Factors Of Waste Generation Environmental Sciences Essay

Factors Of Waste Generation Environmental Sciences Essay As a development country, the economic keep on growing and a lot of construction project will be carry out. Since this construction project is kept on increases, it will face a major problem on waste management. It is no longer strange or new for the construction waste and pollution produced in the sites which affect the environment issue. Reuse and recycling of construction waste is now a big recommendation for nowadays construction industry. There is a waste management which conducts a different management process in all over the world. Malaysia is using the Site Waste Management Plan to control the waste in our country. However, there are not much contractor follow the Site Waste Management Plan and just simply dump the construction wastes anywhere. The aim of this study is to learn the ways of recycling and reuse of construction waste management in a construction. Basically this study focus on what type of waste recycle to be use, which construction waste can be recycle or cannot be recycle, and the successful demolition of waste and issue of waste. With the study of waste management in Malaysia, I can know how the contractor did the waste management and how much level of awareness about waste minimization by contractor. 1.2 Introduction Construction waste is no longer a new issue or topic for a construction industry. Some waste is unavoidable even the design is perfect in a construction industry. Construction projects are required to make sure that it give impulse to the economy, improve the standard of living and provide opportunity for jobs. The overall construction industry make profit to the country however it is not an environmentally-friendly industry as it will cause air, water, noise and land pollution which all can be linked to the construction industry (Mohd Nizam Bin Yusoff, 2010). It is to be said that the construction industry creates chances and injects money into a nations economy by giving an opportunity for foreign and local investment (M. Agung, 2009). However, despite these contributions, the construction industry has also been linked to global warming, environmental pollution and degradation (Jones Greenwood, 2009). As we all know that not only construction can generates a huge amount of pollutants, including solid waste, noise, dust and water, other industries also will generate but in a small amount as compare to construction industries (Ball, 2002; Morledge Jackson, 2001). To start construction activities, construction cannot start if no any other direct influence industries. There are many direct influences on many other industries which define as both purchasing the inputs from other industries and providing products to almost all other industries, eliminating or reducing waste will produce a great amount of cost savings to society (Polat Ballard, 2004). Although Material Storage Management (MSM), the new concept for minimizing the waste in the construction industry is recognize, but contractor is not fully participate for this new concept. As the cost of labour is expensive than building materials cost, contractor rather allow construction material waste than put more human resources in managing the waste materials (Yau and Wong, 1997; Wong, 2000). Since foreign country are advance in controlling the construction waste strategies, Malaysia as a developer country should also consider about the problem occur in construction waste management. Recycling of construction waste will help the communities to reach the goal by preserve valuable space in their local landfills (Schlauder and Brickner, 1993). Nowadays many reuse and recycle method for construction waste which will lead to minimization of construction waste. Contractors will have to participate on such recycle method to overcome construction waste management problems. 1.3 Problem Statement Construction waste has affected the environmental problems especially for many large and developing cities. About 38% of the construction waste is generated from construction, which is among 6,408 tonnes of waste per annum are produced from construction activities. The amount wastes generate from construction industries is high as compare to other industry. This problem will affect the cost to expel the construction and demolition waste rising rapidly as it is becoming more and more expensive. The construction and demolition waste (CD) is the most critical waste in the whole world. According to Malaysia Environmental Quality Report 2005, the total quantity of wastes in a year is 548,916.11 metric tonnes. This is a huge amount of wastes that we need to be considered and find out a way to control this situation. As from the Malaysia Environment Quality Report 2005, the oil and hydrocarbon waste has the highest percentage 22.4 while phenol/ Adhesive/ Resin waste has the lowest percentage of 0.3. On the other hand, for the type of industry, electronic waste is the highest with percentage of 23.7 while printing and packaging waste is the lowest with percentage of 0.5. Construction industry is a huge consumer of non-renewable resources and a massive producer of waste and the operation of the buildings are responsible for about half of the toal CO2 emissions (K. A. M. Kamar, Z. A. Hamid 2011). Therefore, it is needed to find out the solution and way to conduct waste control to minimize the construction waste. This must be start from now on and being practice by all construction industry to avoid pollution of environment and reduce the construction waste. 1.4 Scope of Study Construction waste management is too wide for carrying out a research as waste is classified into two types, waste of material and waste of manpower. In this situation, I will narrow down the scope of study for construction waste management in order to get my work done smoothly. In this case, I specify my scope of work by focusing on several aspects on construction waste management. Main focus of my research is on the Kuala Lumpur construction companys waste management practices in Malaysia. I will mainly focus on type of construction waste material which are metal and also concern about metal industry. This is because metal is considers as the middle waste produce in the construction industry and it is a common waste. Metal is always being used by construction industry and almost all the metal waste are not reuse or recycle in a proper ways. Besides, I will also focus on how the contractor reuse, recycle and remove other construction waste material from site. As for different construction industry, they will practice different ways of settling the construction waste and this will be interesting to be known. 1.5 Aim and Objectives Aims: To study the ways of recycling and reuse of construction waste management in a construction. Objectives: 2.2 To investigate the issue of waste generate by construction industry. 2.3 To determine the several factors lead to the waste generation and the success for recycling and demolition of construction waste. 2.4 To determine which construction waste can be recycling and which construction waste cannot be recycle. 1.6 Research Methodology Literature Review I will carry out my research by conducting literature review to further understand and be more familiar on the title and scope of research that I had chosen. I will try to read ad much information as I can about my topic which mainly obtains from internet, journal, books, newspapers, magazine and reference books. My literature review focus on the ways to recycle construction waste material, cause an effect of construction waste material and construction waste material pollution issue. As an overall picture, I carry out literature review to furnish myself on the construction waste management scope in our country. Questionnaire As for this research on construction waste in Malaysia, I will conduct questionnaire which mainly focus on main contractor, developer and sub-contractor. I will give out my questionnaire to about 70 construction firm to help me complete my survey question. I expected that I will receive about 30 respondents to enable me to analyze on the result and continue carry out my research study. The survey questions are design based on the aim and objectives that is stated earlier. Interview Interview will be conduct with main contractor or site agent to further understand their ways to remove construction waste in the site. Throughout interview, I can find out the difficulties of handling construction waste. Contractor can share some experience on how to reduce the waste or how to remove the waste on construction site to me and I think this might be helpful for me to do my research. Chapter 2: Literature Review 2.1 Definition of waste Nowadays the amount of construction waste contribute in a development country is extremely high. As compare to other waste produce by other industries, the construction waste is the highest generation of waste. Waste can be simply define or describe as the material which is