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Young Farmers in Agriculture Sector of Turkey: Young Farmers Support Program

Authors:
  • Kırşehir Ahi Evran University, Agricultural Faculty

Abstract and Figures

Although Turkey's agricultural sector is important in terms of national economy, it faces some important structural problems such as decrease in human capital in the agricultural sector. In order to solve these problems, within the "National Agricultural Project", a policy instrument named "Support for Young Farmers Projects" (YFPS) was added to the support in 2016. The aim of this study was to evaluate the criteria used in the selection of the beneficiaries of young farmers' support within the scope of YFPS in Turkey. A survey was prepared to determine what features young farmers benefiting from project support have and the extent to which the selection criteria served the purposes of the support program. The survey was conducted in the TR 71 Region, which is at the center of Turkey, in June-August, 2017. A total of 248 young farmers (139 supported, and 109 non-selected farmers for support) were interviewed. The methodology used in this study was the Categorical Regression. The results showed that the applicants who benefited more from YFPS were in the following order: Female> married> those aged 18-30> people from rural areas with a population of 1,000 or less> those with education in agricultural production> the disabled / martyr's relatives / ghazi, and those from enterprises with an annual income of TL 10,000 or less. YFPS has breathed new life into agriculture by encouraging youths in rural areas, but this support has to be aimed at creating economically sustainable and viable enterprises.
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J. Agr. Sci. Tech. (2019) Vol. 21: 15-26
15
Young Farmers in Agriculture Sector of Turkey: Young
Farmers Support Program
M. Kan
1
*, F. Tosun2, A. Kan1, H. Gokhan Dogan1, I, Ucum2, and C. Solmaz2
ABSTRACT
Although Turkey's agricultural sector is important in terms of national economy, it faces
some important structural problems such as decrease in human capital in the agricultural
sector. In order to solve these problems, within the "National Agricultural Project", a
policy instrument named "Support for Young Farmers Projects" (YFPS) was added to
the support in 2016. The aim of this study was to evaluate the criteria used in the selection
of the beneficiaries of young farmers' support within the scope of YFPS in Turkey. A
survey was prepared to determine what features young farmers benefiting from project
support have and the extent to which the selection criteria served the purposes of the
support program. The survey was conducted in the TR 71 Region, which is at the center
of Turkey, in June-August, 2017. A total of 248 young farmers (139 supported, and 109
non-selected farmers for support) were interviewed. The methodology used in this study
was the Categorical Regression. The results showed that the applicants who benefited
more from YFPS were in the following order: Female> married> those aged 18-30>
people from rural areas with a population of 1,000 or less> those with education in
agricultural production> the disabled / martyr’s relatives / ghazi, and those from
enterprises with an annual income of TL 10,000 or less. YFPS has breathed new life into
agriculture by encouraging youths in rural areas, but this support has to be aimed at
creating economically sustainable and viable enterprises.
Keywords: Human capital, Rural areas, Rural development, Young farmers.
_____________________________________________________________________________
1
Department of Agricultural Economics, Agricultural Faculty, Ahi Evran University, Kırşehir, Turkey.
2 Agricultural Economic and Policy Development Institute, Ministry of Food, Agriculture, and Livestock,
Ankara, Turkey.
* Corresponding author; e-mail: mustafa.kan@ahievran.edu.tr
INTRODUCTION
Turkey has an important place among the
countries of the region in terms of plant and
animal production. In the last decade, the
contribution of Turkish agriculture to GDP
was 8%, and the share of agricultural
product exports in total exports was 10%.
The fact that the agricultural sector received
19.5% share in Turkey's employment in
2016 is another reason for the importance of
this sector in Turkey (TURKSTAT, 2017).
According to the World Bank statistics for
2016, 26.11% of the total population in
Turkey lives in rural areas (The World
Bank, 2017). It would not be wrong to say
that a large part of this population provided
their living from agriculture. Turkey is a
candidate country for European Union (EU)
and it was ranked the 1st among the
European Union countries and 8th in the
World for agricultural production value of
approximately 52.3 billion dollars, in 2016.
Agriculture is an important sector for
Turkey and it is in the first place in export
and production in the world for many
products.
Although the agricultural sector is
important for Turkey, it is a fact that it
cannot contribute to the economic
development at the desired level, especially
due to its structural problems (Yavuz, 2005;
Özertan, 2013; TOBB, 2013; Doğan et al.,
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__________________________________________________________________________ Kan et al.
16
2015; TİM, 2016). In addition to this,
economic problems such as input costs,
product prices, producers' prices are also
maintaining the update on the agriculture of
Turkey and among the problems that are
reported in every platform. In the 2013-2017
Strategic Plan prepared by the Ministry of
Food, Agriculture, and Livestock, five
strategic goals have been put forward in
overcoming these problems. These are listed
as "Agricultural Production and Supply
Security", "Food Reliability", "Plant Health,
Animal Health and Welfare", "Agricultural
Infrastructure and Rural Development" and
"Institutional Capacity Increase" (GTHB,
2013). It should be noted that the
harmonization process of the European
Union (EU) is also effective in
determination of policies and strategies
within the scope of the Strategic Plan.
In parallel with the determined strategies
to solve the problems of agriculture, Turkey
implements agricultural policy measures in
many areas. Within the scope of agricultural
policy measures implemented to reach
strategic targets, there are deficiency
payments, compensation payments,
livestock support (feed crops, artificial
insemination, milk premiums, disease free
livestock areas, beekeeping and fisheries),
product insurance support, rural
development and environmental protection
programs. Turkey created a new support
model entitled "National Agricultural
Project" at the end of 2016 in order to come
to a leading position in the region with its
competitiveness in agriculture, production
diversity, and standards. This project
consists of two main themes, namely, "Basin
Based Support Model" in plant production
and "Domestic Production Support Model in
Livestock Production”.
Nevertheless, apart from the problems that
appear, when we examine the problems of
agriculture sociologically, the aging of the
agriculture society in Turkey and the fact
that youngsters in rural areas are not seeing
the agriculture sector as an income
generating and prosperity sector are the
forefront problems. In general, Turkey's
population is aging and it is seen that this
aging is more in rural areas and agricultural
sector. Especially the rural-to-urban
migration and the changes in the statistic
because of the new law (see the influence of
the Metropolitan Act after 2012) show that
the rural population is decreasing both
proportionally and numerically. It can be
observed that with the reason of rural
migration, young people do not want to stay
in the countryside for long, resulting in a
population aging in agriculture. Er (2013)
stated that the young population search for
jobs outside the rural areas depends on such
factors as the rapid increase in the
unemployment rate in rural areas and the
complete profile of the unemployment
profile of young people. Additionally,
agriculture is not seen as an attractive
employment area by young people and the
employment potential of non-agricultural
sectors in rural areas is low. Also, the
growing services and industry sector attracts
low-skilled young population in the rural
area and negatively affects the young
population in agriculture (Arlı et al., 2014).
