Ideally, employers want workers who are productive and require less management. Employers must consider many factors when deciding whether or not to pay for employee training. While employers should be wary about newly trained workers leaving, many employers require workers to remain with the firm for a certain amount of time in exchange for the paid training. Businesses may also face employees who are unwilling to accept training. This can happen in industries dominated by unions since increased job security could make it more difficult to hire trained professionals or fire less-trained employees.
However, unions may also negotiate with employers to ensure its members are better trained and thus more productive, which reduces the likelihood of jobs being shifted overseas. Workers increase their earning potential by developing and refining their capabilities. Employees want to learn advanced techniques or new skills to vie for a higher wage. Usually, workers can expect their wages to increase at a smaller percentage than the productivity gains by employers.
The worker must consider a number of factors when deciding whether to enter a training program:. Some employers pay for all or a portion of the training expenses, but this is not always the case. Also, the worker may lose income if the program is unpaid and prevents the employee from working as many hours as was done previously. Many countries have placed greater emphasis on developing an education system that can produce workers able to function in new industries, such as science and technology.
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This is partly because older industries in developed economies were becoming less competitive, and thus were less likely to continue dominating the industrial landscape. Also, a movement to improve the basic education of the population emerged, with a growing belief that all people had the right to an education. When economists speak of "education," the focus is not strictly on workers obtaining college degrees. Education is often broken into specific levels:.
Female education and economic growth in Pakistan | distsotilighsing.cf
A country's economy becomes more productive as the proportion of educated workers increases since educated workers can more efficiently carry out tasks that require literacy and critical thinking. However, obtaining a higher level of education also carries a cost. A country doesn't have to provide an extensive network of colleges or universities to benefit from education; it can provide basic literacy programs and still see economic improvements.
Countries with a greater portion of their population attending and graduating from schools see faster economic growth than countries with less-educated workers. As a result, many countries provide funding for primary and secondary education to improve economic performance. In this sense, education is an investment in human capital , similar to an investment in better equipment.
The enrollment ratio differs as a metric from calculating education spending as a percentage of GDP , which doesn't always correlate strongly with the level of education in a country's population.
Therefore, a country spending a high proportion of its GDP on education doesn't necessarily ensure that the country's population is more educated. For businesses, an employee's intellectual ability can be treated as an asset. The more well-trained workers employed by a firm, the more that firm can theoretically produce. An economy in which employers treat education as an asset is often referred to as a knowledge-based economy.
Like any decision, investing in education involves an opportunity cost for the worker. Hours spent in the classroom means less time working and earning income. Employers, however, pay more wages when the tasks required to complete a job require a higher level of education. As a result, although an employee's income might be lower in the short-term to become educated, wages will likely be higher in the future, once the training is complete.
The Cobweb Model helps to explain the effects of workers learning new skills. The model shows how wages fluctuate as workers learn a new skill, but also how the supply of workers is impacted over time.
The model shows that as workers learn a new skill, higher wages occur in the short-run. However, as more workers get trained over time and enter the workforce, to chase the higher wages, the supply of workers increases. The result is lower wages due to the excess supply of workers.
As wages fall, fewer workers are interested in the job leading to a reduction in the supply of workers. The cycle begins again with training more workers and increasing their wages in the short run. Since training and education take time to complete, shifts in the demand for particular types of employees have different effects in the long and short term. Economists demonstrate this shift using a cobweb model of labor supply and labor demand. In this model, the supply of labor is analyzed over the long term, but the shifts in demand and wages are viewed in the short term as they move toward a long-term equilibrium.
In the short-run, the increase in demand for better-trained workers results in an increase in wages above the equilibrium level graph A. We can see the shift in increased demand D2 and where it intersects W2 representing the increased wages. However, L, which represents the short-term labor curve, also intersects W2 and D2. Instead of the increase in wages being along the long-run labor supply curve S , it's along the more inelastic short-run labor supply curve L. As more and more workers are trained graph B , the supply of labor shifts right L2 and moves along the long-run labor supply curve S.
With the increase in the availability of new workers, there is downward pressure on the wage rate, which falls from W2 to W3 graph C. Because of the falling wage rate, fewer workers are interested in training for the skills demanded by employers. As a result, wages rise up to W4 , although the increase in wages is coming in smaller and smaller increments.