produce by human or from industry which does not has residual value ( Serpell and Alarcon, 1998). There are a lot of definitions to describe waste as show below: Waste can be defined as that which can be throw away or dispose without reducing customer value. (Polat and Ballard, 2004) The loss or damage of whatever kind of resources is considered as waste. The waste on materials, time (labour and equipment), and capital is mainly conducted by activities that generate direct or indirect costs but do not increase any value to the last product from the point of view of the customer. (Formoso et al., 2002) Any substances or objects that are mainly for disposed or intended to be disposed or are needed to be disposed off by the provisions of national laws are defined as waste. (The Basal Convention, 1989) The by-product which is generated or remove from a construction work, renovation work and demolition work or sites of building and civil engineering structure is consider as waste. (Cheung, 1993) For any substances or article which are need to be disposed of as being broken, worn out, contaminated or otherwise spoiled is consider as waste. (Section 75 of U.K. Environmental Protection Act (EPA), 1990) Table 2.1 Definitions of waste There are many waste generate everyday in a construction site such as construction waste, material waste and solid waste. Construction waste: Construction wastes are the wastes that are generated from the various activities carry out from the construction which is relatively clean and heterogeneous building material (Tchobanaglous et al., 1993). It is also define as the waste which includes the delay in time consuming, unsafely, rework, unnecessary transportation journeys, far distances, improper management of programme and poor constructability (Lee, et al., 1999). Besides that, (Peavy et al., 1985) indicated construction waste as the waste which is conducted from building works, demolition works and refurbishment works for individual housing, commercial building or other structures. According to (Shen et al., 2004), Construction wastes are arising from the different types of construction activities including the excavation, civil and building construction, site clearance, demolition activities, roadwork and building renovation which result the wastes in the formation of building debris, rubble, earth, concrete, steel, timber and mixed site clearance materials. For the new construction wastes, it is composed primarily of mixtures of unused or damaged raw materials as well as off cuts (discarded cut material) and packaging (Magdich, 1995). Materials waste: Materials waste is mean by whatever material that are far away from earth materials which requires to be transported elsewhere from the construction site or used among the construction site itself for the objective of land filling, incineration, recycling, reuse or composting, other than the intended specific purpose of the project due to materials damage, excess, un-reuse, or non-compliance with the specifications or being a by-product of the construction process (Ekanayake Ofori, 2000). Material wastes are categorized by the activity which are over-ordering, overproduction, wrong progressing, unsatisfied storage, manufacturing defects and theft or vandalism by human ( Garas et al., 2001). Solid waste: Wastes generate from human and animal activities are called solid waste. Wastes establish by public authorities for final disposal, including hazardous waste, liquid-solid sludge from industry and water/waste water plants are within this definition (Kiely , 1997). Solid waste is also to be said as the waste which is in solid form that are unusable or unwanted generally conducted by human activities (Peavy et al., 1985). 2.2 Issue of Waste When due to the issue of waste, the construction waste is or will subsequently become a serious environmental issue in many cities and countries all around the world (Chen et al., 2002; Ferguson et al., 1995; Shen et al., 2000, 2002; Smallwood, 2000; Wong and Tanner, 1997). (Faniran and Caban, 1988; Kibert, 1994; Ferguson et al., 1995; Graham and Smithers, 1996; Guthrie et al., 1999; Symonds, 1999; Lawson and Douglas, 2001.) Stated that waste management for construction and demolition activities has become the major environmental problems in many municipalities. Whenever there is a construction activities carry out, there will produce waste. Waste from the construction industry will cause global warming, environmental pollution and degradation (Jones Greenwood, 2009). Environmental problems in many big cities are also cause by the construction waste generated in construction activities (Begum et al., 2006; Chen et al., 2002; Teo Loosemore, 2001). There are several construction materials which contribute the cause of wastes such as steel reinforcement, premixed concrete, cement, sand, lime and premixed mortar, bricks and blocks, ceramic tiles pipes and wires Formoso et al., (2002). Based on the analysis on sources of wastes concluded that a high amount of material wastes is generated due to the flow of activities like material delivery, inventories and internal transportation and handling, which are usually neglected by site management (Formoso et al., 2002). A research from Environmental Protection Department stated that a daily average of 37,690 tonnes of Construction and Demolition (CD) wastes was conducted (EPD, 2000 a). Besides that, due to the development country which the construction industry activities increasing rapidly and shortage of sustainable landfill sites, the construction wastes are becoming a serious problem forcing the professionals and researchers to focus on the way to reuse the construction wastes (Masood et al, 2002). Globally estimate that many landfill sites around the world will receive 10-30% of construction and demolition (CD) waste frequently (Fishbein, 1998) while (Magdich, 1995) stated that construction and demolition wastes to be throwing to the landfills will contribute 25 percent from all the wastes. There are about 1-10% of the purchased construction materials will be leave at the site for the residential projects as waste (Bossink and Brouwers, 1996). Recent research which carry out in UK stated that at least 10% of all raw materials delivered to the sites will be wasted in the case of damage, loss and over-ordering (Guthrie et al., 1998). In the year of 2005, our lan dfills will be fully dispose of waste and the construction industry will no longer depend on landfills to dispose waste (EPD, 2002a). Other wastes are easy to be handled but for the construction waste, it is more difficult to be reuse or recycle due to the high levels of contamination and a huge degree of heterogeneity. (Bossink and Brouwers, 1996) say that construction waste also contains an extremely high amount of chemical wastes which is harmful and hard to be handling. Usually for the construction waste generate in construction activities will be dump to landfills and in recent days construction waste is recommended to be recycle to recognize its value and potentials of reusing them in future construction project (Trankler, et al., 1996; Peng et al., 1997). As for the total landfills wastes, construction and building activities takes 30% of the total volumes in the States while UK adds more than 50% and Australia takes 20%-30% (Teo and Loosemore, 2001). Research on the construction and demolition wastes has been done which indicate that about 15%-30% of all solid waste by weight and more than 90% of this waste is from landfill in the gulf region, especially in Kuwait (Kartam, et al. 2004). Untitled.png Figure 2.2 Hierarchy of construction and demolition waste (Peng et al., 1997). There are limited practices among the construction sector on the waste minimization, reuse and recycling method because of the building materials which are at relatively low cost (Begun et al 2009). There is no forcing that the construction companies must practice sustainable resource and waste management which conclude that illegal dumping is still an issue for the authorities (Begun et al 2009). As this figure 2.2.1 is concern, it specified that for the solid waste, it contribute the most among the other waste produce in a construction industry in Malaysia. Untitled.png Figure 2.2.1 Percentage of solid waste in 1994 by  ¼Ã‹â€ Hassan et al. ¼Ã…’1998). 