Post-Accession Structural Transformation of the Croatian Dairy and Beef Sectors Under CAP: A Partial Equilibrium Model-Based Assessment of Contraction Dynamics and Food Security Implications

Abstract

Croatia’s accession to the European Union in 2013, followed by the abolition of the EU milk quota regime in 2015, exposed a structurally vulnerable dairy and beef sector to the dual pressure of single-market price convergence and post-quota production reallocation. While prior partial equilibrium modelling work on Croatian agriculture has assessed broad accession impacts and CAP reform scenario comparisons, no study has yet quantified the post-quota structural transition trajectory of the Croatian dairy and beef sectors with mechanism-level interpretation under the actually implemented CAP framework. This study simulates and analytically interprets the medium-term (to 2030) trajectories of the Croatian dairy and beef sectors using the AGMEMOD partial equilibrium framework, with an updated Croatian country-level model incorporating CAP 2023–2027 parameters, the post-quota dairy module specification, and historical data extending to 2024. Results indicate continued structural contraction: dairy cow numbers decline from 70.9 thousand head (2024) to 66.0 thousand head (2030); milk production falls 8.6% to 399.6 million litres; total cattle population declines by 4.0% and beef and veal meat production falls 11.0% to 33.1 thousand tonnes. Self-sufficiency rates deteriorate to 41% for milk and 51% for beef by 2030. The study contributes empirical evidence on small Member State post-quota adjustment dynamics, demonstrates that the current CAP 2023–2027 instruments are unlikely to reverse the contraction trajectory under baseline assumptions, and raises explicit food security implications for national agri-food policy.

1. Introduction

The accession of Central and Eastern European Countries (CEECs) to the European Union (EU) represented a transformative shift in their agricultural landscapes. Historically, these sectors were characterized by a “dual farm structure”, a coexistence of large-scale agricultural enterprises and numerous small-scale family farms which often resulted in a productivity lag compared to the “Old Member States” [1,2,3,4]. While integration into the single market and the adoption of the Common Agricultural Policy (CAP) mechanisms have catalyzed growth and narrowed this productivity gap, the transition has also fundamentally altered production structures across the region, often resulting in a decrease in the volume and value of livestock production in relation to crop production [5,6,7].

Croatia, as the final CEEC to join the EU on 1 July 2013, entered this economic environment with similar agricultural sector structural challenges to its post-communist EU Member State predecessors. Defined by a dual farm structure where large-scale agri-complexes coexisted with a high proportion of small family farms, the Croatian agricultural sector faced significant challenges upon EU accession. This integration fundamentally reshaped the landscape by exposing domestic producers to the competitive pressures of the single market; however, this shift affected many family farmers, especially in the livestock sector, where they struggled to maintain the productivity and economies of scale. Furthermore, the integration process necessitated the adoption of Common Agricultural Policy (CAP) mechanisms alongside a convergence of domestic prices toward the lower levels prevailing in the single EU market [8,9].

A second structural shock followed the accession: the abolition of the EU milk quota regime in 2015 fundamentally altered the post-quota dairy market environment in which the new Member States, including Croatia, were operating. The removal of the quota rent that had historically supported the maintenance of dairy herds in less competitive Member States exposed Croatian dairy producers to direct competitive pressure from large-scale, capital-intensive dairy systems in the EU dairy belt. Under these combined pressures, single-market price convergence after 2013 and post-quota dairy reallocation after 2015, the Croatian beef and dairy sectors have experienced a structural contraction whose magnitude warrants systematic analysis.

Since accession, the beef and dairy sectors’ share in total agricultural output fell from 19.8% in 2013 to 15.8% in 2024, while self-sufficiency declined from roughly 75% to 60% in beef and veal and from roughly 65% to below 50% in milk [10,11].

These shifts are detailed in Table 1: over the post-accession period, the total cattle population declined by approximately 4.5%, while the dairy cow population fell by 57.8%, with the remaining categories largely stable relative to their 2013 levels.

Table 1. Changes in the Croatian cattle herd (2013–2024).

Category (Heads)	2013	2015	2017	2019	2021	2023	2024
Young cattle under 1 year	144.762	147.99	155.868	151.584	156.331	144.76	150.028
for slaughter	19.267	19.964	20.263	19.179	19.737	18.596	19.366
female	51.689	47.067	57.081	62.449	65.248	56.215	57.891
male	73.806	80.959	78.524	69.956	71.346	69.949	72.771
Cattle between 1 and 2 years	92.178	88.167	99.923	106.689	106.663	115.311	114.15
heifers (breeding)	37.771	38.101	40.319	49.824	47.535	54.216	43.56
heifers for slaughter	7.45	7.296	7.115	8.688	8.734	9.429	9.339
male	46.957	42.77	52.489	48.177	50.394	51.666	61.251
Cattle over 2 years	205.492	203.935	194.966	161.966	164.593	155.133	158.352
dairy cows	168.025	151.502	139.443	130.025	102.333	71.423	70.884
other cows	13.46	18.999	21.55	11.867	39.807	59.927	59.150
other (bulls, etc.)	24.007	33.434	33.973	20.074	22.453	23.783	28.318
Total Cattle	442.432	440.092	450.757	420.239	427.587	415.204	422.530

Source: Author’s calculation based on Croatian Bureau of Statistics (CBS) database [12].

The year-on-year fluctuations visible in Table 1 (notably the 2018 adjustment in total cattle and the 2022 step decline in dairy cows) reflect the official CBS data, including methodology adjustments in the national agricultural statistics over the post-accession period. These data are reported as published; no smoothing has been applied.

As Croatia was not self-sufficient in beef and veal meat production or milk at the time of EU accession, this trend has persisted and intensified during the years of membership. To further illustrate this, the production, import and export dynamics of beef and veal meat and milk are presented in Table 2.

