1. business and industrial
2. agriculture and forestry
3. farms and ranches

Institucionet e Përkohshme Vetëqeverisëse / Privremena Institucija Samouprave / Provisional Institutions of Self Government
Qeveria e Kosovës / Vlada Kosova / Government of Kosovo
Ministria e Shërbimeve Publike / Ministarstvo javnih službi / Ministry of Public Services
Series 2: Agriculture and Environmnet
Statistics
Agricultural Household Survey
2005
Agricultural Household Survey 2005
Preface
This is the fifth time that SOK conducted the Agriculture Household Survey. The aim of this
survey is to collect reliable statistical data on the agriculture sector in Kosovo.
The results of the Agricultural Household Survey 2005, as presented in this Publication, provide
an important source of information on the current agricultural situation in Kosovo.
Further improvements in data reliability can be expected once a Population Census and
Farm Register are conducted in Kosovo.
This publication is a result of cooperation between the Statistical Office of Kosovo (SOK) and
the Ministry of Agriculture, Forestry and Rural Development (MAFRD).
The whole activity was supported by the European Agency for Reconstruction (EAR),
financed Project ‘Complementary Services to the Agricultural Statistics and Policy Advisory
Unit Kosovo (ASPAUK II), implemented by NR International/ ADAS.
This Publication was prepared by the Department of Agriculture and Environment Statistics in
SOK comprising the following persons:
Bajrush Qevani – Director of Department,
Haki Kurti – Chief of Section,
Rexhep Fejzullahu – Senior Officer
Habib Strana - Senior Officer
This Publication was prepared in cooperation with consultants from ASPAUK II Project: Emma
Chapman, Avni Ramadani, Lulzim Shala, Muhedin Nushi, Valerie Evans, Gill Green and Sophia
Davidova.
SOK would also like to thank all regional office employees of SOK, field enumerators
and respondents for their cooperation and contributions.
We would welcome any comments and suggestions you may have regarding this publication
in order to improve the content publication in future.
Acting CEO of SOK
Mr.sc. Ramiz Ulaj
August, 2006
Agricultural Household Survey 2005
Abbreviations and Acronyms
ADAS
AHS
ASPAUK II
AWU
EAR
EU
FADN
HH
LFS
LSMS
MAFRD
MF
MPS
NAG
NPK
PPS
PSU
SOE
SOK
UNMIK
Agriculture Development & Advisory Service
Agriculture Household Survey
Complementary Services to the Agricultural Statistics and Policy Advisory
Unit Kosovo
Annual Work Unit
European Agency for Reconstruction
European Union
Farm Accountancy Data Network
Household
Labour Force Survey
Living Standard Measurement Survey
Ministry of Agriculture, Forestry and Rural Development
Multiplication Factor
Ministry of Public Services
Nitrate Ammonia Calcareous
Nitrogen Phosphorus Potassium
Probability Proportional to Size
Primary Sample Unit
Socially Owned Enterprises
Statistical Office of Kosovo
United Nations Interim Administration Mission in Kosovo
Key to symbols
..
.
0
0, 0
kg
t
hp
%
Zero
Data not available
Not applicable
Magnitude less than half of unit employed
Magnitude less than half of unit employed ha Hectares
Kilogram
Tone
Horse power
Per cent
In tables where figures have been rounded to the nearest final digit, there might be a
slight discrepancy in the sum of the constituent items as shown.
Agricultural Household Survey 2005
Contents
Objectives, methodology and scope of the survey………………………………………….5
Agricultural households………………………………………………………………………14
Land use and farm structure………………………………………………………………..20
Crops…………………………………………………………………………………………..28
Forestry………………………………………………………………………………………..33
Livestock……………………………………………………………………………………….35
Agricultural inputs……………………………………………………………………………..38
Agricultural labour……………………………………………………………………………..42
Farm expenditure……………………………………………………………………………..45
Annex 1.
List of municipalities by region
47
Annex 2.
Adjusted tables of Agricultural Household Survey 2004
48
Annex 3.
Questionnaire
50
3
Agricultural Household Survey 2005
1.
1.1
Objectives, methodology and scope of the survey
Survey objectives and scope
The objective of the Agricultural Household Survey 2005 is to provide data on the agricultural
situation in Kosovo, namely: demography of agricultural households; land use and farm structure;
livestock; crops; forestry; agricultural inputs; labour force and farm expenditure. The survey aims to
help assess the level of development of the agricultural sector in Kosovo and provide the basis for
future monitoring of trends in the sector.
The survey covers land farmed by agricultural households, living and farming in rural areas 1. It does
not include land belonging to agricultural households in rural areas that are not farming or land
belonging to agricultural households living in urban areas in Kosovo or abroad unless rented by
agricultural households from the rural areas. Additionally, land belonging to state owned enterprises
- not farmed by agricultural households - is not included in the survey.
Data are presented at Kosovo and regional level, and at municipality level in some cases. Data at
regional level are more robust than at municipality level, as for some municipalities the number of
households interviewed in each stratum is small. However, municipality data are presented in some
chapters, in order to provide detail required by data users. Annex 1 presents the municipalities by
region used in the Survey.
The survey was conducted in November and December of 2005. It has been conducted annually
since 2001. Large farms have been fully enumerated.
1.2
Survey frame
In late August and September 2004 all rural villages in Kosovo were visited. There were 1,414
villages visited.
Based on a face-to-face questionnaire with the village heads, estimates were obtained for purposes
of updating the sample frame. For each village, estimates were given by the village head for:
• Number of households in the village;
• Number of agricultural households in the village;
• Number of families living in the village at present;
• Number of families from the village who are living outside the village;
• Number of inhabitants of the village;
• Number of inhabitants currently living in the village;
• Number of inhabitants of the village who are living outside the village.
This frame (list) of all the villages in Kosovo was used to randomly select villages to have a full
door-to-door listing done – the beginning of a farm register.
Beginning in the autumn of 2004, and adding to it in the autumn of 2005, 426 villages were
completely listed door-to-door and each household visited in this listing was asked for the land
owned, land under cultivation, land use, number of livestock by category, whether the owner or
someone else was farming the land.
In the autumn of 2005, all the records (one household per line) for the 426 villages listed door-todoor were entered in a database at SOK. There were approximately 67,000 records entered.
1
At least one member of the agricultural household must be farming.
5
Agricultural Household Survey 2005
Only those records fulfilling the agricultural holding definition within Kosovo and only those that were
actively farming (i.e. not outside of the country) were retained as agricultural households. Twentyone percent of the households listed in these 426 villages did not qualify for the definition of agricultural
households, resulting in a 21 percent reduction of the numbers of households.
After this reduction there were approximately 52.700 agricultural households in the 426 listed
villages.
1.3
Sample design
The survey was based on a two-level stratified sample. The first level of stratification was by region
in order to obtain regional estimates and to ensure full geographical coverage. The second level of
stratification was by farm size to ensure representation of agricultural households. Once a village was
chosen to be in the 2005 survey, the agricultural households in the village were stratified into three
size categories (using land under cultivation as the value for stratification): 0-1,5 ha, 1,51-3,0 ha, and
greater than 3 ha. After stratification, households were randomly selected for interview.
Tables 1.1 and 1.2 show the numbers of agricultural households interviewed in the 2005 survey in
each size stratum by region and by municipality. The sample size (total number of households
interviewed) was 4.446.
Table 1.1: Number of households interviewed by farm size by region
0 – 1,5 Ha (inc.)
1,5 - 3 Ha (inc)
3 + Ha
Large and specialised farms
Total
Prishtinë
284
182
138
33
637
Mitrovicë
217
227
150
33
627
Pejë
227
202
166
69
664
6
Gjakovë
227
186
183
43
639
Prizren
274
181
152
44
651
Ferizaj
214
226
160
12
612
Gjilan
269
190
132
25
616
Total
1.712
1.394
1.081
259
4.446
Agricultural Household Survey 2005
Table 1.2: Number of households interviewed by farm size by municipality
Municipality
0 - 1.5
Ha (inc.)
1.5 - 3
Ha (inc)
Kosovo
Deçan
Gjakovë
Gllogovc
Gjilan
Dragash
Istog
Kacanik
Klinë
F.Kosovë
Kamenicë
Mitrovicë
Leposaviq
Lipjan
Novobërdë
Obiliq
Rahovec
Pejë
Podujevë
Prishtinë
Prizren
Skënderaj
Shtime
Shtërpcë
Suharekë
Ferizaj
Viti
Vushtrri
Z.Potok
Zveçan
Malishevë
1.712
94
74
61
99
64
77
72
59
27
72
53
20
50
10
23
59
91
71
42
67
80
44
9
77
89
98
42
13
9
66
1.394
70
66
26
79
22
66
44
39
16
49
30
31
38
7
15
50
97
51
29
49
74
49
23
51
110
62
66
13
13
59
3 + Ha
1.081
53
48
29
58
14
71
24
44
17
34
25
15
31
7
10
82
51
22
22
27
46
39
4
60
93
40
47
11
6
51
Large and
specialised
farms
259
6
8
5
6
11
40
2
8
0
6
7
0
17
1
1
29
21
5
4
33
3
1
0
0
9
13
23
0
0
0
Total
4.446
223
196
121
242
111
254
142
150
60
161
115
66
136
25
49
220
260
149
97
176
203
133
36
188
301
213
178
37
28
176
To reduce the heterogeneity of the sample frame, and thus improve the estimates, all farms that
were beyond the normal distribution, in terms of farm size or numbers of livestock, were identified
and enumerated fully. These are referred to as large and specialized farms. Thresholds for large
and specialized farms were established in 2004.
Table 1.3 presents the thresholds used for selection of large and specialized farms.
7
Agricultural Household Survey 2005
Table 1.3 Thresholds for large and specialized farms by farm type
Production
Potatoes
Cereals
Industrial crops
Orchards
Vineyards
Horticulture open
Horticulture covered
Cattle
Sheep
Goat
Pigs
Poultry
Selected Threshold
10 ha
50 ha
All farms
1,5 ha
4 ha
3 ha
0,30 ha
35
200
40
35
4000
In the absence of a complete farm register, a list of all farms in Kosovo above the threshold size
was compiled. This was accomplished through reference to existing data sets, and 259 large and
specialized farms were identified and fully enumerated. These are referred to in this publication as
‘large and specialized farms’. They are not necessarily commercial farms. All other agricultural
households are referred to in the subsequent chapters as “small agricultural households or farms”.
1.4
Estimation procedure
The aim in conducting a survey is to obtain information about a particular population, in this case
the agricultural households in Kosovo. When the sample (which is a subset of the population under
examination) has been selected and the information collected and processed, there still remains the
task of linking the information gathered from the sample back to the overall population. This means
a certain sample of agricultural households are interviewed (in this year’s sample 4.446 farms), and
from the answers and information given by the households in the sample it is necessary to make
estimates of the whole population, which is all the agricultural households in Kosovo.
Underpinning the estimation process is the sampling weight of a unit (in this case the unit is an
agricultural household), which indicates the number of units in the population that are represented
by this sampled unit. That is, for each agricultural household interviewed, how many agricultural
households does this one interviewed household represent? The number of households that the
one sampled household represents is its weight.
8
Agricultural Household Survey 2005
Box 1. A simple example of survey weights
Let’s assume we have a village with 60 agricultural households. We decide to randomly choose 5
of these households to interview and we will use the information provided by the interviews to
estimate certain variables for the village – let’s say we will estimate the area planted with wheat
and the number of cows in the village.
These are the results of the interviews of the 5 households:
Household
number
Area (ha) planted with
wheat
Number of
cows
Sampling
weight
1
1.0
0
12
2
0.44
2
12
3
0.20
1
12
4
0.85
3
12
5
0
2
12
The sample weight for each household is 12 because there are 60 households in the village, and
we chose 5 of them to interview, so each household represents 60/5= 12 households.
To estimate the number of cows in the village, we multiply each household’s value by the weight
for that household (12). So the estimate for the total number of cows in the village is
(0*12)+ (2*12)+(1*12)+(3*12)+ (2*12)=96 cows.
Likewise for the area of wheat planted, the calculation would be
(1.0*12)+ (0.44*12) + (0.20*12) + (0.85*12) + (0*12) =12+5.28+2.4+10.2+0=29.88 ha.
Of course, so few households interviewed will not provide a reliable estimate for that particular
village, but this example illustrates how weights are applied. In this case, we also did not stratify
the households in any way – we could have had better estimates if we were able to group the
agricultural households in groups corresponding to the amount of land each household farmed,
and then calculate weights for each of these size groupings.
It is the responsibility of the sampler to determine a sampling plan that ensures enough units are
interviewed to give reliable estimates.
Constraints to defining survey weights in Kosovo
In the weighting example given in Box 1, it was known that there were 60 households in the village
and so 5 households to interview were chosen, it was obvious that each interviewed household had
a weight of 12. The challenge in Kosovo is that the total number of resident households or
agricultural households is not known, so determining weights to multiply the sampled households by
is difficult, and will remain so until there is a definitive census to establish a sample frame from
which all surveys can calculate reliable weights, or a complete farm register of all the agricultural
households in Kosovo which can be used as the frame for agricultural surveys.
9
Agricultural Household Survey 2005
Calculation of Weights for the 2005 Agricultural Household Survey
In 2005, the following reasoning and information to determine weights was used. The somewhat
differing approach used in 2004 will also be described, so that readers will be able to compare the
two and reconcile the differences in the two years’ estimates.
The tables below illustrate the three steps used to calculate the weights for the 2005 survey (and
serve as an example of how weights are calculated for surveys in general).
Register as a proportion of the total villages in each region.
Step 1: Calculation of the multiplication factors – number of villages included in the Farm
Table 1.4 shows the number of villages registered (column a) compared to the total number of
villages in that region in Kosovo (column b). Based on these figures, a multiplication factor from the
two values for each region was calculated using:
MF = b / a
Where MF is multiplication factor; b is total number of villages, and; a is number of villages in the
Farm Register.