2.3 Factors of waste generation 2.3.1 Classification of waste There are classifications of wastes in the construction industry. Research from the pass indicated that the material waste will occur or appear throughout the construction project no matter in initial stage, design stage, construction stage or operation stage (Craven et. al., 1994; Faniran and Caban, 1998; Gavilian and Bernold, 1994; Spivey, 1974). Basically for the building construction waste there will divide into two categories namely structure waste and finishing waste (Skoyles and Skoyles, 1987). Structure wastes are those wastes such as concrete fragment, reinforcement bars, abandoned timber plate and pieces. On the other hand, for finishing wastes, it included a wide range of waste materials which is generated during the finishing stage of the building (C.S.POON*, ANN T.W.YU and L.JAILLON 2003). Furthermore, wastes are being arranged into specific categories like demolition materials, packaging materials, wood, concrete, asphalt, garbage and sanitary wastes, scrap metal, products, rubber, plastic and glass, and pesticides and pesticide containers (Spivey, 1974). Singapore defined the classification of construction material waste into three major categories namely material waste, labor waste and machinery waste (Ekanayake and Ofori, 2000): Material waste: Any kind of materials which is unused and rejected as worthless or unwanted. Labor waste: Simply mean that the waste conducted by laborer such as concrete wasted due to unsatisfied workmanship, brick lay wrongly and broken of floor tiles. Machinery waste: Machinery which is order to the site but did not carry out the construction activities. Classification of solid waste is as below: Municipal waste which the wastes are paper, plastics, food wastes, ashes, and special wastes include Street sweepings and dead animals. Industrial waste which the wastes are timber, demolition and construction waste, treatment plant waste, hazardous waste. Hazardous waste which the wastes are radioactive substances, chemicals, biological waste, flammable waste and explosives. (Kiely , 1997). 2.3.2 Construction Industry Waste Generation A study on the generation of construction waste in the construction industry is very important. Waste generates in many kind of situation and it is important to be identified to reduce and improve the waste management. Nowadays a lot of countries were developing well in construction industry and cause the generation of huge amount of construction waste. Demand for houses and major infrastructure projects make the amount of construction waste keep increasing rapidly which will cause environmental issue (Nasaruddin et. al., 2008; Siti and Noor, 2008). Construction and demolition wastes surpass the volume of municipal wastes in most of the countries. This simply means that construction activities generate and produce a large amount of waste (Sim Lee Gaik, 2005). (Graham and Smithers, 1996) stated that as long as a construction activities or project is concern, there are several factors which will lead to the production of waste. Basically, it is often that the construction wastes are come from the result of human error in design, procurement method, material handling, residues of raw materials and unexpected change in building design (Bossink and Brouwers, 1996). Generally about 10% of the materials delivered to construction site will become wastes at the end of the construction activities (Magdich, 1995). A study contribute that the largest waste generated materials or component is woody (Goetz, 1998). As for other countries, waste generation is show as below: Hong Kong generated the major solid waste in construction industry and in the year of 1998, it generated approximately 32,710 tons of construction and demolition (CD) wastes per day (Poon et al., (2001). Greece surpasses 3.9 million tons of construction and demolition wastes for the year of 2002 which will continue increase the amount of waste subsequently (Fatta et al., 2003). Australian landfills have 20% to 30% of construction waste out of all wastes are being dispose (Craven et al., 1994). Brazil is to be saying that the amount of construction waste generated will be 20% of all materials delivered to site (Formoso et al., 2002). United States Environmental Protection Agency (USEPA) mention that the amount of 124 million metric tons of building-related construction and demolition wastes or 1.2kg per person per day were produced in the year of 1996 (Weber et al., 2002). India has the total generation of construction waste about 14.7 million tons per year as stated in Central Pollution Control Board India (Pappu, 2006). Country CD Wastes (percentages %) The Netherlands 26 Australia 20-30 United States 20, 23, 24, 29 Germany 10 Finland 13-15 Table 2.3.2 CD Wastes as Percentage of All Solid Wastes Entering Landfills in Various Countries (Source: Bossink and Brouwers, 1996) Untitled.png Chart 2.3.2 CD Waste Generation in Million Tons Waste generate in Percentage Tourist Hotel and Industrial Projects 19% Commercial Projects 16% Low Rise Building 13% Government Projects 11% Tunnel and Infrastructure 8% High Rise Building 33% Table 2.3.2.1 Cumulative Percentages of Projects Generating Construction Waste in Egypt (Mohd Firdaus Bin Mustaffa Kamal, 2009) The involvements of waste generation are divided into five sections such as design, procurement, materials handling, construction/ renovation and demolition. The table below shows the different type of project phase which cause waste generated: (Graham and Sniithers., 1996) Untitled.png Table 2.3.2.2 Causes of waste in different project phase The construction and demolition wastes generate rubbish, wood/ related products and miscellaneous wastes where their percentage of waste generation is as follow: Rubbish 40%-50% such as concrete, asphalt, bricks, blocks and dirt. Woods and related products 20%-30% such as pallets, stumps, branches, forming and framing lumber, treated lumber and shingles. Miscellaneous wastes such as painted or contaminated lumber, metals, tar-based products, plaster, glass, white goods, asbestos and other insulation materials, and plumbing, heating and electrical parts. Tchobanoglous et al. (1993) 2.3.3 Wastes in Malaysia Malaysia, a developing country wishing to achieve status by 2020 is facing a big problem and challenge of decoupling economic growth and waste generation (National Economic Advisory Council, 2010). Construction waste generating in Malaysia is becoming more and more pressing issue (Begum et. al, 2007; Begum et. al., 2010). (Recycling Today, 16 March 2004) indicated that Malaysia has a subsequently high waste generator from the construction industry. It can be said that Malaysias construction waste is one of the largest waste rate and yet despite a number of government policy initiatives to address this problem, suitable resource and waste management on site remains a low priority for the majority of the contractors (Begum, 2009). Due to the rapid development and urbanization happen in Malaysia, our country produces about 25,600 tonnes of waste daily (Fazleena Aziz, 2010). There are five states in Malaysia which produce 70% of the total amount of waste in the country and there are Kuala Lumpur, Selangor, Pahang, Terengganu and Kelantan (Grant, 2001). 30 construction sites are conducted in a study which identified six types of waste materials namely concrete (12.32%), metals (9.62%), bricks (6.54%), plastics (0.43%), woods (69.10%) and others waste (2%). Among these wastes, woods contribute the most in our country (Faridah et. al., 2004). 28% of municipal solid waste and construction waste been generated in the central and southern regions of Malaysia (Mohd Nasir et Al., 1998). Overall summary of 16,000 tons of domestic waste is produced per day by local communities and the amounts per capita change from 0.45 to 1.44 kg per day which very much depending on the economic status of the areas concerned. This simply mean that waste generate about 1kg per capita per day (GAIA Global Meeting, 2003). Based on a research from Alam Flora Sdn. Bhd., there are only 76% of solid wastes are able to be collect back in Malaysia and only about 5% being recycle, with the rest of 95% disposed at the countrys 112 landfills (Alam Flora Sdn. Bhd., 2007). For our country Malaysia, it is quite surprise to say that the Government spends RM400 million per year on waste disposal and the waste is only refers to municipal solid waste which is a huge amount of money (The Star, 2005). Another issue happen in Malaysia is illegal dumping. Seberang Perai of Pulau Pinang stated that there are illegal dump site near along the road which is a very irresponsibility way of clearing the construction wastes (Faridah et. al., 2004). Besides Seberang Perai, the issue of illegal dumping is happening rapidly all over Malaysia (Yahaya and Larsen, 2008). Another study done in Johor which conclude that there are 42%-46% of illegal dumping sites are of construction waste (Rahmat and Ibrahim, 2007). Recent news indicated that almost 30 tons of construction waste was found to be dump illegally in tropical mangrove swamp near Bandar Hilir, Malacca and construction debris problem near roadside at Section 17, Petaling Jaya, Selangor (The Star, 2011; The Star, 2012). Those irresponsibility actions of illegal dumping will cause risk to human health and environmental problem (Faridah et. al., 2004; Rahmat and Ibrahim, 2007). The National Strategic Plan for Solid Waste Management was form in 2005 which mainly focus on solid waste management in peninsular Malaysia and the duration is until 2020 providing the foundation for the subsequent years (United Nations Development Programme, 2008). 