Table 2. Production and trade dynamics of beef meat and milk in Croatia (2013–2024).

Category	Unit	2013	2015	2017	2019	2021	2023	2024
Beef and veal Meat
Domestic Production	1000 t	47.27	42.26	42.20	45.43	43.18	38.38	37.24
Domestic Use	1000 t	55.8	57.5	61.3	63.3	62.7	62.1	62.9
Export	1000 t	3.35	4.33	5.85	7.66	6.66	7.36	9.41
Import	1000 t	10.22	17.38	22.04	24.75	26.84	35.44	38.36
Milk
Domestic Production	million l	737.51	706.43	690.18	581.77	541.34	454.32	437.44
Domestic use	million l	906.24	896.60	920.21	961.37	957.09	966.40	964.25
Export	million l	35.47	35.53	50.24	54.32	42.87	44.25	48.56
Import	million l	186.47	207.94	255.15	276.76	317.19	404.21	421.09

Source: Author’s calculation based on Croatian Bureau of Statistics (CBS) database [12]; Domestic Use derived from supply–use balance, consistent with values used in Table 4 and Table 5.

Beyond their economic output, the beef and dairy sectors are two of the pillars of national food security and play a vital role in maintaining the socio-economic fabric of rural areas [13,14,15]. These sectors are primary drivers of rural employment and are essential for preventing land abandonment and demographic decline in peripheral regions [16,17]. High-quality protein production from these sectors is fundamental to a resilient food system, while their activities support local economies and related service industries [18,19].

Despite the strategic importance of these sectors for Croatian agricultural policy and the magnitude of the contraction observed during the post-accession period, the literature has not yet provided a systematic mechanism-level analysis of the post-quota structural transition trajectory under the actually implemented CAP 2023–2027 framework. Prior AGMEMOD applications to Croatian agriculture have addressed the broader question of accession impacts at an aggregate cross-sectoral level [9] and the comparative assessment of CAP reform scenarios as policy counterfactuals [20], but neither has focused specifically on the post-quota dairy and beef trajectory under the implemented CAP framework, with mechanism-level interpretation and food security implications [21]. In this study, food security implications are understood as the capacity of domestic production to meet national demand for staple animal proteins—captured through self-sufficiency ratios and import dependence—recognizing that, within the EU single market, availability is also secured through intra-EU trade rather than through domestic self-sufficiency alone. This is the analytical gap that the present study addresses.

The objective of this study is to simulate and analytically interpret the medium-term (to 2030) trajectories of the Croatian dairy and beef sectors using the AGMEMOD partial equilibrium framework, with an updated Croatian country-level model that incorporates the CAP 2023–2027 instruments as set out in the Croatian CAP Strategic Plan, the post-quota dairy specification consistent with the AGMEMOD 2017 outlook, and historical data extending to 2024. The analysis identifies the modelling drivers behind the simulated contraction trajectory, places the Croatian outcomes within the wider CEEC pattern, and derives food security implications for national agricultural policy.

To structure the analysis, three hypotheses are examined.

H1. 

Under the baseline CAP 2023–2027 framework, the Croatian dairy and beef sectors continue their structural contraction through 2030.

H2. 

The projected gains in milk yield per cow are insufficient to offset the decline in the dairy herd, so that aggregate milk production continues to fall.

H3. 

The deterioration in self-sufficiency continues, with direct implications for national food security.

These hypotheses are addressed through three research questions:

RQ1. 

What are the simulated medium-term trajectories of production, trade, and self-sufficiency in the Croatian dairy and beef sectors to 2030?

RQ2. 

Which modelling mechanisms generate these trajectories?

RQ3. 

Are the CAP 2023–2027 instruments, as implemented in the Croatian CAP Strategic Plan, sufficient to reverse the contraction under baseline assumptions?

The paper is structured as follows: Section 2 reviews the EU dairy and beef policy framework, surveys the post-accession structural transformation literature for CEECs, and positions the present study within the AGMEMOD applications to Croatian and CEEC agriculture. Section 3 details the AGMEMOD methodology and the Croatian-specific implementation. Section 4 presents the baseline simulation results. Section 5 discusses the mechanisms, comparison with the prior CEEC literature, and food security implications. Section 6 concludes.

2. Literature Review and Conceptual Framework

2.1. EU Dairy and Beef Policy Framework

The EU dairy market has undergone a profound transformation over the past three decades. The milk quota regime (1984–2015) constrained Member State production, supported domestic prices through the implicit quota rent, and shielded smaller and less competitive dairy systems from full competitive pressure. Its abolition, agreed in the 2003 Fischler reform and completed in 2015, marked a fundamental break with this regime.

The post-quota period has been characterized by significant production reallocation across the EU. The 2015 dairy market crisis exposed EU producers to global market signals once the quota cushion was removed; while the larger, capital-intensive systems of the EU dairy belt expanded production after 2015, smaller producers in less competitive Member States, including a number of CEECs, faced accelerated structural pressure [21,22].

The EU beef market followed a different policy trajectory. Historically supported through coupled premia, beef payments were progressively decoupled from the 2003 Fischler reform onward, while the 2013 reform preserved Member State discretion to retain Voluntary Coupled Support for sensitive sectors such as suckler cows and beef cattle; most Member States chose some level of coupled support, predominantly for livestock-related activities [20].

The CAP 2023–2027 framework, implemented through national CAP Strategic Plans, has further restructured the support architecture, retaining Voluntary Coupled Support for selected sensitive sectors alongside the new eco-schemes and a strengthened conditionality regime. The Croatian CAP Strategic Plan [23] implements these instruments with specific national choices on the level and allocation of Voluntary Coupled Support and on eco-scheme design, providing the policy environment for the present simulation.

