Rural Unemployment

8/6/2019 Rural Unemployment

http://slidepdf.com/reader/full/rural-unemployment 1/27

Rural Unemployment

SIR ARTHUR LEWIS INSTITUTE

OF SOCIAL AND ECONOMIC STUDIES(SALISES)

Programme: M.Sc. in Social Policy

Course Code: SALI6031

Course Name: Techniques of Applied Social Statistical Analysis

Lecturer: Dr. Godfrey St. Bernard

EDUCATION, TRAINING AND UNEMPLOYMENT INRURAL JAMAICA.

Due Date: Monday, May 30, 2011

Student’s Name: Norician Anderson

Student ID#: 05-047799

1 | P a g e



Rural Unemployment

Table of Contents

I. Introduction 3

II. Background to the Study 8

III. Literature Review 9

IV. Methodology 13V. Analysis of data 15

VI. Conclusion and Recommendation 25

VII.Bibliography 27

VIII.Appendix 29

I. Introduction

Over 60% of the poorest people in Jamaica live in rural areas (Statistical Institute of Jamaica &

Planning Institute of Jamaica, 2010). The rural population is particularly vulnerable to poverty as

most are dependent on agriculture for survival. There was a slight contraction in the prevalence

of poverty in rural Jamaica between 1999-2008 (See figure 1.0). Improved agricultural

2 | P a g e



Rural Unemployment

performances through the recovery from Hurricane Dean in 2007 and increased food prices (led

by the global food crisis of 2008) are factors attributed to the reduced rural poverty levels in

2008 ( Planning Institute of Jamaica 2009, Statistical Institute of Jamaica & Planning Institute of

Jamaica, 2010).

Figure 1.0: Distribution of poverty by region (per cent), 1999-2008

Source: Jamaica Survey of Living Conditions, 2008, (STATIN & PIOJ)

Nonetheless, rural neglect has been customary in many socio-economic developments and this

has adversely affected the livelihood of the rural population in Jamaica. In the pre-independence

period, sugar production was the largest employer of rural labour, the third highest contributor to

GNP and Jamaica’s chief agricultural export (Harrison, 1998). The heavy dependency on

agriculture continued up until the 1950s, and with the decline of sugar, it later involved the

cultivation and export of banana, coffee and other revenue earning commodities which provided

a means of employment for many rural residences as they engaged in peasantry or worked on

plantations (Mintz, 1985). In the presence of population growth pressures and the decline in the

employability of agriculture, during the post-independence period, there was a thrust for

economic growth in other sectors.

Economic developments were primarily concentrated in urban areas and involved the use of

foreign investment and the granting of fiscal incentives (e.g. tax holiday, duty free importation,

low rental factory space) as an “invitation” to invest in the manufacturing sector (Martinussen

1997); however this afforded minimal employment opportunities for the rural populous.

Noteworthy is the theory that the widening of Jamaica’s economic base beyond the agricultural

sector through foreign investment in another sector (i.e. manufacturing sector) would absorb the

surplus labour evidenced through high unemployment and underemployment (Martinussen

1997). However, in actuality, Benn (1987) noted that the foreseen level of job creation was

3 | P a g e



Rural Unemployment

below expectation and that unemployment increased from 6% to 14% between 1956 and 1966.

Robotham (1995) also noted that there had been a marked increase in the levels of inequality.

Currently, the structure of the Jamaican economy has rendered the agriculture sector (and by

extension the rural populous) relatively inferior and obsolete to the higher revenue generating

services sector which contributed to 81.7% of the gross domestic product (GDP) in 2009

(Planning Institute of Jamaica, 2009). Furthermore, the Labour force survey shows that the

unemployment rate was more prevalent among elementary occupations (15.5%), service workers

and shop and market sales workers (12.7%), clerks (10.7%), and craft and related trade workers

(9%), and less prevalent among professionals, senior officials and technicians (3.6%), plant and

machine operators and assemblers (7.9%) and skilled agricultural and fishery workers (1.3%)

(Statistical Institute of Jamaica, 2008). Consequently, less skilled and trained workers may be

more vulnerable to unemployment.

Rural communities had also been neglected with respect to education and training developments.