This cycle of wage increases and labor increases continues until it has reached equilibrium: the original upward shift in demand meets the long-run supply of labor graph F.
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The female education has negative and male education has a positive impact on economic growth of Nigerian economy. This study recommends that government should focus on policies regarding educational system, increase female enrollment and improve female contribution to economic growth.
Hafner and Mayer-Foulkes, find out the determinants of economic growth and development in a relation to high human development, high-income level and declining the fertility rate over the 72 developing countries in the time period to This study found no significant relationship between human development and income. In developed nations only changes in income and human development is essential for developed lifestyle; but in developing countries, the fertility rate is showing negative relation to the human development and positive to the income.
By employing dynamic panel models the results reveal that there is an insignificant relationship between Female Labor Force Participation and economic growth. This study suggested that policymakers have to design new policies which can effectively increase the labour force participation rate for future economic benefits. Shahid studied to investigate the relationship between labour force participation and economic growth in Pakistan over the time to By using Augmented Dicky Fuller and Phillip Perron and Johnson co-integration the result shows that there exists a positive and significant relationship between the variables in the long run.
The impact of education on personal and economic growth
Moreover, the insignificant relationship found between variables in short run. The policy implication is that government should build a new education and training institutes that promote the skilled labour which directs the economic growth. Urhie investigated the impact of Public Education Expenditure on both the education attainment and Economic Growth in Nigeria for the time period to By employing Least Squares estimation technique the results show that capital education expenditure has a negative effect and recurrent education expenditure have a positive impact on economic growth.
This study suggested that in order to boost the economic growth make sure the efficient allocation of education expenditure. Li studied the association between fertility rate and economic growth for developing countries during the time period to By employing pooled OLS and fixed effect the results reveal that the total fertility rate and economic growth is negatively associated for a recent scenario because the quantity of human capital is scarce in nature so people tend towards higher fertility rate in order to get more returns from each child.
Firstly, by increasing fertility rate economic growth also increases and later decline because of higher fertility rate Burdines the economic system. Mallick et al.
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By using FMOLS and Pedroni co-integration, the results show that there is long-run positive and significant relationship between education expenditure and economic growth. Education is key variable for economic growth so that government of each country should be prior education sector and increases its spending on a share of the budget. Moreover, the government spends for each sector of education including technical educations for the long-term economic benefits.
Nowak and Dahal attempted to examine the association between education and economic growth in Nepal for the time period to By employing the OLS and Johansen Co-integration technique the results reveal that there is a significant and positive relationship between education and economic growth in a long run. This study recommends that policymakers must pay serious attention to the development of education system and make efforts for improvement of the quality of primary, secondary and higher education level that further leads to economic growth.
Afridi, studied to investigate the relationship between human capital and economic growth in Pakistan during the time period to There is a positive impact of birth rate and physical capital on economic growth so the result demonstrates that human capital plays significant role in the progress of the economy. These results suggest that there is effective need to invest for the better outcomes in the long run for the bright future of Pakistan. More expenditure on health and education make sure the people to serve the nation efficiently.
Square OLS to capture the impact of female education on economic growth. This study examines the relationship of Female education, female labour force participation, Fertility rate, Education expenditure with economic growth. The data has been taken from World Bank Indicator over the time period to The specified model as follows:.
These variables have a different level of correlation; Female education, female Labor force participation, fertility rate, education expenditure and GDP. Female education has a positive correlation with female Labor force participation and economic growth. On the contrary female education has a weak negative correlation with Fertility Rate and Education Expenditure. Female Labor force participation has a strong positive correlation with economic growth and weak positive with Education expenditure but there is a strong negative correlation between fertility rate and female labour force participation.
The fertility rate has a strong negative correlation with economic growth and weak positive with education expenditure. The fertility rate has a weak negative correlation with education expenditure. Before applying the model the stationary of the variables have been tested by ADF test. The results show mix results that is Female education, fertility rate and labour force is integrated at first order I 1 , whereas GDP and Education Expenditure is integrated at the level I 0.
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In the above table, the coefficient value of education expenditure is 0. The coefficient value of fertility rate is The probability value of fertility rate is 0. The value of the coefficient of the female labour force is 1. The probability of female labour force participation is 0. The coefficient value of female education is 0. The value of R-squared shows the impact of all the independent variables on dependent variable as the high-income is 0.
The value of adjusted R-squared 0.