2.2. Post-Accession Structural Transformation in CEEC Livestock Sectors

A substantial empirical literature has documented the structural transformation experienced by CEEC agricultural sectors in the years following EU accession. The dual farm structure characteristic of these economies, large-scale corporate farms (typically successors to former state and collective farms) coexisting with a high proportion of small family farms created divergent adjustment trajectories. While the corporate farms typically had the scale, capital and management capacity to adapt to single-market competition, family farms in livestock sectors faced significant constraints: limited access to investment capital, fragmented production structures, weak processing infrastructure in some segments, and competitive pressure from imports of more standardized products from larger EU producers [2,6,24].

The systematic divergence of CEEC agricultural performance during the first decade of EU membership has been documented, with crop sectors typically expanding while livestock sectors contracted in many Member States [5,6]. An early outlook for CEEC agricultural markets anticipated some of these dynamics [7]. The contraction of Slovak livestock production over 2004–2017 has been documented, with cattle herd reductions in line with patterns observed elsewhere in the region [25]. A longer-term assessment confirms that, twenty years after the first wave of CEEC accessions, the regional pattern of relative livestock contraction remains observable [24]. Across this literature, the modelling-based assessment of how this contraction interacts with the most recent CAP reform (CAP 2023–2027 Strategic Plans) at the level of an individual small Member State remains underdeveloped, particularly for Croatia.

2.3. AGMEMOD Applications to CEEC and Croatian Agriculture

The AGMEMOD framework (Agricultural Member State Modelling) is a dynamic, multi-product, multi-country partial equilibrium model that has been developed and maintained by the AGMEMOD Partnership since the early 2000s [21,26,27]. The model adopts a bottom-up approach: a common country-model template is applied to each EU Member State (and to selected non-EU countries), with country-specific behavioural equations estimated econometrically on national time-series data. Country-level models are subsequently combined into an aggregate EU model that imposes the supply–use identity at both the country and EU level. AGMEMOD is one of the three principal partial equilibrium models used by the European Commission’s Joint Research Centre within the iMAP modelling platform, alongside CAPRI and AGLINK [21,28].

AGMEMOD has been applied to a wide range of CEEC agricultural policy questions. The framework has been used to analyse the impact of alternative direct payment options on agricultural markets across ten new EU Member States [27]. Also, the application of Macedonia, a non-EU country, focused on livestock, dairy and grain sectors, has also been developed [29]. AGMEMOD has further been used to assess the impact of Russia and Ukraine on EU agricultural price formation [30]. Most recently, the AGMEMOD framework has been integrated into a comprehensive medium-term outlook for EU Member States with explicit treatment of the EU-N13 (the Member States that joined the EU after 2004), including specific projections for the dairy and beef sectors [21].

Two prior studies have applied the AGMEMOD framework to Croatian agriculture. An aggregate ex post and ex ante assessment of the accession impact across all main Croatian crop and livestock sectors has been provided, using the pre-CAP-2022 policy framework and an aggregate sector-wide perspective; the dairy and beef sectors were treated as components of a wider sectoral landscape rather than as the analytical landscape [9]. Three CAP post-2022 reform scenarios for the main Croatian crop and livestock markets have also been simulated, with the focus on comparative differences between scenarios as policy counterfactuals [20].

The present study differs from these prior contributions in several respects. First, the analytical focus is sharpened from broad cross-sectoral assessment to the dairy and beef sectors specifically, identified in Section 1 as the structurally most exposed Croatian livestock segments. Second, the empirical anchor is the post-quota era (post-2015) rather than the broader accession period, allowing the analysis to focus specifically on the structural adjustment dynamics generated by the post-quota transition. Third, the policy environment is the CAP 2023–2027 framework as actually implemented in the Croatian Strategic Plan [23], not a hypothetical reform scenario used in our prior work. Fourth, the AGMEMOD Croatian country-level model has been updated with the post-quota dairy specification [21] and historical data extended to 2024. Fifth, and most importantly, the analytical content moves beyond simulation to mechanism-level interpretation of the modelling drivers and to explicit food security implications (Section 5) under the implemented CAP framework.

3. Material and Methods

3.1. The AGMEMOD Framework: Operational Specification

The AGMEMOD model used in this research is a dynamic, multi-product, multi-country partial equilibrium model similar to GOLD model [31,32]. For the Croatian application, the model implements a country-specific template covering the main agricultural commodity markets, with explicit treatment of the dairy and beef sub-models that are the focus of this study. In order for the model to satisfy the partial equilibrium condition at the country and EU level, the following supply–use identity must hold for each commodity in each year:

Production_t + Import_t + Beginning stocks_t = Consumption_t + Export_t + Ending stocks_t

(1)

Within each commodity sub-model, the supply–use identity is closed by an endogenously determined closure variable (typically imports or net exports), while behavioural equations describe producer and consumer responses to market signals (prices, costs, lagged endogenous variables) and exogenous drivers (macroeconomic conditions, policy instruments, world market prices).

3.2. Croatian Country-Level Model: Data Sources and Calibration Period

The Croatian AGMEMOD country-model used in this study is implemented in AGMEMOD(v8.0), with the post-quota dairy specification consistent with Salamon et al. [21] and the implementation of CAP 2023–2027 instruments as set out in the Croatian CAP Strategic Plan [23]. The model is calibrated on the available historical Croatian series and anchored to the most recent observed year (2024), spanning the late pre-accession adjustment phase and the full post-accession period including the 2015 milk quota abolition. The simulation horizon is 2025–2030.

Data sources are as follows: endogenous variables (production volumes, areas, animal stocks, slaughter, supply–use balance components) are sourced primarily from the Croatian Bureau of Statistics (CBS) database and from the Annual Reports on the State of Agriculture (Green Reports) published by the Croatian Ministry of Agriculture. EU-level reference data and EU key prices are sourced from Eurostat and from the European Commission DG AGRI dashboard, supplemented by FAOSTAT for cross checks where required. Exogenous macroeconomic variables (population, GDP per capita, exchange rate, inflation rate) are taken from the Croatian Bureau of Statistics, Eurostat, and the IMF World Economic Outlook database. Policy parameters are taken from the Croatian CAP Strategic Plan and the relevant EU regulations [33].