Educational reforms in the 1970s which involved universally free secondary and college

education was a means of redressing social inequalities by enabling persons to have the ability to

access government jobs which typically required a secondary school diploma (Meditz &

Hanratty, 1987). However, this free education reform created other social problems such as

overcrowded classrooms, lowered quality of education, and low school attendance (especially at

the secondary level) and the reform was later abandoned during the years of structural

adjustment. Furthermore, social inequalities persisted especially through the structure of the

education system which was comprised of different types or “class” of schools; at the secondary

level these were namely the traditional high schools, the vocational institutes and the technical

high schools and the comprehensive high schools; at the primary level there were the preparatory

schools (private primary schools), the public primary schools and the “all age” or elementary

schools and at the tertiary level there were the University of the West Indies, the College of Arts,

4 | P a g e



Rural Unemployment

Science, and Technology (CAST), the College of Agriculture, various teachers colleges and

community colleges (many of which are also socially stratified, typically located in urban

communities and of which approximately 5% of the Jamaican population attend) (Meditz &

Hanratty, 1987).

In recent years, the Economic and Social Survey of Jamaica has indicated an increase in the level

of investment in education and training in Jamaica especially in the area of infrastructural

development, maintaining school relief; providing nutritional and educational material support

and improving quality of teacher education (Planning Institute of Jamaica, 2009). Records have

also shown that a school was built in Westmoreland in 2009 in the bid to increase the number of

space within existing schools (Planning Institute of Jamaica, 2009). Notwithstanding this,

Bullock (2010) underscored that the fragility of rural existence has engendered a significant

rural-urban population drift of a largely uncertified and untrained rural population, "in search of

a better life". In addition, Bullock (2010) asserted that rural urban migration generated a

catalogue of problems such as squatter communities, substandard housing, substandard sanitation

and public health, and crime.

This study presumes that regardless of the increased expenditure on education and training,

socio-economic investments continue to be unevenly distributed and as such, there is still a high

prevalence of rural unemployment, as majority of the rural population remains largely

uncertified and untrained. The purpose of this study is to investigate the likelihood of there

being a difference in the education and training levels of unemployed persons based on their area

of residence.

The objective of this study is to test the following hypothesis:

Research hypothesis:

5 | P a g e



Rural Unemployment

Null hypothesis: There is no difference in the likelihood of unemployed persons having higher

levels of education and training in rural areas when compared with the Kingston Metropolitan

Area or Other Towns.

Alternative hypothesis: The likelihood of unemployed persons having higher levels of education

and training is lower in rural areas when compared with the Kingston Metropolitan Area or

Other Towns.

The specific objective is:

i. To determine the odds of unemployed persons receiving vocational training with

certificate, technical or professional training with certificate, apprenticeship, on the job

training or no training with respect to “KMA”, “Other Towns” or “Rural Areas”.

ii. To determine the odds of unemployed persons having passed “none”, “less than 3 CXC”,

“More than 3 CXC”, “CAPE” or “DEGREE” examination/s in KMA, Other Towns or

Rural Areas.

6 | P a g e



Rural Unemployment

I. Background

The International Labour Organization (1982) defines unemployed as comprising all persons

above a specified age who during the reference period were without work (i.e. were not in paid

employment or self-employment) and currently available for work (i.e. were available for paid

employment or self-employment during the reference period) and seeking work (i.e. had taken

specific steps in a specified recent period to seek paid employment or self-employment).

Likewise, the Statistical Institute of Jamaica (2008) refers to unemployed as individuals who are

“looking for work” and “wanting work, available for work” .

Jamaica can be classified into three geographical planes (Cornwall, Middlesex and Surrey) wherein

Cornwall (western region) includes parishes such as Westmoreland, Hanover, St. James, St.

Elizabeth, Middlesex (middle region) includes the parishes such as Clarendon and St. Catherine

and Surrey (eastern region) with parishes such as Kingston, St. Thomas and Portland. Another

classification is the division into fourteen parishes. Bourne, Eldemire-Shearer, McGrowder,

Crawford (2002) noted another classification in 2007 of cities (urban areas) which constitute

27.3% of the population, peri-urban 30.2% and rural areas, 42.5%. For the purpose of this study,

Jamaica will be classified into “KMA” areas which constitute Kingston and St. Andrew, Spanish

Town and Portmore, “Other Towns” which constitute urbanized areas outside of the KMA

7 | P a g e



Rural Unemployment

region such as Mandeville in Manchester or May Pen in Clarendon and the “Rural” areas will be

comprised of the non- urbanized areas outside of the KMA region and Other Towns. As such,

rural unemployment refers to persons from the rural areas of Jamaica who are looking for work,

want work and are available for work.