Approximately half of Turkey's population
is under age of 30 and this fact can be
regarded as a sign that new or different
employment opportunities are needed for the
young population. It is regarded as important
to provide conditions for employment of
young population in agriculture sector for
this need. The young population in rural
areas is away from agriculture for reasons
such as inadequate income in rural areas,
limited social opportunities in the villages,
fragmented or scarce land, and lack of
alternative job opportunities in rural areas.
This has also results as affecting the
demographic structure of the rural inhabitant
in the negative direction. It is stated that the
rapid depletion in agriculture today will
cause major problems in terms of food
production in the future (Doğanay and Alım,
2010). For this reason, agriculture should be
encouraged again, education and health
services should be restructured in rural areas
and social facilities should be developed.
Sustainability in agricultural production can
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Young Farmers in Turkey ___________________________________________________
17
only be achieved when the young population
is kept in agriculture.
In order to solve these existing problems, a
policy instrument called "Youth Farmer
Projects Support (YFPS)" was added to the
support in "National Agricultural Project" in
2016. Ministry of Food, Agriculture, and
Livestock has started to provide the YFPS
with a notification published in the Official
Gazette dated April 5, 2016 in the scope of
Rural Development Supports. According to
the notification, it is aimed to support
sustainable agriculture, support
entrepreneurship of young farmers, raise
income level, create alternative income
sources and support the projects for
agricultural production in the rural area that
will contribute to the employment of young
population in rural areas. In the scope of this
support, project-based support for the aging
of the young population, which meet
specific criteria for agriculture under the age
of 41, has begun. Initial support started in
2016 and this program was planned for 3
years in the first stage. Within this scope,
30.000 TL grants are given to young farmers
who meet the support criteria specified in
the following project subjects. Project topics
are (Official Gazette, 2016);
1. Animal production oriented:
a) Cattle, sheep, and goat breeding
projects,
b) Bee breeding and bee products
production projects,
c) Poultry and silkworm breeding
projects,
2. Plant production oriented:
a) Closed fruit garden plant projects,
b) Seedling, sapling, indoor and outdoor
ornamental plant growing projects,
c) Controlled greenhouse projects,
d) Edible cultivated mushroom production
projects,
3. For production, processing, storage
and packaging of medicinal and
aromatic plants with local products:
a) Projects on medicinal and aromatic
plant production, processing, storage
and packaging,
b) Projects on organic or good agricultural
practices on plant and animal
production, using geographical
indigenous gene sources,
c) Projects on the production of food with
geographical indication.
This project, which aims at keeping young
farmers in agriculture and deals with
agriculture, is an important policy argument
also aimed at preventing the aging of the
agricultural population in rural areas. With
the project call, 540,112 applications were
made in 2016 throughout Turkey, of whom
393,719 were accepted and 14,977 were
supported. This number reached 16,067 in
2017 (GTHB, 2017). Support will continue
in 2018 that is the third year of the project,
and no policy statement has been made for
the post yet.
This study aimed at a general evaluation of
YFPS, which started in 2016 and is ongoing
in 2017 and expected to be implemented in
2018 as well. In this context, attempts were
made to show which young farmer's profile
is supported and how the criteria in support
are effective at the time of selection by
conducting surveys with a total of 248
people benefiting from and not benefiting
from YFPS in the TR71 Region (Aksaray,
Kırıkkale, Kırşehir, Nevşehir and Niğde
districts) within the scope of Turkish
Statistical Region Units Classification 2
(TSRUC2)
MATERIALS AND METHODS
The study was carried out in May-
September 2017 in the 3 districts where the
YFPS was given the most within the TR71
region of Turkey (Aksaray, Kırıkkale,
Kırşehir, Nevşehir ve Niğde) within the
scope of the NUTS-2 classification. The
main material of the study is the data
obtained through a questionnaire survey
with 139 young farmers who were randomly
selected from a total of 453 people
benefiting from YFPS in the selected
provinces and 109 randomly selected
applicants who applied for YFPS but were
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18
Figure 1. The region in which the study was performed.
unable to benefit from the evaluation. The
region in which the work was performed is
shown in Figure 1.
The questionnaire forms of the study were
prepared within the scope of the project
"Determination of the parameters that could
be a criterion for young farmers' support
and the tendency of the young people to stay
in agriculture" and the evaluation criteria
specified in the YFPS were taken into
consideration in determining the questions.
In the study, Categorical Regression
Analysis (CATREG) was used in order to
determine the effectiveness of the selection
of the main criteria to be considered in the
evaluation of the individuals entitled to
benefit from the project and those who were
not (Gifi, 1996; Meulman and Heiser, 2004).
Categorical regression analysis based on
optimal scaling is a multivariate analysis
technique that can be used when the
dependent variable is categorical, with both
linear and nonlinear relationships between
variables (Cengiz, 2008).
In this analytical technique, the measured
data at nominal, ordinal, and numerical
measurement levels can be included in the
functioning of the analysis. The categorical
variables are digitized in order to reflect the
characteristics of the original categories. The
criterion to obtain optimal linear regression
equations is considered when the digitization
process is performed. In other words,
various non-linear transformations are used
to find the most appropriate regression
model. Mentioned transformation is
designed to maximize the relationship
between each of the independent variables
and the dependent variable (Meulman and
Heiser, 2004). As a consequence,
Categorical Regression is a multiple
regression model applied to transformed
variables with Optimal Scaling. The loss
function used in the functioning of the
model is given as follows:
(1)
Where, J is the number of independent
variable, y is dependent variable, xj is
independent variables,
j is regression
coefficients,
r and
j are the transformation
functions for dependent and independent
variables, respectively, and e is the error
term (Kooij et al., 2006).
Each variable included in the analysis can
be represented by the matrix Gj of size Nxkj.
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Young Farmers in Turkey ___________________________________________________
19
Table 1. Discussed dependent and independent variables and their properties in the scope of CATREG.
Variables
Variable categories
Gender
Male
Woman
Marital status
Married
Single
Age
Age 18-30
Age 31-40
Residence population
1,000 and below
1,001-10,000
10,001 and over
Distance to city center
Closer than10 Km
Between 10-40 Km
Far from 40 Km
Education level
Literacy Secondary school
High school and over
Training in agricultural production
Not trained
Trained
Status of being disabled/Martyr's
relatives/Ghazi
No
Yes
Annual operating income of business
10,000 TL and below
Over 10,000 TL
Support redemption condition
Not used
Used
N, which is the number of rows of the
indicator matrix, represents the number of
units in the analysis and kj, the column
number, represents the category number of
variable j. The indicator matrix Gj is a
matrix of values 0 and 1. Related line units
to which they belong; If j is in the category
of the variable, then the column-alignment
takes the value 1, while the other column's
value is 0. Thus each row consists of values
0 and 1, and when there is no missing
observation, the sum of each row in the
matrix is 1.