3.3. Model Equation Structure

The Croatian country module comprises three principal categories of relationship:

(i)

Behavioural relationships (calibrated): the price-responsive supply and demand equations—for example whole-milk supply, milk yield per cow, the cattle and suckler cow equations, and the per capita demand equations—whose parameters are calibrated to theoretically consistent elasticities rather than obtained by free single-equation estimation. Because the Croatian national series are short and span major structural breaks (the 1990s transition, EU accession in 2013, and milk quota abolition in 2015), unconstrained single-equation estimation is not statistically informative for these relationships, so their parameters are calibrated; this is standard practice within the AGMEMOD Partnership [21]. Several of the principal reported quantities—dairy cow numbers, beef and veal production, and the calf-crop—then follow as accounting identities (category (iii) below), while whole-milk supply is itself one of the calibrated behavioural equations.

(ii)

Fixed and stylized relationships: a small number of relationships represented by fixed-coefficient calibrated rules (for example the cow-slaughter demographic rule), used where temporal variation in the relevant variables is too weak to identify a behavioural response. Throughout, parameters are calibrated to the Croatian production structure so that the implied own-price, income, and supply elasticities take theoretically consistent signs and economically plausible magnitudes. The principal elasticities underlying the simulated dairy and beef trajectories are summarized in Table 3a; their signs confirm the behavioural consistency of the calibration.

(iii)

Identities: non-behavioural relationships imposed by the model architecture, including the supply–use identity (Equation (1)), the dairy cow identity (dairy cows = whole-milk supply/milk yield per cow), the beef production identity (sum over slaughter categories of slaughter × slaughter weight), and the closure variable identity that determines net imports endogenously to balance the supply–use identity in each year.

Conventional regression diagnostics (R², t-statistics, Durbin–Watson) are not defined for the identity-based relationships that determine the principal dairy and beef quantities, and would be statistically uninformative for the short underlying national series. Coefficient signs and magnitudes for the calibrated behavioural equations have been verified against theoretical expectations and biological constraints as part of the country team self-validation procedure (Section 3.5). The principal calibrated elasticities of the dairy and beef module are summarized in Table 3a. Table 3 summarizes the equation classification for the principal behavioural relationships in the Croatian dairy and beef sub-models.

Table 3. Classification of principal behavioural equations in the Croatian AGMEMOD country model. (a) Key calibrated point elasticities underlying the simulated dairy and beef trajectories.

Behavioural Relationship	Sub-Model	Type	Notes
Whole-milk supply	Dairy	Calibrated	Function of the milk price-to-input-cost ratio and a structural-break dummy
Milk yield per cow	Dairy	Calibrated	Function of trend (technological progress) and price–cost ratio
Dairy cows	Dairy	Identity	= whole-milk supply/milk yield per cow
Per capita milk demand	Dairy	Calibrated	Function of own-price, GDP per capita, lagged consumption
Dairy product prices (transmission)	Dairy	Calibrated	Linked to Germany as the EU dairy key market
Beef cow ending stocks	Beef	Calibrated	Function of beef price, calf price, and lagged stocks
Calf-crop equation	Beef	Identity	Links dairy and beef cow ending stocks to calf production
Slaughter category proportions	Beef	Calibrated	Stylized proportions reflecting Croatian slaughter structure
Slaughter weight per category	Beef	Calibrated	Function of lagged slaughter weight, price, category proportion
Beef and veal production	Beef	Identity	= sum over categories of (slaughter × slaughter weight)
Per capita beef demand	Beef	Calibrated	Function of own-price, cross-prices (pork, poultry), GDP per capita
Beef price transmission	Beef	Calibrated	Linked to Italy/EU-average beef key market
Imports	Both	Closure variable	Determined endogenously to balance the supply–use identity
Net exports (EU-level)	Both	Identity	= total EU production + stocks − use − ending stocks
(a)
Relationship	Elasticity type		Value
Whole-milk supply	Own-price (supply)		0.99
Milk yield per cow	Own-price (supply)		0.73
Suckler cow herd	Own-price (supply)		0.35
Cattle slaughter	Own-price (supply)		0.34
Beef and veal demand	Own-price (demand)		−0.31
Beef and veal demand	Income		0.89
Milk demand	Income		0.72

Source: Authors’ classification following the AGMEMOD Partnership modelling framework. Authors’ calibration of the AGMEMOD Croatian country module; point elasticities evaluated at sample means. Own-price demand elasticities are negative, income and own-price supply elasticities positive, consistent with theoretical expectations.

Table 3. Classification of principal behavioural equations in the Croatian AGMEMOD country model. (a) Key calibrated point elasticities underlying the simulated dairy and beef trajectories.

Behavioural Relationship	Sub-Model	Type	Notes
Whole-milk supply	Dairy	Calibrated	Function of the milk price-to-input-cost ratio and a structural-break dummy
Milk yield per cow	Dairy	Calibrated	Function of trend (technological progress) and price–cost ratio
Dairy cows	Dairy	Identity	= whole-milk supply/milk yield per cow
Per capita milk demand	Dairy	Calibrated	Function of own-price, GDP per capita, lagged consumption
Dairy product prices (transmission)	Dairy	Calibrated	Linked to Germany as the EU dairy key market
Beef cow ending stocks	Beef	Calibrated	Function of beef price, calf price, and lagged stocks
Calf-crop equation	Beef	Identity	Links dairy and beef cow ending stocks to calf production
Slaughter category proportions	Beef	Calibrated	Stylized proportions reflecting Croatian slaughter structure
Slaughter weight per category	Beef	Calibrated	Function of lagged slaughter weight, price, category proportion
Beef and veal production	Beef	Identity	= sum over categories of (slaughter × slaughter weight)
Per capita beef demand	Beef	Calibrated	Function of own-price, cross-prices (pork, poultry), GDP per capita
Beef price transmission	Beef	Calibrated	Linked to Italy/EU-average beef key market
Imports	Both	Closure variable	Determined endogenously to balance the supply–use identity
Net exports (EU-level)	Both	Identity	= total EU production + stocks − use − ending stocks
(a)
Relationship	Elasticity type		Value
Whole-milk supply	Own-price (supply)		0.99
Milk yield per cow	Own-price (supply)		0.73
Suckler cow herd	Own-price (supply)		0.35
Cattle slaughter	Own-price (supply)		0.34
Beef and veal demand	Own-price (demand)		−0.31
Beef and veal demand	Income		0.89
Milk demand	Income		0.72

