Does human capital play an important role in farm size growth? The case of Slovenia - New Medit
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Does human capital play an important role in
farm size growth?
The case of Slovenia
S̆tefan Bojnec*, Imre Fertő**
DOI: 10.30682/nm2101d
JEL codes: C21, C23, I25, Q12, Q18
Abstract
The paper investigates the drivers of farm size and farm size growth in Slovenia during the period 2007-
2017 using a farm-level Farm Accountancy Data Network dataset within a quantile regression frame-
work. Farm size growth is measured by growth in utilized agricultural area per farm. The findings suggest
that growth in farm land size is driven by initial farm land size and policy subsidy support. Contrary to
expectations, human capital does not play an important role in either farm land size or farm land size
growth according to quantile regressions. These findings from inter-quantile comparative analysis are
important for farm-related structural and rural development policy.
Keywords: Farm growth, Human capital, Subsidies, Slovenian Farm Accountancy Data Network.
1. Introduction ter understand the mechanisms of farm structural
change, and the key drivers that influence the
It is well known from the literature that the
observed trends in farm size growth.
number of farms in developed countries has de-
In empirical studies, several factors have been
clined, and also that average farm size has in-
identified as influencing farm structural change,
creased (Eastwood et al., 2010; Lowder et al.,
2016). The relationship between farm size and including relative prices, technological change,
farm size growth indicates structural changes in size economies, farm debt, sunk costs, policy
farms with implications for farm policy and man- variables, demographic variables, and indicators
agerial farm practices and competitiveness. The related to off-farm employment and regionally
claim that the relationship between farm/firm specific patterns and spatial dependencies (God-
size growth and farm/firm size is independent is dard et al., 2002; 2006; Huettel and Jongeneel,
known in the literature as Gibrat’s (1931) Law 2011). Akimowicz et al. (2013) developed and
(Distante et al., 2018). The motivation behind tested a model of drivers of farm size growth
this paper is a desire to move a step beyond test- in Southwestern France. Barbosa (2020) inves-
ing the validity of Gibrat’s Law and investigate tigated Portuguese farming firms’ growth, fo-
the drivers of Slovenian farm size growth to bet- cusing on human capital and managerial capa-
* University of Primorska, Faculty of Management, Koper – Capodistria, Slovenia.
** Institute of Economics, Centre for Economic and Regional Studies, Lorand Eotvos Research Network, Budapest,
Hungary; Hungarian University of Agricultural and Life Sciences, Kaposvár Campus, Faculty of Business Adminis-
tration, Kaposvár, Hungary.
Corresponding author: stefan.bojnec@fm-kp.siNEW MEDIT N. 1/2021
bilities, while Adinolfi et al. (2020) investigated of quantile regressions. This is followed by a
gender differences in farm entrepreneurship and discussion and description of the implications
farming performance in Italy. Although there is of the results. The final section derives the main
literature about structural change in agriculture, conclusions.
our understanding of different patterns of struc-
tural change is limited.
2. Pre-existing literature
The farm size required (in terms of economies
of size in the short term, and scale and scope In the literature there is no a single measure
economies in the long term) to reach (steady) of farm size (Lund, 1983; Lund and Price, 1998;
equilibrium can be determined by various fac- Alvarez and Arias, 2004) and different measures
tors (Jones and Kalmi, 2012; Akimowicz et al., have been used to capture this factor, such as the
2013; Adamopoulos and Restuccia, 2014; Gollin, physical magnitude of inputs (e.g. total UAA per
2019). Our aim is to specify and establish a robust farm, or total head of livestock per farm), and
relationship between farm size growth and its the economic size of outputs. Akimowicz et al.