Table 1.4 Calculation of the multiplication factor
a
No. villages in Farm
Region
Register
Prishtinë
85
Mitrovicë
84
Pejë
54
Gjakovë
44
Prizren
60
Ferizaj
51
Gjilan
48
426
Total
* As recorded in the head of village database, SOK
b
Total No. of villages*
270
317
180
155
193
121
178
1.414
MF=b/a
Multiplication factor
3,2
3,8
3,3
3,5
3,2
2,4
3,7
Step 2: Estimation of the total number of agricultural households by region and farm size
The total number of agricultural households in each region by farm size was estimated by applying
the multiplication factor (presented in Table 1.4) to the number of agricultural households for each
size category included in the Farm Register.
Table 1.5 shows the total number of agricultural households in the Farm Register, by region and size
category. For each region, the agricultural households are divided into four size category strata
(three size strata and the “large and specialized farm stratum). In order to estimate the total number
of agricultural households in each size category in each region the multiplication factor (mf) was
applied to the number of agricultural households included in the farm register (c).
E = MF * c
Where E is estimate, MF is multiplication factor, and c is count
10
Agricultural Household Survey 2005
Table 1.3: Estimation of the total number of agricultural households
E=MF*c
0 - 1.5 Ha (inc.)
Estimate (E)
1.5 - 3 Ha (inc)
Estimate (E)
3 + Ha
Estimate (E)
Large and specialised farms
Total
Prishtinë Mitrovicë
9.365(c)
4.172(c)
Pejë
3.734(c)
Gjakovë
3.679(c)
Prizren
6.786(c)
Ferizaj
4.875(c)
Gjilan
4.231(c)
Total
29.968
15.854
12.322
12.877
21.715
11.700
15.655
120.092
3.084(c)
1.575(c)
1.385(c)
1.347(c)
1.210(c)
1.144(c)
1.341(c)
9.869
5.985
4.570
4.715
3.872
2.746
4.962
1.524(c)
623(c)
600(c)
519(c)
416(c)
315(c)
576(c)
4.877
2.367
1.980
1.816
1.331
756
2.131
15.259
33
33
69
43
44
12
25
259
44.747
24.240
18.941
19.451
26.962
1. 214
36.718
2.773
172.328
Using this method of calculating the total number of agriculture households in Kosovo a total of
172.328 agricultural households is estimated. This estimate of 172.328 is consistent with the estimates
of total agricultural holdings in 2001-20033 and thus yields estimates of livestock and crops that
are more consistent with what is expected by the Ministries than the estimates in 2004, when the
total number of agricultural households assumed was significantly lower (see the comparison
of the two methodologies discussed further in this chapter). Until a census is completed and a reliable
frame can be established for the number of households and agricultural households
in Kosovo there will be debate around the weights applied as the weights flow directly from the
number of agricultural households assumed.
Step 3: Calculation of the weights
The weights for the survey were determined by calculating the proportion of agricultural households
interviewed as compared with the estimated total number of agricultural households in each region
and stratum as presented in Table 1.5. Therefore:
W=E/S
where W is weight; S is sample size; and E is estimate of the total number of agricultural
households.
Following this method, weights are calculated for each size stratum and region to improve the
reliability of the estimates. By using farms in the same size category and region to estimate for all
the farms in this same category and region, estimates are improved. Table 1.6 shows the weights
that were calculated for each region and each stratum (farm size).
Table 1.6: Weights
W = E/S
0 – 1,5 Ha (inc.)
1,5 - 3 Ha (inc)
3 + Ha
Large & specialized farms
Prishtinë
Mitrovic ë
Gjakovë
Prizren
105.521
54.224
73.062
26.366
Pejë
54.281
22.626
56.728
25.347
79.253
21.392
Ferizaj
54.673
12.149
Gjilan
58.196
26.114
35.339
1
15.783
1
11.928
1
9.926
1
8.758
1
4.725
1
16.145
1
Box 2 provides an example of how these three steps were followed in practice. Once Kosovo has a
complete Farm Register, steps 1–2 will no longer be necessary.
3
The total agricultural household frame used in previous years was: 2001: 154.752; 2002: 157.600; 2003: 169.473;
2004: 117.000.
11
Agricultural Household Survey 2005
Box 2. An example of how the Survey weights were calculated
Step 1. In Peje there are 54 villages in the Farm Register out of a total of 180 villages. The
multiplication factor is therefore: 180 / 54 = 3, 3.
Step 2. In the 54 villages of Pej ë the Farm Register has 3.734 recorded agricultural households
in the smallest size category of 0 – 1,5 ha. The estimate for the number of agricultural households
in all of Peje’s 180 villages for that size category is calculated by multiplying 3.734 by the
multiplication factor of 3,3.
Therefore:
E = MF * c or 12..322 = 3,3 * 3.734
Following the same procedure the estimate for the number of farms in the 1,5 – 3 category is
4.570 agricultural households and for farms > 3 ha it is 1.980. The large and speci alised farms
interviewed in Peje were 69. These farms do not have a multiplication factor since they are all
interviewed once they have been identified and therefore do not represent any other farms.
Step 3. In Peje 664 households were interviewed in total, of which in size category 0 – 1, 5 ha,
227 were interview ed. The weight applied to farms interviewed from Pejë in size category 0 – 1,5
ha is therefore 12.322 divided by 227:
W = E / S or
54.281 = 12.322 / 227
The weight applied to agricultural households of size category 0 – 1,5 ha in Peje was therefore
54.281.
Difference in the weighting methodology for 2004 survey compared to 2005 survey
In 2004 instead of calculating a multiplication factor from the number of villages included in the
Register compared to the number of villages in the region (see Table 1.4) a different multiplication
factor was calculated. The total number of households in each municipality that were registered was
compared to the total number of agriculture households estimated for all the villages in the
municipality, as estimated by the head of villages when visited in 2004. That is, instead of using
numbers of villages registered compared to number of total villages, as in 2005, in 2004 the number
of households listed door-to-door was compared to the total number of agricultural households
estimated by the heads of villages.
However, as in 2005 the work to complete door-to-door listings continued, it was felt to be much
more accurate than the estimates of head of villages (we noted sometimes large discrepancies in
the numbers estimated by the head of villages compared to the numbers that were actually found
going door-to-door). For this reason, in 2005 it was judged to use simply the numbers of villages
and not the head of village estimates of the number of agriculture households in the village, to
calculate multiplication factors.
In order to compare the survey results from 2004 and 2005 using the same weights, some of the
most important tables were re-run using the 2004 survey data with the 2005 weights applied (see
Annex 2).
12
Agricultural Household Survey 2005
1.5
Definitions
The survey was carried out using the following definitions:
The definition of a household is a union of persons that live together, and pool their income.
The definition of an agricultural household is one that possesses and cultivates more than 0.10 ha
utilized arable land 2, or less than 0, 10 ha of utilized arable land but has at least:
• 1 cattle and a calf, or 1 cattle and 1 heifer, or
• 1 cattle and 2 grown sheep’s or goats, or
• 5 grown sheep’s or goats or
• 4 grown sheep’s and pigs together, or
• 3 grown pigs, or
• 50 grown poultry, or
• 20 beehives, or
• More than 20 m 2 of fish pond.
The total land area of the household includes all land belonging to the household, both used and
not used, and rented land. Plots that are physically located within the holding of the interviewed
household, but are rented out or given for free to others to farm, are included in the total land area
of the household. Potentially, there could be double counting if people who use these plots are
included in the survey sample. Having in mind the relatively small sample size, the probability of
double counting is judged to be low.
1.6
Field Procedure
The method of data collection was face-to-face interviews based on a questionnaire (Annex 3).
Field and regional supervisors maintained close field work supervision and contact with
headquarters to resolve problems encountered.
A data checking procedure was carried out. It comprised three levels: (i) checking completed
questionnaires in the field by field supervisors; (ii) checking completed questionnaires in SOK
central offices by permanent staff of the Agricultural Department, and (iii) logical checks during data
entry. Following completion of the fieldwork, a further quality control was carried out.
2
Arable land, kitchen gardens, green house, orchard, vineyard, meadow
13
Agricultural Household Survey 2005
2
Agricultural households
The Survey collected information about agricultural household members. As many demographic
changes have occurred in Kosovo in the past decades and in the absence of a recent Population
Census, this Survey provides a key source of information for this type of information. The planned
population census should provide fuller information on the agricultural population and its structure.
This chapter presents data on agricultural households in 2005 concerning age, gender and
education of household members. It should be noted that only households that were defined as
agricultural according to the definition presented in Chapter 1 have been counted. Also, only
households living and farming in the villages have been included in the survey. Table 2.1 shows the
total agricultural population by age group.
Table 2.1: Agricultural population by age group
Age Group
Number
%
Cumulative %
Up to 14 years
397.261
29,7
29,7
15 - 29 years
30 - 49 years
400.789
318.552
30,0
23,8
59,7
83,6
50 - 64 years
133.194
10,0
93,5
86.497
1.336.293
6,5
100,0
100,0
65 and over
Total
The table indicates total agricultural population of around 1.336.000. Kosovo is characterized by a
large young population. The agricultural population within the age group of 15 to 29 years is 30
percent. There is a small population older than 65 years, namely 6,5 percent. These data are
similar to the data of AHS 2001 and LFS where rural population is estimated to be 1,3 million. 3 Data
from LSMS estimated rural population to 1,2 million. All these surveys indicate that in Kosovo the
agricultural population still accounts for a high percentage of the total population.
Figure 2.1: Agricultural household size
16 and over
members
6, 1%
13 - 15 members
5, 5%
Up to 4 members
16, 4%
9 - 12 members
18, 0%
5-8
members
54, 1%
3
As explained in Chapter 1, in 2005 a different approach was used to determine weights. If the 2005 methodology were applied
to 2004 data, the estimate of the agricultural population in 2004 would be 1,294,018.
14
Agricultural Household Survey 2005
Figure 2.1 presents the distribution of agricultural households by size. Agricultural households in
Kosovo are large. Most of the households have 5-8 members, 54,1 percent. The average number of
household members is 7,8. Very large households, with 16 and more members, account for 6,1
percent.
Out of the total agriculture population, in 2005 around 11 percent lived outside the household for
more than six months. The largest number were male within age group 15-49, who in 2005 spent
10-12 months outside the household.
Table 2.2 presents the age structure of the agricultural population by region, and Table 2.3 shows the
data at municipality level.
Table 2.2: Age structure of the agricultural population by region
Region
Up to 14
Number
%
Age
30 – 49
15 - 29
Number
50 - 64
65 and over
%
Number
%
Number
%
Number
%
Total
Number
%
Kosovo
Prishtinë
397.261
87.261
29,73
28,2
400.789
94.678
30,0
30,6
318.552
71.793
23,8
23,2
133.194
34.916
10,0
11,3
86.497
20.271
6,5
6,6
1.336.293
308.920
100
100
Mitrovicë
49.064
28,0
53.861
30,8
42.055
24,0
17.981
10,3
12.051
6,9
175.012
100
Pejë
Gjakovë
41.817
56.581
29,7
31,8
43.090
53.583
30,6
30,1
33.067
41.195
23,5
23,2
13.588
16.266
9,6
9,1
9.405
10.277
6,7
5,8
140.968
177.903
100
100
Prizren
80.995
31,6
76.436
29,9
61.606
24,1
22.016
8,6
14.886
5,8
255.939
100
Ferizaj
Gjilan
38.438
43.105
31,5
27,7
36.069
43.070
29,6
27,7
29.216
39.620
24,0
25,4
11.992
16.433
9,8
10,6
6.133
13.474
5,0
8,7
121.848
155.703
100
100
The regional differences in the age structure of agricultural population are small. Gjakova, Prizren
and Ferizaj have a higher percentage of young persons under 14 years of age, while the regions of
Mitrovica, Prishtina, Peja and Gjakova have a higher percentage of population in the age group of
15 to 29 years. The regions of Prishtina, Mitrovica and Gjilan have a higher share of age groups 50
to 64 and more than 65 years old. The share of the core group of the working population, between
30-49 years old, is similar among the regions, with the highest percentage in Gjilan, 25.