Characteristic of Rural Unemployment

Approximately 47% (617,800) of the labour force population were in rural region of

Jamaica in October 2008. The unemployment rate for the rural region of Jamaica has increased

from 9.9% in October 2007 to 11% in October 2008. The unemployment rate is 6.4 percentage

points higher for females (13.8%) than males (7.4%) in 2008 and particularly severe among

persons aged 14-19 (39.9%) and 20-24 (22.0%) in 2008. The unemployment rate was more

prevalent among elementary occupations (15.5%), service workers and shop and market sales

workers (12.7%), clerks (10.7%) and craft and related trade workers (9%) and less prevalent

among professionals, senior officials and technicians (3.6%), plant and machine operators and

assemblers (7.9%) and skilled agricultural and fishery workers (1.3%). It is important to

underscore that the unemployment rate for gender, age, and occupation was not necessarily

related to the rural region but could be used to infer the characteristic of rural unemployment.

II. Literature Review

The differences in education and training among unemployed persons in Jamaica may be

explained by George Beckford’s theory of structural underdevelopment conditioned by the slave

plantation system. Beckford (1972) argued that the plantation, as a total institution, fashioned the

whole environment in which the people of the Third World had inherited. Consequently,

individuals (especially peasants) were less inclined to undertake wage work on the plantation

because of the legacy of slavery; and would typically work on the plantation in situations where

8 | P a g e



Rural Unemployment

there was no other ways of making a living (Beckford, 1972: 19). Beckford (1972) then

explained that plantation economy, as the dominant force in many third world societies,

generally benefitted from better quality of land and the availability of the resources needed for

production whilst the subsistence of the peasants was marginalized. Beckford (1972) further

explained that despite attempts by the government to provide assistance to peasantry,

incremental resources generally flow towards the plantation sector and the peasantry has

increasingly been forced to seek possibilities for advancement through migration and or wage

work on the plantation.

With respect to education and training, Beckford (1972) explains that the educational system was

a metropolitan creation and as such black people who passed through the system assimilated

their culture and essentially became black Europeans. These “black Europeans” are the ones

who later became the political leaders and the trade unionist who were intent on transferring the

constitutional power from Europeans Crown to the colonies but inadvertently, for the most,

helped to maintain the status quo of social hierarchies that limit the potential of marginalized

groups.

A study to determine the factors associated with the difference in academic performance among

third and fourth grade primary school students found that teacher’s perceptions of a child’s

academic ability and teacher characteristics affected academic performance. The results showed

that each additional score point in which teachers attribute student achievement to student ability

corresponded to a 21.01 point increase in Language achievement and a 21.59 point increase in

Mathematics scores (Casassus, Cusato, Froemel & Palafox 2002). In addition, teachers who did

not have a/n additional job/s, who believed that they were being adequately paid and that they

were not over-burdened and who had some post-secondary training had students who performed

better based on their test scores (Casassus, Cusato, Froemel & Palafox 2002).

9 | P a g e



Rural Unemployment

There was also a gender differential for educational performance wherein girls outscored boys in

Language and boys outscored girls in Mathematics. The socio-economic level of the school, as

perceived by the Principal of the school, was related to an increase of 5.64 points in student

Language achievement and of 5.88 points in Mathematics. Other school characteristics such as

the size of the school library, the quantity of instructional materials and the student teacher ratio

had a positive effect on academic achievement (Casassus, Cusato, Froemel & Palafox 2002).

Parent characteristics such as education and parental involvement were positively related to

academic performance (Casassus, Cusato, Froemel & Palafox 2002). The results showed that the

education of parents or guardians, defined as the mean value of the number of years of schooling

of parents and guardians, increase Language scores of child/ren by 0.97 points and by 0.81 points

in Mathematics scores per year for education. Parental involvement in the child/ren education also

played an important role in academic performance whereby children with parents that read to

them every day scored 5.88 more points in Language and 4.31 more points in Mathematics than

the children of those parents or guardians who did not (Casassus, Cusato, Froemel & Palafox

2002).

Household characteristics also affected performance, as children living in households with 10 or

more books scored 4.54 points higher in Language and 5.20 points higher in Mathematics than for

those from households not having this number of books (Casassus, Cusato, Froemel & Palafox

2002). Overall, the results from the Casassus et. al study underscored the importance of having

positive social, infrastructural and physiological investment in children during the early years of

education. It also showed the potential impact of generational deprivation wherein less educated

parents also had children who also underperformed.