2.3.4 Purpose of Waste Management The main purpose of conducting waste management is to reduce/ remove the amount of waste produced and in the same time reducing disposal costs and the environmental impact (Pitt et al., 2002). Waste need to be carries out by using recycle and reusing method so that it will not affect the environment factors and improve our future life. According to (Woolley, 2000), with the help of waste management in term of reducing, reusing and recycling of CD waste, it will help to increase the lifetime of landfills and reduce exploration of natural resources. One of the strategies to reduce waste is by recycling as it contributes to three main advantages (Edwards, 1999): Reduce demand for new resources Reduce transport and production energy costs Use the waste which would otherwise he lost to landfill sites. It is important to carry out waste management from now on although a very small amount of construction and demolition wastes is now recovered by waste management, for sure there will be greater amount of wastes to be recycle in the future in such a way that higher tipping fees, mandatory landfill diversion legislation and the success of entrepreneurs in processing both source-separated and mixed wastes (Tchobanoglous et al., 1993). As by using the recycling method for construction waste, it can help to decrease the demand on land for disposing the waste and also help to conserve natural materials and to reduce the cost of waste treatment prior to disposal (Poon, 2002). Waste management is used for a sustainable development which meets the needs of the present without compromising the ability of future generations to meet their own needs (Brundtland, 1987). 2.3.5 Waste Management It is a major problem suffered worldwide about the management of construction waste (Adam, 2004). Recycling of construction wastes simply mean that the separation and recycling of recoverable waste which are form during the construction and remodeling stage (Mohd Nizam Bin Yusoff, 2010). Research indicated that 90% of the construction wastes can be recyclable to be reused (Mohd Nizam Bin Yusoff, 2010). The main point of view that will cause the waste generation is by design stage. Design stage will taken into control of materials waste on construction sites as it is taking a central role to help minimizing waste produced (Shen, et al., 2004). To manage the construction wastes well, the method of managing is very important as it should be part of the project management functions and involve employees participation (Shen and Tam, 2002). A lot of various management methods have been applied and discuss from previous research in order to improve the control on construction wastes (Sim Lee Gaik, 2005) and (Koskela, 1992; Alarcon, 1997) mention that many methods have been drawn up and developed such as in the way of policy and programmes to help to reduce the construction waste. Construction management plan is introduce to improve materials resource efficiency by carry out reuse, recovery and recycling as well as to minimize the issue of illegal dumping by properly introduce the waste removal processes (Defra, 2009). As for a successful waste management, the construction waste should not be directly disposed but it needs to pass through several processes before being disposed. The method to treat the proper waste management is to follow the waste management hierarchy (Peng et. al., 1997). By following the concept of waste management hierarchy it will give advantages to the environmental and economy problem to a country (Tchobanoglous and Keith, 2002). Figure 2.3.5 Waste Management Hierarchy (Source: Peng et. al., 1997) Another waste management methodologies in the form of hierarchy in descending order from reducing waste, re

Education and Economics Essay

I. Introduction: The conventional theory of human capital developed by Becker (1962) and Mincer (1974) views education and training as the major sources of human capital accumulation that, in turn, have direct and positive effect on individuals’ life time earnings. In the Mincerian earning function, the coefficient of school years indicates the returns to education, i. e. , how much addition in earnings takes place with an additional school year. There exists a wide range of literature that estimated the rates of returns to education for different countries [Pascharapoulos (1980; 1985; and 1994); Pascharapoulos and Chu Ng (1992)]1. In Pakistan, most of the nationally representative household surveys do not contain information on variables, such as, completed years of schooling, age starting school, literacy and numeracy skills, quality of schooling, and technical training. Due to the unavailability of completed school years, one can neither compute the potential experience nor observe the effect of an additional year of schooling on individual earnings. Therefore, the available literature in Pakistan is lacking in estimating the returns to education by using the Mincerian earning function2. In recent years, the government of Pakistan has started nation-wide survey, Pakistan Integrated Household Survey (PIHS), to address the imbalances in the social sector. This survey ? The authors are Senior Research Economist and Research Economist at the Pakistan Institute of Development Economics (PIDE) Islamabad. 1 Pascharapoulos (1994) provide a comprehensive update of the estimated rates of returns to education at a global scale. He observed high social and private profitability of primary education (18%and 9% respectively) in all regions of world. The private rate of returns at this level were found highest in Asia (39%) as compared to other regions. He also noted a considerable increase in total earnings by an additional year of education in all regions of world; 13% in Sub-Saharan Africa; 10% in Asia; 12% in Europe/Middle East/North Africa; and 12% in Latin America/Caribbean. 2 At national level, only two studies are available in Pakistan that used the Mincerian earning function approach to examine the returns to education [see Shabbir and Khan (1991) and Shabbir (1994)]. However, both these studies are based on twenty years old data set. 2 provides rich information on the above mentioned variables that were missing in the earlier household surveys. This study uses the data of PIHS to examine the returns to education by using Mincerian earning function and thus aims to fill the vacuum that, due to the lack of appropriate data, exists in the literature on returns to education in Pakistan. In this paper we will first estimate the earning function with continuous school years with the assumption of uniform rate of returns for all school years. It is argued that different school years impart different skills therefore we extend our analysis to examine the addition in earning associated with extra years of schooling at different levels of education, i. e. , how much increase in earnings takes place with an extra year of schooling at different levels, such as, primary, middle, matric, intermediate, bachelors and masters. By doing so we overcome the problem that exists in the available literature in Pakistan. To our knowledge no study has yet adopted this method to examine the returns to education in Pakistan3. The impact of technical training and school quality on the earnings of fixed salaried and wage earners will be examined in this study. Based on the available data in Pakistan, most of the studies, for example, Haque (1977), Hamdani (1977), Guisinger et al (1984), Khan and Irfan (1985), Ahmad, et al (1991); and Ashraf and Ashraf (1993a, 1993b, and 1996) estimated the earning functions by defining the dummy variables for different levels of education4. These studies observe low rates of returns at different levels of education as compared to other developing countries. However, a positive association between levels of education and earnings and an inverse relationship between the degree of income inequality and educational attainment has been noted. In order to examine the inter- 3 Most of the studies on returns to education in Pakistan used dummy variables for different levels of education where the rates of returns at different levels of education are computed by the estimated coefficients. 