15
Agricultural Household Survey 2005
Table 2.3: Age Structure of the agricultural population by municipality
Municipality
Kosovo
Deçan
Gjakovë
Gllogovc
Gjilan
Dragash
Istog
Kaçanik
Klinë
F.Kosovë
Kamenicë
Mitrovicë
Leposaviç
Lipjan
Novobërdë
Obiliq
Rahovec
Pejë
Podujevë
Prishtinë
Prizren
Skënderaj
Shtime
Shtërpcë
Suharekë
Ferizaj
Viti
Vushtrri
Z.Potok
Zveçan
Malishevë
Up to 14
Number
%
397.261
18.163
19.396
19.696
16.459
12.828
14.333
12.505
11.493
7.038
8.690
10.500
1.095
17.274
745
7.632
19.021
15.991
24.002
10.874
18.177
22.171
8.407
1.375
24.627
16.157
17.956
12.394
1.736
1.163
25.362
29,7
28,7
33,8
30,5
27,8
27,1
30,0
32,0
30,8
26,6
24,3
28,6
12,1
29,9
11,2
29,2
33,3
28,6
27,0
28,2
30,7
30,9
32,1
27,6
32,9
31,3
29,6
29,0
19,8
19,9
34,0
15 - 29
Number
400.789
19.376
16.963
20.829
15.931
12.514
14.164
11.085
13.256
7.283
9.889
11.284
2.405
15.902
2.297
8.633
17.244
15.671
29.891
9.844
18.910
22.288
8.571
1.382
22.119
15.035
17.250
13.696
2.739
1.445
22.894
%
Age
30 - 49
Number
%
30,0
30,6
29,6
32,3
26,9
26,4
29,7
28,3
35,5
27,5
27,7
30,7
26,7
27,5
34,4
33,0
30,2
28,0
33,7
25,5
31,9
31,0
32,8
27,7
29,6
29,1
28,4
32,0
31,2
24,8
30,7
318.552
14.962
12.647
14.571
15.191
12.210
11.449
9.950
7.549
6.505
8.397
9.289
2.120
13.589
1.666
5.611
13.587
14.070
20.354
9.498
13.484
17.022
5.511
1.319
18.403
12.439
16.032
9.953
2.014
1.653
17.510
23,8
23,6
22,0
22,6
25,6
25,8
24,0
25,4
20,2
24,6
23,5
25,3
23,5
23,5
25,0
21,4
23,8
25,2
22,9
24,6
22,8
23,7
21,1
26,4
24,6
24,1
26,4
23,3
23,0
28,3
23,5
16
50 - 64
Number
133.194
6.784
4.769
6.306
6.297
5.096
4.560
3.752
3.125
3.038
4.648
3.910
1.872
6.814
1.482
2.637
4.713
5.903
9.325
5.314
5.423
5.960
2.564
553
5.988
5.124
5.547
4.000
1.246
934
5.509
%
10,0
10,7
8,3
9,8
10,6
10,8
9,6
9,6
8,4
11,5
13,0
10,7
20,8
11,8
22,2
10,1
8,2
10,6
10,5
13,8
9,2
8,3
9,8
11,1
8,0
9,9
9,1
9,4
14,2
16,0
7,4
65 and over
Number
%
86.497
4.069
3.621
3.112
5.402
4.664
3.243
1.838
1.929
2.607
4.096
1.728
1.531
4.190
483
1.666
2.587
4.233
5.173
3.040
3.206
4.400
1.112
360
3.706
2.824
3.975
2.720
1.032
639
3.310
6,5
6,4
6,3
4,8
9,1
9,9
6,8
4,7
5,2
9,8
11,5
4,7
17,0
7,3
7,2
6,4
4,5
7,6
5,8
7,9
5,4
6,1
4,2
7,2
5,0
5,5
6,5
4
11,8
11,0
4,4
Total
Number
%
1.336.293
63.354
57.397
64.513
59.281
47.311
47.748
39.130
37.352
26.473
35.720
36.712
9.022
57.768
6.673
26.179
57.151
55.868
88.745
38.570
59.201
71.841
26.165
4.990
74.843
51.579
60.760
42.762
8.766
5.835
74.585
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Agricultural Household Survey 2005
Table 2.3 indicates differences in the age structure among municipalities. Malisheva has the highest
percentage of young persons up to 14 years of age, 34 percent, followed by Gjakova with
33.8 percent and Rahovec with 33,3 percent (the average for Kosovo is 29,7 percent). Klina has
the highest share, 35,5 percent, of young active working population between 15-29 years old.
This percentage is also high in Novobërdë, 34,4 percent, and Podujeva, 33,7 percent (average for
Kosovo, 30 percent). The share of the age group 30–49 years old is approximately the same in all
municipalities. In Kosovo the agricultural population older than 50 years of age is 16,5 percent. In
some municipalities, Leposaviç, Novo Bërdë, Zveçan and Zubin Potok the share of the
agricultural population over 50 years old is much higher, 37,7 percent, 29,4 percent, 27,0 percent
and 26,0 percent respectively. One of the reasons is the migration of young people due to the lack
of jobs and career prospects in the villages.
Table 2.4: Gender structure of the agricultural population by region
Region
Kosovo
Prishtinë
Mitrovicë
Pejë
Gjakovë
Prizren
Ferizaj
Gjilan
Male
Number
708.988
163.908
96.186
73.565
91.751
135.095
66.515
81.969
%
53,1
53,1
55,0
52,2
51,6
52,8
54,6
52,6
Female
Number
627.304
145.012
78.826
67.403
86.152
120.844
55.334
73.734
Total
%
46,9
46,9
45,0
47,8
48,4
47,2
45,4
47,4
Number
1.336.293
308.920
175.012
140.968
177.903
255.939
121.848
155.703
%
100
100
100
100
100
100
100
100
Results of the survey indicate a higher percentage of males, 53, 1 percent. At regional level, the
imbalance is more pronounced in Mitrovica, 55 percent male population, Ferizaj, 54,6 percent,
and Prishtina, 53,1 percent. The predominance of males in the agricultural population was also
recorded in the 2004 survey.
All municipalities have more males than females (Table 2.5). The difference is particularly large in
Zveçan, 59,2 percent, Kaçanik, 55,6 percent, and Skënderaj, 55,5 percent male inhabitants. The
predominance of males in agricultural population appears to persist despite the pre- and post-war
emigration which involved more males than females.
17
Agricultural Household Survey 2005
Table 2.5: Gender structure of agricultural population by municipality
Municipality
Kosovo
Deçan
Gjakovë
Gllogovc
Gjilan
Dragash
Istog
Kaçanik
Klinë
F.Kosovë
Kamenicë
Mitrovice
Leposaviç
Lipjan
Novobërdë
Obiliq
Rahovec
Pejë
Podujevë
Prishtinë
Prizren
Skënderaj
Shtime
Shtërpcë
Suhareka
Ferizaj
Viti
Vushtrri
Z.Potok
Zveçan
Malishevë
Male
Number
708.988
32.400
29.509
32.413
30.347
24.442
24.421
21.754
19.237
14.677
18.981
19.942
4.885
30.338
3.648
13.726
29.840
29.906
48.675
20.433
31.635
39.863
13.575
2.647
39.607
28.550
32.640
23.583
4.452
3.452
39.410
%
53,1
51,1
51,4
50,2
51,2
51,7
51,1
55,6
51,5
55,4
53,1
54,3
54,1
52,5
54,7
52,4
52,2
53,5
54,8
53,0
53,4
55,5
51,9
53,0
52,9
55,4
53,7
55,1
50,8
59,2
52,8
Female
Number
627.304
30.954
27.887
32.100
28.933
22.869
23.327
17.376
18.115
11.795
16.739
16.770
4.138
27.430
3.026
12.452
27.311
25.962
40.070
18.137
27.565
31.978
12.590
2.343
35.236
23.029
28.120
19.180
4.314
2.383
35.174
Total
%
46,9
48,9
48,6
49,8
48,8
48,3
48,9
44,4
48,5
44,6
46,9
45,7
45,9
47,5
45,3
47,6
47,8
46,5
45,2
47,0
46,6
44,5
48,1
47,0
47,1
44,6
46,3
44,9
49,2
40,8
47,2
Number
1.336.293
63.354
57.397
64.513
59.281
47.311
47.748
39.130
37.352
26.473
35.720
36.712
9.022
57.768
6.673
26.179
57.151
55.868
88.745
38.570
59.201
71.841
26.165
4.990
74.843
51.579
60.760
42.762
8.766
5.835
74.585
%
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
In the survey, data were gathered on education level. Table 2.6 presents the level of education
attained by the agricultural population by age group.
18
Agricultural Household Survey 2005
Table 2.6: Education attainment of agricultural population by age-group (from 15-64
years of age)
Education level
None
Some Primary
Primary Completed
Some Secondary
Secondary Completed
Some High School
High School Completed
Some Faculty
Faculty Completed
Total
15 - 29 years
Number
%
4.113
1,0
27.580
6,9
129.504
32,3
66.993
16,7
142.989
35,7
3.859
1,0
2.980
0,7
18.069
4,5
4.702
1,2
400.789 100,0
Age Group
30 - 49 years
Number
%
6.825
2,1
13.557
4,3
130.416
40,9
5.839
1,8
132.335
41,5
2.455
0,8
10.466
3,3
5.707
1,8
10.953
3,4
318.552 100,0
50 - 64 years
Number
%
16.303
12,2
31.016
23,3
49.987
37,5
1.944
1,5
23.416
17,6
931
0,7
5.057
3,8
1.050
0,8
3.490
2,6
133.194
100,0
Total
Number
27.241
72.153
309.907
74.776
298.740
7.245
18.502
24.825
19.145
852.534
%
3,2
8,5
36,4
8,8
35,0
0,8
2,2
2,9
2,2
100,0
The largest share of the agricultural population has primary or secondary education. The share of
these two groups taken together is 71 percent of the adult agricultural population in active working
age. At the two extremes, no education and some or fully completed tertiary education, the shares
of population are small; without any education 3,2 percent and fully completed tertiary education
2,2 percent. The Table shows though a gradual improvement in the number of persons attending
tertiary education reflected in the higher percent of persons attending University in the lower age
groups.
Table 2.7: Education attainment of agricultural population by gender (from 15-64 years
of age)
Education level
None
Some Primary
Primary Completed
Some Secondary
Secondary Completed
Some High School
High School Completed
Some Faculty
Faculty Completed
Total
Male
Number
6.179
24.076
109.110
46.651
216.701
4.867
14.300
17.101
14.370
453.354
%
1,4
5,3
24,1
10,3
47,8
1,1
3,2
3,8
3,2
100,0
Female
Number
21.061
48.077
200.797
28.125
82.039
2.378
4.202
7.725
4.775
399.180
Total
%
5,3
12,0
50,3
7,0
20,6
0,6
1,1
1,9
1,2
100,0
Number
27.241
72.153
309.907
74.776
298.740
7.245
18.502
24.825
19.145
852.534
%
3,2
8,5
36,4
8,8
35,0
0,8
2,2
2,9
2,2
100,0
There are differences in education attainment among Kosovo male and female agricultural
population aged 15-64 (Table 2.7). The share of male without any education is only 1,4 percent,
while for female is 5,3 percent. The number of females without education is over three times
higher than males. In general, Kosovo agricultural families educate their daughters up to the
end of the primary school. For this reason, the adult females with completed primary education
amount to about 50 percent, while 48 percent of males have completed secondary school. This
gender difference is due not only to the priority given by families in rural areas to educate their
sons, but is also determined by the distance from the place of residence to school, transport
facilities and on the existing physical infrastructure. In villages with primary schools both
genders are usually sent to school. Other surveys (LSMS 2000, LFS 2001 and 2002) also found
large differences in education between the rural and urban population.
19
Agricultural Household Survey 2005
3. Land use and farm structure
The Agricultural Household Survey 2005 collected data from agricultural households about the
use of each plot of land, owned or operated, including land left fallow. As explained in Chapter 1,
it also collected data for plots that were physically located within the holding of the interviewed
household but were rented out or given for free to others to farm. These plots account for a small
land area, 2.841 ha, or around 0,8 percent of the total land use. In the subsequent tables this area
is included in the category ‘other’. It was felt necessary to include these plots in order to account
comprehensively for all land used by the agricultural households.
Chapter 1 indicated that in 2005 259 large and specialized farms were identified. However, three
of these farms do not have agricultural land as they are specialized in intensive livestock
production. For this reason, in tables devoted to land use only 256 large and specialized farms
are included.
Table 3.1 presents the total land use by the main categories.
Table 3.1: Total land use
Land use
Utilised arable land and kitchen gardens
Orchards
Vineyards
Greenhouse
Meadows
Subtotal cultivated land
Pastures
Left fallo w
Subtotal agriculture land
Forestry
House yard
Other
4
Total
Area (ha)
138.861
4.016
907
162
89.844
233.789
8.425
23.052
26. 265
76.700
16.082
3.391
361.439
%
38,42
1,11
0,25
0,04
24,86
64,68
2,33
6,38
73,39
21,22
4,45
0,94
100,00
Agricultural land, owned or operated by households, accounts for around 73 percent of the total
land area of agricultural households. The remaining is land under forests and house yards.
Agricultural land includes utilized arable land plus kitchen gardens, orchards, vineyards,
greenhouses, meadows, pastures, and land left fallow (the kitchen gardens were pooled in the
category of utilized arable land for simplification of data collection). The use of agricultural land by
main categories is presented in Figure 3.1. 5
4
5
Applying the 2005 approach to weights on 2004 data results in a total land area of 359,476 ha in 2004.
This figure does not include forestry, house yards and the category other.
20
Agricultural Household Survey 2005
Figure 3.1: Use of agricultural land
Meadows and
pastures
37%
Utilised arable
land and
kitchen garden
52%
Left fallow
9%
Other
2%
The largest part of agricultural land, 52 percent, is utilized arable area; the second largest
category comprises of meadows and pastures. According to the survey, 9 percent of agricultural
land is left fallow. A quarter of all agricultural households have some land left fallow. Around one
third of the farmers who left land fallow indicate that this is due to the low economic profitability.
Figure 3.2: Reasons stated by farmers for land left fallow
Low economic profitability
30, 6
25, 3
Lack of equipment
14, 7
Lack of manpower
12, 1
Lack of security
Other reasons
8, 4
Lack of inputs
5, 1
Crop rotation
2,6
Mines
1, 1
0.0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
Per cent
The other important reasons indicated by farmers are the lack of inputs, equipment or household
labour. Although on average agricultural households have enough equipment for the cultivated
area and excess labour, for some households these appear to be a constraint.
Table 3.2 shows irrigated area expressed in hectares and as a percentage of the total cultivated
area per region and table 3,3 presents the same indicators by municipality.
21
Agricultural Household Survey 2005
Table 3.2: Irrigation of cultivated land by region
Region
Irrigated area (ha)
% of land irrigated
% of total irrigated
land in Kosovo
Kosovo
41.860
27,9
100,0
Prishtinë
5.136
27,0
25,0
Mitrovicë
3.416
16,5
7,8
Pejë
13.429
50,4
17,4
Gjakovë
12.967
48,4
20,1
Prizren
4.588
19,4
11,0
Ferizaj
1.484
29,0
9,7
840
17,2
9,1
Gjilan
Table 3.3: Irrigation of cultivated land by municipality
Municipality
Kosovo
Deçan
Gjakovë
Gllogovc
Gjilan
Dragash
Istog
Kaqanik
Klinë
F.Kosovë
Kamenicë
Mitrovicë
Leposaviç
Lipjan
Novobërdë
Obiliq
Rahovec
Pejë
Podujevë
Prishtinë
Prizren
Skenderaj
Shtime
Shtërpcë
Suharekë
Ferizaj
Vitie
Vushtrri
Z.Potok
Zveçan
Malishevë
Area (ha)
% of land irrigated
41.860
5.783
2.662
395
251
579
4.753
611
722
1.174
275
684
243
832
218
476
4.522
7.954
1.179
862
2.073
461
264
242
1.451
366
314
1.873
99
55
486
27,9
61,3
35,3
31,6
14,6
13,1
47,7
34,6
20,6
35,1
16,9
21,0
12,8
26,7
23,3
15,6
45,9
71,9
22,5
29,5
33,8
15,5
23,2
45,7
26,5
25,7
21,0
15,6
22,3
11,5
8,0
% of total irrigated
land in Kosovo
100,0
9,2
4,3
6,6
3,2
1,7
5,8
3,5
1,8
2,4
2,5
1,8
0,6
4,6
0,8
0,8
6,6
9,8
5,7
4,0
3,5
2,5
1,6
0,8
4,4
3,8
3,4
1,9
0,7
0,2
1,3
Irrigation, as reported by farmers, is used on around 41.860 ha, representing around 28 percent of
the total cultivated land. By region, the largest share of irrigated land is in Peja and Gjakova. By
municipality, the largest share of irrigated land is in Peja and Deçan. These two municipalities
22
Agricultural Household Survey 2005
have extensive irrigation systems and account for nearly 20 percent of the total irrigated area in
Kosovo. According to the farm structure, among small farms between 25-30 percent of the
cultivated land is irrigated, while in the large and specialized farms around 48 percent are
irrigated.