Zilvere (2002) noted that there was evidence of regional disparities in terms of development,

employment opportunities and education in Lativa. The social realities in the rural areas of

10 | P a g e



Rural Unemployment

Lativa were generally characterized by high levels of unemployment and widespread poverty

(Zilvere, 2002). Zilvere (2002) highlighted that the limited number of affordable households,

poor road infrastructure, high transportation cost, low wages, stereotypes and the difference in

social values of rural inhabitants were generally obstacles to their mobility as it defined their

ability to access jobs in their profession.

Zilvere (2002) further explained that some regions of the country had an undeveloped

infrastructure which made it more difficult to attract investments and as such unemployment

increased. In addition, the chances of residents to acquire high-quality education also differed

and as such talented intellectuals generally leave the economically undeveloped regions to move

to more developed regions, thereby exacerbating the economic backwardness of undeveloped

regions.

Zilvere (2002) also noted that the decline in unemployment was bolstered by structural changes

in the economy which involved retraining courses for unemployed people, most of which had

little education. Individuals who were less willing to be re-trained often faced periods of long-

term unemployment likewise women who were involved in child care also faced period of long

term employment as they loss their professional skills and relations with their previous employer.

Revenga (2002) noted, in reference in Slovak Republic, that traditional safety nets create a

culture of dependency wherein persons were less likely to seek employment while receiving

government benefits however when benefits were terminated they searched and usually found a

job. Revenga (2002) explains the social benefits system in Slovak Republic is designed in such a

way that there is little incentive for an individual to seek a job especially if the person is

unskilled and market wages are low, as these persons will lose their entitlements once they get a

job.

11 | P a g e



Rural Unemployment

III.Methodology

i. Sampling Procedure

The sampling for the labour force survey was based on a two-stage stratified random sampling

design, where there was a Primary Sampling Unit (PSU) and a selection of dwelling from the

primary units. The PSU is an Enumeration District (ED), which constitutes a minimum of 100

dwellings in rural areas and 150 in urban areas. An ED is an independent geographic unit that

shares a common boundary. This means that the country was grouped into strata of equal size

based on dwellings (EDs). Based on the PSUs, a listing of all the dwellings was made and this

became the sampling frame from which a master sample of dwelling was compiled which

provided the sampling frame for the labor force

The labour force (or the economically active population) is comprised of all persons 14 years and

over of either sex who engage in the supply of labour for the production of economic goods and

services for a particular reference week of the survey. For the purpose of this study, the sample

of unemployed respondents (1041 individuals) was selected from the labour force sample (7,500

individuals). The labour force surveys were undertaken by the Statistical Institute of Jamaica on

a quarterly basis (January, April, July and October) however the survey utilized for this study

was done in April 2009.

ii. Data Collection

The 2009 Labour Force Survey dataset from the Derek Gordon Databank, Sir Authur Lewis

Institute & Economic Studies, UWI, Jamaica was used for this study. The general contents of the

survey include the socio-economic and demographic characteristics, components and

characteristics of the labour force, characteristics of the employed labour force including level of

training, characteristics of the unemployed labour force including level of training and

characteristics of those outside the labour force. However, the specific area of the survey

12 | P a g e



Rural Unemployment

analyzed for this study, looked at the characteristics of the unemployed labour force relating to

level of training and highest academic examination passed (See appendix for questionnaire).

iii. Method of Measurement

Training will be measured by the type of training received which will include vocational with

certificate, professional or technical with certificate, apprenticeship, on the job training or no

training. Education will be measured by the highest academic examination passed which will

include none, Less than 3 CXC’s, More than 3 CXCs, CAPE or Degree. Regions of Jamaica will

be measured as “KMA”, “Other Towns” and “Rural” areas.

I. Analysis of Data

Demographic characteristics of sampled population

13 | P a g e



Rural Unemployment

The sample consisted of 1041 respondents (ages 14 to 99 years), with a mean age of 32.63 years

(SD 12.61 years). Of the sample of respondents, 43.7% were males and 56.3% were females.

Most of the respondents were from the rural Area (49.5%). Moreover, majority of the

respondents were either the head of the household (41.4%) or the child of the head of the

household (40.1%). On examining area of residence by sex, it was found that 58.3% of the

women were in rural areas when compared to 53.6% in the KMA region and 55.1% in other

towns (See Table 1.0). In addition, 43% of the unemployed child/ren of the head of the

household were in rural regions when compared with the child of the head of the household in

KMA (33%) or Other Towns (41%).