driving forces in terms of farm-specific utilized (2013) argue that the choice of UAA per farm may
agricultural area (UAA) and the share of rented be a more relevant measure of farm size than one
land, farmer/manager personal- or human-cap- related to economic farm size due to the varia-
ital-related factors (age, education/training, and bility of farm production choices and commodity
gender), policy factors (subsidies), and territorial prices over time. Similarly, in our study, UAA per
or rural variables. It is known from the literature farm is used as a measure of farm size and farm
that farms are heterogeneous and that the dynam- size growth. Farm size growth measured as an in-
ics of structural change differ between countries crease in UAA per farm may be limited by the
and farm-size categories over time (Upton and quantity of UAA that is available and the number
Haworth, 1987; Johnson and Ruttan, 1994; Weer- of farms. While a part of UAA can be dedicated to
sink, 2018; Colombo et al., 2018). non-agricultural uses and vice versa, a decrease in
In comparison to previous studies, this paper the number of farms can determine the increase in
adds to the exiting literature by specifying the the remaining average farm size, which can thus
drivers of farm size growth while controlling for be differently distributed over time.
potential farm-specific effects that could influ- One strand of literature focuses on the drivers
ence the results. As novelty is the use of quantile of farm size growth using Gibrat’s Law of pro-
regression techniques and the implications of this portionate growth, which specifies that farm size
methodological approach with additional infor- growth is unrelated to initial farm size. The idea
mation that can provide in comparison to more that no equilibrium farm size exists may suggest
conventional regression methods. The shape of that farm size growth is a random phenomenon.
farm size distribution across quantiles can pro- Empirical research has yielded rather contradic-
vide a better understanding of the structure of tory results about the relationship between farm
these effects, which can differ across quantiles. size and the growth of farm size by country and
Finally, in addition to the contribution the re- over time. Some studies (Weiss, 1998; Rizov and
search makes to the literature, the importance of Mathijs, 2003; Bakucs and Fertő, 2009) have re-
this paper for farm structural policy is related to jected the validity of Gibrat’s Law for farm size
its use of inter-quantile comparative analyses. growth, finding that small farms tend to grow
It is thus also of relevance to rural development faster than large ones. Other studies (Kostov et
policies and farm managerial and entrepreneurial al., 2005) found no evidence to reject the valid-
practices that involve responding to a changing ity of Gibrat’s Law. Bakucs et al. (2013) inves-
institutional and policy-enabling environment. tigated the relationship between farm size and
The rest of the paper is organized as follows. farm size growth in field crop and dairy farms
First, we briefly describe pre-existing literature in France, Hungary, and Slovenia using quantile
about firm/farm size growth. Then, we present regression. The results for Hungary are consist-
the methodology, data, and the empirical results ent with previous studies that suggested that Gi-
58NEW MEDIT N. 1/2021
brat’s Law should be rejected because smaller and the management techniques that are applied
farms grow faster than their larger counterparts. (Sumner and Leiby, 1982).
Similarly, the validity of Gibrat’s Law can be re- Akimowicz et al. (2013) found that farm size
jected for French and Slovenian dairy farms, but growth was significantly driven by farm structur-
not for Slovenian crops farms, because the rate of al characteristics, the farmer’s age, the existence
growth of crop farms in terms of land is inde- of a successor, and spatial rural-urban influenc-
pendent of their size. Bojnec and Fertő (2020a) es, but not human capital variables. Similarly to
investigated the validity of Gibrat’s Law for the the area of interest of Akimowicz et al. (2013),
growth of a sample of Slovenian farms in the pe- our paper focuses on drivers of farm size growth
riod 2007-2015 using a cross-sectional depend- and the intensity of farm size growth by different
ence test and four different groups of panel unit quantiles. We investigate the drivers of farm land
root tests. The results confirmed the validity of size and farm land size growth in Slovenian agri-
Gibrat’s Law independent of measures of farm culture with a focus on initial farm size in terms
size (inputs in the form of land and labour per of UAA per farm and the share of rented land,
farm, and outputs as economic size per farm) farmer/manager personal- or human-capital-relat-
and type of panel unit root test. All farm sizes ed factors (age, education/training, and gender),
witnessed an increase in average farm size. Bo- farm subsidies, and farm location in rural areas.