Similarly, for each variable included in the
analysis, the vector of yj category
digitizations (kjx1 dimensional) can be
generated. With the help of these defined
indicator matrices and the category
digitization vectors, the loss function can be
written as follows:
(2)
In the operation of the analysis, this loss
function is minimized by Alternating Least
Squares (ALS) algorithm. In the steps of the
algorithm, digitizations are made and the
regression model coefficients are estimated.
Later on, the value of the lost function is
calculated. The iterations continue until the
contraction in the loss function becomes
meaningless. When the loss function
becomes minimum, the iterations are
stopped. In this way, optimal category
digitizations and model coefficients are
obtained (Cengiz, 2008).
CATREG analysis does not work as linear
regression because transformations at
variable levels are not linear. In CATREG
analysis, the variables are digitized to reflect
the characteristics of the original categories,
and these quantified variables are included
in the regression model as numerical
variables. CATREG coincides with linear
regression analysis by transforming
categorical variables into numeric with the
help of transformations (Xu et al., 2010).
ALS (Alternating Least Square)
Logarithm was used in the quantification of
the variables considered under CATREG
scope. The scale types of the variables
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20
included in the scope of the analysis are
mostly nominal and ordinal. The variables
and their characteristics discussed in the
CATREG framework are presented in Table
1. The variables discussed in Table 1 include
9 out of 13 criteria which are the scoring
criteria within the scope of YFPS.
RESULTS AND DISCUSSION
The initial stage of development is the
development of human and social capital.
When the relationship between development
and human capital is examined, human
capital has a close relationship with the
possibilities of health and education (Ateş,
1998), and since the late 1980s, human
capital has begun to be regarded as a
qualified workforce with a good education
level, and economic growth has begun to be
regarded as a driving force (Nesterova and
Sabirianova, 1998). The concept of human
capital is used to express the whole of
concepts such as knowledge, skills, abilities,
health status, place of social relations, and
level of education that a person or society
has. This concept constitutes the basic
source of economic growth (Kar and Ağır,
2003) and has emerged as an alternative to
the physical capital in industrial society and
has gained importance as a development
strategy for different countries. Human
capital, which is expressed as the personnel
infrastructure of the information society, is
in essence a concept that defines specialized
people (Özyakışır, 2011).
One of the most important problems in
rural areas is aging and young people are
inclined towards urban areas more than rural
areas, especially non-agricultural sectors. It
is reported that this is not only a problem in
Turkey, but also in many other countries
(Aggelopoulos and Arabatsiz, 2010; EC,
2013; ECA, 2017; Nag et al., 2018). In this
context, the young farmer support program
is an important supporting argument for the
Common Agricultural Policy, especially in
order to ensure that young farmers mainly in
the EU stay in agriculture, to support new
business establishments, or to encourage
more efficient production. In Turkey, the
project-focused Young Farmer Project
Support started in 2016, for the first time, to
aim directly at young farmers and to
encourage them to stay in agriculture.
Criteria to be taken into consideration in
the selection of young farmers to be
supported under the scope of YFPS have
been stated in the Communiqué on
Supporting Young Farmers' Projects under
the Rural Development Supports No
2016/16” published in Official Gazette No.
29675 dated 05 April 2016. The project
supports were distributed with the
evaluations made among the highest scoring
points according to the criteria specified in
Communiqué E-4. Accordingly, the criteria
such as age, gender, educational status,
marital status, living place population,
distance from the center to the living place,
ownership status of the project site, status of
being disabled / martyr’s relatives / ghazi,
and project theme are taken into
consideration.
The determination of the young farmers to
be supported under the YFPS has been made
through the Evaluation Commissions
established by Provincial and District Food
Agriculture and Livestock Provincial
Directorates, which constitute the provincial
organization of the Ministry of Food,
Agriculture and Livestock. In addition to the
criteria set out in the Communiqué
published in these evaluations, the
commission was also given the authority to
award a score of 10 points. Categorical
Regression Analysis was conducted to find
out which criterions were more prevalent in
the evaluations made by the commission and
to find out how these criteria served the
intended purpose.
When the installed model was tested; the
model established as a result of categorical
regression was found statistically significant
(F= 8.00; P= 0.00). The model's multiple R-
value and R2 value was calculated as 0.52
and 0.24, respectively. These results led to
the conclusion that YFPS selection criteria,
which are explained explanatory variables,
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Young Farmers in Turkey ___________________________________________________
21
Table 2. Model summary statistics.
Sum of squares
SD
Average of squares
F
P
Regression
67.38
11
6.13
8.00
0.00
Error
180.62
236
0.77
Total
248.00
247
Multiple R2: 0.52 R2: 0.27 Corrected R2: 0.24
Table 3. CATREG results showing some of the evaluation criteria of the Young Farmer Project Support.
Variables
Variable categories
Frequency
Digitization
value
β
coefficient
Coefficient
of variables
categories
Variable level
Gender
Male
98
-1.24
0.42***
-0.52
Classification
Woman
150
0.81
0.34
Marital status
Married
205
0.46
0.12*
0.05
Classification
Single
43
-2.18
-0.25
Age
Age of 18-30
139
-0.89
-0.10*
0.09
Grading
Age of 31-40
100
1.13
-0.11
Residence population
1,000 and below
142
-0.27
-0.21***
0.06
Grading
1,001-10,000
101
0.03
-0.01
10,001 and over
5
6.90
-1.46
Distance to city center
Closer than10 Km
26
-2.20
-0.07
0.16
Grading
Between 10-40 Km
162
0.17
-0.01
Far from 40 Km
60
1.40
-0.10
Education level
Literacy
Secondary school
174
-0.65
-0.03
0.02
Grading
High school and
over
74
1.53
-0.04
Training on
agricultural production
Not trained
182
-0.60
0.08*
-0.05
Classification
Trained
66
1.66
0.13
Status of being
disabled/Martyr's
relatives/Ghazi
No
218
-0.37
0.08*
-0.03
Classification
Yes
30
2.70
0.22
Annual operating
oncome of business
10,000 TL and
below
131
-0.95
-0.12*
0.11
Grading
Over 10,000 TL
117
1.06
-0.12
Support redemption
condition
Not used
109
-1.13
Classification
Used
139
0.89
* Statistically significant at the 90% confidence level; ** Statistically significant at the 95% confidence level, ***
Statistically significant at the 99% confidence level.
could account for about 24% of the selection
result (Table2).
