Project title: Measuring unemployment on hills of Chitwan Project location: Chandi Bhanjyang, Chitwan Responsible Organization: IAAS, Rampur Project Leader: Praveen Sapkota Collaborators: DADO, Economist (Punya Pd. Regmi) Duration of Research: Start-August 2009 End- August 2011 Total Budget: Rs. 17, 36,385/- 1. Introduction
Unemployment is the condition of not having a job, often referred to as being "out of work", or unemployed. Not having a job when a person needs one, makes it difficult if not impossible to meet financial obligations such as purchasing food to feed oneself and one's family, and paying one's bills; failure to make mortgage payments or to pay rent may lead to homelessness through foreclosure or eviction. Being unemployed, and the financial difficulties and loss of health insurance benefits that come with it, may cause malnutrition and illness, and are major sources of mental stress and loss of self-esteem which may lead to depression, which may have a further negative impact on health. 1.1 Background information In economics, unemployment refers to the condition and extent of joblessness within an economy, and is measured in terms of the unemployment rate, which is the number of unemployed workers divided by the total civilian labor force. Growing unemployment and under employment has been a chronic problem in Nepal. According to the 1991 census of population, 81.23% of the total population is engaged in agriculture and a huge bulk of them is self employed. These people who are engaged in agriculture do not have the year round employment. The 8th plan has estimated the rate of underemployment to be 7.6% in 1992. The rate of under employment in rural areas is estimated to be around 50% As of reference of last 7 days in the NLSS, 1996, 67.2 % of the total is categorized as employed, 3.4% as unemployed and 28.4% as not active. In this survey a person is defined as employed, if he/ she worked at least one hour during the reference period and if he or she did not work at all during the reference period but was available and looked for job or did not look for work for reasons other than those listed above were considered as inactive. Rural urban differences indicate that the unemployment rate if higher in total areas that in urban areas. Consequently the proportion of inactive population is much larger in urban areas compared to rural part of the country. Of the total employed, if analyzed by hours of work 47.1% are underemployed (hrs of work, per week less than 40), proportion of underemployed population in much larger in rural that in urban areas. Because of this reason, the country has to create more job opportunities for unemployed as well as for the new entrants into the labor force. Realizing this fact, the government has formed a high level employment committee which is working to devise a scheme to create productive employed to 66 thousand people.
1.2 Problem statement: 1. There is decrease in income, increase in unemployment, increment of population and decrease in employment labor 2. Increase in health problem, malnutrition, muscle drain, brain drain etc.
1.3 Research question: 1. Does unemployment affect the development of village? 2. What is the impact of employment and unemployment under men and women in ruling household expenditure? 3. What percentage of the people is feasibility unemployed?
1.4 Justification: 1. More employment could be created in rural areas
1.5 Scope: a. To determine the effect of immobilized and unemployed person in a family b. No. of people employed under different headings c. Analysis of unemployed figures in a society d. An overview of living standard of people in hilly areas of Chitwan e. Improvement of social environment will be observed f. Role of different sector will be observed g. To outline the factors affecting unemployment under different headings
1.6 Objectives: 1. To discuss the standards on measuring unemployment, economically inactive population, and to examine the experience of measuring unemployment in Chitwan 2. To access factor affecting unemployment 3. Improvement in social environment 4. Distribution of employment in different study
1.7 Limitations: There are limitations in using standard questionnaires to obtain the required information. First, the subjective nature of the replies to the household surveys can lead to errors of different kinds. Respondents may not understand the questions, forget certain activities or purposely provide incorrect information. Second, as with any sampling method, errors creep into the results, especially in estimates concerning population groups for which the corresponding sample size is small. Third, such surveys require an important statistical infrastructure, with substantial financial resources and a network of experienced interviewers and supervisors.