jnec and Fertő (2020b) compared the growth Our main hypothesis is that farmer/manager per-
of Hungarian and Slovenian samples of farms sonal- or human-capital-related variables are pos-
using quantile regression for the period 2007- itively related to land farm size distribution and
2015. Results suggested rejecting the validity of land farm size growth (Sumner and Leiby, 1987;
Gibrat’s Law for Hungarian farms, and, to a less- Barbosa, 2020). However, Akimowicz et al.
er extent, for Slovenian farms when the growth (2013) and Barbosa (2020) have reported mixed
of farms was measured by growth of output per findings in relation to different farmer/manager
farm (where smaller farms grew faster than the personal and human capital variables.
largest farms), but not in relation to an increase
in farm inputs (i.e. land and labour per farm).
3. Methodology
Smaller, mostly individual Hungarian farms
grew faster than larger, mostly corporate farms. Different econometric approaches have been
Akimowicz et al. (2013) investigated drivers developed in the literature to test the validity
of farm size growth in Southwestern France. of Gibrat’s Law (the relationship between farm
The former examined the factors that can ex- size and farm size growth). Studies of drivers
plain farm size growth in developed countries, of farm size growth, in addition to initial farm
among them farm structural change (which can size, include various control variables related
be expressed by the diversification of farm to farm-specific variables on the input and out-
activities, farm mechanization, and specializa- put side, as well as policy and territorial factors
tion), the search for an equilibrium farm size (Akimowicz et al., 2013).
or economies of scale or economies of scope, The econometric specification of the regres-
farmer- and human-capital-related factors, oth- sion used specifically
Gibrat’s Law for with
testing the validity
the definition of variables i
of model
er classical factors, and territorial spatial factors Gibrat’s Law with the definition of model varia-
the stochastic process underlying Gibrat’s (1931) La
that depend on farm location. Farm mechaniza- bles is the following equation (1), which repre-
tion and specialization may be important drivers sents the stochastic process underlying Gibrat’s
of farm structural change and farm size growth, (1931) Law:
generating economies of scale (Chavas, 2001). S i ,t
Some previous studies have highlighted that farm = aS ib,t1--11e i ,t (1)
S i ,t -1
size can be determined by human capital and
managerial capabilities (Barbosa, 2020) such where Si,t and Si,t-1 are the size of the ith farm th
as farmer age, the experience of the former in in the period where i,t and Si,t-1 are the size of the i farm in
t and Sin the previous period t-1,
the agricultural sector, their level of schooling, respectively. εi,t is the disturbance
respectively. εi,t is the disturbance in period
in period t, t, indepe
all farms, whilst β1 measures the effect of initial size
59 then farm size growth rate and initial farm size a
Gibrat’s Law holds. If the coefficient is less than one,Gibrat’s Law with the definition of model variables different is the different equation
following methodological approaches
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indicating
rate of where0NEW MEDIT N. 1/2021
iable, we use total subsidies in euros (SE605). often being the case with the few privatized
The Statistical Office of Slovenia (SORS) price commercial farms which typically rent land
indices are used as deflators of nominal values from the state fund for agricultural land and for-
over time with a 2010 base year. We use bal- ests). Subsidies are an important source of farm
anced panel data. income. For the analysed sample of farms, they
increased at constant prices of 2010 from 9,667
euro per farm in 2007 to 11,187 euro per farm
5. Results
in 2017. Most farm managers and farm owners
We first present descriptive statistics and then have some kind of agricultural education, which
econometric models. has increased during the analysed period. Their
average age in the reference year 2007 was 42.8
years and in the final year 2017 was 52.2 years,
5.1. Descriptive statistics
while during the period of analysis the average
Table 1 illustrates the averages of farm size age was 48.3 years, and 81% farm managers
and explanatory variables in the reference year and farm owners were male.