When the contribution of the independent
variables to the model is examined; it is seen
that the variables such as gender, marital
status, age, residence population, education
about agricultural production, being
disabled/martyr’s relatives/ghazi status and
annual operating income variables have a
meaningful effect on determining the
recipients of YFPS (P< 0.10). It is seen that
the distance of residence to the
provincial/district center and the educational
status variables have no meaningful effect
on determining the YFPS recipients (P>
0.10) (Table 3).
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22
The coefficient of the effect can be
calculated as a result of multiplying the
digitized values of the variable categories
obtained by optimal scaling by β
coefficients obtained as categorical
regression (Cengiz, 2008). The effect
coefficients show how the independent
variable categories are related to the
dependent variable. High coefficient of
effect indicates that the level of the
relevant variable is in the same direction
(positive) as the dependent variable. In
Table 3, the effects of statistically
significant 7 variables’ coefficients to the
model as a result of categorical regression
have been examined.
According to Table 3:
In terms of gender variable; it is seen
that the rate of selection of female
(0.34) individuals to YFPS is higher
than that of male (-0.52) individuals.
In terms of marital status variable;
married (0.05) individuals were
selected to have higher YFPS while
single individuals (-0.25) were
inversely related to being selected to
YFPS.
In terms of age variable; it is seen that
individuals aged 18-30 years (0.09)
were higher in YFPS and those aged
between 31-40 years (-0.11) showed
opposite behavior.
Regarding the residence population
variable; individuals from a population
of 1000 or less (0.06) were selected to
have higher YFPSs whereas those
living in higher populations (-0.01 and
-1.46) were found to have an inverse
relationship with YFPSs.
From the point of view of the training
in agricultural production variable; the
individuals with this training (0.13)
were selected to have higher YFPS;
whereas those who did not have this
education (-0.05) were inversely
related to the selection of YFPS.
In terms of being disabled/martyr's
relative/ghazi variable; the victimized
individuals in this regard (0.22) were
selected at a higher rate while the
individuals with no victim (-0.03)
were in an inverse relation to be
selected for YFPS.
In terms of annual operating income
variable; individuals who were
applying from business with an annual
income of TL 10,000 or less (0.11)
were selected at a higher rate while
individuals who are applying from
business with an annual income of TL
10,000 and above (-0.12) were in an
inverse relationship with this issue.
Among the selection criteria, project
issues are of special importance.
Between the applications made
according to the project subjects stated
in the communiqué, it appears that the
cattle and sheep breeding projects are
seen to constitute the majority. However,
it is seen that the proportionally less
applied topics during the support phase
appeared to be more foreground (Figure
2). Intensification in the certain project
subjects, increasing the chances of
young farmers resorting to the project
subjects that were less accumulated in
the selection, while other farmers did not
qualify, even though they provided the
criteria. Especially during the selection,
attention to the distribution according to
the project subjects in the region has
been influential in giving the election
score by the commission.
By considering the given criteria, the
general situation of young farmers who
were selected and not selected is given in
Table 4. In the Chi-square analysis,
when the table was analyzed, support
utilization status and the criteria of
gender, marital status, education status,
being disabled/martyr’s relatives/ghazi
status of the young farmer, population of
the residence and distance to the city
center of the residence were determined
to be statistically significant at different
levels of importance.
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Young Farmers in Turkey ___________________________________________________
23
Figure 2. Distribution of the projects submitted and supported by the themes (GTHB, 2017).
Table 4. The general situation of young farmers who were selected and not selected.
Factors
Get
supported (%)
Not
supported (%)
Average
(%)
Chi
square (χ2)
Economic and demographic factors
Age
Between 18-30
59.71
51.38
56.05
1.72
Between 31-40
40.29
48.62
43.95
Gender
Male
20.86
63.30
39.52
46.04***
Female
79.14
36.70
60.48
Education level
Literacy Secondary
school
74.82
64.22
70.16
3.28*
High school and over
25.18
35.78
29.84
Marital status
Married
90.65
72.48
82.66
14.07***
Single
9.35
27.52
17.34
Training on
Agricultural
Production
Not trained
72.66
74.31
73.39
0.09
Trained
27.34
25.69
26.61
Status of being
Disabled/ Martyr's
relatives / Ghazi
No
84.89
91.74
87.90
2.70*
Yes
15.11
8.26
12.10
Annual Operating
Income
10,000 TL and below
52.52
53.21
52.82
0.01
Over 10,000 TL
47.48
46.79
47.18
Social Security Status
No social security
43.88
45.87
44.76
0.10
Have social security
56.12
54.13
55.24
Geographical
factors
Population of
Residence
1,000 and below
64.03
48.62
57.26
10.67**
1,001-10,000
35.97
46.79
40.73
10,001 and over
0.00
4.59
2.02
Distance to city center
Closer than 10 Km
9.35
11.93
10.48
6.45**
Between 10-40 Km
71.94
56.88
65.32
Far from 40 Km
18.71
31.19
24.19
* It is statistically significant at the 90% confidence level; ** It is statistically significant at the 95%
confidence level, *** It is statistically significant at the 99% confidence level.
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__________________________________________________________________________ Kan et al.
24
CONCLUSIONS
In this study, it was determined how the
criteria determined in the selections were
effective and the general characteristics of
the farmers benefiting from the support
during the assessment of the application of
YFPS, which started in 2016. As conclusion,
it can be said that the project title, the
property status of the subject for investment,
and the commission evaluation note, which
were not included in the model, might have
played an important role in determining the
farmers who will benefit from YFPS. In this
support, which is preoccupied with the
support of young people and women of low
income who are in agricultural production or
want to be found, the selection criteria were
effective but insufficient to make this
distinction.
In particular, there are structural
differences between the program for young
farmers in EU countries and the program for
implementation in Turkey. At the beginning
of these differences, it appears that such
supports in the EU countries are supportive
(not entirely welcoming) to young people
seeking new business or economically
sustainable. Although support for production
by young farmers in low-income families
seems logical, the fact that the issues
concerning the lack of continuity of
production, the problem of poor young
people who have benefited from cattle
livestock project support (procurement of
the cattles on non-production age, because
of that they suffered on feeding of the cattles
in terms of financially, and the
appropriateness of selected animal breeds
are the most important obstacles to the
success of the project.