1.8 Hypothesis: a. There is no inequalities in employment opportunities b. There are no any factors that effect for unemployment c. There is no inequality of employment generation d. There is no equal share of different sector for different job seekers
2. Review of literature A distribution-sensitive measure of unemployment by.Vani K. Borooah The measurement of unemployment, like that of poverty, involves two distinct steps: identification and aggregation. In this process, the issue of identifying the unemployed has received considerable attention but, once they have been identified, the aggregation problem has been addressed by arriving at a unemployment rate through simply counting heads. This, in particular, leads to differences in the unemployment experiences of individuals that underlay the unemployment rate, being ignored. This paper proposes a methodology, based on the measurement of income inequality, for adjusting unemployment rates to make them "distribution-sensitive". Consequently, different levels of social loss will, depending on the distribution of unemployment experiences, be associated with the same value of the conventionally defined unemployment rate. A numerical example illustrates the methodology. Measuring the Equilibrium Effect of Unemployment Benefits Dispersion, University of Southern California We analyze the impact of unemployment benefits and minimum wages using an equilibrium search model which allows for dispersion of benefits and productivity levels, job-to-job transitions, and structural and frictional unemployment. The estimation method uses readily available aggregate data on marginal distributions of unemployment durations as well as wages and benefit levels. We investigate the efficiency of the imposition of a single benefit level for all household types and the introduction of an Earned Income Tax Credit A Kalman-Filter Approach to Estimating the Natural Rate of Unemployment By .Victor V. Claar
In order to be able to conduct effective monetary policy as the unemployment rate falls, policymakers must be armed with some estimate of the natural rate of unemployment. Of course, relatively more accurate estimates of the natural rate afford additional room for the effectiveness of monetary policy at warding off accelerating inflation during periods of economic growth. Using an annual series (1948-1996) of unemployment rate data from the Bureau of Labor Statistics' Current Population Survey, this paper employs the Kalman filter in order to estimate the natural rate of unemployment in the United States in 1996. In addition, the Kalman filter estimation yields smoothed estimates of the time series of the natural rate over the period 1948-1996. An especially appealing feature of the model is that it is consistent with a broad variety of macroeconomic models since it follows directly from a standard macro-principles decomposition of actual unemployment into its frictional, structural, and cyclical components.
The Measurement of Unemployment: An Empirical Approach by. W. Craig Riddell Although the unemployment rate is one of the most widely cited and closely monitored economic statistics, the definition and measurement of unemployment remain controversial. An important issue is whether non-employed persons who display a marginal attachment to the labor force (for example, those who are available for and desire work but are not searching for work) should be classified as unemployed or non-participants. Although this issue has been extensively debated, it has never been tested empirically. This paper carries out empirical tests of this and related hypotheses using a unique longitudinal data set from Canada. We find within the marginally attached a "waiting" group whose behavior indicates that they would be more appropriately classified as unemployed rather than out-of-the-labor force. The remainder of the marginally attached exhibit behavior between that of the unemployed and the balance of non-participants, suggesting that the desire for work, among non-searchers, conveys substantial information about labor force attachment and future employment status. Our methods also apply to heterogeneity within the unemployed, and we investigate behavioral variation linked to differences in job search methods and reasons for entry into unemployment. Although those using "passive" job search do exhibit behavior somewhat distinct from "active" searchers, our results reject the practice of classifying passive job searchers as out-of-the-labor force. 3. Outputs: a. Factors affecting unemployment will be identified b. Improvement in social environment will be observed c. Employment distribution and unemployment will be notified d. Role of different sector is known
4. Research methodology: The study involves a combination of information collection, literature, review, and analysis.
4.1 Study site: The field visit and analysis of measuring of unemployment is done in different hilly areas (Darechowk, Chandi Bhanjyang and Saktikhor) of Chitwan district of Nepal.
4.2 Data and their sources:
In preparing the research proposal advantage of primary data are needed. The primary data can be obtained from the people from each household employed under different sectors. The secondary sources will be GO, NGO or intermediate government organization. Others sources are human development report, Nepal living standard survey, central bureau of statistics, survey of employment, income distribution and consumption patterns of Nepal.
4.3 Sampling design
With the addition of open and close ended questions, farmers will be interviewed. Major sector responsible for unemployment and employment will be agriculture, livestock, business, industrial, diary work, cottage, trekking etc. and also towards the factor affecting unemployment. Focus group discussion, a tool PRA will be handed on. By calculating the population mean level of employment will be carried on.
All the house hold engaged on their daily work on different sectors will be measured. The major factor for their unemployment related to this data will be calculated. For this random samples of 50 household will be obtained. Some no. of major employment and unemployment people will be selected using the proportionate of simple random sampling and stratified random sampling.
No of person in a family (T) Employment provided by different sectors No of persons been employed (t) Mean level of employment (×) (m) Unemployed= total -employed U=T-t Agriculture a Govt. services b Cottage industries c Livestock rearing d Poultry raising e Business f Trekking g Tourism h others i Table 1: Collection of total no of family, indivisual employed, and mean no of employed persons Indivisual of age between being employed House hold number 1 2 3 4 5 6 7 8 9 8-15 X11 X12 X13 X14 X15 X16 X17 X18 X19 16-35 X21 X22 X23 X24 X25 X26 X27 X28 X29 36-60 X31 X32 X33 X34 X35 X36 X37 X38 X39 61-85 X41 X42 X43 X44 X45 X46 X47 X48 X49 86-over X51 X52 X53 X54 X55 X56 X57 X58 X59 Table 2: no of individual of different ages being employed X11= individual of no. 1 house being employed from age between 8-15 years. X12= individual of no. 2 house being employed from age between 8-15 years. X21= individual of no. 1 house being employed from age between 16-35 years.