Source: Authors’ classification following the AGMEMOD Partnership modelling framework. Authors’ calibration of the AGMEMOD Croatian country module; point elasticities evaluated at sample means. Own-price demand elasticities are negative, income and own-price supply elasticities positive, consistent with theoretical expectations.

3.4. Key Markets and Price Transmission

The price transmission equations link Croatian domestic prices to EU key market prices through self-sufficiency rate modulated functions. The key markets used in this study are: (i) Germany for raw milk and dairy products (consistent with the AGMEMOD Partnership convention identifying Germany as the EU dairy key market, given its dominant share of EU milk production and its status as the price reference market for dairy commodities); (ii) Italy and the EU-average price for beef and veal (reflecting Italy as the principal trading partner for Croatian beef and veal exports and the EU-average as a benchmark for the broader CAP 2023–2027 reference framework). World market prices, where required for the EU key-price formation, are sourced from the FAPRI World Outlook and the OECD-FAO Agricultural Outlook.

3.5. Validation Procedure

Validation follows the standard two-phase AGMEMOD procedure [21,26]:

Phase 1—country team self-validation: The country team checks (i) the in-sample tracking of the calibrated behavioural equations against historical Croatian Bureau of Statistics data; (ii) sign consistency of the calibrated coefficients with theoretical expectations (positive own-price elasticity for supply, negative own-price elasticity for demand, positive cross-price elasticity for substitutes, etc.); (iii) magnitude consistency with elasticities reported in the AGMEMOD Partnership and in prior published partial equilibrium models for comparable Member States; (iv) biological constraint consistency (dairy cow numbers and milk yield per cow within physiologically plausible ranges; slaughter weights consistent with breed structure; calf-to-cow ratios within realistic bounds). Where in-sample tracking is unsatisfactory or where coefficient signs are inconsistent with theory, equations are re-specified or their parameters re-calibrated to restore theoretical consistency.

Phase 2—external validation: The country team baseline projection is cross compared against the AGMEMOD EU-N13 outlook [21] for the dairy and beef sectors, identifying systematic divergences and reconciling them where possible. Croatian dairy and beef sector experts, including agricultural economists familiar with the Croatian production structure and representatives of the relevant producer associations, are consulted for qualitative validation of the projection trajectories, with feedback structured around the standard AGMEMOD fact-sheet format (“much too high/too high/about right/too low/much too low” assessment of each principal simulation, plus identification of drivers and game changers). Adjustments to equation specification, parameters, or exogenous assumptions are made where the qualitative validation identifies systematic implausibilities.

Because the principal dairy and beef quantities are determined through identities and historically anchored equations, in-sample fit statistics are uninformative as a validation criterion; validation therefore relies on the theoretical consistency and biological plausibility checks of Phase 1 and the EU-N13 cross-comparison of Phase 2 rather than on in-sample prediction-error metrics. The simulated Croatian trajectory is directionally consistent with the broader EU medium-term agricultural outlook, in which the EU cow herd contracts and milk production reaches a turning point as the dairy herd decline ceases to be offset by yield gains, and with the lower competitiveness of the new Member States’ livestock sectors documented in the AGMEMOD EU-N13 outlook [21]. Quantitatively, the EU agricultural outlook to 2035 projects the EU cow herd to contract by approximately 9.6% and EU beef production by approximately 6.7% relative to the 2022–2024 average [34]; the simulated Croatian contraction (dairy cows down 6.9% and beef and veal down 11.0% by 2030) is of the same direction and broadly comparable in magnitude, though steeper for beef, consistent with Croatia’s less consolidated and smaller-scale production structure and with the shorter Croatian projection horizon (2030 versus 2035).

3.6. Equation Specifications of Dairy and Beef Sub-Models

The general behavioural equation form used in the model is as follows:

$$Y=f\left(X_1;X_2;X_3\right)$$

(2)

Which is operationalised in linear in parameters form as follows:

$$Y=\alpha +{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_3{X}_3\dots +ϵ$$

(3)

where Y is the dependent variable, X_i are explanatory variables, α is the intercept, β_i are regression coefficients, and ε is the error term.

The principal behavioural relationships in the livestock sub-model are as follows. Breeding herd ending stocks:

$${cct}_{i,t}=f\left({cct}_{i,t-1}^k,p_{i,t},V\right)$$

(4)

With cct_i,t denoting the number of breeding animals of species i in year t, p_i,t the relevant real price, and V a vector of exogenous variables (policy support, costs, lagged-dependent).

spr_i,t = f(ccti,t − 1, ypai,t)

(5)

Slaughter by category j within species i:

ktti,tj = f(ccti,tj, pi,t, zi,tj, V)

(6)

Average slaughter weight:

slwi,t = f(slwi,t − 1, pi,t, zi,tj, V)

(7)

Total meat production from species i (identity):

ktti,t = ∑j(ktti,tj × slwi,tj)

(8)

Per capita demand for meat type i:

upci,t = f(upci,t − 1, pi,t, pk,t, gdpct, V)