Table 1.0: Demographic characteristic of respondents by regions of JamaicaVariable Regions Level of

significanceRural Area

n = 515 (49.5%)

Other Towns

n = 274 (26.3%)

KMA

n = 252 (24.2%)

Age Group χ2= 11.981,

p= 0.447*

14-19 66(12.1%) 33(12.0%) 27 (10.7%)

20-24 111 (21.6%) 52 (19.0%) 46 (18.3%)

25-34 153 (29.7%) 85 (31.0%) 81 (32.1%)

35-44 101 (19.6%) 50 (18.2%) 52 (20.6%)

45-64 53 (10.3%) 34 (12.4%) 27 (10.7%)

55-64 25 (4.9%) 12 (4.4%) 8 (3.2%)

65 and over 6 (1.2%) 8 (2.9%) 11 (4.4%)

Total (n=1041) 515 (100%) 274 (100%) 252 (100%)

Sex χ2= 1.718,

p= 0.424*

Male 215 (41.7%) 123 (44.9%) 117 (46.4%)

Female 300 (58.3%) 151 (55.1%) 135 (53.6%)

14 | P a g e



Rural UnemploymentTotal (n=1041) 515 (100%) 274 (100%) 252 (100%

Relationship to Head of

Household

χ2 = 7.676,

p =0.104*

Head 168 (39.1%) 88 (38.6%) 103 (49%)

Spouse 78 (18.1%) 46 (20.2%) 37 (17.6%)

Child 184 (42.8%) 94 (41.2%) 70 (33.3%)

Total (n= 868) 430 (100%) 228 (100%) 210 (100%)

* The p-value is for each variable by area of residence (i.e. rural, other towns and KMA).

An examination of the explanatory variables in the study showed that the percentage share of

respondents who had received no training (68.7%) and had passed no academic examination

(80.5%) was greatest in rural areas (See Table 2.0).

Table 2 .0: D istribution of Level of Training and Highest Academic Examination passed of respondents by regions of Jamaica .

Explanatory Variables Rural Area Other Towns KMA

Level of

significance

Level of Training χ2 = 40.499

p =0.000

None 333 (68.7%) 163 (61.7%) 130 (52.8%)

Vocational with certificate 86 (17.7%) 39 (14.8%) 42 (17.1%)

Professional/ technical with

certificate

5 (1.0%) 10 (3.8%) 17 (6.9%)

Apprenticeship 50 (10.3%) 46 (17.4%) 44 (17.9%)

On the job training 11 (2.3%) 6 (2.3%) 13 (5.3%)

Total (n=995) 485 (100%) 264 (100%) 246 (100%)

Highest Academic Examination

Passed

χ2 = 28.304

p =0.000

None 392 (80.5%) 191 (75.5%) 164 (71.6%)

15 | P a g e



Rural UnemploymentLess than 3 C.X.C 41(8.4%) 22 (8.7%) 25 (10.9%)

More than 3C.X.C 52 (10.7%) 31 (12.3%) 27 (11.8%)

CAPE 0 (0%) 2 (0.8%) 0 (0%)

Degree 2 (0.4%) 7 (2.8%) 13 (5.7%)

Total (n=969) 487 (100%) 253 (100%) 229 (100%)

A cross tabulation of the Rural and “Other Towns” region of Jamaica by Level of Training (χ2

= 15.372, p =0.004) ( See Table 3.0) and a logistics regression of Rural and “Other Towns” by

Level of Training ( See Table 4.0) was used to analyze the likelihood of having varying levels of

training in Rural Areas.

Table 3.0 Cross tabulation of the R ural and Other Towns regions by Level of Trainingreceived.

16 | P a g e



Rural Unemployment

Regions

TotalRural AreasOther Towns

Areas

Training Vocational with certificate Count 86 39 125

% within Training 68.8% 31.2% 100.0%

% of Total 11.5% 5.2% 16.7%

Professional/Technical withcertificate

Count 5 10 15

% within Training 33.3% 66.7% 100.0%

% of Total .7% 1.3% 2.0%

Apprenticeship Count 50 46 96

% within Training 52.1% 47.9% 100.0%

% of Total 6.7% 6.1% 12.8%

On the job training Count 11 6 17

% within Training 64.7% 35.3% 100.0%

% of Total 1.5% .8% 2.3%

None Count 333 163 496

% within Training 67.1% 32.9% 100.0%

% of Total 44.5% 21.8% 66.2%

Total Count 485 264 749

% within Training 64.8% 35.2% 100.0%

% of Total 64.8% 35.2% 100.0%

Table 4.0: Logistic regression of unemployment in rural areas co mpared with Other Townareas by training