4 In Pakistan, the data on education in most of the nationally representative household surveys have been reported in discrete form that denotes the completion of different levels of education, such as, ‘primary but incomplete middle’, ‘middle and incomplete matric’, and so on. 3 provincial differentials in returns to education, Shabbir and Khan (1991) estimated the Mincerian earning function by using a nationally representative sample, drawn from the of Population, Labour Force and Migration Survey (1979) for the literate wage earners and salaried males. Later Shabbir (1994) estimated the earning function on the extended sample of the same data set. These studies found 7 to 8 percent increase in earnings with an additional year of schooling. Although the results are consistent with those of comparable LDCs but may not reflect the recent developments in Pakistan’s economy as these studies are based on the data set which are 20 years old now. Since 1979, the economy of Pakistan has passed through various changes, especially after the inception of the Structural Adjustment Programme in late 1980s. For example, the literacy rate has increased from 26 percent to 45 percent and enrolment at primary level has increased by 67 percent. Public and household expenditures on education have also increased [Economic Survey (1998-99)]. Moreover, due to the fiscal constraints, the employment opportunities in the public sector have started shrinking and the economy is moving towards more openness with stronger role of private sector in recent years. In this scenario, it becomes imperative to re-test the role of human capital as both private and public sectors are moving towards more efficiency and productivity. This study is important from three standpoints. First, in order to estimate the effect of education on earnings, the most recent and nationally representative household survey data is used which provides detailed information on the variables that were missing in previous surveys. Second, it uses the splines of education in the earning function to examine the additional earnings associated with extra school years at different levels. Third, this study investigates the role of some important factors such as, technical training, school quality, and literacy and numeracy skills on earnings for the first time. 4 The rest of the paper is organised as follows: section 2 presents an overview of the education sector. Section 3 outlines the model for empirical estimation and describes data. Section 4 reports the results. Conclusions and policy Implications are presented in the last Section. II. The Education Sector in Pakistan: An Overview: Education plays an important role in human capital formation. It raises the productivity and efficiency of individuals and thus produces skilled manpower that is capable of leading the economy towards the path of sustainable economic development. Like many other developing countries, the situation of the education sector in Pakistan is not very encouraging. The low enrolment rates at the primary level, wide disparities between regions and gender, lack of trained teachers, deficiency of proper teaching materials and poor physical infrastructure of schools indicate the poor performance of this sector. The overall literacy rate for 1997-98 was estimated at 40 percent; 51 percent for males and 28 percent for females; 60 percent in urban areas and 30 percent in rural areas. These rates are still among the lowest in the world. Due to various measures in recent years, the enrolment rates have increased considerably. However, the high drop-out rate could not be controlled at primary level. Moreover, under-utilisation of the existing educational infrastructure can be seen through low student-institution ratio, (almost 18 students per class per institution) low teacher-institution ratio (2 teachers per institution) and high studentteacher ratio (46 students per teacher). The extremely low levels of public investment are the major cause of the poor performance of Pakistan’s education sector. Public expenditure on education remained less than 2 percent of GNP before 1984-85. In recent years it has increased to 2. 2 percent. In addition, the allocation of government funds is skewed towards higher education so that the benefits of public subsidy on education are largely reaped by the upper income class. Many of the highly educated 5 go abroad either for higher education or in search of better job opportunities. Most of them do not return and cause a large public loss. After mid-1980s, each government announced special programs for the improvement of the education sector. However, due to the political instability, none of these programs could achieve their targets. The Social Action Program was launched in early 1990s to address the imbalances in the social sector. This program aims to enhance education; to improve school environment by providing trained teachers, teaching aids and quality text books; and to reduce gender and regional disparities. The Phase-I of SAP (1993-96) has been completed and Phase-II is in progress. The gains from the Phase-I are still debatable because the rise in enrolment ratio has not been confirmed by the independent sources. Irrespective of this outcome, government has started work on Phase-II of SAP. In this Phase, government is paying special attention to promote technical and vocational education, expanding higher education in public as well as in the private sector, enhancing computer literacy, promoting scientific education, and improving curriculum for schools and teachers training institutions in addition to promoting primary and secondary education. Due to low levels of educational attainment and lack of technical and vocational education, Pakistan’s labour market is dominated by less educated and unskilled manpower. A considerable rise in the number of educational institutions and enrolment after 1980s is not yet reflected in Pakistan’s labour market. This might be due to the fact that most of the bachelor’s and master’s degree programmes emphasise only on academic education without developing specific skills. The sluggish demand for the graduates of these programs in the job markets leads to unemployment among the educated and the job market remains dominated by the less educated. In this scenario, it becomes important to explore the role of education for the economic benefit of individuals. 6 III. Theoretical Model and Estimation Methodology: We start with the human capital model developed by Becker (1964) and Mincer (1974) where natural logarithm of monthly earnings are the linear function of completed school years, experience and its square. In mathematical form the equation can be written as: ln Wi = ? 0 + ? 1 EDU i + ? 2 EXPi + ? 3 ( EXPi ) 2 + Ui (1) where ln Wi stands for natural logarithm of monthly earnings, EDUi represents completed years of schooling, and EXPi is the labor market experience of ith individual. ?1 implies the marginal rate of return to schooling. A positive value of ? 2 and negative value of ? 3 reflects the concavity of the earning function with respect to experience. Ui is the error term, assumed to be normally and identically distributed. It has been argued in the literature that different school years impart different skills and hence affect earnings differently. Therefore, it is misleading to assume a uniform rate of return for all educational levels. Most of the previous studies used dummy variables to capture the effect of different levels of education. In order to examine the effect of school years at different levels of education, van der Gaag and Vijverberg (1989) divided the years of schooling according to the school systems of Cote d’ Ivore. Similarly Khandker (1990) also used years of primary, secondary and post-secondary schooling in wage function for Peru. Both studies found significant differences in returns to education at different levels of education. Following van der Gaag and Vijverberg (1989), we divide the school years into seven categories according to the education system of Pakistan. In Pakistan, the primary education consists of 5 years of schooling; middle requires 3 more years; and by completing 2 more years of schooling after middle, an individual obtains a secondary school certificate i. e., Matric. After matric , i. e. , 10 years of schooling, students have a choice between technical and formal education. Technical education 7 can be obtained from technical institutions which award diploma after 3 years of education while the certificate of intermediate can be obtained after two years of formal education. After the completion of intermediate certificate, students can enter either in the professional colleges for four years or in non-professional bachelors degree program for two years in a college. Those who choose non-professional degree can pursue their studies in a university for masters for two more years. At this stage the graduates of professional and non-professional colleges complete 16 years of education. They can now proceed to the M. Phil. or Ph. D. degrees. In order to examine the returns to education at different splines of education, we estimate the following extended earning function. ln Wi = ? 0 + ? 1Yrs Pr imi + ? 2 YrsMid i + ? 3YrsMati + ? 4 YrsInteri + ? 5 YrsBAi + (2) ? 6 Yrs Pr of i + ? 7 EXPi + ? 8 ( EXPi ) 2 + Ui where YrsPrim, YrsMid, YrsMat YrsInter YrsBA YrsProf are defined as: YrsPrim = D5EDUi YrsMid = D8EDUi YrsMat = D10EDUi YrsInter = D12EDUi YrsBA = D14EDUi YrsProf = D16EDUi where D5 = 1 if where D8 = 1 if where D10 = 1 if where D12 = 1 if where D14 = 1 if where D16 = 1 if 0< EDU ? 5 5< EDU ? 8 8< EDU ? 10 10< EDU ? 12 12< EDU ? 14 EDU > 14 The coefficients associated with YrsPrim, YrsMid, YrsMat YrsInter YrsBA YrsProf in equation 2 imply an increase in income with one year increase in education at respective levels. For example, the returns to five completed years of education at primary level will be 5*? 