(9)

For the dairy sub-model, milk yield per dairy cow:

ypct = f(trend, pwnt/icit, V)

(10)

Whole-milk supply is determined behaviourally as a function of the milk-price-to-input-cost ratio (Supplementary Materials S1); milk yield per cow is given by Equation (10); and the dairy cow number then follows from the following identity:

ccdairyt = sprt/ypct

(11)

3.7. Baseline Assumptions

The medium-term baseline simulation of the Croatian dairy and beef sectors assumes: (i) continuation of the CAP 2023–2027 framework throughout the projection period [35], with the Croatian CAP Strategic Plan instruments implemented as set out in the official Strategic Plan documents; (ii) stable climatic conditions over the projection horizon (no extreme weather shocks); (iii) absence of major external shocks such as significant macroeconomic disruption, animal disease outbreaks, or geopolitical disturbances of the EU dairy/beef trade; and (iv) continuation of historical trends in the exogenous macroeconomic variables (population, GDP per capita, exchange rate, inflation rate) in line with national and international medium-term projections (Croatian Bureau of Statistics; IMF World Economic Outlook). The baseline thus serves as a reference scenario against which alternative scenarios can be compared in future work.

4. Results

4.1. Beef and Veal Sector Simulation

The baseline simulation for the Croatian beef and veal sector indicates a continued contraction of domestic production capacities and a deepening reliance on imports through 2030 (Table 4). These outcomes are conditional on the baseline assumptions set out in Section 3.7 and should be interpreted as the trajectory implied by current policy continuation rather than as an inevitable outcome. The total cattle population is projected to follow a steady downward trajectory, decreasing from 422.5 thousand heads in 2024 to 405.7 thousand heads by the end of the decade, representing a 4.0% decline. While beef and veal meat production volume is anticipated to drop by 11.0%, domestic use is simulated to rise by 2.7%, reaching 64.6 thousand tonnes by 2030. Imports are expected to continue their upward trend, increasing by 4.7% to reach 40.2 thousand tonnes by 2030, while exports are simulated to face a sharp contraction of 21.4%, falling from 9.4 thousand tonnes in 2024 to 7.4 thousand tonnes.

Table 4. Baseline outlook simulation on Croatian beef and veal sector (2013–2030).

Year	Live Animals (1000 Heads)	Production (1000 t)	Domestic Use (1000 t)	Imports (1000 t)	Exports (1000 t)	Net Exports (1000 t)	Self-Sufficiency (%)
2013	442.4	47.3	55.8	10.2	3.4	−6.9	76%
2014	440.6	44.4	56.8	14.5	4.2	−10.3	71%
2015	440.1	42.3	57.5	17.4	4.3	−13.1	66%
2016	444.6	44.4	61.1	20.0	6.5	−13.4	62%
2017	450.8	42.2	61.3	22.0	5.9	−16.2	58%
2018	414.1	43.8	62.6	22.6	7.6	−15.0	65%
2019	420.2	45.4	63.3	24.7	7.7	−17.1	66%
2020	422.9	43.4	62.7	22.5	6.2	−16.3	66%
2021	427.6	43.2	62.7	26.8	6.7	−20.2	66%
2022	421.8	41.2	63.0	31.3	7.1	−24.2	65%
2023	415.2	38.4	62.1	35.4	7.4	−28.1	62%
2024	422.5	37.2	62.9	38.4	9.4	−29.0	59%
2025 *	419.4	36.7	62.7	38.6	9.2	−29.4	59%
2026 *	416.1	36.4	62.8	38.8	9.3	−29.4	58%
2027 *	411.2	35.5	62.9	39.0	8.6	−30.4	57%
2028 *	408.7	34.8	63.1	39.2	8.5	−30.7	55%
2029 *	407.5	34.1	63.8	39.5	8.2	−31.4	53%
2030 *	405.7	33.1	64.6	40.2	7.4	−32.8	51%
Change (%) 2030/2024	−4.0%	−11.0%	2.7%	4.7%	−21.4%	−13.1%	−13.3%

* Data from 2025 onwards represent baseline simulation results, based on the baseline assumptions detailed in Section 3.7. Source: AGMEMOD v8.0 modelling results; historical data based on Croatian Bureau of Statistics.

As a result of these simulated market dynamics, the self-sufficiency rate is projected to deteriorate significantly. After falling from 76% at the time of EU accession (2013) to an estimated 59% in 2024, the simulation indicates a further decline to just 51% by 2030. This represents a 13.3% reduction in self-sufficiency relative to 2024, suggesting that, by the end of the decade, Croatia will be able to satisfy barely half of its domestic beef and veal meat demand through national production.

The dairy decline propagates to beef through the calf-crop equation (Equation (5)), as the cohort of male calves available through the dairy-to-beef pathway diminishes. The expansion in suckler and other beef cows (from 13.5 to 59.2 thousand head over 2013–2024) only partially offsets this, yielding the projected 11.0% decline in beef and veal production over 2024–2030. With domestic use relatively stable (per capita demand equations driven by income and population), the supply–use identity closes through rising imports and falling self-sufficiency, reinforced by deteriorating price competitiveness transmitted from EU key markets (Germany for dairy, Italy and EU-average for beef). On the production side, meat output is generated by the slaughter and slaughter weight equations operating against this moderately declining stock base.

4.2. Dairy Sector Simulation

The baseline simulation for the dairy sector follows a similar trend to that observed in the beef and veal sector, characterized by a continued decline in the national dairy herd (Table 5). The number of dairy cows is expected to decrease from 70.9 thousand heads in 2024 to 66.0 thousand heads by 2030, representing a reduction of 6.9%. While the model accounts for a gradual improvement in milk yield per cow projected to rise by 2.5% to reach 6513 L by 2030, this technological progress is insufficient to compensate for the diminishing number of animals. Consequently, total milk production is projected to fall by 8.6%, dropping from 437.44 million litres in 2024 to 399.62 million litres by the end of the decade. This decline continues a sharp historical downturn; for context, production in 2030 is estimated to be nearly 46% lower than it was at the time of EU accession in 2013.