2007 and the final analysed year 2017. UAA To present density estimation on grouped data
farm size is used as the farm size variable. The graphically in the case of mean values of farm
average size of farmland in UAA was 16.4 ha per size expressed in UAA in ha per farm, we use a
farm in 2007, while the largest farm in the sam- comparison of kernel density distribution func-
ple was 110.6 ha. Average farm size increased tion with parametric estimation of the Lorenz
by 0.9 hectares between 2007 and 2017. Farms curve which is also applied to grouped data.
in Slovenia are still largely cultivating their own While there were no radical changes in farm
land, although the share of rented land has sta- size land distribution between 2007 and 2017,
bilised. In 2007 and 2017, on average 30% and the kernel distribution function for land (UAA
29%, respectively, of land was rented (ranging in ha per farm) in Figure 1 confirms a slight
from farmers cultivating only their own land shift in average farm size land concentration
– i.e. no rented land –, to farms operating on towards rights suggesting a slightly larger av-
completely rented land, the latter situation more erage farm land size.
Table 1 - Descriptive statistics of variables (reference year 2007 and final year 2017).
Number of
Variables Mean Std. Dev. Min Max
observations
Land (in UAA in ha) 2007 113 16.4 13.4 3.0 110.6
Land (in UAA in ha) 2017 113 17.3 13.7 2.7 100.2
Age (in years) 2007 113 42.8 13.3 14.0 73.0
Age (in years) 2017 113 52.2 13.5 23.0 83.0
Training dummy 2007 113 1.44 0.63 1.00 3.00
Training dummy 2017 113 1.63 0.68 1.00 3.00
Gender dummy 2007 113 0.19 0.39 0.00 1.00
Gender dummy 2017 113 0.19 0.39 0.00 1.00
Rented land (in %) 2007 113 30 28.1 0.00 100
Rented land (in %) 2017 113 29 27.4 0.00 100
Total subsidy (in euro) 2007 113 9667.1 8921.1 0.0 66601.0
Total subsidy (in euro) 2017 113 11186.9 10934.6 1175.0 66013.6
Source: Authors’ estimations based on FADN data.
61NEW MEDIT N. 1/2021
Figure 1 - Kernel distribution function for land (UAA Figure 2 - Lorenz curves for land distribution (UAA
in ha per farm). in ha per farm).
Source: Authors’ estimations based on FADN data. Source: Authors’ estimations based on FADN data.
A slight increase in average land farm size Table 2 presents quantile regressions of log
is seen from the Lorenz curves for the distri- (land in UAA) per farm in 2007. The results of
bution of land in UAA in ha per farm (Figure these quantile regressions are mixed and suggest
2). Finally, Lorenz curves of farm size land dis- that agricultural education/training has a nega-
tribution close to the 45° line, which means a tive impact for q10, but is insignificant for the
linear distribution, suggest a more equal than remaining quantiles. The cultivation and opera-
unequal land farm size distribution in the Slo- tion of the smallest farms requires less knowl-
venian farming structure. edge and experience. Farm growth is positively
linked to the proportion of rented land and log
(subsidy) received by all quantiles. As subsidy
5.2. Econometric models
payments are input-based, there was a positive
We test two econometric models that were de- link between subsidies and the growth of farm
signed to explain two aspects of farm size growth. size in UAA from 2007 onwards. Farm size
First, the logarithm of farm size observed in 2007 growth is negatively linked to the variable fe-
expressed in terms of UAA per farm, specified male for q90, while for other quantiles the role
as log (land in UAA) per farm in 2007. Second, of gender in farm size growth is insignificant.
the logarithm of the intensity of growth between Also insignificant is the role of the age and rural
2007 and 2017, the period for when growth is, dummies on farm size growth by all quantiles.