Farm structure is dominated by small family farms. The land operation is very fragmented and
agricultural holdings are typically under two hectares, and producing for household needs. The
large and specialized farms account for 4.928 ha of agricultural land, or 1,9 percent of the total
agricultural land.
Table 3.4 presents the distribution of farms size by farm structure. Farms are classified in 11
groups according to their agricultural land area. Ninety seven percent of small household farms
are under five hectares, and these account for 81 percent of the agricultural land in small farms,
while 3 percent of farms over five hectares account for 19 percent of the land. In 2005, the mean
farm size of the small household farms, counting agricultural land only, was 1,5 ha. The standard
deviation is small, 1,74.
The distribution of large and specialized farms differs substantially. The mean farm area is 19,3
ha with a standard deviation of 53. Forty five percent of farms are below 5 hectares but the
agricultural land area of these farms accounts for only 7 percent of the agricultural land in large
farms. At the same time, 55 percent of farms are over 5 ha and this group accounts for 93 percent
of the land.
23
Agricultural Household Survey 2005
Table 3.4: Agriculture land by farm size and farm structure
Farm Size
0 - 0.5 ha
0.51 - 1 ha
1.01 - 1.5 ha
1.51 - 2 ha
2.01 - 3 ha
3.01 - 4 ha
4.01 - 5 ha
5.01 - 6 ha
6.01 – 8 ha
8.01 – 10 ha
Over 10 ha
Total
No of farms
33.657
46.145
39.129
14.512
21.610
6.756
3.875
2.412
1.712
702
973
171.483
Small
Area (ha)
10.474
34.895
49.039
25.935
53.484
23.120
17.478
13.240
11.764
6.182
14.728
260.337
% of farms
19,6
26,9
22,8
8,5
12,6
3,9
2,3
1,4
1,0
0,4
0,6
100,0
Large and specialised farms
No of farms Area (ha) % of farms
5
2
2.0
9
6
3.5
4
5
1.6
12
24
4.7
31
78
12.1
32
110
12.5
21
96
8.2
12
65
4.7
31
217
12.1
24
219
9.4
75
4.105
29.3
256
4.928
100.0
24
No of farms
33.662
46.154
39.133
14.524
21.641
6.788
3.896
2.424
1.743
726
1.048
171.739
Total
Area (ha)
10.476
34.901
49.044
25.958
53.561
23.231
17.573
13.305
11.981
6.401
18.833
265.265
% of farms
19,6
26,9
22,8
8,5
12,6
4,0
2,3
1,4
1,0
0,4
0,6
100,0
Agricultural Household Survey 2005
Bearing in mind the number and land area under small farms, the overall size distribution of
agricultural land in Kosovo is almost identical to the distribution of small household farms and the
mean farm size is 1,5 ha. This very fragmented farm structure impedes the development of
commercial agriculture and perpetuates subsistence farming.
Taking all farms together, Figure 3.3 indicates that the largest share of agricultural land, 28
percent, is under farms between 1 and 2 ha.
Figure 3.3: Share of agricultural land in different farm size groups
Over 10 ha
7%
8.01 - 10 ha
2%
6.01 - 8 ha
5%
5.01 - 6 ha
5%
4.01 - 5 ha
7%
3.01 - 4 ha
9%
20%
2.01 - 3 ha
1.01 - 2 ha
28%
17%
0 - 1 ha
0%
5%
10%
15%
20%
25%
30%
Table 3.5 represents the distribution of farms according to the size of their agricultural area and
farm structure by region. The highest concentration of the smallest farms, up to 1.5 ha, is in
Prishtina and Prizren. The large and specialised farms are located mainly in Peja.
Table 3.6 presents the land use by size categories and farm structure. The differences between
the farm groups are substantial. For the smallest farms, the arable land is slightly beyond onethird of the total land area, whilst in the large farms it is two-third. In the smallest household farms,
house yards account for nearly 7 percent of the total area.
25
Agricultural Household Survey 2005
Table 3.5: Farm size groups and farm structure by region
Region
Kosovo
Prishtinë
Mitrovicë
Pejë
Gjakovë
Prizren
Ferizaj
Gjilan
0 - 1.5 Ha (inc.)
Area (ha)
%
142.678
100,0
30.331
21,3
22.671
15,9
12.775
9,0
14.956
10,5
28.562
20,0
14.183
9,9
19.199
13,5
Small farms
1.5 - 3 Ha (inc)
Area (ha)
%
109.372
100,0
27.323
25,0
20.804
19,0
12.624
11,5
14.492
13,3
11.785
10,8
8.009
7,3
14.335
13,1
3 + Ha
Area (ha)
%
104.180
100,0
33.444
32,1
18.842
18,1
14,123
13,6
11.075
10,6
8.120
7,8
5.576
5,4
13.000
12,5
Large and specialised
farms
Area (ha)
%
5.209
100,0
621
11,9
460
8,8
2.409
46,2
532
10,2
356
6,8
499
9,6
331
6,4
Total
Area (ha)
361.439
91.718
62.777
41.931
41.056
48.824
28.268
46.866
%
100,0
25,4
17,4
11,6
11,4
13,5
7,8
13,0
Table 3.6: Total land area by land use and farm structure
Small
1.5 - 3 Ha
0 - 1.5 Ha
Land use
Utilised arable land and kitchen garden
Area (ha)
%
Area (ha)
Large and specialised
farms
Area (ha)
%
3+
%
Area (ha)
%
49.387
34,6
41.627
38,1
44.367
42,6
3.479
66,8
1.534
308
1,1
0,2
1.383
268
1,3
0,2
1.049
318
1,0
0,3
50
14
1,0
0,3
58
0,0
74
0,1
20
0,0
10
0,2
Meadows
Subtotal Cultivated Land
Pastures
Left fallow
34.509
85.796
4.651
7.403
24,2
60,1
3,3
5,2
27.945
71.297
2.303
7.403
25,6
65,2
2,1
6,8
26.132
71.88 6
1.425
8.174
25,1
69,0
1,4
7,8
1.258
4.811
46
71
24,2
92,4
0,9
1,4
Subtotal Agric Land
Forestry
97.850
33.964
68,6
23,8
81.003
22.729
74,1
20,8
81.485
19.770
78,2
19,0
4.928
238
94,6
4,6
Orchards
Vineyards
Greenhouse
House yard
Other
Total
9.679
1.185
142.678
6,8
4.367
4,0
2.000
1,9
36
0,7
0,8
100,0
1.273
109.372
1,2
100,0
927
104.182
0,9
100,0
6
5.208
0,1
100,0
26
Agricultural Household Survey 2005
During the Survey data were collected about the ownership status of land plots. Table 3.7
indicates that the small farms operate almost exclusively on their own land. Large and
specialised farms use predominantly rented land. They are depending on state land; nearly 54
percent of their agricultural land is rented from the state.
Table 3.7: Agricultural land area by ownership and farm structure
Ownership
Owned
Rent from private individual
Use private land for free
Rent from state
Use state land for free
Other
Total
Small farms
Area (ha)
%
339.392
95,27
7.379
2,07
4.633
1,30
3.665
1,03
999
0,28
163
0,05
356.230 100,00
27
Large and
specialised
Area (ha)
%
1.575
30,24
759
14,58
63
1,21
2.806
53,87
6
0,12
0
0,00
5.209
100,00
Total
Area (ha)
%
340.966
94,34
8.138
2,25
4.696
1,30
6.471
1,79
1.005
0,28
163
0,04
361.439
100,00
Agricultural Household Survey 2005
4. Crops
The main areas of arable land are concentrated in valleys and flat areas in the north and east.
Traditionally, vegetable and fruit production has been concentrated mainly in the west. Recently,
fruit production has started increasing in other parts as well. Grazing pastures and forests are
located in the mountain areas.
This chapter presents data on areas under cultivation by crop (in hectares); production levels (in
tonnes) and yields (in tonnes per hectare). Figure 4.1 portrays the main crops cultivated in
2005, grouped in five categories: grains; fodder crops; vegetables; fruits; and, others6.
Figure 4.1: Area under crops by categories
Other
0,1%
Fruits
2,1%
Grains
49,0%
Fodder crops
41,4%
Vegetables
7,4%
The survey results show that cereals and fodder crops account for the largest area of cultivated
land in Kosovo, around 90 percent, while fruit and vegetables account for the remaining 9.5
percent.
Favourable agronomic conditions prevailed in 2005. This has been reflected in the overall
production levels and yields. Table 4.1 shows the planted area, production and yield by crop.
6
Industrial crops and seedlings
28
Agricultural Household Survey 2005
Table 4.1: Crop area, production and yield *
Crop
Area (ha)
Grains
114.622,1
Wheat
69.349,2
Rye
468,3
Barley
3.355,5
Malting barley
986,9
Oats
3.502,9
Maize
15.996,9
Maize (mixed
20.962,3
Vegetables
17.333,1
Potato
3.806,6
Tomato
741,3
Aubergine
11,2
Pepper
2.620,5
Pumpkin
65,4
Pumpkin (mixed
1.332,6
Courgette
88,7
Mushroom
0,2
Cucumber
235,6
Water melon
630,7
Melon
135,7
Cabbage
775,9
Cauliflower
28,6
Spinach
53,3
Lettuce
35,0
Beetroot
22,5
Parsley
6,1
Leek
65,8
Onion
852,1
Radish
1,5
Garlic
111,9
Beans
293,9
Beans (mixed
5.349,8
Peas
21,5
Other legumes
12,3
Carrot
34,3
Yield
Production (t) (t/ha)
273.376,7
1.360,3
11.268,3
2.842,9
9.835,4
62.222,6
79.917,6
3,9
2,9
3,4
2,9
2,8
3,9
3,8
87.361,2
15.020,4
158,8
54.988,6
738,1
8.305,7
1.543, 0
2,5
6.074,3
13.464,6
2.127,4
18.938,0
202,2
424,5
434,1
174,8
43,9
999,9
11.033,0
22,4
538,7
776,4
7.479,7
111,7
85,8
318,8
23,0
20,3
14,2
21,0
11,3
6,2
17,4
10,7
25,8
21,3
15,7
24,4
7,1
8,0
12,4
7,8
7,2
15,2
12,9
14,6
4,8
2,6
1,4
5,2
7,0
9,3
Crop
Fodder crops
Hay (meadow)
Grass
Lucerne
Trefoil
Vetch
Wheat fodder (green)
Rye fodder (green)
Barley fodder
Oat fodder (green)
Maize fodder (green)
Fruits
Apple
Pear
Quince
Medlar
Plum
Apricot
Peach
Cherry
Sour cherry
Walnut
Hazelnut
Chestnut **
Strawberry
Raspberry
Blackberry
Vine grape
Grape
Other
Yield
Area (ha) Production (t) (t/ha)
96.777,3
65.680,9
186.959,1
2,8
7.506,5
31.301,6
4,2
13.011,2
55.365,1
4,3
3.615,4
13.342,7
3,7
193,3
1.065,9
5,5
210,7
1.128,7
5,4
70,9
227,2
3,2
38,0
227,0
6,0
4.995,8
24.462,3
4,9
1.454, 6
25.620,4
17,6
4.924,4
1.081,0
7.085,0
6,6
380,5
2.759,2
7,3
47,4
293,8
6,2
14,9
78,3
5,3
2.143,2
12.032,3
5,6
31,7
178,2
5,6
38,4
173,2
4,5
60,9
320,8
5,3
47,4
249,5
5,3
66,4
388,0
5,8
3,7
10,7
2,9
419,7
55,6
299,0
5,4
0,8
1,4
1,8
44,8
54,2
1,2
364,0
2.167,0
6,0
543,5
3.495,6
6,4
127,7
Notes:
* This table does not include production of the second crop: maize 803 tonnes , tomatoes 311 tonnes , peppers 261 tonnes , cucumbers 141
tonnes , cabbage 135 tonnes ,
spinach 267 tonnes , salad 1 tonne. Also it does not include autumn crop: wheat 53,000 ha, rye 600
ha, barley for beer 370 ha, mixed grass 100 ha, lucerne 170 ha, trefoil 130 ha, vetch 70 ha.
** Area under Ches tnut (1,547 ha) is recorded as forest land and is not included in fruits.
The table shows that wheat and maize are the most important crops in Kosovo in terms of
cultivated area and production. The most important vegetables are beans (particularly as a
mixed crop with maize), potato and pepper. Within the group of fodder crops, hay (meadow) and
Agricultural Household Survey 2005
alfalfa have the largest areas and production. In 2005, the yields were good, particularly for
arable crops such as wheat, maize and feed barley, as well as for potatoes, beans and peppers.
In orchards, the largest area is under plums and apples. In 2005, around 7.000 tonnes of apples
and 12.000 tonnes of plums were produced. Although the agri-ecological conditions for fruit
production are relatively good and labour is available, the sector faces several impediments for
further development. There has been a lack of investments due to the limited financial capacity
of agricultural households. Orchards are old and the varieties are of low quality. Some
municipalities such as Klina, Istog, Peja, Gjakova and Gjilan are better known for their fruit
production.