1. Similarly, the returns to for six, seven and eight of education will be 5*? 1+? 2, 5*? 1+2? 2, and 5*? 1+3? 2 respectively. On the same lines we can compute the returns to education at each level as: 8 Returns to Primary =5*? 1 Returns to Middle =5*? 1+3*? 2 Returns to Matric= 5*? 1+3*? 2+2*? 3 Returns to Intermediate=5*? 1+3*? 2+2*? 3 +2*? 4 Returns to Bachelor’s =5*? 1+3*? 2+2*? 3 +2*? 4 +2*? 5 Returns to MA/Prof=5*? 1+3*? 2+2*? 3 +2*? 4 +2*? 5 +2*? 6 The data are drawn from the nationally representative Pakistan Integrated Household Survey 1995-96. In order to assess the performance of the Social Action Programme (SAP), the government of Pakistan has launched the series of Pakistan Integrated Household Surveys (PIHS), a collaborative nation wide data collection effort undertaken by the Federal Bureau of Statistics (FBS). So far two rounds have been completed. The first round of the PIHS is different from other round on two counts. Firstly, the information on employment and wages is available only in this round. Secondly, only 33 percent of the sample used in the first round is being repeated in the subsequent rounds. This implies that all of these rounds are independent cross-section data sets and can not be properly linked with each other to be used as panel data. Therefore, the appropriate sample can only be drawn from the first round of PIHS. This round was conducted in 1995-96, which covers 12,622 households and more than 84,000 individuals. The 1995-96 PIHS provides a detailed information on completed school years5. In addition, this survey contains information on age started school. This information is particularly important for our study to calculate the potential experience of a worker. The indicator for experience used by Mincer (1974) is a good proxy for U. S. workers as they start school at the uniform age of six years6. However, this assumption does not hold in Pakistan, as in this country there is no uniform age to start school. In urban areas, children as young as three years start going to school whereas in rural 5 This is the only nation-wide data set that provides this particular information. Similarly no other survey contains information on public and private school attendence and year starting school. 6 Mincer defined experience as (Age-education-6). 9 areas the school starting age is higher. 7 This information enables us to construct potential experience as (age-schools years-age starting school). Although experience is still a proxy for actual experience but it is relatively better measure than age and the Mincer type potential experience. In addition to education and experience, various other factors, such as quality of schooling, technical training and quality of schooling have significant impact on earning8. It has been argued that because of the market-oriented approach adopted by the private schools, the graduates of these schools earn more as compared to the graduates of public schools9. According to Sabot (1992), Behrman, Ross, Sabot and Tropp (1994), Alderman, Behrman, Ross and Sabot (1996a), Alderman, Behrman, Ross and Sabot (1996b), and Behrman, Khan, Ross and Sabot (1997), the quality of education has positive, significant and substantial impact on cognitive achievements and hence on post school productivity, measured by earnings. These studies observed higher earnings of the graduates of high quality school than those who attended a low quality school. A recent study by Nasir (1999) found considerably higher earnings for the private school graduates. These schools, however, charge higher fees. â€Å"Estimates of average annual expenditure per pupil in both government and private schools indicates that the total cost of primary level in rural areas is Rs. 437 (Rs 355 for government schools and Rs. 1252 for private schools), compared with Rs. 2038 in urban areas (Rs.1315 for government and Rs. 3478 for private schools). This means that the cost of primary schooling is almost three times that of public schools in urban 7 The issue of age starting school has been highlighted by Ashraf and Ashraf (1993) and because of the nonavailability of this information, they used age as proxy for experience. 8 See Summers and Wolf (1977); Rizzuto and Wachtel (1980); Behrman and Birdsall (1983); Booissiere, Knight and Sabot (1985); Knight and Sabot (1990);Behrman, Ross, Sabot, and Tropp (1994); Behrman, Khan, Ross and Sabot (1997). 9 Various studies found the effectiveness of private schools to acquire cognitive skills [Colemen, Hoffer and Kilgore (1982); and Jimenez, Lockheed, Luna and Paqueo (1989)]. For Pakistan, Sabot (1992), Behrman, Ross, Sabot and Tropp (1994), Alderman, Behrman, Ross and Sabot (1996a), Alderman, Behrman, Ross and Sabot (1996b), and Behrman, Khan, Ross and Sabot (1997) found a significant variation in the cognitive skills among children with same number of school years. These studies conclude that some of the differences are due to the family characteristics while some are due to the quality of schooling. 10  areas and nearly four times in rural areas. The differences in cost of schooling also reflect the degree of quality differentials in public and private schools, and between urban and rural schools. A relatively better provision of school facilities and quality of education in private schools is causing a continuous rise in school enrolment in urban areas† [Mehmood (1999) page 20]. The PIHS provides information on the type of school attended10. On the basis of this information we can identify workers according to the school they attended and therefore examine the effect of type of school on individual earnings. In order to capture the quality of education an individual received, a dummy variable is included in the model that takes the value ‘1’ if individual is a graduate of private schools and ‘0’ otherwise. The effect of post-school training on earning has been found positive and substantial in many developing countries [see Jimenez and Kugler (1987); van der Gaag and Vijverberg (1989); Khandker (1990); and Nasir (1999)]. The PIHS contains information on years of technical training. This information helps us to examine the effect of technical training received on individual earnings. We use completed years of technical training as independent variable in the earning function. The existence of vast gender gap in human capital accumulation is evidenced by various studies in Pakistan11. The PIHS reports vast gender disparities in literacy and enrolment rates. The literacy rate among females is half than that of males’ literacy rate for whole Pakistan. This difference has increased to three-folds for rural areas. The gender difference is however smaller for the gross enrolment rate at primary level. For the higher levels of education, this difference 10. The coefficient of private school may also capture the effect of socio-economic background of workers. The data, however, does not contain such information, therefore we are unable to separate the effect of parental characteristics from the effect of private schools in worker’s earnings. 11 Sabot (1992); and Alderman, Behrman, Ross and Sabot (1996b); Sawada (1997); Shabbir (1993); and Ashraf and Ashraf (1993a, 1993b, and 1996) 11 shows an increasing trend. Similarly vast gender gap has been observed in returns to education where males earn more than the female workers [Ashraf and Ashraf (1993a, 1993b and 1996) and Nasir (1999)]. In order to capture the effect of gender, a dummy variable is introduced in the model that takes the value ‘1’ for males and ‘0’ otherwise. The regional imbalances in the provision of limited available social services are more pronounced in Pakistan. Rural areas are not only underdeveloped in terms of physical infrastructure but also neglected in gaining basic amenities. Haq (1997) calculated the disaggregated human development index for Pakistan and its provinces. He noted that nearly 56 percent of population is deprived of basic amenities of life in Pakistan; 58 percent in rural areas and 48 percent in urban areas. According to the 1995-96 PIHS, the literacy rate in urban areas is 57 percent and in rural areas it is 31 percent. The gross enrolment rate was noted 92 percent in urban areas and 68 percent in rural areas. Because of these differences low returns to education are observed in rural areas [Shabbir (1993 and 1994) and Nasir (1999)]. To capture the effect of regional differences, a dummy variable is used that takes the value ‘1’ if individual lives in urban areas and zero otherwise. The four provinces of Pakistan exhibit different characteristics in terms of economic as well as social and cultural values. Significant provincial differentials in rates of returns to education have been noted that reflect not only the differences in market opportunities but also indicate uneven expansion of social services across provinces [Khan and Irfan (1985); Shabbir and Khan (1991); Shabbir (1993); Shabbir (1994); and Haq (1997)]. The effects of these differences are captured through the use of dummy variables for each province in the earning function, Sindh being the excluded category. 