The fact that there are uncertainties about
the definition of farmers in Turkey and the
fact that farming is not fully found as a
profession lead to some problems in the
determination of target population. In the
context of support, women are expected to
be more prominent in the selections, and
thus giving young women an advantage in
scoring in the selection can be seen as a
positive discrimination. However, another
finding is that the outcome of this situation
does not occur at the desired level. It has
been seen that many female farmers who
have benefited from the support, or who are
in the application for the support, are in a
position to assist their husband instead of
taking direct responsibility for agricultural
production.
As a result, when the selection criteria of
YFPS are evaluated in terms of the
magnitudes of the effect coefficients, it is
seen that applicants who benefited more
from YFPS were in the following order:
Female> married> age between 18-30>
people from residence with a population of
1000 or less> those who have an education
in agricultural production> victims of being
disabled/martyr’s relatives/ghazi and from
enterprises with an annual income of TL
10,000 or less. It is seen that Young Farmer
Project Support has added vitality to the
rural area by the enthusiastic youth of
agricultural communities. However, these
supports must be directed at creating an
economically sustainable business. Selection
criteria and evaluation criteria should
consider project issues, regional structures,
and young entrepreneurs should be
supported in the form of credit-supported
grant schemes rather than direct grants.
Increasing the quality of human capital in
agriculture should be a priority, distributed
resources must be monitored, and impact
assessment should be done.
ACKNOWLEDGEMENTS
The data of the study was compiled from the
project “Genç Çiftçi Desteklemelerine Kriter
Olabilecek Parametrelerin ve Gençlerin
Tarımda Kalma Eğilimlerinin Belirlenmesi
(TR71 (Kırıkkale, Aksaray, Niğde, Nevşehir,
Kırşehir) Bölgesi)- Determination of the
Parameters Being Able to a Criterion for
Supporting Young Farmers and the
Tendency of Young People to Stay in
Agriculture-TR71 Region” supported by the
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Young Farmers in Turkey ___________________________________________________
25
Ministry of Food, Agriculture, and
Livestock in Turkey.
REFERENCES
1. Aggelopoulos, S. and Arabatsiz, G. 2010.
European Union Young Farmers Program: A
Greek Case Study. New Medit., N9(2): 50-
55.
2. Arlı, R., Balcı, M. ve Abay, C. 2014.
Gençlerin Kırsalda Çiftçilik Yapma
Eğilimleri: Akhisar İlçesi Örneği. Ulusal
Aile Çifçiliği Sempozyumu 30-31 Ekim
2014, Ankara. (in Turkish)
3. Ateş, S. 1998. Yeni İçsel Büyüme Teorileri
ve Türkiye Ekonomisinin Büyüme
Dinamiklerinin Analizi. Doktora Tezi,
Sosyal Bilimler Enstitüsü, Çukurova
Üniversitesi, Adana.
4. Cengiz, D. 2008. Kategorik Regresyon
Analizi ile Öğrencilerin Benlik Algılarını
Etkileyen Özelliklerin Belirlenmesi Öneri
Dergisi, 8(29): 193-198. (in Turkish)
5. Doğan, Z., Arslan, S. ve Berkman, A. N.
2015. Türkiye’de Tarım Sektörünün İktisadi
Gelişimi ve Sorunları: Tarihsel Bir Bakış.
Niğde Üniversitesi İktisadi ve İdari Bilimler
Fakültesi Dergisi, 8 (1): 29-41. (in Turkish)
6. Doğanay S. ve Alım M. 2010. Türkiye’de
Kırsal Nüfusun Şehir Algısı Üzerine Bir
Araştırma: Yeşilyurt Köyü (Trabzon). Doğu
Coğrafya Dergisi, 15 (23): 171-184. (in
Turkish).
7. EC (European Commission). 2013.
Overview of CAP Reform 2014-2020.
Agricultural Policy Perspectives Brief, No:
5, December 2013. Available at:
https://ec.europa.eu/agriculture/sites/agricult
ure/files/policy-perspectives/policy-
briefs/05_en.pdf.
8. ECA (European Court of Auditors). 2017.
EU Support to Young Farmers Should Be
Better Targeted to Foster Effective
Generational Renewal. No: 10. Available at:
www.eca.europa.eu/en/Pages/DocItem.aspx
?did=41529, (23 Oct. 2017).
9. Er, C. 2013. Tarım Gençlere Sevdirilmeli.
Hasad Dergisi 114-126.
10. Gifi, A. 1996. Non-Linear Multivariate
Analysis. John Willey & Sons Ltd Press,
Chichester.
11. GTHB (Gıda Tarım ve Hayvancılık
Bakanlığı). 2013. Gıda Tarım ve
Hayvancılık Bakanlığı Stratejik Plan 2013-
2017. (in Turkish) Available at
https://www.tarim.gov.tr/SGB/Belgeler/Strat
ejik%20Plan%202013-2017.pdf
12. GTHB (Gıda Tarım ve Hayvancılık
Bakanlığı). 2017. Genç Çiftçi Projesi
Desteği İstatistiki Veriler (Yayınlanmamış).
(in Turkish).
13. Kar, M. ve Ağır, H. 2003. Türkiye’de Beşeri
Sermaye ve Ekonomik Büyüme: Nedensellik
Testi. II. Ulusal Bilgi, Ekonomi ve Yönetm
Kongresi Bildiriler Kitabı, İzmir, SS.181-
190. (in Turkish).
14. Kooij, A. J., Van Der Meulman, J. J. and
Heiser, W. 2006. Local Minima in
Categorical Multiple Regression. Comput.
Stat. Data Analysis, 50(2): 446- 462.
15. Meulman, J. and Heiser, W. 2004. SPSS
Categories 13.0. SPSS, Inc., Chicago.
16. Nag, A., Kumar Jha., S., Mohammad, A.,
Maiti, S., Gupta, J., Gosain, D. K., Datta, K.
K. and Mohanty, T. K. 2018. Predictive
Factors Affecting Indian Rural Farm
Youths’ Decisions to Stay in or Leave
Agriculture Sector. J. Agr. Sci. Tech.,
20(2):221-234.
17. Nesterova, V. D. and Sabirianova, Z. K.
1998. Investment in Human Capital under
Economic Transformation in Russia. EERC
Working Paper Series, No: 99/04
18. Özertan, G. 2013. Türkiye Tarım
Sektörü’nde Yapısal Dönüşüm ve Teknoloji
Kullanımının Rolü Researc NO: EC 2013-1,
Boğaziçi Üniversitesi Ekonomi Bölümü. (in
Turkish) Available at:
http://www.econ.boun.edu.tr/public_html/Re
PEc/pdf/201301.pdf
19. Özyakışır, D. 2011. Beşeri Sermayenin
Ekonomik Kalkınma Sürecindeki Rolü:
Teorik Bir Değerlendirme (in Turkish).