In Survey, information was collected about the cultivated land area with zero production. Figure
4.2 shows the planted area with zero production.
Figure 4.2: Planted area with zero production by crop group
1000
913
900
800
700
ha
600
500
400
300
320
213
200
116
100
0
Grains
Vegetables
Fodder crops
Fruits
Altogether, in 2005 there were 1.562 ha with zero production. On average, this represents a low
share of the planted area, 0,7 percent. However, the figure indicates that the largest area with
zero production was under orchards. In 2005, it accounted for 23 percent of the total area under
fruit trees. The main reasons for the lack of production were either, too old orchards or too new
plantings, hail and frost, and plant diseases. The importance of different reasons, as stated by
farmers, is presented in Figure 4.3.
30
Agricultural Household Survey 2005
Figure 4.3: Reasons for zero production
Other,
5%
Other weather conditions,
11%
New plants, 40%
Frost, 15%
Disease, 29%
2005 survey also collected data about the use of crop harvest. This information can provide
useful insights into the degree of commercialization of agricultural households. Table 4.2 shows
the share of crop use by region.
Table 4.2: Average use of harvested crops by region in percent
Region
Household
needs
Animal feed
Sold
Processed and
then sold
Lost
Kosovo
69,0
21,6
5,6
0,4
3,5
Prishtinë
74,6
18,9
4,8
0,2
1,5
Mitrovicë
70,6
21,3
5,3
0,3
2,6
Pejë
67,5
20,7
8,6
0,1
3,1
Gjakovë
62,5
22,4
9,8
0,5
4,8
Prizren
62,7
27,5
5,9
0,0
3,9
Ferizaj
78,6
15,5
3,0
0,1
2,9
Gjilan
66,2
24,8
1,9
1,4
5,6
Data indicate that crops are mainly used within the households, either directly for human
consumption (between two-thirds and three-quarters of the harvest) or as feedstuff for animals.
The share of commercialised production, either as primary agricultural products or after some
processing, is small, varying from 3 percent in Ferizaj and Gjilan to 10 percent in Gjakove.
Harvest losses vary amongst regions, reaching 5,6 percent in Gjilan.
Figure 4.4 presents the use of crop by farm structure, namely small farms, and large and
specialised farms.
31
Agricultural Household Survey 2005
Figure 4.4: Average use of harvested crops by farm structure in percent
Small farms
Processed and sold
0.4%
Sold
5.3%
Lost
3.2%
Animal feed
21.1%
Household needs
70.0%
Large and specialised farms
Sold
16.7%
Processed and sold
0.2%
Lost
3.6%
Household needs
54.1%
Animal feed
25.4%
As noted in Chapter 1 the holdings referred to as ‘large and specialised farms’ are defined as
those holdings that are outside the normal distribution for farm size for the different farm types. It
is also stated in Chapter 1 that this farms are not necessarily commercial farms. This is reflected
in the Figure. Although the large and specialised farms sell a larger share of their production than
the small farms, they still sell less than one-fifth of the output. This points out towards the
overwhelmingly subsistence character of Kosovo agriculture. The large and specialised farms use
a slightly larger share of crops for animal feed than the small farms as they are more specialised
in livestock production.
32
Agricultural Household Survey 2005
5. Forestry
Forestry is an important sector in Kosovo for economic, environmental and social reasons. New
legislation for forestry management has recently been introduced based on international
conventions.7 In the Survey information was gathered from households on forests in the
agricultural household sector, wood usage and types of wood used. 8
Table 5.1 presents for each region the number of agricultural households that possess forest.
Table 5.1: Agricultural households with forest by region
Region
Kosovo
Prishtinë
Mitrovicë
Pejë
Gjakovë
Prizren
Ferizaj
Gjilan
Total No.of HHs
172.328
44.747
24.240
18.941
19.451
26.962
15.214
22.773
HHs with forest
77.165
15.087
14.681
5.928
8.039
15.372
9.079
8.979
%
45
34
61
31
41
57
60
39
The largest share of households that have forest is in Mitrovicë and Ferizaj. At municipality level
the highest share of households with forest is in Zubin Potok, Zveçan, Kaçanik and Leposaviç.
The territory of these municipalities is known to be mountainous. The importance of forests in
these areas is high and in many cases wood is an important source of income for agricultural
households.
Table 5.2: Wood utilization by region in cubic meters (m³)
Region
Total utilization
Fire wood
m³
m³
Technical/Industrial
m³
Kosovo
Prishtinë
400.480
76.697
393.109
75.558
7.371
1.139
Mitrovicë
86.180
85.375
805
Pejë
Gjakovë
21.127
36.073
21.104
35.934
23
139
Prizren
58.237
57.712
526
Ferizaj
Gjilan
59.788
62.378
59.757
57.669
31
4.709
Table 5.2 presents reported wood utilisation by region. Most firewood is used in the region of
Mitrovice.
Wood utilisation falls into two categories, firewood and technical/ industrial wood. Most wood is
used as firewood, while only 2 percent is used for technical and industrial 9 purposes (Figure
7
The forestry law of Kosovo was approved in 2003. It provides for forest management based on the annex III of the
United Nations Session Report on Environment and Development (Rio De Janeiro from 3 -14 June, 1992).
8
Additional information regarding Kosovo forestry can be obtained from MAFRD, Forestry Department, Forestry
Inventory 2002/2003.
9
Electrical poles, railway pontoon/connectors, furniture, flooring, and tannin and cork from wood bark.
33
Agricultural Household Survey 2005
5.1). This is expected, given that most of the woods in Kosovo are not suitable for production or
technical-industrial usage.
Figure 5.1: Utilization of forests
Technical/Industrial
2%
Fire Wood
98%
The most important forests in Kosovo are oak and mixed beech and oak. Figure 5.2 indicates
the types of wood used.
Figure 5.2: Wood type
Spruce/Pine/Fire
1%
Chestnuts
2%
Willow/Poplar
1%
Beech
6%
Oak
37%
Beech/Oak Mixed
53%
34
Agricultural Household Survey 2005
6. Livestock
Statistics on the number of animals according to the size of household farm, small or large and
specialised, were gathered by the Survey. In Kosovo there are a number of relatively large
household farms specialised in livestock. Information was also gathered about the livestock
products sold in order to provide insights into their contribution to the cash revenue of
households.
Table 6.1 shows the number of livestock by type and farm structure (small and large and
specialized farms).
Table 6.1: Livestock number as of October-November 2005
Livestock type
Cattle
Calves less than 6 months
Bulls and heifers 6 months to 1 year
Bulls and heifers 1 year to 2 years
Bulls and heifers more than 2 years
Milk cows
Bulls
Buffalo
Pigs
Piglets up to 6 months
Bearing sows
Boars for insemination
Sheep and goats
Lambs
Sheep for breeding
Rams for insemination
Goats
Equines
Horses
Donkeys
Poultry
Chickens
Other poultry
Beehives
Small farms
349.196
76.282
52.747
22.341
7.300
185.316
4.609
602
47.348
24.390
14.678
8.281
135.789
19.826
93.672
14.327
7.964
6.718
6.159
559
2.160.466
1.978.242
182.224
69.378
Large and
specialised farms
2.631
447
362
241
130
1.391
40
20
116
83
23
10
16.091
3.337
10.982
821
951
85
76
9
470.549
408.209
62.340
194
Total
351.827
76.729
53.109
22.582
7.430
186.707
4.649
622
47.464
24.473
14.701
8.291
151.880
23.163
104.654
15.148
8.915
6.803
6.235
568
2.631.015
2.386.451
244.564
69.572
Cattle are the major livestock, of which 53 percent are dairy cows. Households have a small
number of buffalo, around 622, which are included in total cattle. In 2005, less than 1 percent of the
cattle herd were in the large and specialised household farms. The cattle herd is very
fragmented. The average number of cattle per household for households with cattle is 1,26 in the
small farms and 4,3 in the large and specialised farms. The average number of milk cows
for those households that have milk cows is 1,53 in the small farms and 4,4 in the large and
specialised farms. Dispersion is typical for other type of livestock as well. The small farms have
on average 17 sheep and goats, and 19 poultry, whilst the large farms have much higher
numbers. These statistics underline the subsistence character of livestock sector in the small
household farms.
35
Agricultural Household Survey 2005
The data presented in Table 6.1 differ from the one included in the Agricultural Household
Survey 2004 due to the change in the approach to the definition of weights, presented in
Chapter 1. When the new approach is applied to 2004 data (see Annex 1) it appears that there
was an increase in the total number of cattle by around 5 percent, chicken by 12 percent, but a
substantial decrease of the pig population, by 14 percent.
The livestock numbers presented in the above table are as of October-November 2005. The
survey also recorded the number of purchased, slaughtered and sold animals during the year
(Table 6.2). In Kosovo households sell young cattle, mainly up to one year old.
Table 6.2: Number of animals purchased, sold or slaughtered
Animal Type
Subtotal cattle
Calves less than 6 months
Bulls and heifers 6 months to 1 year
Bulls and heifers 1 year to 2 years
Bulls and heifers more than 2 years
Milk cows
Bulls
Buffalo
Subtotal pigs
Piglets up to 6 months
Bearing sows
Boars for insemination
Subtotal sheep and goats
Lambs
Sheep for breeding
Rams for insemination
Goats
Subtotal horses/donkeys
Horses
Donkeys
Subtotal poultry
Chickens
Other poultry
No. Purchased
16.018
3.087
3.413
1.772
988
6.513
229
16
4.475
1.675
314
2.486
14.615
1.665
11.155
1.795
81
81
.
407.405
345.085
62.320
36
No.
Sold
46.015
14.307
12.956
6.725
1.401
10.246
379
24.570
22.498
1.234
837
63.626
44.964
7.843
6.743
4.075
175
175
.
138.024
127.853
10.171
No.
Slaughtered
30.738
5.486
12.100
6.417
2.320
4.140
192
83
22.050
5.409
6.163
10.479
9.863
3.950
2.947
575
2.391
.
.
.
765.287
718.184
47.102
Agricultural Household Survey 2005
In 2005, some households (around 40,000) sold also livestock products (Table 6.3).
Table 6.3: Livestock products sold
Livestock products
Average
value/HH (Euro)
No. of HHs
Total value
(Euro)
Meat
2.623
1.034
2.713.294
Milk
14.343
502
7.194.335
Cheese
13.871
246
3.414.864
Fat (grease)
1.486
188
279.378
Other dairy products
4.384
202
885.955
Eggs
1.934
2.461
4.760.272
Honey
1.343
571
767.513
841
299
251.356
40.826
496
20.266.967
Other products
Total
Although meat has the highest average value per household, a relatively low number of
households sell meat in comparison to dairy products (milk and cheese). In Kosovo, the sales of
meat by households are seasonal and occur either during late autumn to preserve meat for the
winter season or are related to religious festivals. Eggs are mainly sold by large and specialised
farms.
37
Agricultural Household Survey 2005
7. Agricultural inputs
In the Survey data were collected about agricultural inputs, namely agricultural machinery and
equipment, fertilisers and manure. Data were not collected on the use of equipment, operating
costs or equipment hire. Data were not collected on fertiliser prices or on the use of other inputs
either. Labour input is discussed separately in Chapter 8.
Agricultural machinery and equipment
Information was gathered regarding the number of machinery and equipment, and the number
of households who own different machinery. The value figures, indicated as unit values, refer to
the owner’s judgment on how much they could get for the machine if they sold it. As in the
previous Agricultural Household Surveys, it is supposed that for various reasons the owner’s
judgment tends to underestimate the market value.
Table 7.1 shows machinery, equipment and implements owned by farms presented by farm
structure (small farms and large and specialised farms).
38
Agricultural Household Survey 2005
Table 7.1: Machinery and equipment in agricultural households
Small farms
Equipment type
% of farms
owning
machinery
Number
owned
Unit
value
21,5
33,8
46,6
13,2
26,4
39,0
6,0
3,8
3,9
0,6
1,8
8,8
5,9
0,7
0,5
2,2
0,5
25.050
46.605
60.296
14.589
30.808
46.770
6.076
3.349
2.951
506
3.661
2.860
228
311
211
758
742
598
280
672
678
684
460
1.462
1.349
3.213
426
9,7
3,1
6,1
6,0
2,5
1,1
12.544
0,8
4,6
2,3
1,2
0,5
Large and specialised farms
% of
Number
Unit
farms
owned
value
owning
machinery
Tractor and associated machines
Large tractor ( over 40 HP)
Small tractor ( under 40 HP)
Plough
Disk harrow
Tooth harrow
Trailer
Sowing machine
Miller machine
Fertiliser spreader
Manure spreader
Sprayer
Mower
Hayrack
Corn silage machine
/Potato lifter ( with cleaning drum)
Hay baler
Intertillage implements
Motocultivator and associated machine
Motocultivator
Plough
Trailer
Miller machine
Mower
Intertillage implements
Other machinery and equipmen
Combine harvester
Mill ( larger- for farm use)
Water pump ( large capacity)
Milking machine
Other
45,9
55,6
70,7
29,3
51,0
71,0
33,2
29,7
30,5
5,4
31,3
29,7
21,2
12,7
13,9
15,4
7,3
186
166
285
104
158
238
125
90
100
18
103
97
69
35
38
47
24
8.713
3.850
619
777
358
1.326
1.502
990
664
1.562
859
1.080
595
1.627
1.536
3.844
752
8.032
7.107
2.948
1.570
1.097
144
335
254
276
194
25,9
9,7
11,6
22,0
4,6
3,9
76
28
31
64
12
10
1.378
138
372
393
358
360
964
3.767
1.932
727
476
6.936
356
489
515
756
9,7
21,6
17,0
10,8
3,9
42
65
65
50
11
11.088
817
1.064
1.664
2.696
1.427
7.278
4.350
370
391
1.709
387
4.177
Farmers own quite a large number of tractors. The comparison between small and large farms
indicates that around 55 percent of small farms own a tractor, whilst it appears that all large
farms have a tractor. Having in mind the tiny plots of arable area on the small farms, the
difference in comparison to the large farms is not surprising, as small farmers may use
contracted machinery services or hire machinery instead of purchasing their own. They are also
financially constrained. Most of the tractors owned by small farms are below 40 horse power.