BStandard

Error Wald df Sig.OddsRatio

95% C.I.for Odds Ratio

Lower Upper

Vocational with certificate -0.076 0.215 0.126 1 0.723 0.926 0.607 1.413

Professional/Technical withcertificate

1.408 0.556 6.409 1 0.011 4.086 1.374 12.149

Apprenticeship 0.631 0.226 7.826 1 0.005 1.88 1.208 2.924

On the job training 0.108 0.516 0.044 1 0.834 1.114 0.405 3.066

None 1.360

17 | P a g e



Rural Unemployment

The results showed that the odds of having vocational training with certificate are 7.4% lower for

Other Towns when compared to Rural Areas (OR= 0.926). The odds of having professional or

technical training with certificate were four times better in other towns when compared with

rural areas (OR= 4.086). The odds of having apprenticeship training were 88% high for Other

Towns when compared to Rural Areas (OR= 1.88). The odds of having on the job training were

11% higher for Other Towns when compared to Rural Areas (OR= 1.114). The odds of having

no training was 36% higher for Rural Areas when compared to Other Towns (OR= 1.360).

The difference in the odds of having apprenticeship training is statistically significant for Rural

Areas and Other Towns (p =0.005).

A cross tabulation of the Rural and Other Towns region of Jamaica by highest academic

Examination Passed (χ2 = 12.361, p =0.015) ( See Table 5.0) and a logistics regression of Rural

and “Other Towns” by highest academic examination Passed ( See Table 6.0) was used to

analyze the likelihood of having passed varying levels of examinations in Rural Areas.

Table 5 .0 Cross tabulation of the R ural and Other Towns regions by Highest AcademicExamination Passed.

Region

Total

RuralOther

Towns

Highest academic None Count 392 191 583

18 | P a g e



Rural Unemploymentexamination passed % within

Exampassed

67.2% 32.8% 100.0%

% of Total 53.0% 25.8% 78.8%

Lessthan 3CXC

Count 41 22 63

% withinExampassed

65.1% 34.9% 100.0%

% of Total 5.5% 3.0% 8.5%

Morethan 3CXC

Count 52 31 83

% withinExampassed

62.7% 37.3% 100.0%

% of Total 7.0% 4.2% 11.2%

CAPE Count 0 2 2

% withinExampassed

.0% 100.0% 100.0%

% of Total .0% .3% .3%

Degree Count 2 7 9

% withinExampassed

22.2% 77.8% 100.0%

% of Total .3% .9% 1.2%


% withinExampassed

65.8% 34.2% 100.0%

% of Total 65.8% 34.2% 100.0%

Table 6 .0: Logistic regression of unemployment in rural areas compared with Other Townareas by highest academic examination passed

B S.E. Wald df Sig.OddsRatio


Lower Upper

Less than 3 CXC .096 .279 .120 1 .729 1.101 .638 1

More than 3 CXC .202 .243 .687 1 .407 1.224 .759 1

CAPE 21.922 28420.722

5.950E-07

1 .999 3.316E+09

.000

Degree 1.972 .807 5.975 1 .015 7.183 1.478 34None 1.341

The results showed that the odds of having passed Less than 3 CXCs are 10% higher for Other

Towns when compared to Rural Areas (OR= 1.101). The odds of having passed more than 3

19 | P a g e



Rural Unemployment

CXCs are 22% higher in Other Towns when compared to rural areas (OR= 1.224). The odds of

having passed CAPE is significantly higher in Other Towns when compared to Rural Areas

(OR= 3.316E+09). The odds of having passed an academic examination for a Degree is seven

times higher for Other Towns when compared to Rural Areas (OR=7.183 ). The odds of having

passed no exam is 34% higher for Rural Areas when compared to Other Towns (OR= 1.341).

A cross tabulation of the Rural and KMA region of Jamaica by level of Training (χ2 = 37.043, p

=0.000) (See Table 7.0) and a logistics regression of Rural and KMA by levels of training ( See

Table 8.0) was used to analyze the likelihood of having varying levels of training in Rural Areas.

