake some form of training after ceasing formal schooling. Training offered in colleges and universities, in private and commercial institutions, distance learning and on-site training were all included in the survey. The AETS was administered as a supplement to the Labour Force Survey (LFS) which is a household survey whose sample is representative of the civilian, non-institutionalized population over the age of fifteen. The sample size of the AETS is about 40,000 individuals against LFS in which data is collected from 102,000 people. The response rate too is higher in LFS than AETS. However, AETS provides information related to adult learning in Canada on incidence, frequency, volume, type of training, and self-reported motivations, which is not collected through LFS. Because of these advantages over the LFS, data from AETS was compiled and analyzed statistically. However, not all variables and sub-categories were identical in all three surveys from which data was compiled and analyzed. For instance, questions concerning language, ethnicity, disability status and professional/managerial status were asked in 1994 and 1998 but not in 1992. Similarly, immigration status data was available only from the 1998 survey. Since the objective of the study was to compare estimates of training incidences and training duration, the date set common to most surveys was taken. The survey of 1998 had the maximum variables and through this study it became possible to examine how the additional variables impacted the training duration and incidence. Based on the probit and tobit regression models the data was analyzed. The study found that between 1992 and 1998 men’s participation in all types of training declined by 2.6 percent. Duration of the training also decreased by 7.2 hours for men. In the case of women too participation and duration of training both dropped overall. The reasons for decline too have been evaluated by the authors based on the data collected in all the three years under study. This study also found that many factors affect training decisions and that a multivariate statistical approach is useful. The core economic variables that influence training decisions include age, job tenure, hours worked and education attainment. Training participation declines with age but higher education levels increase training incidences for both men and women. The analysis also revealed that in addition to these core economic variables some other worker and employment characteristics also influenced the training decisions. Gender differences were observed in the sense that while there was a decline in training with age for men, this was not the case as far as women were concerned. This was supported by the fact that the effect of post secondary education on training was greater for women than men. Participation in training was low from employees from smaller firms or from unionized firms. There was more participation in training from the public sector workers than from the private sector. There study found certain variables from the 1998 survey which were not found in the two previous surveys under study. Canada has a lot of immigrant community and French is the predominant language. The analysis revealed that the respondents in French were significantly less likely to participate in training than the respondents to the survey in English. Immigrants were less likely to undertake training than the native born or those who had immigrated as children. Disability also impacted the training decisions. Training is not a decision that an individual takes; he is provided with training as the business deems necessary. Accordingly, people in supervisory positions or managerial posts were more likely to receive training than other classes of workers. Job tenure has a significant impact on training. Those with five years of job tenure are less likely to participate in training but this could change after the 5-year period. However, this was applicable in the case of men. This implies that when workers are stable in their jobs the training incidence decreases but this is not known whether the need decreases or because of the high costs involved the organizations prefer to train others. At the same time, once the 5-year tenure is over, the incidences of training increases, which is a finding that needs further investigation. To obtain a comprehensive analysis of the factors that influence training decisions, job tenure and past education should be considered as important factors. In addition, personal and job circumstances also affect training decisions. The life cycle model of human capital states that education and training are lifetime activities and are related to the working career. Age and education definitely have significant influence over training duration and participation, but job tenure and the number of hours worked do not impact the training decisions. However, these factors are not sufficient to determine what influences or does not influence training decisions. The study concludes that the patterns of training decision differ across gender, and also differ across private and public sector organizations. Worker characteristics and the characteristics of the organization also influence the training incidences. Immigrants, people with disability are less likely to train than those without disability and those who are native born. Hence, the study has been able to achieve its objectives of evaluating the factors that influence training decisions. 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