The majority of equipment owners also own a plough, harrow and trailer. Other types of
equipment are fairly uncommon. Although combine harvesters are not commonly owned, the
survey indicates there are about 1006 in Kosovo. Around 10 percent of large and specialised
farms own a combine harvester.
39
Agricultural Household Survey 2005
The equipment available, in terms of quantity, as data about the age of machinery were not
collected, appears to be enough for the cultivated area. Although much better mechanized, the
large farms make little difference to the number of machines owned at Kosovo level.
For the same type of machinery and equipment, the unit values are often higher on the large
farms than in the small farms. Large farmers own more powerful, more expensive and better
maintained equipment.
Use of fertilizers and manure
Table 7.2 presents the percentage of households who use different types of fertilizers.
Fertilizers are used by most farmers. NPK, often used as a base dressing at planting, is the
most frequently used of all in-organic fertilizers, and most of the rest are NAG and Urea, which
are mainly used as top dressing applications after crop germination. NPK is used by 75 percent
of small farms and 82 percent of large farms. An agricultural household may use more than one
type of fertilizer.
Table 7.2: Use of fertilizers and manure by household (%)
Type
NPK
NAG
URE
Other
Manure
Small farms
74,6
35,1
42,7
1,5
53,7
Large & specialised farms
81,9
40,5
42,5
1,5
68,0
Altogether 11 percent of small farms and 8 percent of large farms do not use any kind of
fertilisers. Around 56 percent of small farms and 32 percent of large farms do not use manure.
Only about 5 percent of farms use neither fertilisers nor manure. A slightly larger proportion of
large farms use fertilisers and/or manure than small farms. The main reasons are the financial
capacity of large farms to purchase inputs and the stricter application of farm technologies by
larger farmers. Some of the small farmers also lack proper technological knowledge.
Table 7.3 shows the use of fertilisers and manure according to crop group.
Table 7.3: Use of fertilizer and manure by crop group*
Fertilizers
Crops
kg/ha
13,.93
117
731
6
175.596
1.532
152
1.761
102
462
27
80.740
4.658
2.227
23
2.661
27
104
1
101,398
1.048
138
170
35
150
30
21
4
12.189
2.475
141
4
60
179
14.760
63
Area (ha)
NPK (t)
kg/ha
NAG (t)
kg/ha
114.622
27.684
242
9.718
85
Vegetables
17.333
5.492
317
2.636
Fodder crops
96.777
7.904
82
4.924
682
Grains
Fruits
Other **
Total
128
233.784
8.5
41.780
Manure
Other
(t
URE (t)
5
17.975
kg/ha Used (t)
kg/ha
72
0
0
276
3.808
77
1,318
6
370.475
1.585
Notes: * The table does not include fertilizer used on the second crop, which are 22 tones NPK; 24 tones NAG; 7
tonnes URE and 373 tonnes manure.
** Industrial and medical crops, seedlings
Table 7.3 shows the use of fertilizers and manure by crop; crops are presented in groups and
the average use of fertilizers and manure per hectare is indicated. It is important to point out that
the quantities are in gross terms. This means that there is not direct information about the net
40
Agricultural Household Survey 2005
use of active substances in different fertilizers. Vegetables have the highest application rate per
hectare, with 317 kg /ha NPK, 152k g/ha NAG, 102 kg/ha UREA and around 4.658 kg/ ha
manure. Grains have 242 kg /ha NPK, 85 kg/ha NAG, 117 kg/ha UREA and 1.532 kg/ ha
manure. Most of the fertilizers were used for cereals.
41
Agricultural Household Survey 2005
8. Agricultural labour
Data about agricultural labour are important in order to assess to what extent agriculture can
absorb rural labour and the degree to which non-farm jobs are required in rural areas. The latter
can indicate that policies beyond agriculture, targeting rural development are necessary. For
this reason, the Survey collected information about the employment on-farm of household
members depending on their commitment to farming, full-time, part-time or occasional. Persons
who worked at least 20 hours per week in agriculture were classified as part-time engaged in
farming; those who worked around 56 hours per week were considered as engaged full-time
and persons who worked less than 20 hours were defined as occasional labour.
Information was also collected about the number of working days of hired farm labour. Their
working days were subsequently converted into Annual Work Units (AWU) using standards from
EU member countries. One AWU was estimated to be equal to 1.800 working hours. The length
of the working day was defined at 8 hours resulting in 225 working days per year per one fulltime employed.
Table 8.1 presents the number of household members engaged on the farm by gender and
degree of commitment to the household farm.
Table 8.1: The number of household members engaged on-farm
Age
< 16 yrs
16-65 yrs
> 65 yrs
Total
Age
< 16 yrs
16-65 yrs
> 65 yrs
Total
Age
< 16 yrs
16-65 yrs
> 65 yrs
Total
Male Full Time
Number
%
9.717
76,7
93.964
81,1
4.732
76,3
108.413
80,5
Full Time
Female Full Time
Number
%
2.947
23,3
21.835
18,9
1.472
23,7
26.254
19,5
Part Time
Male Part Time
Female Part Time
Number
%
Number
%
11.822
55,2
9.605
44,8
93.523
61,6
58.245
38,4
5.758
69,9
2.480
30,1
111.104
61,2
70.331
38,8
Occasional
Male Occasional
Female Occasional
Number
%
Number
%
14.353
52,2
13.122
47,8
88.047
49,3
90.372
50,7
5.114
43,5
6.644
56,5
107.515
49,4
110.138
50,6
Total
Number
12.663
115.799
6.205
134.667
%
100,0
100,0
100,0
100,0
Total
Number
21.428
151.769
8.238
181.434
%
100,0
100,0
100,0
100,0
Total
Number
27.475
178.420
11.758
217.653
%
100,0
100,0
100,0
100,0
Altogether, 533.755 members of working age have some degree of engagement in on-farm
work. This represents nearly 57 percent of all members of agricultural households above 14
years of age. It is obvious that agriculture alone cannot provide employment for the agricultural
population and other sectors of the economy should be at least as important in providing
employment in rural areas as farming.
The table shows that for all age groups the participation of male members of households in fulltime on-farm work is much larger than the female one (about fourth-fifth of all full-time engaged
household members are male). There are also gender differences among people who work
42
Agricultural Household Survey 2005
part-time, but they disappear in the group engaged occasionally in farming, e.g. 49 percent male
and 51 percent female. The prevalence of female as occasional labour is particularly obvious in
the highest age group, above 65 years of age. Usually females in this age group are engaged in
easier on-farm tasks.
Most of the household members engaged in agriculture, 84 percent, are of active working age,
between 16 and 65 years old. The remaining are either young people below 16 years of age, 12
percent, or people at retirement age above 65. Young people are mainly engaged occasionally
or part-time as they are at the age when most of them are in full-time education.
Table 8.2 presents the number of days worked on household farms by hired waged workers.
Gender and age data are also given.
Table 8.2: Hired agricultural labour, working days
Age
< 16 yrs
16-65 yrs
> 65 yrs
Total
Male Person Days
Number
572
354.193
0
354.765
%
99,1
98,3
0
98,3
Female Person
Days
Number
%
5
0,9
6.143
1,7
0
0
6.148
1,7
Total
Number
577
360.335
0
360.913
%
100,0
100,0
0
100,0
Table 8.2 indicates that people who are 65 years of age and older are not used as hired labour.
Applying the procedure to convert working days into Annual Work Units (AWU) explained
above, the working days in the table represent 1,604 full-time employed hired waged persons.
This small number of hired agricultural workers is related to the small size of household farms
which cannot absorb much labour in addition to the household members. Moreover, the average
number of members per household in Kosovo is high, providing abundant household labour.
The predominant proportion of hired labour is male. Most frequently, the wage per day falls
within the range of 10-12 Euro (Table 8.3). Small gender differences in the pay of persons in
active working age are observed.
Table 8.3: Average wage by age group and gender (Euro)
Age
< 16 yrs
16-65 yrs
Average wage
Male
Female
10,0
10,0
12,4
11,6
Table 8.4 shows household members engaged in farming in full-time equivalent by region. In
order to provide this information, it has been assumed that two part-time workers are equivalent
to one full-time engaged in agriculture and that four occasional workers are equivalent to one
full-time worker.
43
Agricultural Household Survey 2005
Table 8.4: Full-time equivalent workers by gender by region
Region
Kosovo
Prishtinë
Mitrovicë
Pejë
Gjakovë
Prizren
Ferizaj
Gjilan
Male
190.844
43.407
29.002
25.518
20.228
33.311
19.154
20.224
Female
88.954
16.071
9.710
15.079
13.354
16.845
10.162
7.733
Total
279.798
59.479
38.712
40.596
33.583
50.156
29.315
27.957
The regions of Prishtina and Prizren have the highest number of agriculture household
members engaged on-farm in full-time equivalent. This applies to both genders.
44
Agricultural Household Survey 2005
9. Farm expenditure
Data about farm expenditure and revenue were collected during the Agricultural Household
Survey in an attempt to fill the existing gap in respect to economic statistics at farm and
household level. Gradually, such farm level economic data will be made available through the
Farm Accountancy Data Network (FADN), consistent with the EU definitions. Data on farm
expenditure are sensitive to the way farmers value their own labour and household members
labour input on-farm. Commonly, this value is under-reported, resulting in an underestimation of
wage and salary costs.
The mean expenditure per farm is 703 Euro and the reported cash revenue is 744 Euro. Small
farms report expenditure of 656 Euro and cash revenue of 678 Euro. Compared to 2004, when
costs exceeded cash revenue, in 2005, on average, the revenue was enough to cover
production expenditure. However, the cost-revenue difference is negligible. This is due to the
fact that the largest part of the production is consumed on-farm. This production has not been
valued and therefore has not constituted part of the revenue. This means that farming is used
mainly to cover household needs. In order to have cash income, agricultural households need
alternative sources of income.
The large and specialised farms have much higher cash revenues, the mean is 41,849 Euro
and the average expenditure are 30,780 Euro.
Table 9.1 shows farm production expenditure by major items and by farm structure.
The main categories of expenditure are fertilizers, contracted services and rent paid for hired
machinery, fuel, animal feed and purchase of livestock, and seeds. These items account for
more than three-quarters of farm expenditure for the sector. The small share of expenditure on
maintenance of farm buildings is due to the fact that often the only asset small household farms
possess is a plot of land. The other cost item with a very small share in total farm expenditure is
interest paid on loans. In Kosovo bank loans are not widely used in farming. Farmers borrow
informally from friends and family without any formalised arrangements for payment of interest.
Some farmers tend not to count these as loans. Wages and salaries have a low share, 5
percent of total farm expenditures. This is due, first, to the low level of wages, and second, to
the fact that usually farmers do not account for the expense of their own labour or the expense
of other household members.
There are large differences in the structure of expenditure between small and large farms. Small
farms spend around 60 percent of their total expenditure on crop cultivation, namely seeds,
fertilizers, fuel, and contracted services and machinery hire. Several large farms specialise in
livestock. This has influenced their costs of which 51 percent are for animal feed and livestock
purchase. Large farms have hired labour and pay 10 percent of total expenditure as wages and
salaries. As expected, they use more non-owned buildings and capital and, thus, also pay more
for rentals of land and buildings, and interest on loans.
45
Agricultural Household Survey 2005
Table 9.1: Structure of farm expenditure
Small farms
Expenditure type
Fertilizers
Manure
Chemicals
Seeds
Animal feed
Livestock purchase
Veterinary services
Wages and salaries
Fuel
Machinery repairs and maintenance
Contracted services & rent for machinery hire
Maintenance and repair of farm buildings
Rental of farm land and buildings
Electricity, telephone etc.
Interest on loans
Other operative expenditures
Total expenditure
Euro
(‘000s)
16.912
289
2.199
7.465
6.656
8.201
2.172
3.655
11.031
3.477
13.387
1.389
1.327
1.298
237
1.856
81.552
%
20,7
0,4
2,7
9,2
8,2
10,1
2,7
4,5
13,5
4,3
16,4
1,7
1,6
1,6
0,3
2,3
100,0
Large and
specialized
farms
Euro
%
(‘000s)
481
5,9
24
0,3
156
1,9
494
6,0
2.946
35,8
1.271
15,5
83
1,0
843
10,3
510
6,2
125
1,5
171
2,1
175
2,1
399
4,9
90
1,1
183
2,2
269
3,3
8.218
100,0
Total
Euro
(000’s)
17.393
313
2.355
7.959
9.602
9.472
2.255
4.498
11.541
3.601
13.558
1.564
1.726
1.388
420
2.125
89.771
%
19,4
0,3
2,6
8,9
10,7
10,6
2,5
5,0
12,9
4,0
15,1
1,7
1,9
1,5
0,5
2,4
100,0
Table 9.2 shows farm expenditure per region. In order to simplify the table, some cost
categories have been aggregated. Fertilisers, manure and chemicals have been put together in
the group ‘fertilisers and agro-chemicals’; animal feed, purchase of livestock and veterinary
services are under the general category of ‘livestock’; machinery repairs and maintenance,
contracted services and rent for machinery hire, and fuel are under ‘machinery’. All smaller
items have been aggregated into ‘other expenses’.