Girişimcilik ve Kalkınma Dergisi, 6(1): 46-
71.
20. Resmi Gazete (Official Gazette). 2016.
Kırsal Kalkınma Destekleri Kapsamında
Genç Çiftçi Projelerinin Desteklenmesi
Hakkında Tebliğ (Tebliğ No: 2016/16). (in
Turkish),
http://www.resmigazete.gov.tr/eskiler/2016/
04/20160405-2.htm
21. The World Bank. 2017. Rural Population
(% of Total Population). Available at
https://data.worldbank.org/indicator/SP.RU
R.TOTL.ZS?locations=TR
22. TİM (Türkiye İhracatçılar Meclisi). 2016.
Tarım Raporu. (in Turkish) Available at
Downloaded from jast.modares.ac.ir at 12:02 IRST on Sunday December 30th 2018
__________________________________________________________________________ Kan et al.
26
www.tim.org.tr/files/downloads/Raporlar/Ta
rim_Raporu_2017.pdf
23. TOBB (Türkiye Odalar ve Borsalar Birliği).
2013. Türkiye Tarım Sektörü Raporu. (in
Turkish) Available at
https://www.tobb.org.tr/Documents/yayinlar
/2014/turkiye_tarim_meclisi_sektor_raporu_
2013_int.pdf
24. TURKSTAT. 2017. Different Statistical
Databases. Available at
http://www.turkstat.gov.tr/Start.do
25. Xu, J., Danny, H. and Capretz, L.F. 2010.
Building an OSS Quality Estimation Model
with CATREG. IJCSE, 2(6); 1952- 1958.
26. Yavuz, F., 2005. Türkiye’de Tarım. Tarım
ve Köy İşleri Bakanlığı Yayınları, Ankara.
(in Turkish).




"
"""YFPS

 YFPS              

TR 71 

  Categorical Regression
YFPS< <
<<
<ghazi
       YFPS         
                

Downloaded from jast.modares.ac.ir at 12:02 IRST on Sunday December 30th 2018
... In order to prevent the negative effects of a considerable loss of the most dynamic part of the rural workforce, agriculture and rural development policies and programs must provide young people with concrete and viable opportunities in their rural areas of origin to contribute to their development [17,21,23,5,10,16]. There is a diverse range of interventions to address rural youth migration, reflecting its many root causes. ...
... A nation's economic growth directly impacts all elements that are directly or indirectly related to the economy (Khan et al., 2020). The agriculture industry is directly related to the economy, and farmers constitute the agriculture sector's backbone (Humphries et al., 2019;Kan et al., 2019). Increasing their income solves the problems plaguing farmers, rural areas, and peasants. ...
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Due to its vital role in economic development, the agriculture sector has recently garnered global attention. To increase the income of the agriculture sector, the agricultural finance institution and government support are required. Consequently, this study examines the effect of agricultural credits supplied by micro-financial institutions, the profitability of agribusiness microfinance organizations, government subsidies, government agricultural loans, and economic growth on the income of Indonesian farmers. From 1991 to 2020, secondary sources such as central bank databases and World Development Indicators (WDI) were used to collect the study's secondary data. The autoregressive distributed lag (ARDL) method was utilized to examine the understudy structures. In Indonesia, agricultural credits, the profitability of agribusiness microfinance institutions, government subsidies, government agricultural loans, and economic growth were found to have a strong and positive relationship with farmers' income. Using government and micro�financial institutions to enhance farmers' incomes, the study aids policymakers in formulating relevant policies.
... Within the Young Farmer Grant Support Program (YFGP) framework, selections were made every year within the framework of specific criteria in determining the young farmers who will benefit from the grant support. Kan et al. (2019) evaluated the selection criteria of young farmers within the scope of YFGP in their study in the TR71 Region in Turkiye, which includes Kırıkkale province. As a result of the study, they stated that respectively; the people that are female, married, between the ages of 18-30, applying from settlements with a population of 1000 or less, having an education in agricultural production, who have a disability/being a relative of a martyr/veteran, and an annual income of 10.000 TL or less, benefited from this support at a higher rate. ...
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This study aimed to reveal the situation of young women farmers (YWFs) who benefited from cattle farming support for three years in Kırıkkale, one of the provinces where the study was carried out. In Kırıkkale province, 397 young farmers were supported and 250 of them were YWFs. The projects with the highest grant support were cattle farming projects, and they constituted 62.22% of the projects (247 units). The rate of YWF who benefited from cattle farming support for three years was higher than young men farmers (YMF) and was determined as 59.51%. In this study, face-to-face survey questionnaires were filled in the 2020 year with 36 YWFs and 36 YMFs. As a result of the study, it was determined that YMFs have more experience in cattle breeding than YWFs. It is seen that especially YWFs are married and their families have high non-agricultural income; their husbands support especially YWFs at the application stage. 52.78% of YWFs and 69.44% of YMFs stated that they want to expand their farms with the given support. As a result of the study, it was determined that there was a significant increase in the number of animals after the given support to the young farmers, and it was revealed that the most important problem of the young farmers was that they had financial difficulties in the supply of production inputs. It is seen that this project, which has both social and economic aspects, encourages YWFs to take more part in agricultural activities. However, it is important to determine more effective criteria at the selection stage, follow up and supervise the beneficiaries of the incentives both during and after the project, and support the successful ones to grow their farms.
... ment results since the early 2000s (World Bank, 2017). The number of people living and employed in rural areas of Turkey has been declining since 2000, both in absolute and relative terms (Kan et al., 2019). As a result of legislative changes in 2013 (Law No. 6360), which redefined rural areas and classified villages as neighborhoods of municipalities, exact figures for the rural population are unknown (Republic of Turkey Ministry of Development, 2019). ...
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This article explores the potential of alternative food networks (AFNs) for food security and resili­ence as COVID-19 has raised challenges to the global food supply chain. Pandemic-induced dis­ruptions to conventional food production, distri­bution, and consumption networks have revealed problems with the global food system and have drawn attention to the re-localization and regional­ization of food systems. Lockdown and mobility restrictions have also disrupted the availability, quality, and stability of food. We evaluate how AFNs have responded to these challenges in a non-western context through a case-study ap­proach informed by participant observation and semistructured interviews. After examining the multiple factors that have been critical to the emergence and expansion of AFNs in Turkey since the mid-2000s, we argue that these food distribu­tion networks have aimed to address food security, environmental sustainability, and farmer liveli­hoods in complementary ways. We provide a time­line of state-led measures in response to COVID-19 in Turkey as we consider their impacts on food distribution systems and access in urban areas. We then compare two AFNs: a food community work­ing within a participatory guarantee system, and a consumer cooperative that connects producers and consumers in urban areas. Although the two AFNs faced initial challenges due to disruptions in deliv­ery services and lockdowns, they have been able to continue their services and address increasing de­mand. They also provided special solidarity pack­ages for those adversely affected by the economic impacts of COVID-19. By building on the existing networks and relationships of trust between con­sumers and producers, and the capacity and will­ingness of producers to adapt to the new regulatory environment, the two AFNs have been able to continue their activities and start new initiatives.