Table 7 .0 Cross tabulation of the R ural and KMA regions by Level of Training

20 | P a g e



Rural Unemployment

Regions

TotalRural Areas KMA

Training Vocational with certificate Count 86 42 128

% within Training 67.2% 32.8% 100.0%

% of Total 11.8% 5.7% 17.5%

Professional/Technical with

certificate

Count 5 17 22

% within Training 22.7% 77.3% 100.0%

% of Total .7% 2.3% 3.0%

Apprenticeship Count 50 44 94

% within Training 53.2% 46.8% 100.0%

% of Total 6.8% 6.0% 12.9%

On the job training Count 11 13 24

% within Training 45.8% 54.2% 100.0%

% of Total 1.5% 1.8% 3.3%

None Count 333 130 463

% within Training 71.9% 28.1% 100.0%

% of Total 45.6% 17.8% 63.3%


% within Training 66.3% 33.7% 100.0%

% of Total 66.3% 33.7% 100.0%

Table 8.0: Logistic regression of unemployment in rural areas compared with KMA byLevel of Training

B S.E. Wald df Sig.OddsRatio


Lower Upper

Vocational withcertificate

.224 .215 1.087 1 .297 1.251 .821 1.90

21 | P a g e



Rural UnemploymentProfessional/Technicalwith certificate

2.164 .519 17.381 1 .000 8.709 3.148 24.09

Apprenticeship .813 .231 12.366 1 .000 2.254 1.433 3.54

On the job training 1.108 .423 6.872 1 .009 3.027 1.323 6.93

None .000 0.507

The results showed that the odds of having vocational training with certificate are 25% higher for

KMA when compared to Rural Areas (OR= 1.251). The odds of having professional or technical

training with certificate were eight times better in KMA when compared with rural areas (OR=

8.709). The odds of having apprenticeship training were two times better for KMA when

compared to Rural Areas (OR= 2.254). The odds of having on the job training were 3 times

better for KMA when compared to Rural Areas (OR= 3.027). The odds of having no training

was 51% higher for Rural Areas when compared to KMA (OR= 0.507).

The difference in the odds of having professional training with certificate, apprenticeship

training or no training are statistically significant for Rural Areas and KMA (p =0.000).

Table 9 .0 Cross tabulation of the R ural and KMA regions by Highest AcademicExamination Passed.

Regions

Total Rural

Areas KMA

Exam passed None Count 392 164 556

22 | P a g e



Rural Unemployment% within Exampassed

70.5% 29.5% 100.0%

% of Total 54.7% 22.9% 77.7%

Lessthan 3CXC

Count 41 25 66

% within Exampassed

62.1% 37.9% 100.0%

% of Total 5.7% 3.5% 9.2%

Morethan 3CXC

Count 52 27 79% within Exampassed

65.8% 34.2% 100.0%

% of Total 7.3% 3.8% 11.0%

Degree Count 2 13 15

% within Exampassed

13.3% 86.7% 100.0%

% of Total .3% 1.8% 2.1%


% within Exampassed

68.0% 32.0% 100.0%

% of Total 68.0% 32.0% 100.0%

Table 10 .0: Logistic regression of unemployment in rural areas compared with KMA byhighest academic examination passed

B S.E. Wald df Sig. Odds Ratio


Lower Upper

Less than 3 CXC .377 .270 1.943 1 .163 1.457 .858 2.475

23 | P a g e



Rural UnemploymentMore than 3 CXC .216 .255 .719 1 .397 1.241 .753 2.045

Degree 2.743 .765 12.851 1 .000 15.537 3.467 69.617

None .000 1.638

The results showed that the odds of having passed Less than 3 CXCs are 46% higher for KMA

when compared to Rural Areas (OR= 1.457). The odds of having passed more than 3 CXCs are

24% higher in KMA when compared to rural areas (OR= 1.241). The odds of having passed an

academic examination for a Degree is fifteen times higher for KMA when compared to Rural

Areas (OR=15.537). The odds of having passed no exam is 64% higher for Rural Areas when

compared to KMA (OR= 1.638).

The difference in the odds of having passed an academic examination for a degree or having

passed no examination is statistically significant for Rural Areas and KMA (p =0.000).

II. Conclusion and Recommendations

The study sought to investigate the likelihood of there being a difference in the education and

training levels of the unemployed respondents sampled based on their area of residence. The

results showed that difference in education and training were particularly acute with respect to

24 | P a g e



Rural Unemployment

KMA and Rural areas and less so with respect to Other Towns and Rural Areas. A review of the

statistically significant results showed that the odds of having passed an academic examination

for a Degree was fifteen (15) times better in KMA and seven (7) times better in Other Towns

when compared with Rural areas. The odds of having passed no examination 64% higher in rural

areas when compared with KMA and 34% higher in rural areas when compared to Other Towns.

The odds of having professional training was eight (8) times better in KMA and four (4) times

better in Other Towns when compared to Rural Areas. The odds of having apprenticeship

training is two (2) times better in KMA when compared to Rural Areas and 88% higher in Other

Towns when compared to rural areas. The odds of having no training is 51% higher in Rural

Areas when compared with KMA and 36% higher in rural areas when compared with Other

Towns.