Table 9.2: Type of farm expenditure by region (‘000s Euro)
Region
Fertilizers
and agrochemicals
Seeds
Livestock
Machinery
Wages and
salaries
Other
expenditure
Total
Kosovo
20.061
7.959
21.329
28.700
4.498
7.223
89.771
Pristinë
5.199
1.916
4.726
7.102
1.060
1.252
21.254
Mitrovicë
2.335
1.311
2.582
3.535
516
450
11.029
Pejë
2.266
991
2.613
2.821
548
669
9.907
Gjakovë
3.395
1.133
3.555
5.295
1.070
2.960
17.408
Prizren
2.151
892
4.039
3.801
500
398
11.781
Ferizaj
1.426
660
1.411
2.339
292
764
6.892
Gjilan
3.290
1.057
2.402
3.808
511
430
11.499
22
9
24
32
5
8
100
Percent (%)
46
Agricultural Household Survey 2005
Annex 1. List of municipalities by region
ALBANIAN
Region
Municipality
SERB
Region
Municipality
Gjakovë
Deçan
Rahovec
Gjakovë
Ðakovica
Dečane
Orahovac
Ðakovica
Gjilan
Gjilan
Kamenicë
Viti
Gnjilane
Gnjilane
Kamenica
Vitina
Mitrovicë
Skenderaj
Vustrri
Leposaviç
Mitrovicë
Zveçan
Zubin Potok
Mitrovica
Srbica
Vučitrn
Leposavič
Mitrovica
Zvečane
Zubin Potok
Pejë
Pejë
Klinë
Istog
Pec
Peč
Klina
Istok
Prishtinë
Obiliq
Fushë Kosovë
Lipjan
Prishtinë
Podujevë
Novobërdë
Gllogovc
Priština
Obilič
Kosovo Polje
Lipljan
Priština
Podujevo
Novobrdo
Glogovac
Prizren
Dragash
Suharekë
Malishevë
Prizren
Prizren
Dragaš
Suva Reka
Mališevo
Prizren
Ferizaj
Shtime
Kaçanik
Stërpcë
Ferizaj
Uroševac
Štimlje
Kačanik
Štrpce
Uroševac
47
Agricultural Household Survey 2005
Annex 2. AHS 2004 adjusted tables
Selected tables from the Agricultural Household Survey 2004 have been adjusted using the same
methodology for determining weights as in 2005. These tables are presented in this annex for
comparative purposes only.
Table 2: Agriculture population by age-group
Age group
Number
%
Cumulative %
Up to 14 years
15 - 29 years
392.957
382.757
30,4
29,6
30,4
59,9
30 - 49 years
311.992
24,1
84,1
50 - 64 years
65 and over
129.647
76.665
10,0
5,9
94,1
100,0
1.294.018
100,0
Total
Table 7: Land use
Land Type
Area (ha)
Utilized arable land
Kitchen gardens
Orchards
Vineyards
Green house
Meadows
Subtotal cultivated land
Pastures
Left fallow
Subtotal agricultural land
House yard
Forestry
Other
Total land area
153.386
3.272
4.458
1.291
255
73.016
235.678
6.011
23.260
264.948
12.993
81.411
123
359.476
48
Agricultural Household Survey 2005
Table 12: Crop area, production and yield
Crop
Area (ha)
Production Yield
(t)
(t/ha)
Grains
112.266
Wheat
69.405
262.335
3,8
425
1.155
2,7
Rye
Barley
Barley for beer
3.451
9.956
2,9
952
3.067
3,2
Crop
Area (ha)
Forage crops
101.425
Production
(t)
Yield
(t/ha)
Hay (meadow)
Mixed grass
68.444
4.572
176.627
13.205
2,6
2,9
Lucerne
Trefoil
17.432
3.830
62.554
12.732
3,6
3,3
Oats
3.456
7.396
2,1
Vetch
295
1.078
3,7
Maize
34.578
124.224
3,6
Vegetables
16.123
Wheat (green)
Rye (green)
143
683
554
1.734
3,9
2,5
Potatoes
3.246
68,641
21,1
Barley (green)
78
238
3,0
Tomato
845
15.209
18,0
Aubergine
14
357
25,4
Oats (green)
Maize (green)
4.678
1.270
12.031
21.424
2,6
16,9
Peppers
2,806
54.999
19,6
Pumpkin
1,207
8,961
7,4
Fruits
Apple
5.749
915
12.116
13,2
301
3.799
12,6
49
12
823
216
16,7
17,7
2.641
25.363
9,6
86
1,277
14,9
Pear
Cucumbers
Water melon
274
679
7,980
12,911
29,1
19,0
Quince
Medlar
Melon
144
2.140
14,8
Plum
Cabbage
Cauliflower
777
10
20.692
190
26,6
19,1
Apricot
Peach
40
24
508
292
12,6
12,2
Spinach
Lettuce
58
39
468
382
8,0
9,8
Cherry
Sour Cherry
67
50
616
494
9,2
9,9
Red beet
21
497
24,1
Walnut
76
1.448
19,1
Parsley
Leek
7
75
42
1,327
6,1
17.6
Hazelnut
Chestnut
10
250
30
993
2,9
4,0
914
13.785
15,1
Strawberry
19
85
4,5
Raspberry
Vine grape
4
431
6
1.792
1,6
4,2
860
115
3.930
4,6
Courgette
Onion
Radish
Garlic
1
126
8
718
11,6
5,7
4,679
22
7,316
50
1,6
2,3
Grape
Other
Leguminous plant
40
89
2,2
Total cultivated land
Carrots
53
634
12,0
Beans
Peas
49
235.678
Agricultural Household Survey 2005
Table 16: Livestock numbers as of Nov. – Dec. 2004
Animal Type
Cattle
Dairy cows
Other cattle
Pigs
Sows
Sheep
Ewes
Goats
Equine
Poultry
Chicken
Other poultry
Beehives
Small farms
330.607
179.161
151.445
53.499
17.063
73.022
52.187
13.103
8.955
1.837.674
1.775.680
61.993
59.554
Large farms
4.611
2.616
1.995
1.396
983
18.580
13.336
1.429
116
364.286
363.475
811
505
50
Total
335.218
181.777
153.440
54.895
18.046
91.602
65.523
14.532
9.071
2.201.960
2.139.155
62.804
60.059
INSTITUCIONET E PËRKOHSHME VETQEVERISËSE
PRIVREMENA INSTITUCIJA SAMOUPRAVE
PROVISIONAL INSTITUTIONS OF SELF GOVERNMENT
QEVERIA E KOSOVES / MINISTRIA E SHËRBIMEVE PUBLIKE
VLADA KOSOVA / MINISTARSTVO JAVNIH SLUŽBI
GOVERNMENT OF KOSOVA / MINISTRY OF PUBLIC SERVICES
ENTI I STATISTIKES SË KOSOVËS
ZAVOD ZA STATISTIKU KOSOVA
STATISTICAL OFFICE OF KOSOVO
QUESTIONNAIRE
Survey of Agriculture Households 2005
Identification
Municipality
Settlement/ Village
_
Head of Household
__________________
First
father’s name
Last
Phone
Respondent name
__________________
First
Last
Phone
Enumerator
Date ____/____/ 2005
First
Last
PSU Code
No. HH
Team
Supervisor
Date ____/____/ 2005
First
Last
First
Last
Operator
Date ____/____/ 2005
This data is confidential and is used for statistics research only
1
Table of Contents
Page
1
2
3
4, 5, 6
7
7
8
8
9
10
11
11
12
12
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Title
1
2
3
4
5
6
7
8
9
10
11
12
13
Identification
Member of Agricultural Household in 2004-2005
Total Area of Land
Crops planted and harvested (during 2004-2005 season)
Mixed Crops planted and harvested (during 2004-2005 season)
Comparison of Planted Areas
Cultivation of the second crop after the 1st harvesting
Autumn sowing 2005
Machinery and Agricultural Equipment
Livestock
Livestock Products
Farm Labour
Farm Expenditure in the last 12 months
Gross Farm Income in the last 12 months
Table 1- Members of Agricultural Household in 2004-2005
(1.1)
(1.2)
Number
Male
(1.3)
-1
Female - 2
First name
Age (in
completed
years)
(1.4)
(1.5)
Education
1. No education
2. Some Primary School
FOR CHILDREN 3. Primary School completed
LESS THAN ONE
4. Some Secondary
YEAR, WRITE “0 ”
5. Secondary School completed
6. Some High School
7. High school completed
8. Some Faculty
How many
months has
[NAME] lived
away from this
household in
the last 12
months?
IF ABSENT
MORE THAN 12
MONTHS, WRITE
12
9. Faculty completed
01
(HEAD)
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
2
TABLE 2- PLOTS OWNED OR CULTIVATED
P
L
O
T
N
U
M
B
E
R
(2.1)
(2.2)
(2.3)
(2.4)
(2.5)
LIST ALL PLOTS What is the ownership status
Area of the plot
OWNED AND ALL of this plot?
PLOTS
CULTIVATED ON
NON-OWNED
1
LAND (whether OWN
rented or used for RENT FROM PRIVATE
INDIVIDUAL
2
free)
USE PRIVATE LAND
FOR FREE
3
RENT FROM STATE
4
USE STATE LAND
FOR FREE
5
OTHER (SPEC____)
6
m2
ha
are
NAME OF PLOT
(2.7)
(2.6)
OFFICE USE In the past cropping year (1Nov 2004- 31 Oct
ONLY
2005), what has this land been used for?
(2.9)
(2.10)
1
>>NEXT PLOT
(2.11)
(2.12)
FALLOW LAND
During the last 12 What is the main reason the plot
months has this was left fallow in the 2004-2005
plot been
crop year?
irrigated at least CROP ROTATION
2
1
once?
GREENHOUSE
3
LACK OF INPUTS
2
MEADOW
4
LACK OF MANPOWER
3
GO TO NEXT LACK OF EQUIPMENT
4
PASTURE
5 >>NEXT PLOT
PLOT
LOW ECONOMIC
ORCHARD
6
VINYARD
7
PROFITABILITY
5
LEFT FALLOW
8 >>(2.9)
MINES
6
FORESTRY
9 >>(2.11)
YES
1
LACK OF SECURITY
7
2
OTHER (SPECIFY__)
8
RENTED/LOANED TO OTHER 10 >>NEXT PLOT NO
OTHER (SPECIFY)
11 >>NEXT PLOT
HOUSE YARD
UTILIZED ARABLE LAND
AND KITCHEN GARDENS
ha
(2.8)
IRRIGATION
(2.13)
How many
years has
this plot
been
fallow?
GO TO
NEXT
PLOT
YEARS
What is the main
tree type in this
plot?
BEECH
OAK
BEECH/ OAK
MIXED
SPRUCE/
PINE/ FIR
CHESTNUTS
WILLOW/
POPLAR
1
2
Was this
foresty plot
used in the
last 12
months?
3
How much wood in
m3, for firewood or
technical/
industrial, did your
household use
from this plot in the
past 12 months?
4 YES 1
5 NO 2>>
NEXT
6
FIRE
PLOT WOOD
m3
1
1 HOUSE YARD
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
TOTAL CULTIVATED LAND
(2.14)
FORESTRY
* USE LAND TYPES 2, 3, 4, 6, AND 7 FROM Question (2.7)
3
TECH/
INDUS
m3
TABLE 3A- CROPS PLANTED AND HARVESTED IN PURE STAND
(3.0) Did this household plant or harvest any crops in purestand in the 2004-2005 crop year?
(3.1)
Code
(3.2)
(3.3)
PUT A CHECK MARK IN COL
3.1 BESIDE ANY CROP
PLANTED OR HARVESTED
IN THE 2004-2005 CROP
Plot number(s)
YEAR (1Nov 04- 31 Oct 05). from Table 2
(3.4)
(3.5)
OFFICE USE
ONLY Total
hectares
Area planted
ha
ari
(3.6)
m2
ha
(3.7)
(3.8)
What was
Yield?
the quantity
harvested of
[CROP] in
KG?
kg
kg/ha
YES
1
NO
2 >> TABLE 4
(3.9)
(3.10) (3.11) (3.12)
(3.13)
(3.14) (3.15) (3.16) (3.17)
What percentage of the [CROP] harvested do you expect
to ….
How much fertiliser in kg and of which
lose to
use for your use for sell?
use to
type did you use on the [CROP] land?
household animal
process and insects,
then
to sell? rodents,
needs?
feed?
rotting etc.? NPK
NAG
URE
tjera
%
%
%
%
%
kg
kg
kg
kg
(3.18)
How much
manure in kg
did you use
on the
[CROP]
land?
kg
Grains
101
Wheat
102
Rye
103
Barley
104
Barley for beer
105
Oats
106
Maize
Vegetables
207
Potatoes
208
Tomato
209
Aubergine
210
Peppers
211
Pumpkin
212
Courgette
213
Mushrooms
214
Cucumbers
215
Water melon
216
Melon
217
Cabbage
218
Cauliflower
219
Spinach
220
Lettuce
these 5 must add to 100%
AREA SUB-TOTAL PAGE 4
A
4
TABLE 3B- CROPS PLANTED AND HARVESTED IN PURE STAND
(3.1)
(3.2)
(3.3)
Code
PUT A CHECK MARK IN COL
3.1 BESIDE ANY CROP
PLANTED OR HARVESTED
IN THE 2004-2005 CROP
Plot number(s)
YEAR (1Nov 04- 31 Oct 05). from Table 2
221
Red beet
222
Parsley
223
Leeks
224
Onion
225
Radish
226
Garlic
227
Beans
228
Peas
229
Leguminous plant
230
Carrots
(3.4)
(3.5)
OFFICE USE
ONLY Total
hectares
Area planted
ha
ari
(3.6)
m2
ha
(3.7)
(3.8)
What was
Yield?
the quantity
harvested of
[CROP] in
KG?
kg
kg/ha
(3.9)
(3.10) (3.11) (3.12)
(3.13)
(3.14) (3.15) (3.16) (3.17)
What percentage of the [CROP] harvested do you expect
to ….