as expressed in equation (3). The aim of using We also estimated our models with squared age
the two models was to compare the effect of the variable, but the coefficients were insignificant
explanatory variables on indicators of farm size for both level and squared terms in all quan-
and their evolution. The first regression reveals tiles. Therefore, except for training and gender,
the impacts of various factors on initial farm size. no other considerable inter-quantile differences
The second regression focuses on the effects of can explain the structural changes in the farming
the same explanatory variables on the intensity sector and/or potential changes in (nor specifici-
of farm size growth. Notice that the explanatory ty of) technology related to UAA per farm size
variables we employed concerned the year 2007, growth since 2007. A significant positive influ-
and these are the initial characteristics likely to ence for farm size growth of log (land in UAA)
explain the variation in farm size, and, more par- per farm in 2007 is mainly caused by the share of
ticularly, the growth in farm size in terms of both rented land and subsidies, with some differences
variables observed in 2017. in magnitude across quantiles.
62NEW MEDIT N. 1/2021
Table 2 - Quantile regression for farm land size: log (land in UAA) per farm in 2007.
q10 q25 q50 q75 q90
Age -0.001 0.000 0.000 0.001 0.001
Training -0.095*** -0.030 0.039 0.023 0.030
Gender -0.042 -0.035 -0.030 -0.079 -0.329***
Rented land 0.463*** 0.448*** 0.334** 0.659*** 0.456*
log (subsidy) 0.777*** 0.738*** 0.678*** 0.589*** 0.518***
Rural 0.018 0.036 -0.029 0.009 -0.205
Constant -4.605*** -4.351*** -3.637*** -2.773*** -1.633
Number of observations 109 109 109 109 109
Pseudo R 2
0.6066 0.5408 0.5069 0.4917 0.5019
Note: *** pNEW MEDIT N. 1/2021
6. Discussion and implications ized crops farms, and more extensive livestock
and dairy production on grassland (i.e., wide-
Farm size distribution, farm structural chang-
spread pastures and meadows, particularly in
es, and drivers of farm size growth are some of
less favoured hilly and mountain areas).
the most often studied research issues in agri-
Second, in contrast to theoretical expectations,
cultural economics (Sumner, 2014). They are
farmer-specific personal characteristics and hu-
also common subjects of agricultural and rural
man-capital-related variables do not play an
development policy objectives related to diversi-
important role in farm land size and farm land
fied spatial farming structures in developed and
size growth (Sumner and Leiby, 1982). This a
developing countries and are considered impor-
striking finding, although the situation regarding
tant variables in relation to competitiveness, and
farmer/manager education/training for Slovenia
agricultural and farm sustainable development
is similar, for example, to that identified by Aki-
(Key and Roberts, 2007; Piet et al., 2012; Bar-
mowicz et al. (2013) for Southwestern France.
tolini and Viaggi, 2013). According to the 2010
However, in Slovenia, the age of farmers was
General Agricultural Census (Eurostat, 2020a)
found to be insignificant across quantiles, while
and the 2016 Farm Structure Survey (Eurostat,
greater female participation reduces farm land
2020b), farm fragmentation of the smallest
size and farm land size growth in upper quan-
farms, farm concentration of the largest farms,
tiles. Therefore, farmer/manager-specific per-
and farm size growth vary considerably across
sonal characteristics and human-capital-related
EU-28 member states. The heterogeneity in farm
variables were largely found to be an insignifi-
size distribution has also been confirmed by the
cant driver of farm land size and farm land size
typology and distribution of small farms in Eu-
growth for the Slovenian sample of FADN farms
rope (European Commission, 2013; D’Amico et
for most quantiles.
al., 2013; Guiomar et al., 2018).