X31= individual of no. 1 house being employed from age between 36-60 years. Etc.
4.4 Data analysis Percentage distribution of population of 10 years and above by employment category and by various geographical areas
Geographical area Total Employed Unemployed Non active Central 100 66.0 3.8 30.2 Ecological region Hills 100 67.9 2.6 29.5 Area of residence Rural 100 68.8 3.2 28.0 Urban 100 47.3 6.6 46.1 Source: Nepal living standard survey, 1996 CBS
Percentage distribution of population for 10 years and above by employment category and by gender, 1995/96 Gender Total Employed Unemployed Non active Male 100 71.0 4.2 24.8 Female 100 63.7 2.8 33.6 Source: central bureau of statistics, Nepal living standard survey, 1996
Percentage of unemployment to labor force Area Male Female Both Rural 5.47 5.68 5.57 Source: CBS, 95/96
Employed and unemployed population
This comprises all employed persons. For a person aged 15 years or over to be classified as employed, that person should: (a) Be engaged in performing work for pay or profit during the seven days before enumeration; or (b) Have formal job attachment. Unpaid family workers and persons who work for no pay in a family business are also considered as employed.
For a person aged 15 or over to be classified as unemployed, that person should: (a) Not have had a job and should not have performed any work for pay or profit during the seven days before enumeration; and (b) Have been available for work during the seven days before enumeration; and (c) Have sought work during the 30 days before enumeration.
Notwithstanding the above, the following types of persons are considered as unemployed:
(a) Persons without a job, who have sought work but have not been available for work because of temporary sickness; and (b) Persons without a job, who have been available for work but have not sought work because they (i) have made arrangements to take up a new job or to start business at a subsequent date; or (ii) were expecting to return to their original jobs; or (iii) believed that work was not available to them.
Wit the help of mean, median, standard deviation, unemployment % will be measured. For the comparative study and measurement of employment and unemployment regression analysis will be used to estimate the relationship between factors and its affect on unemployment.
The unemployment rate (measured in percent) is:
For the purpose of calculating the unemployment rate, unemployed persons are considered to be those who are willing and able to work for pay but are unable to find jobs. The civilian labor force includes all those willing and able to work for pay - both unemployed and employed. In practice, it is notoriously difficult to measure the number of unemployed workers actually seeking work, particularly those whose unemployment benefits have expired before finding work. There are several different methods for measuring the number of unemployed workers, each with its own biases, making comparisons between methods difficult. After calculation of no of persons being employed in different sectors, mean level of employment will be calculated. Then the data observed will be calculated according to gini coeffeicient. Then total no of employement will be calculated. Thus we calculate the total unemployed after deducting from the total no of person in a family. Gini coefficient
It is similar to Lorenz curve approach. Gini coefficient measures the area between actual distribution line and equal distribution line. The value of Gini coefficient varies from 0-1. If the value of G is 0, it shows that there is no income inequality. It can be expressed mathematically as
G = 2 (y1+2y2+……………..+nyn)-1/n-1 N2Y-
Where G= Gini coefficient N= no of persons being employed Yi = percentage of employed personnel provided by different sectors y = mean level of employment
5. Beneficiaries: Primary beneficiaries goes to the people living there through the sector responsible and the factor by which they re dragged beyond the unemployment. The secondary beneficiaries will be the district office which can measure the unemployed person and try to help them with the efficient work needed for them. The tertiary beneficiaries will be the government of Nepal to calculate the living standard of the people of Nepal and its effect in development of hilly areas and the district. 6. Budget summary: S. N. Items Year 1 (NRS) Year2 (NRS) Year3 (NRS) Total (NRS) 1 Staff cost 2,52,000 33,000 29,000 3,14,000 2 Operational cost Transportation 1,50,000 25,000 20,000 1,90,000 TADA 1,50,000 44,400 50,000 11,400 Telephone 50,000 50,000 50,000 1,50,000 Surfing 4000 2500 4000 10500 Security 13,000 13,000 13,000 39,000 3 Equipments and supply Computer 4,00,000 - - 4,00,000 Stationary (pen, pencils, record book etc.) 1,00,000 60,000 50,000 2,10,000 4 Training and publication 90,000 40,000 1,10,000 1,85,000 Subtotal 15,09,900 Overhead 5% 75,495 Contingency 10% 1,50,990 GRAND TOTAL 17,36,385/-
7. Risk and assumptions o Social environment remain suitable o Farmers cooperation will be available o Cost effective result will be achieved o Fund will be available at time. o Respondents will understand the questions, without forgetting any activities and provide correct information o Active participation of collaborator
THANK YOU
FOR YOUR COMMENT praveenmusic@gmail.com