How much fertiliser in kg and of which
use for your use for sell?
use to
lose to
type did you use on the [CROP] land?
household animal
process and insects,
then to sell? rodents,
needs?
feed?
rotting etc.? NPK
NAG
URE
tjera
%
%
%
%
%
kg
kg
kg
kg
(3.18)
How much
manure in kg
did you use
on the
[CROP]
land?
kg
TOTAL FERTILIZER USED FOR
VEGETABLE PLOTS
Forage plants
331
Hay (meadow)
332
Mixed grass
333
Lucerne
334
Trefoil
335
Vetch
301
Wheat (green)
302
Rye (green)
303
Barley (green)
305
Oats (green)
306
Maize (green)
Industrial and Medical crops
453
Medical crop
454
Tobacco
455
Sunflower
456
Sugarbeet
457
Oil beet
458
Soy
these 5 must add to 100%
AREA SUB-TOTAL PAGE 5
B
5
TABLE 3C- CROPS PLANTED AND HARVESTED IN PURE STAND
(3.1)
Code
(3.2)
(3.3)
PUT A CHECK MARK IN COL 3.1
BESIDE ANY CROP PLANTED
OR HARVESTED IN THE 20042005 CROP YEAR (1Nov 04- 31 Plot number(s)
Oct 05).
from Table 2
Fruits
536
Apple
537
Pear
538
Quince
539
Medlar
540
Plum
541
Apricot
542
Peach
543
Cherry
544
Sour Cherry
545
Walnut
546
Hazelnut
547
Chestnut
548
Strawberry
549
Raspberry
550
Blackberry
(3.4)
(3.5)
OFFICE USE
ONLY Total
hectares
Area planted
ha
ari
(3.6)
m2
ha
(3.7)
(3.8)
What was
Yield?
the quantity
harvested of
[CROP] in
KG?
kg
kg/ha
(3.9)
(3.10) (3.11) (3.12)
(3.13)
(3.14) (3.15) (3.16) (3.17)
What percentage of the [CROP] harvested do you expect
to ….
How much fertiliser in kg and of which
use for your use for sell?
use to
lose to
type did you use on the [CROP] land?
household animal
process and insects,
then to sell? rodents,
needs?
feed?
rotting etc.? NPK
NAG
URE
tjera
%
%
%
%
%
kg
kg
kg
kg
(3.18)
(3.19)
How much
manure in kg
did you use
ASK FOR
on the
OTHER THAN
[CROP]
ORCHARD
land?
PLOTS
kg
Scattered
trees
Number
TOTAL FERTILIZER FOR FRUIT CROPS
551
Vine grape
552
Grape
Seedlings
600
Seedlings
AREA SUB-TOTAL PAGE 6
C
6
TABLE 4A - MIXED CROPS PLANTED 2004-2005
(4.0) Did this household plant any plots with mixed crops in the 2004-2005 crop year?
(4.1)
(4.2)
(4.3)
(4.4)
(4.5)
Total area of the plot
ha
ari
(4.6)
(4.7)
(4.8)
(4.9)
(4.10)
(4.11)
OFFICE USE What percentage of
ONLY Total this plot was planted
hectares with…
%
%
%
(4.14)
(4.13)
(4.15)
ha
ari
(4.16)
(4.17)
(4.18)
(4.19)
(4.20)
Beans
Quantity
harvested of
maize
m²
kg
Planted area
kg/ha
ha
ari
(4.21)
(4.22)
(4.23)
Pumpkin
Quantity
harvested of
beans
m²
701
must add to 100%
D
(4.12)
1
2 >> TABLE 5
Maize
Planted area
m²
YES
NO
kg
Quantity
harvested of
pumpkins
Planted area
kg/ha
ha
ari
m²
702
kg
kg/ha
703
TABLE 4B- DISPOSITION OF CROPS IN MIXED PLANTING, AND THEIR FERTILIZATION
MIXED PLOT SUB-TOTAL
(4.24)
CROP
(4.25)
(4.26)
(4.27)
(4.28)
(4.31)
(4.32)
(4.33)
(4.29)
(4.30)
What percentage of the [CROP] harvested in these mixed crop plots do you
How much fertiliser in kg and of which type did
expect to
you use on the [CROP] land?
use for your
use for animal sell?
use to
lose to
household needs? feed?
process and insects,
then to sell? rodents,
rotting etc.?
NAG
URE
Të tjera
NPK
%
701
Maize
702
Beans
703
Pumpki
%
%
%
%
kg
kg
kg
kg
(4.34)
How much manure in kg
did you use on the
[CROP] land?
kg
WRITE QUANTITY OF FERTILIZER USED BY TYPE, FOR TOTAL AREA
OF THE PLOT
these 5 must add to 100%
TABLE 5- TOTAL PLANTED AREA CALCULATION
ha
A
B
C
D
TOTAL
ari
m
2
ha
SUB-TOTAL FROM PAGE 4
SUB-TOTAL FROM PAGE 5
SUB-TOTAL FROM PAGE 6
SUB-TOTAL OF MIXED CROPS FROM THIS PAGE (PAGE 7)
THIS TOTAL MUST BE COMPARED TO THE TOTAL CULTIVATED AREA IN TABLE 2 AND ANY DISCREPANCIES CORRECTED
7
TABLE 6- CULTIVATION OF THE SECOND CROP AFTER THE FIRST HARVESTING,
IN CROP YEAR 2004-2005
(6.0): Did you have any plots that you planted with a second crop after the first harvesting?
YES
NO
(6.1)
(6.2)
(6.3)
Code
PUT A CHECK MARK IN COL
6.1 BESIDE ANY CROP
PLANTED OR HARVESTED AS
A SECOND CROP IN THE 2004
2005 CROP YEAR (1Nov 04- 31
Plot
Oct 05).
number(s)
from table 2
806
Maize
808
Tomatoes
810
Peppers
814
Cucumbers
817
Cabbage
818
Cauliflower
819
Spinach
820
Salad
823
Onions
824
Carrots
830
Leek
899
Other_____
(6.4)
(6.5)
OFFICE USE
ONLY
Total hectares
Planted area
ha
ari
(6.6)
m2
ha
(6.7)
(6.8)
Yield?
What was the
quantity
harvested of
[CROP] in KG?
kg
kg/ha
1
2
>> TABLE 7
(6.9)
(6.10) (6.11) (6.12)
(6.13)
(3.14)
(3.15) (3.16) (3.17)
What percentage of the [CROP] harvested do you expect
to ….
How much fertiliser in kg and of which type
use for your use for sell?
use to
lose to
did you use on the [CROP] land?
household animal
process
insects,
needs?
feed?
and then to rodents,
sell?
rotting etc.?
NPK
NAG
URE
tjera
%
%
%
%
%
kg
kg
kg
kg
(3.18)
How much
manure in kg
did you use on
the [CROP]
land?
kg
Crop name
these 5 must add to 100%
TABLE 7- AUTUMN SOWING 2005
(7.0) Did you sow any crop in Autumn 2005 for harvest in 2006?
(7.1)
(7.2)
(7.3)
ha
901
Wheat
902
Rye
903
Barley
904
Barley for beer
932
Mixed Grass
933
Lucerne
934
Trefoil
935
Vetch
ari
1
2 >> TABLE 8
(7.5)
OFFICE USE
ONLY
Total
hectares
Planted area
Crop name
Code
(7.4)
YES
NO
m2
ha
8
TABLE 8- MACHINERY AND AGRICULTURAL EQUIPMENT (owned now)
(8.0) Does your household own any machinery or agricultural equipment in working order?
YES
NO
(8.1)
(8.2)
Type of equipment
Code
RECORD ONLY MACHINES OWNED AND IN WORKING
CONDITION
1
2 >> TABLE 9
(8.3)
For how much could you sell
this machine (or these
Number owned machines) in TOTAL in EURO?
EURO (€)
Tractor and associated machines
1
Large Tractor (over 40 horse power)
2
Small Tractor (under 40 HP)
3
Plough
4
Disk Harrow
5
Tooth Harrow
6
Trailer
7
Sowing Machine
8
Miller Machine
9
Fertiliser spreader
10
Manure spreader
11
Sprayer
12
Mower
13
Hayraker
14
Corn silage machine
15
Potato lifter (with cleaning drum)
16
Haybaler
17
Intertillage implements
Motocultivator and associated machines
30
Motocultivator
31
Plough
32
Trailer
33
Miller Machine
34
Mower
35
Intertillage implements
Other machinery and equipments
40
Combine Harvester
41
Mill (larger – for farm use)
42
Water Pump (large capacity)
43
Milking Machine
44
Other• (Specify)_____________________
9
TABLE 9- LIVESTOCK
(9.0):Does your household own any livestock or poultry now, or has it owned any livestock or
poultry in the last 12 months?
YES
NO
(9.2)
(9.3)
(9.4)
(9.5)
(9.6)
Purchased Sold in the Slaughtered Vaccinated in
Number
the last 12
in the last 12 last 12
in the last 12
owned now
months
months
months
months
(9.1)
Cattle
1.1
1.2
1.3
1.4
1.5
1.6
1
2 >> TABLE 10
Calves less than 6 months
6 months to 1 year
Bulls and
1 year to 2 years
heifers
more than 2 years
Milk cows
Bulls
Total:
Buffalo
2
Buffalo
Pigs
3.1
3.2
3.3
Piglets up to 6 months
Bearing sows
Boars for insemination
Total:
Sheep
4.1 Lambs
4.2 Sheep for breeding
4.3 Rams for insemination
Total:
Goats
5
Goats
Horses/Donkeys
6.1 Horses
6.2 Donkeys
Total:
Poultry and other
7.1 Chickens
7.2
8
Other poultry
Beehives
10
TABLE 10- LIVESTOCK PRODUCTS
(10.0) Did your household sell any meat or fresh by-products from your livestock, during the last 12 month?
YES 1
NO
2 >> TABLE 11
(10.1) What sort of fresh by-products did you sell during the last 12 months,
and what was the total amount you sold them for?
1
2
3
4
5
6
7
8
Meat
Milk
Cheese
Fat (Grease)
Other dairy products
Eggs
Honey
Other products
€
€
€
€
€
€
€
€
TABLE 11- FARM LABOUR
(11.1) How many household members worked full-time or part time on this household’s agriculture
in the 2004-2005 crop season?
(11.2)
(11.3)
(11.4)
Full Time Workers
# Male
Age
# Female
(11.5)
(11.6)
(11.7)
Part Time Workers
Occasionally
(at least 20 hrs/week)
(less than 20 hrs/week)
# Male
# Female
# Male
# Female
< 16 yrs
16-65 yrs
> 65 yrs
(11.8) How many person-days of hired labour did your household employ
for agriculture work in the 2004-2005 crop season?
(11.9)
Age
(11.10)
Male
Total number of
Average wage for
person-days
one day in EURO
(11.11)
(11.12)
Female
Total number of
Average wage for
person-days
one day in EURO
< 16 yrs
16-65 yrs
> 65 yrs
11
Table 12- Farm Expenditure (during past 12 months)
Answer the following questions about the operating expenses of this farm / agricultural household
in the last 12 months:
► Include only the farm business share of amounts paid, e.g. EXCLUDE private share
of expenses
Code
Expenditure category
12.1
12.2
12.3
11.4
12.5
12.6
12.7
12.8
12.9
12.1
12.11
Fertilizers.
Manure.
Chemicals - pesticides (herbicides, insecticides, fungicides etc.).
Seed and plants.
Animal Feed and supplements.
Purchase of Livestock and poultry.
Veterinary services, drugs, semen, breeding fees, etc.
Wages and salaries, in cash or in kind.
All fuel (diesel, gasoline, oil, wood, natural gas, etc.) for farm activities
Repairs and maintenance to farm machinery, equipment and farm vehicles .
Custom Work and Machine Rental Expenses - custom work, contract work,
machinery rental, custom trucking, harvesting, combining, etc.
Regular maintenance and repair of farm buildings and fences
Rental of farm land and buildings
(including community pasture and grazing fees)
Electricity for farm use
Interest costs for farm loans.
All other farm business operating expenses such as freight, packaging materials,
12.12
12.13
12.14
12.15
12.16
Amount in €
irrigation fees, legal and accounting fees, etc. (Do not include depreciation)
12.17
TOTAL farm business operating expenses for the last 12 months.
Table 13- Gross Farm Income (during past 12 months)
Enter all gross farm income received during the last 12 months. Report gross receipts without
subtracting any expenses.
► Include: receipts from all agricultural and forest products sold
► Include: Rents received for land or equipment
► Do not include: sales of capital items (for example: land, machinery); incomes received by your
household’s members not associated with your farm activities. (for example, if a member of your
household works as a teacher at the secondary school, his/her wages should be not be recorded, as they do
not form a part of the gross income of your farm).
Code
Gross Receipts
13.1
TOTAL GROSS INCOME, e.g. TOTAL gross farm receipts of your farm
for the last 12 months?
NOTE:
Amount in €
IF THE FARM HAD NO INCOME (THAT IS, THE FARM SOLD NO CROPS, OR LIVESTOCK, OR PROCESSED
BY-PRODUCTS) THEN YOU MUST WRITE “0”.
12
Remarks
Here you can write your or the respondent’s remarks about the interview.
Statistical Office of Kosovo (SOK) - a brief
description
The Statistical Office as a professional office has been in operation since
1948, and has passed through all the historic phases of Kosovo. On August
2nd 1999 the Office restarted its work as an independent and professional
institution of public administration of Kosovo. Kosovo Consolidated Budget
and various donors for particular projects finance the Office.
A Statistical Regulation (Regulation 2001/14) came into force 2 July 2001.
SOK is an executive agency attached to the Ministry of Public Services
(MPS). A Master Plan (medium term development plan) for the statistical
system in Kosovo has been produced.
Organization structure: Seven Regional Offices (Pristine, Peja, Gjakova,
Prizren, Ferizaj, Gjilan and Mitrovica) and Head Quarters in Prishtina have at
present a total of 137 employees, 90 at HQ and 47 at the Regional Offices.
There is 1 Long Term Consultant from Statistics Sweden, financed by Sida
and 1 Poject Cordinator, Statistics Sweden Projects, SOK. The Office has a
fully-fledged field organization for surveys with experienced enumerators and
sufficient transport. Local and international expert group are working in the
population census project.
The Office Mission is to fulfill the needs of users for objective statistical data
and analyses in order to support government departments and provide proper
information for decision-makers and other users in Kosovo.
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Address: Statistical Office of Kosovo, Str. Zenel Salihu No: 4,
Pristine
Telephones:
Head-quarters: +381 (0) 38 235 111
Director: +381 (0) 38 235 545 or +381 (0) 38 504 604 ext. 6572
Fax: +381 (0) 38 235 033
E-mail: [email protected]
Web-site: www.ks-gov.net/esk