It is possible, that the odds of the level of training received and the highest academic

examination passed for rural areas with respect to KMA is indicative of an uneven distribution of

resources as is reminiscent in the late Professor George Beckford’s theory of persistent poverty.

From a social policy perspective, this uneven distribution of resources would necessitate

increased level of social investment in the rural areas of Jamaica. This social investment should

not necessarily take the form of additional infrastructural resources (e.g. better roads which

would lower transportation cost, more educational and training institutions which would lower

overcrowding) more so capacity building initiative (e.g. remedial training to increase academic

proficiency or training in new areas ( as noted in Zilvere, 2002) , educational loans and grants to

buy uniform, food etc, parenting programmes that will help to orient parents on the value of

education and training and providing the requisite positive psycho-social environment). In

25 | P a g e



Rural Unemployment

addition, there is a need for the diversification of the educational and training options and the

types of employment opportunities available.

Bearing in mind financial limitation, social policy initiatives aimed at the diversification of the

educational and training options and employment opportunities should consider alternative usage

of natural resources such as eco-tourism, health tourism, more ecologically intensive agriculture

and the building of the professional and service delivery capacity in these areas.

III. B ibliography

Beckford, George W (1972): Persistent Poverty: Underdevelopment in Plantation. Economies of

the Third World: Oxford University Press

Benn, Dennis. The growth and development of political ideas in the Caribbean 1774-1983.

Kingston: Institute of Social and Economic Research, 1987.

Bourne PA, Eldemire-Shearer D, McGrowder D, Crawford T. Examining Health Status of

Women in Rural, Peri-urban and Urban Areas in Jamaica . North Am J Med Sci 2009;

1: 256-271.

Bullock, C. (2010). Agriculture, Rural Poverty & Public Policy. Retrieved on May 26, 2011 from

http://jamaica-gleaner.com/gleaner/20100711/focus/focus1.html

26 | P a g e





Rural Unemployment

Casassus J, Cusato S, Froemel J E, Palafox J C. (2002) First International ComparativeStudy of language, mathematics, and associated factors for students in the third andfourth years of primary school (two reports) Santiago, LLECE

Harrison, M. (1998). Living with the sugar legacy: International Policy Change and Local level

Impact in Rural Jamaica. In D. McGregor, Resource Sustainability and Caribbean

Development (pp. 232-253). Kingston: The Press University of the West Indies.

International Labour Organization: Resolution concerning statistics of the economically active

population, employment, unemployment and underemployment, adopted by the

Thirteenth International Conference of Labour Statisticians (October 1982); see page 4;

accessed May 26, 2011

Jamaica, Statistical Institute of. The Labour Force Survey. Kingston: Statistical Institute of

Jamaica, 2009.

Martinussen, John. Society, State & Market. London: Zed Books Ltd., 1997.

Mintz, Sidney. (1985). From Plantations to Peasantries in the Caribbean. In M. Sidney, & S.Price, Caribbean Contours (pp. 127-153). Baltimore: The John Hopkins University Press

Planning Institute of Jamaica (2009). Economic and social survey of Jamaica 2008. Kingston:

Planning Institute of Jamaica

Planning Institute of Jamaica & The Statistical Institute of Jamaica (2010). Jamaica Survey of

Living Conditions 2008. Kingston: Planning Institute of Jamaica & The Statistical

Institute of Jamaica.

Revenga, A (2002). "Unemployment, Poverty, and Social Exclusion in Central and Eastern

Europe," Chapter 29 in Bernard Funck and Lodovico Pizzati, eds., Labor, Employment,and Social Policies in the EU Enlargement Process, The World Bank, Washington, D.C.,

2002, 337-342.

Robotham, Don. "Social and Economic Policy: Starting Gates and End States." Kingston

University of the West Indies, 1995. 1-7.

Sandra W. Meditz and Dennis M. Hanratty, editors. Caribbean Islands: A Country Study.

Washington: GPO for the Library of Congress, 1987.

Zilvere, R (2002). "Searching for solutions to reduce social exclusion in Lativa" Chapter 30 in

Bernard Funck and Lodovico Pizzati, eds., Labor, Employment, and Social Policies in theEU Enlargement Process, The World Bank, Washington, D.C., 2002, 343-354.

http://www.ilo.org/public/english/bureau/stat/download/res/ecacpop.pdf







Documents

Rural Unemployment