Third, a greater share of rented land is associ-
Our analysis focuses specifically on a sam-
ated with greater farm land size, and, to a lesser
ple of Slovenian FADN farms. Slovenia can be
extent, contributes to farm land size growth for
classified as one of a number of EU-28 member
upper quantiles, except for the largest farm land
states that have on average smaller but growing
size, which might indicate limitations in terms
average farm size (Bojnec and Fertő, 2020a;
of further farm land size growth. These findings
2020b). Similarly to some other countries, farm
suggest that the renting of land and land-leasing
exit occurs particularly among farms of medium
arrangements have become an important driver
size in Slovenia (Bojnec and Latruffe, 2013).
in the restructuring of the Slovenian farming
The present study has confirmed five main
structure towards farm size growth. While tra-
findings that have farm managerial and policy
ditional family farms mostly operated on their
implications. First, there is a negative relation-
own land (traditional or peasant farming), this
ship between initial farm land size and farm land
has changed towards more entrepreneurial oper-
size growth. This suggests that large farms are
ations that involve the renting of land.
growing less than small ones, confirming earlier
Fourth, subsidies positively influence both
results for Slovenian agriculture (Bakucs et al.,
farm land size and farm land size growth. Ac-
2013). The policy insight is that different initial
cordingly, generous Common Agricultural Pol-
farm sizes are an important variable in farm size
icy (CAP) subsidies are found to be a crucial
growth and diversification (Melhim et al., 2009).
driver of farm land size for all quantiles, and
In the short term, this may be connected to an
farm land size growth for the Slovenian sample
increase in economies of size, while in the long
of FADN farms by quantile, except for the low-
term it may be associated with a combination
est q10. This finding may be important from a
of both scope economies for smaller and mixed
farm managerial perspective, as CAP subsidies
farms, and scale economies for larger and more
can be an important driver of farm profitability
specialized farms (in terms of land use). Among
and a relatively stable source of farm revenue,
the latter farms, this may involve larger special-
but are also policy ‒ and thus politically depend-
64NEW MEDIT N. 1/2021
ent. CAP subsidies in Slovenian agriculture have knowledge into farming and agri-food value
been found not only to be important, but also one chain practices. Different types of innovation
of the most stable sources of farm income (Bo- approaches may include product innovation
jnec and Fertő, 2018; 2019a; 2019b). However, involving the implementation of new or signif-
offering generous CAP subsidies has important icantly improved products or services (OECD,
policy implications. Any changes or reductions 2009), process innovation with new or im-
in CAP subsidies could have a diminishing effect proved farm production technologies or delivery
on farm land size, with the potential abandon- methods for increasing added value (such as in
ment of operations, particularly in depopulated, short-supply chains in local agri-food markets
remote, and less favoured areas, and generally and in online agri-food shopping), marketing
on farm land size growth in Slovenia. Howev- innovation through different marketing chan-
er, Unay-Gailhard and Bojnec (2019) find that nels to obtain higher prices, and organisational
agri-environmental policy measures supported innovation that leverages economies of scale for
with subsidies can create green jobs on Sloveni- relatively small- and medium-size farms, such
an farms, particularly in relation to family labour as setting-up producer associations and mak-
on large dairy family farms and hired labour in ing improvements in service cooperatives (e.g.
large field crop farms. On the other hand, Baráth in their organisation and communication) and
et al. (2020) did not find a significant effect for contract farming that can improve efficiency and
three different types of subsidies – investment-, add value (OECD, 2015; Benke and Tomkins,
less-favoured-area-, and agri-environmental sub- 2017; Mishra et al., 2018).
sidies – on total factor productivity and its three Finally, farm growth may be related to some
different components (technical efficiency, scale other factors, among them farm investment,
efficiency, and technological change) in Slove- where an important role may be played by finan-
nian agriculture during the period 2006-2013. cial constraints, farm efficiency, and financial
Therefore, as public budgets and subsidies are status or farm indebtedness (Bojnec and Fertő,
limited and politically dependent on CAP chang- 2016). As argued by Fagiolo and Luzzi (2006)
es, there is a need to improve the targeting, man- for the Italian manufacturing industry and Do-
agement, and monitoring of efficiency in subsidy nati (2016) for the manufacturing and service
implementation: a crucial implication for policy, sectors in Italy, firm size and firm size growth
managerial, and farm entrepreneurial practices. can be explained by liquidity constraints. Farm
Shifting from a government-supported to a growth can also be heterogeneous in relation to
more entrepreneurial farming structure (proba- types of farming and natural factor endowments
bly involving a decrease in subsidies) requires and in terms of locational factors and regional
improvements of the institutional and organ- specificities. Baráth et al. (2018) investigated
izational structure of farming and in agri-food and compared the effect of heterogeneity on pro-
value chains such as promoting the role of duction technology and technical efficiency for
farmer-based organizations for value chain in- a sample of less- favoured-area and non less-fa-
tegration (Francesconi and Wouterse, 2015) voured-area Slovenian FADN farms. The strik-
and networking for small farms as a factor for ing finding was that farms in less-favoured-areas
entrepreneurship (Aubert and Perrier-Cornet, are not more inefficient, but rather use different,
2009; De Hoyos-Ruperto et al., 2013; Ciliberti production-environment-specific technologies.