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This study aimed to assess the prospects of rural micro, small and medium enterprises (MSMEs) in Punjab, Pakistan. A multistage mixed method approach was opted to conduct the study in three districts of central Punjab, Pakistan. In stage I, seminars / workshops were conducted in six villages. Innovative ideas were discussed with the farmers. In stage-II, data were collected from 300 respondents of 12 villages. Data were analyzed using both the quantitative and qualitative methods. More than 75% of the farmers were willing to start a small scale agriculture based business. Young farmers were more inclined (over 70%) for rural entrepreneurship but, less than 50% of them had any sort of business experience and financial power. Only 20% of them knew that loan facilities are available for small scale businesses. Regarding the training facilities to start and manage small scale business, 40% perceived that such facilities were available. The youth were uncertain whether the dependence on five major crops will sustain the future family requirements or not. Similarly, they were uncertain about the functioning of the output markets in order to support the productivity of rural enterprises, implying that the markets are not well established. From the results, it was concluded that the prospects of rural MSME culture in Punjab, Pakistan are bright and it can be achieved by improving the training facilities, easy credit availability and motivating rural youth.
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Kırsal alanlardaki kalkınma sürecine gençlerin dâhil edilmesi girişimleri uzun yıllardır var olmasına rağmen, kırsal alanlarda yaşayan gençlerin yaşadıkları yerler ile ilgili uğraştıkları ekonomik faaliyetler ve kırsal kalkınmaya yönelik görüşleri yeterince sorgulanmamıştır. Bugün dünya nüfusunun önemli bir kısmını gençler oluşturmaktadır. Türkiye de genç nüfusa sahip bir ülkedir. Genç nüfusun ülkelerin gelişmesinde çok büyük öneme sahip olmasının yanı sıra iyi eğitilmeleri, istihdam olanakları ve beklentilerine cevap verilmesi önemli bir unsurdur. Bu çalışmaya konu olan Burdur ili Ağlasun ilçesi tarım ve hayvancılığın başlıca geçim kaynağı olduğu, turizmin ise yörenin zengin potansiyeli ile üçüncü bir sektör olarak ortaya çıktığı gelişim yerlerinden biridir. Bu çalışmada Burdur ili Ağlasun ilçesinde ikamet eden gençlerin yaşadıkları coğrafyada üretim faaliyetlerine ve kalkınmaya hangi alanda ve nasıl baktıklarını ortaya koymak amaçlanmıştır. Bu bağlamda Ağlasun’da ikamet eden 18-25 yaş arasındaki gençlerden ailesi tarım ve hayvancılık ile uğraşan ve kendisi turizm alanında deneyimi olan 10 genç ile kırsal kalkınmaya yönelik görüşlerinin belirlenmesi amacıyla görüşmeler yapılmıştır. Çalışmada nitel araştırma yaklaşımlarından fenemonolojik araştırma deseni tercih edilmiştir. Fenemonolojik araştırmada bireylerin deneyimleri önemli olduğu için fenemone yönelik tecrübeyi yaşamış kişiler örneklemi oluşturmalıdır. Buradan hareketle araştırma kapsamında amaçlı örnekleme kullanılmıştır. Bulgular Ağlasunlu gençlerin tarım, hayvancılık ve turizm alanlarındaki deneyimleri, hazır bulunuşlukları, sorunları, beklentileri ve önerilerini ortaya koymaktadır. Veriler araştırmacılar tarafından hazırlanmış olan yarı yapılandırılmış görüşme formu ile toplanmıştır. Form demografik bilgiler ile Ağlasunlu gençlerin tarım, hayvancılık ve turizm alanlarındaki kırsal kalkınmaya yönelik görüşleri olmak üzere iki kısımdan oluşmaktadır. Görüşme formunda tarım, hayvancılık ve turizm alanlarındaki kırsal kalkınmaya yönelik görüşlerin her biri sorunlar, beklentiler ve öneriler olmak üzere üç başlık altında toplanmıştır.
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Çalışma, TR61 Bölgesinde üreticilerin Genç Çiftçi Projesi desteklerinden yaralanmasını etkileyen faktörlerin belirlenmesi, genç çiftçilerin ve işletmelerinin özelliklerinin ortaya konulması amacıyla yapılmıştır. Çalışmanın hedef kitlesini destekten yararlanmış üreticiler ile yararlanmamış üreticiler oluşturmaktadır. Çalışmanın materyali, bu destekten yararlanan üreticilerden örnekleme yoluyla seçilenler 72 üretici ve karşıt grup olarak aynı yaş grubundaki 72 üretici ile yüz yüze yapılan anketlerden elde edilen verilerden oluşmaktadır. Araştırmada destekten yararlanan ve yaralanmayan üreticilerin ve sahip oldukları işletmelerin özellikleri tanımlayıcı parametreler (minimum, maksimum, ortalama değerler, yüzde oranlar) ile ortaya koyulmuştur. Destekten yararlanan ve yararlanmayan üretici grupları arasındaki farklılıkların tespitinde kesikli verilerde Ki-kare testi, normal dağılım göstermeyen sürekli verilerde Mann–Whitney U testi kullanılmıştır. Destek almayı etkileyen faktörlerin belirlenmesinde İkili Lojistik Regresyon analizi kullanılmıştır. TR61 Bölgesinde, üreticilerin cinsiyet, medeni durum, tarımsal örgüte üye olma durumu ve tarım dışı gelir sahipliğinin, genç çiftçi desteklerinden yararlanmada etkili olduğu belirlenmiştir. Tarım ve Orman Bakanlığı tarafından genç çiftçilere verilen desteklemeler büyük önem arz etmektedir. Genç çiftçi destekleri alana özel çeşitlendirilerek devamlılığı sağlanmalıdır. Genç çiftçi desteğinden yararlanmış olan üreticilerin yaptıkları faaliyetleri geliştirmelerine yönelik eğitimler, genç çiftçileri bir araya getirebilecek farklı örgütlenme modellerinin geliştirilmesi, pazara ulaşmada kolaylık sağlayacak öncelikler, dijital pazarlama yöntemlerinin yaygınlaştırılması gibi ek destekler de verilen genç çiftçi desteğinin etkinliğini artıracaktır.