12 For the purpose of analysis we restrict our sample to wage earners and salaried persons. Our sample contains 4828 individuals. Among them, 4375 are males and 453 are females. Table 1 presents the descriptive statistics of some of the salient features of the important variables. According to the statistics in table 1, average age of the individuals included in the sample is 34 years with 18 years of experience. A typical worker in the sample has completed approximately 10 years of education. A majority is graduated from public schools. Most of the workers live in urban areas. On average an individual earns Rs. 3163 per month. In our sample, there are only 22 percent individuals who received technical training. The average years spent for training are less than one year. A majority of wage earners belong to Punjab, followed by Sindh and Balochistan. Table1 Mean, Standard Deviation and Brief Definitions of Important Variables Variables W Age EDU EXP RWA MALE Urban Private Training Punjab Sindh NWFP Balochistan Mean SD Variables Definitions 3163. 34 3397. 39 Individual’s monthly earnings in rupees consist of wages and salaries. 34. 07 12. 36 Age of an individual in years. 9. 53 4. 36 Completed years of schooling. 18. 14 11. 80 Total Years of labour market experience calculated as (age-school years-age starting school). 2. 37 1. 07 Categorical variables, contains 4 categories of literacy and numeracy. 0. 91 0. 29 Dichotomous variable equal to 1 if individual is male. 0. 60 0. 49 Dichotomous variable equal to 1 if individual belongs to urban area 0. 04 0. 19 Dichotomous variable equal to 1 if individual is a graduate of private school 0. 35 0. 87 Completed years of technical training 0. 38 0. 49 Dichotomous variable equal to 1 if individual belongs to Punjab 0. 31 0. 46 Dichotomous variable equal to 1 if individual belongs to Sindh 0. 15 0. 36 Dichotomous variable equal to 1 if individual belongs to NWFP 0. 16 0. 36 Dichotomous variable equal to 1 if individual belongs to Balochistan 13 IV. Empirical Results The estimated results of equation 1 and equation 2 are reported in table 2. The highly significant coefficients of school years and experience indicate the applicability of human capital model for Pakistan. An additional year of schooling raises individual’s monthly income by 7. 3 percent, which is very close to the prior studies. 12 13 The coefficient of experience shows substantial increase in wages with each additional year. The concavity of age-earnings profile is evident from the negative and significant coefficient of experience squared. The results reveal that an individual with five years of experience earns 31 percent higher wages as compared to non-experience worker. The highest level of earnings is achieved with approximately 30 years of experience. These estimates are relatively low compared to prior studies14. The positive and significant coefficients of gender (0. 401) and regional dummies (0. 178) strengthens the a priori expectation that males earn more than females and earnings are higher in urban areas as compared to rural areas. These estimates are consistent with earlier studies [see Arshaf and Ashraf (1993), Khan and Irfan (1985)]. Furthermore, significant inter-provincial differences in individual’s earnings can be observed in the estimated model. Many studies indicate substantial differences in earnings across school levels. For example, van der Gaag and Vijverberg (1989) noted that an increase of one year in elementary, high and university education causes an increase of 12 percent, 20 percent and 22 percent respectively in 12 The estimated coefficients of school years by Shabbir and Khan (1991), Shabbir (1991), Shabbir (1993) and Shabbir (1994) are found to be in the range of 6 percent to 9. 7 percent. 13 The returns to education are calculated by taking the anti-log of 0. 092 (estimated coefficient of completed school years) and subtracting from 1. To convert into percentage, multiply the value by 100. For details, please see Gujrati (1988) page 149. 14 The difference in the returns to experience could be due to the approach adopted by these studies. Most of the studies used age as a proxy for experience [see for example Khan and Irfan (1985); Ashraf and Ashraf (1993); and Nasir (1999)]. Shabbir (1991) used the Mincerian approach to calculate experience. The present study uses actual age of starting school and actual years of education. These information enable us to calculate total years of labor market experience. This approach is also not the perfect alternative for actual experience, as we do not have information about the starting time of the first job. But when compared with other approaches, it is more precise in measuring experience. 14 earnings. In order to examine the returns to education across different school years, we include the information on schooling according to the education system of Pakistan (equation 2). The results reported in column 3 of table 2 show a positive and significant impact of school years at each educational level on earnings. For example, an increase of one year in education at primary level increases the earnings by 3 percent. Similarly, at middle level, one year of schooling brings about an increase of 4 percent in earnings and the total returns to schooling at middle level are 27 percent. Table 2 Earning Function with and without Levels of Education Variables Coefficient s 6. 122 0. 072* 0. 058* -0. 001* 0. 178* 0. 401* 0. 127* -0. 113* -0. 203* 0. 412 t-ratios Coefficient s 6. 380 0. 058* -0. 001* 0. 150* 0. 264* 0. 098* -0. 112* -0. 166* 0. 027** 0. 040* 0. 050* 0. 057* 0. 071* 0. 082* 0. 429 t-ratios Coefficient s 6. 342 0. 058* -0. 001* 0. 152* 0. 262* 0. 096* -0. 108* -0. 164* 0. 052* 0. 007 0. 025* 0. 038* 0. 047* 0. 063* 0. 075* 0. 429 t-ratios Constant EDU EXP EXP2 Urban Male Balochistan NWFP Punjab RWA Yrs-Prim Yrs-Mid Yrs-Mat Yrs-Inter Yrs-BA Yrs-Prof Adj R2 148. 91 46. 71 26. 49 -19. 20 10. 31 13. 98 4. 94 -4. 34 -10. 21 – 92. 03 23. 85 -16. 84 7. 87 8. 15 3. 40 -4. 06 -7. 75 2. 03 5. 07 8. 69 11. 41 16. 85 21. 98 – 89. 25 23. 84 -16. 88 7. 98 8. 09 3. 32 -3. 91 -7. 63 2. 41 0. 45 2. 45 5. 02 7. 28 11. 47 15. 57 – * significant at 99 percent level. ** significant at 95 percent level. One can note higher returns of additional year of schooling for higher educational levels from this table. For example, the returns to masters and professional education (Yrs-Prof) are more than five- 15 times higher than that of primary school years (Yrs-Prim). The results exhibit a difference of 15 percent between primary graduates and illiterates, the excluded category. This category includes illiterates as well as all those who have not obtained any formal schooling but have literacy and numeracy skills15. To further explore the earning differential between primary school graduates and those who never attended school but have literacy and numeracy skills, we have constructed an index RWA that separates illiterates from those who have literacy and numeracy skills. This index takes the value ‘zero’ if individual does not have any skill; ‘1’ if individual has only one skill; ‘2’ if individual has two skills; and ‘3’ if individual has all three skills. We re-estimated equation 2 with this new variable and the results are reported in column 5 of table 2. According to our expectations, the coefficient of RWA is found not only large (0. 05) in magnitude but also statistically significant at 99 percent level. This indicates that the individuals with all three skills earn 15 percent more than those who have no skill. On the other hand, the coefficient of Yrs-Prim dropped to 0. 007 and became insignificant16. The differential in the earnings of illiterates and those having five years of primary education was 15 percent (0. 03*5=0. 15). This differential however, reduced to approximately 9 percent (0. 007*5+0. 053=8. 8) when we include those who have no formal education but have literacy and numeracy skills. These high returns to cognitive skills indicates the willingness of employer to pay higher wages to the able workers as compared to those who have five or less years of schooling but do not have these skills. Now we examine the effect of technical training and quality of schooling on earnings, first in separate equations and then in a single equation. The impact of technical training on earnings is examined by including years of apprenticeship as continuous variable in our model. The results are reported in column 1 of table 3. The results show a positive and significant impact of technical 15 There are 48 wage earners in our sample who have education less than primary but do not have any of these skill. Whereas we found 76 wage earners who do not have any formal education but have at least one of these skills. 16 This result is consistent with van der Gaag and Vijierberg (1989). 16 Table 3 Earning Functions : Impact of Technical Training and School Quality (Separate Functions) Variables Constant EDU EXP EXP2 Urban Male Balochistan NWFP Punjab Tra.