et al., 2020). A greater role can play by changes
in farm income diversification and farm income
7. Conclusions
sources on entrepreneurially oriented farms and
small- and medium-sized enterprises (Gričar et This paper deals with the drivers of farm land
al., 2019). More entrepreneurial farms and farm size and farm land size growth in Slovenia. It
size growth can be combined through new tech- adds to the existing literature evidence on the
nological innovation, including open innovation drivers of farm size and farm size growth with
from outside farms and the greater transfer of important farm managerial and policy impli-
65NEW MEDIT N. 1/2021
cations. The analysis does control for possible be the age of farmers/farm managers could be
farm-specific effect influencing the results. The of crucial importance for farm labour renewal
main findings lead to the conclusion that initial and long-term farm survival, but may be also a
farm size and CAP subsidies are the main driv- factor of importance in farm investment activi-
ers of farm land size and farm land size growth ties which can create rural jobs and increase the
in Slovenia. However, the results suggest some competitiveness of farming and the rural econ-
diversity across different quantiles. omy. These structural changes in farms can be
The main novelty lies in the application of ad- supported with CAP measures for young farm-
vanced quantile regression econometric methodol- ers and investment subsidies, or non-CAP funds
ogy to FADN farm level data using more explana- such as regional and cohesion funds.
tory variables. The paper starts with the hypothesis Among the study limitations, only input-ori-
that farmer/manager personal or human capital ented UAA per farm is used as a measure of the
variables can play a positive role in land farm size relationship of farm land size to farm land size
and land farm size growth. However, the results growth. In terms of the implications of the study
suggest that farmer/manager-specific personal comparison, this assumption should be contrast-
characteristics and human-capital-related varia- ed with the use of other different input- (e.g. la-
bles were largely found to be insignificant accord- bour, livestock, and capital) or output-oriented
ing to quantiles for farm land size and farm land farm size/farm size growth measures. The find-
size growth in Slovenia. The negative relationship ings and implications might have been different
between initial farmland size and farm land size if different farm size measures had been used.
growth suggests that large farms are growing less Finally, farm size growth can be also driven by
than small ones. In terms of farm land size and other factors that were not specified in our study,
farm land size growth, the impact of generous CAP such as type of farming and regional specifici-
subsidies exceeded that of all other drivers. Rent- ties, the use of different farming technologies,
ing of land and land leasing arrangements have off-farm employment, different market struc-
become an important driver of restructuring of the tures, and production and market risks. These
Slovenian farming structures. are issues for future research.
The findings from this study can be applied
in the more general setting of farm size growth
when relatively small- to medium-sized farms Acknowledgements
dominate farming structures. This is the situa- This study was supported with funding received
tion in the countries neighbouring Slovenia on from the Hungarian and Slovenian Research Agen-
the territory of the former Yugoslavia that share cies as a joint research project within Project
a common recent (20th century) history, as well N5-0094 - Impacts of agricultural policy on the
as for some other transition and emerging mar- regional adjustment in agriculture: A Hungari-
ket economies that are experiencing structural an-Slovenian comparison.
changes in the farming sector. In addition to
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