Table 5. Baseline outlook simulation on Croatian dairy sector (2013–2030).

Year	Dairy Cows (1000 Heads)	Milk Yield (L/Cow)	Milk Production (Million L)	Domestic Use (Million L)	Imports (Million L	Exports (Million L)	Self-Sufficiency (%)
2013	168.0	4271	737.51	906.24	186.47	35.47	66%
2014	159.4	4450	727.56	908.64	197.65	33.14	66%
2015	151.5	4516	706.43	896.60	207.94	35.53	65%
2016	146.5	4565	691.03	905.50	237.89	46.84	65%
2017	139.4	4598	690.18	920.21	255.15	50.24	64%
2018	135.9	4602	654.12	929.63	273.45	55.89	65%
2019	130.0	4608	581.77	961.37	276.76	54.32	55%
2020	109.8	5432	579.10	937.24	281.43	46.58	59%
2021	102.3	5449	541.34	957.09	317.19	42.87	54%
2022	79.0	6610	507.23	955.66	351.30	45.74	53%
2023	71.4	6552	454.32	966.40	404.21	44.25	47%
2024	70.9	6356	437.44	964.25	421.09	48.56	46%
2025 *	70.5	6398	431.33	963.56	426.14	47.82	45%
2026 *	69.5	6411	425.45	964.05	438.46	47.03	44%
2027 *	69.0	6435	417.28	964.28	440.22	46.44	43%
2028 *	68.1	6470	410.85	967.66	445.70	45.78	42%
2029 *	67.2	6507	407.45	973.38	449.02	44.20	42%
2030 *	66.0	6513	399.62	978.87	453.68	42.86	41%
Change (%) 2030/2024	−6.9%	2.5%	−8.6%	1.5%	7.7%	−11.7%	−12.0%

Note: Values for 2013–2024 are observed data (Croatian Bureau of Statistics; Eurostat); values for 2025–2030 are AGMEMOD baseline projections. Part of the increase in average milk yield per cow over the period reflects a composition effect arising from the selective exit of small-scale dairy holdings [36]. * Data from 2025 onwards represent baseline simulation results, based on the baseline assumptions detailed in Section 3.7. Source: AGMEMOD v8.0 modelling results; historical data based on Croatian Bureau of Statistics.

The mismatch between domestic supply and demand remains the primary driver of the sector’s trade dynamics. Domestic use is simulated to remain relatively stable, with a slight upward trend of 1.5%, reaching 978.87 million litres by 2030. To address the growing production deficit, imports are expected to increase by 7.7%, surpassing 453 million litres by 2030. As a result of these shifts, the self-sufficiency rate for milk in Croatia is expected to reach an all-time low of 41% by 2030, representing a 12.0% decrease compared to 2024 levels.

On the supply side, whole-milk supply responds to a milk price–cost ratio (pwn/ici) under sustained pressure: EU dairy belt expansion in the post-quota era transmits downward pressure on raw milk prices through the German key market, while production costs rise with input trends. The resulting price–cost ratio disadvantages Croatian producers, generating a gradual contraction in whole-milk supply. With milk yield per cow improving only modestly (Equation (10), from 6356 to 6513 L/cow), the dairy cow number recovered from the identity (dairy cows = whole-milk supply/milk yield per cow, Equation (11)) declines correspondingly over the projection horizon.

The CAP 2023–2027 instruments operative under the baseline provides partial support but do not, on their own, reverse the simulated contraction over the projection horizon; whether alternative or recalibrated instruments could reverse it is not tested in this baseline-only study. Policy implications are discussed in Section 5.

5. Discussion

The simulated contraction trajectory of the Croatian dairy and beef sectors should be understood not as a forecast in the strict sense, but as the equilibrium outcome of the AGMEMOD recursive solution under the baseline assumptions and the CAP 2023–2027 policy environment. The trajectory is generated by the interaction of three principal mechanisms identified in Section 4; the price–cost-driven contraction of the dairy cow stock, the propagation of dairy decline into the beef sector through the calf-crop pathway, and the endogenous trade adjustment as the supply–use identity is closed under projected supply contraction with relatively stable demand.

Two features of this mechanism deserve specific emphasis. First, the post-quota era has fundamentally altered the policy environment in which the Croatian dairy sector operates. Under the previous quota regime, the implicit quota rent supported maintenance of dairy herds in less competitive Member States, including Croatia, through a price floor effect. After the 2015 abolition, this implicit support has been removed, and the Croatian dairy sector is exposed directly to the competitive dynamics of the EU dairy belt. The continued simulated decline in dairy cows under the baseline reflects the persistence of this competitive pressure, not a disequilibrium adjustment that might be expected to dissipate.

Second, the dairy-to-beef propagation mechanism creates a sectoral coupling that has policy implications. Beef sector outcomes in Croatia cannot be separated from dairy sector dynamics; the calf cohort that supplies the beef chain is closely linked to dairy herd numbers. Policy interventions targeted at one sector therefore have spillover effects on the other. The increasing share of suckler cows visible in Table 1 represents a partial structural compensation, but it does not fully offset the dairy decline.

The Croatian simulation results described in this study fits the broader CEEC pattern of post-accession livestock sector contraction documented in the empirical literature. Csaki and Jambor [5,6], in their assessments of the first decade of EU membership for the new Member States, document systematic divergence between crop sectors (typically expanding) and livestock sectors (typically contracting), particularly for dairy and beef. The specific trajectory observed for Croatia, a particularly sharp contraction in dairy cow numbers, a more moderate cattle population decline, and a continued deterioration of livestock self-sufficiency is in line with patterns observed in Némethová and Hudáková [25] for Slovakia and in the AGMEMOD 2017 EU-N13 outlook [21] for several CEEC Member States. The longer-term assessment by Jambor and Gorton [24] confirms that the regional pattern of livestock contraction has not been substantively reversed twenty years into the CEEC accession experience.