Outrageous Essay Topics for Classification and Division College Tips

Outrageous Essay Topics for Classification and Division College Tips How to Get Started with Essay Topics for Classification and Division College? Process explains how something is finished. A Real Estate company unlike any other centered on the mission of constructing a network of career-minded pros who strive to cultivate their company and their future. Possessing a Hearing Ear dog can many times be a life saver. In a way, pain is the best evil. Each playing season must be represented by each gender also. Then, there's the New York of the commuterthe city that's devoured by locusts daily and spat out each evening. Sometimes they can receive a small conceited as a result of the talent they were possessed with at birth. Anybody who has spent time with or around children will see that each one has a distinctive personality all their very own. Eventually people will observe you don't find out how to play and which you simply don't really care about what happens in the games. The point is to examine this whole for those parts which make this up, the parts which other people may not typically think about. It's wonderful to have a whole group of friends that you are able to go totally geek with. Mind that every one of the names should be of the very same kind of the word, for instance, all adjectives or nouns. Essay Topics for Classification and Division College Secrets For some time period, if only 3 nanoseconds, each person that has ever lived considers this thought entirely earnestly. The third temperament type is known as feisty. What makes both of these positions different from each other is that in most instances the power forward is looked on to handle the majority of the scoring duties and while the small forward is only a defensive specialist with a great deal of energy. The next step is to divide the subject into three distinct items within the extensive category which you have already chosen in step one. Some organisms can survive very high temperatures. All have their own special characteristics and are interesting and important in their very own way. Some bacteria can be beneficial to humans and other kinds are harmful. The secret to all sorts of synthesis is exactly the same. The information that you use to prepare your graphic organizer should depend on your own wisdom and experience of your subject. One of the most fascinating components of a classification essay is exploring the many ways which you can categorize the sections of your subject. Each detail is taken care of in the appropriate method. In your introduction, you could also wish to offer some particular descriptive or informative details to entice the interest of your readers and suggest the aim of the essay. Though some men and women cook for sustenance, others can't appear to earn a meal without reducing some form of wine into a sauce. Regardless of the sport, there's plenty of potential within this subject to explore why folks love sports so much. In case the owner tells the dogs to move forward when they're walking on the road, but there's a car coming, the dog isn't going to cross. Additional people drink for assorted reasons. The Downside Risk of Essay Topics for Classification and Division College A classification essay may be a good source of self-reflection. Now you could be thinking about how to compose a classification essay outline. The of classification or division essays usually contains the subject, and the way that it is classified. The classification essay format takes a framework, too. Let's begin with the principal principles that are critical for classification essay writing, so you may earn a conscious selection of topic in line with the categories you would like to cover. Don't forget that each statement you make in your essay has to be proved. No outside research ought to be used. Gloria Steinem after you have staggered past the phase of denial, you will likely be quite mad. The categories you select for your essay should be totally separate. If this is the case, you've got yourself an excellent topic. Making stream-of-consciousness lists might be useful method to explore a topic. The excellent topic for a classification essay ought to have some logical point, you could classify.

Movie Reflection - 665 Words

Extra Credit: Electric Shadows Reflection The film makes me recall my childhood and my parents’ childhood. It descried a story in a town of Northwest China happened between 1970s and 1980s. At that time, people could only watch the outdoor movie that cemented by celluloid. This film covers the family love, romantic love between two generations and friendship. Also, it gives me a strong feeling of how the Chinese cultural revolution have changed the people’s lives and ideas. From what I learned from the â€Å"brief history of China† and Spence’s â€Å"the search for modern China†, Mao wanted and desired equal outcomes for all people. Even though the Great Leap Forward and Cultural Revolution caused millions deaths, and it was a miserable†¦show more content†¦I know in the early age of my hometown, if a women get divorced, or she get pregnant before marriage, she will be criticize by the whole people who live in the hometown. Even her parents will break up the relationship with her. However, the Chinese people are more open to those situations, people start understand those single mother’s circumstances and encourage them to find a new partner. Well, I feel the divorce rate is higher than the 70s and 80s. Besides all the changes, the film also reveals the importance of Confucius teaching on filial piety. Even though Ling Ling ran away from home, she still concerned her parents silently. She set a telescope outside of her room that she could observe her parents life (Xiao). As mentioned in Teiser’s â€Å"the spirits of Chinese religion†, filial piety is the foundation of all virtues in China (Teiser). For me, I have arguments with my parents, also received punishments from my parents. I know it is not easy to raising me up, I always feel gratitude and I have the responsibility to take care of my parents and treat them nicely. At the end, the film helps me recall all the changes that happened in my li fe such as technology and people’s attitude to single mothers. 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Sam is a man who has a mental disability and he got a woman pregnant. The woman took off when she gave birth and left Sam with the baby. Sam tried very hard to raise his daughter Lucy, but due to the fact that he had a mentality of a 7 year old, he had a hard time. He got help from her God Mom, Annie, who was also Lucy’s piano teacher later on. Sam’s friends, who had disabilities as well, helped him with Lucy. Sam worked at Starbucks and it showed examplesRead MoreReflection on the Movie Lincoln Essay1120 Words   |  5 PagesLincoln Reflection Lincoln, directed by Steven Spielberg, is a historical drama that follows the political aspects of the last four months of the American Civil War and Lincoln’s life as Lincoln strives to gain ratification of the 13th Amendment to the Constitution, which would bring an end to slavery and unlawful involuntary servitude in the United States. Spielberg, unlike other historical directors, has successfully portrayed Abraham Lincoln from several angles; the fatherly Lincoln who cares