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Open Source Software (OSS) has been a popular form in software development. In this paper, we use statistical approaches to derive OSS quality estimation models. Our objective is to build estimation models for the number of defects with metrics at project levels. First CATREG (Categorical regression with optimal scaling) is used to obtain quantifications of the qualitative variables. Then the independent variables are validated using the stepwise linear regression. The process is repeated to acquire optimal quantifications and final regression formula. This modeling process is performed based on data from the OSS communities and is proved to be practically valuable.
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Agriculture has been facing an increasing problem, worldwide, on account of farmers quitting agriculture; and India is no exception to it. In view of this, a study was undertaken to find out the factors predicting future decision(s) of rural farm youth, hailing from Eastern States of India, regarding ‘Whether or not to remain engaged in the agriculture sector’. The data were collected through personal interview with 120 rural farm youth. The results showed that 41.67 per cent of the rural farm youth would leave farming in the future. Binomial Logit Model indicated that the factors like land-holding, entry to farming, attitude towards dairying and crop farming were significant, as far as decision on ‘quitting the farming in the near future’ was concerned. Apart from this, ensuring the ‘Food Security for the Family’ was found to be the main reason for choosing farming as an occupation, as reported by the rural youth engaged in farming. On the other hand, ‘To bring stability in life’ happened to be the prime reason cited by the rural youth that had moved into farming after having tried other occupation(s). Based on the quantitative results, coupled with qualitative information, two distinctive paradigms were developed to reflect ‘How youth becomes a Farmer?’ and ‘How and Why the youth quits Farming?’, with a view to enrich our knowledge on this subject via empirical evidences as obtained from the grassroots level, especially from the Eastern Part of India.
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In recent years, successive reforms of the CAP have placed particular emphasis on the integrated development of the countryside and on strengthening the multiple job-holding of farmers. More specifically, incentives have been granted to young people in the European countryside in order for them to remain in rural areas and improve their income. The aim of the aid Programmes for young farmers is, on the one hand, to renew the age composition of the rural population and, on the other, to improve the structure of their farms. In this way, the issue of the ageing rural population is addressed, while simultaneously exploiting the new labour resources for agriculture, thus providing an impetus for the improvement of its entrepreneurial and competitive profile. The purpose of this paper is to evaluate the aid Programmes for Young Farmers and, more specifically, the First Measure of the Third Axis of the Operational Programme «Rural Development-Regeneration of the Countryside 2000-2006», based on improvements to the level of viability. The methodology used in this case is the Categorical Regression. At first, improvements to the viability level of a sample of farms that were included in the Regional Operational Programmes of the Region of Central Macedonia are checked. On a second level, an analysis evaluation is made on how the effect of the basic socio-economic parameters may have changed, in formulating the final economic viability level of the farms, after the completion of their Investment Plans (future status). The results show that the orientation of the farms, after the implementation of the financing Programme, is towards exploiting the comparative advantages of the various regions by making use of suitable crops.
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This paper employs the data from Russian Longitudinal Monitoring Survey (RLMS) to study human capital determinants of wage and employment changes from 1992 to 1996. We analyze how returns to schooling are changing over the transition period in Russia. The evidence shows that at the beginning of economic reforms (1992-1994) unconstrained wage setting shifted returns in favor of more educated individuals. But the consequent structural changes along with devaluation of some skills and reduction of supply of skilled jobs lead to a decline in the rates of return to schooling. The returns to experience also tend to decline substantially. Compared with workers of state-owned and privatized companies, workers of new private firms have greater returns to schooling and smaller returns to experience. We also find robust evidence of a strong impact on wages caused by firm–specific and regional characteristics. Among other results, higher education tends to reduce the probability of exit from employment and unemployment.
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CATREG is a program for categorical multiple regression, applying optimal scaling methodology to quantify categorical variables, including the response variable, simultaneously optimizing the multiple regression coefficient. The scaling levels that can be applied are nominal, nonmonotonic spline, ordinal, monotonic spline or numerical. When ordinal or monotonic spline scaling levels are applied, local minima can occur. With ordinal or monotonic spline scaling levels, the transformations are required to be monotonically increasing, but this can also be achieved by reflecting a monotonic decreasing transformation. A monotonic transformation is obtained by restricting a nonmonotonic transformation, but the direction of the monotonic restriction (increasing or decreasing) is undefined, and it will be shown that this is the cause of local minima. Several strategies to obtain the global minimum for the ordinal scaling level will be presented. Also, results of a simulation study to assess the performance of these strategies are given. The simulation study is also used to identify data conditions under which local minima are more likely to occur and are more likely to be severe. It was found that local minima more often occur with low to moderately low R2 values, with higher number of categories and with higher multicollinearity.
Gençlerin Kırsalda Çiftçilik Yapma Eğilimleri: Akhisar İlçesi Örneği. Ulusal Aile Çifçiliği Sempozyumu 30-31 Ekim
  • R Arlı
  • M Balcı
  • C Abay
Arlı, R., Balcı, M. ve Abay, C. 2014. Gençlerin Kırsalda Çiftçilik Yapma Eğilimleri: Akhisar İlçesi Örneği. Ulusal Aile Çifçiliği Sempozyumu 30-31 Ekim 2014, Ankara. (in Turkish)
Yeni İçsel Büyüme Teorileri ve Türkiye Ekonomisinin Büyüme Dinamiklerinin Analizi. Doktora Tezi, Sosyal Bilimler Enstitüsü
  • S Ateş
Ateş, S. 1998. Yeni İçsel Büyüme Teorileri ve Türkiye Ekonomisinin Büyüme Dinamiklerinin Analizi. Doktora Tezi, Sosyal Bilimler Enstitüsü, Çukurova Üniversitesi, Adana.
Kategorik Regresyon Analizi ile Öğrencilerin Benlik Algılarını Etkileyen Özelliklerin Belirlenmesi Öneri Dergisi
  • D Cengiz
Cengiz, D. 2008. Kategorik Regresyon Analizi ile Öğrencilerin Benlik Algılarını Etkileyen Özelliklerin Belirlenmesi Öneri Dergisi, 8(29): 193-198. (in Turkish)
Türkiye'de Kırsal Nüfusun Şehir Algısı Üzerine Bir Araştırma: Yeşilyurt Köyü (Trabzon)
  • S Doğanay
  • M Ve Alım
Doğanay S. ve Alım M. 2010. Türkiye'de Kırsal Nüfusun Şehir Algısı Üzerine Bir Araştırma: Yeşilyurt Köyü (Trabzon). Doğu Coğrafya Dergisi, 15 (23): 171-184. (in Turkish).