Two features distinguish the Croatian case within this broader pattern. First, Croatia is the most recent CEEC accession (2013) and the smallest CEEC Member State in absolute production terms; the structural exposure to single-market competition is therefore particularly acute. Second, the magnitude of the dairy cow contraction (−57.8% over 2013–2024) is at the higher end of the CEEC range, suggesting that Croatian dairy production faced particularly severe post-accession adjustment pressure relative to comparable Member States. The simulated results can be explained by this joint exposure to single-market price convergence (after 2013) and post-quota competitive reallocation (after 2015), with both shocks falling on a sector with limited prior preparation in terms of farm consolidation, capital investment, and processing infrastructure.

The simulated self-sufficiency path carries direct food security implications. By 2030, Croatian domestic production is projected to satisfy only 41% of milk demand and 51% of beef and veal demand. Under the EU single-market arrangement, this import dependence does not translate into immediate food security risk, since the EU dairy and beef markets remain net surplus and integrated. Food security in this integrated setting therefore rests on availability and access through the single market rather than on domestic self-sufficiency alone, so the self-sufficiency decline is better read as an indicator of eroding domestic production capacity and resilience than as an immediate supply risk. However, the simulated trajectories raise systemic resilience questions, particularly in the context of the multiple recent stresses on EU agri-food systems documented in the literature [37,38,39,40,41], the COVID-19 pandemic, the energy market shocks of 2021–2022, the geopolitical disruptions associated with the war in Ukraine, and the ongoing structural pressures from climate change and rising input costs.

The CAP 2023–2027 framework as currently implemented in the Croatian Strategic Plan provides Voluntary Coupled Support for cattle (including suckler cows), eco-schemes that incentivize sustainable production practices, Basic Income Support, and other measures that link payments to environmental and animal welfare standards. Under the baseline calibration in this study, these instruments provide partial support to the Croatian dairy and beef sectors but, over the projection horizon, do not reverse the simulated contraction; whether they could be recalibrated or augmented to do so is not tested in the present baseline-only study. The policy implication is that, if reversal of the trajectory or stabilization at higher self-sufficiency levels is a national policy objective, additional or differently calibrated instruments would be required: examples that warrant scenario analysis in future work include enhanced Voluntary Coupled Support, accelerated structural-modernization investment under Pillar II, and targeted farm support measures consistent with EU State Aid rules.

These observations are consistent with a broader strand of the recent literature emphasizing the tension between the environmental and climate ambitions of CAP 2023–2027 reform and the economic viability of livestock production in structurally vulnerable Member States [42,43]. The present study contributes quantitative evidence on this tension for the Croatian case, suggesting that the current calibration of the policy mix prioritizes environmental and structural efficiency outcomes that, in the Croatian context, may be inconsistent with maintaining domestic production capacity in dairy and beef.

6. Conclusions

This study has simulated and analytically interpreted the medium-term (to 2030) trajectories of the Croatian dairy and beef sectors using the AGMEMOD partial equilibrium framework with an updated country-level model implementation under the CAP 2023–2027 framework. The principal quantitative findings are: (i) the dairy cow population is projected to decline from 70.9 thousand head in 2024 to 66.0 thousand head in 2030 (−6.9%), continuing the historical post-accession contraction; (ii) milk production is simulated to fall by 8.6% to 399.6 million litres in 2030, representing approximately 46% of the 2013 production level; (iii) the total cattle population declines by 4.0% to 405.7 thousand head, and beef and veal production falls by 11.0% to 33.1 thousand tonnes; and (iv) self-sufficiency rates deteriorate to 41% for milk and 51% for beef by 2030, the lowest simulated levels in the historical record.

6.1. Policy Implications

The findings have direct policy implications for Croatian agricultural policy. The current calibration of the CAP 2023–2027 instruments under the Croatian Strategic Plan, while providing partial support to the dairy and beef sectors, is unlikely under baseline assumptions to reverse the simulated contraction trajectory. If the maintenance or stabilization of domestic production capacity is a national policy objective, motivated by the food security, rural employment, or territorial cohesion objectives that the literature identifies as legitimate non-trade concerns, then policy adjustments warrant consideration. Specific avenues include recalibration of Voluntary Coupled Support levels for cattle and dairy, intensified Pillar II investment support targeted at dairy modernization, herd consolidation, and processing infrastructure, eco-scheme design that aligns environmental objectives with continuation of dairy and beef production rather than with sector exit and targeted farm support measures consistent with EU State Aid rules. These avenues should be assessed through scenario analysis in future work. They are implications drawn from the baseline evidence rather than policy alternatives tested within the present model.

6.2. Limitations

The principal limitations of the analysis arise from the partial equilibrium framework. As a sectoral model designed primarily for medium-term market and trade analysis, AGMEMOD provides results at an aggregate sectoral level and does not capture adjustments at the individual farm level. Pillar II rural development measures and policy instruments aimed at delivering public goods are not explicitly incorporated. The analysis is conditional on the baseline assumptions about exogenous variables (macroeconomic conditions, climatic conditions, absence of major shocks); deviations from these assumptions would alter the projected trajectories. These limitations point to future research directions. In particular, scenario analysis of the post-2027 CAP reform—the natural extension of this baseline—is left for future work, in line with the standard AGMEMOD sequence in which policy scenarios are assessed as deviations from the baseline. Complementary analytical work could also link the AGMEMOD framework to farm-level models capable of capturing the heterogeneous adjustment dynamics within the Croatian dual farm structure, and to environmental and territorial models that could quantify the public good dimensions outside the partial equilibrium framework.