Academy Review · 2026 · № 2 (65) · pp. 66–80

Equilibrium of the Dairy Business in Ukraine

An econometric look at why milk and dairy prices hold a deterministic, seasonal rhythm over two decades — while competition between households and enterprises keeps the market in balance despite war, crises, and seasonality.

VD
Viktoriia Dmytriieva PhD (History), Associate Professor · Dnipro State Agrarian and Economic University
DOI ↗ ORCID ↗ UDC 330.3 JEL C55 · E32 · E37 · O11 · O13
0%
Agriculture's share of Ukraine's GDP at the end of 2023 — 4th-largest sector
0
Months of producer prices analysed, 2003–2023
0
Average-price values across the price database
0
Product categories tracked, from cereals to dairy
01 · Overview

Abstract

Due to Ukraine's climatic and geographical features, agriculture makes a relatively significant contribution to the country's gross domestic product compared to other industries. At the end of 2023, this sector accounted for 8.5% of total GDP, ranking fourth after the processing industry, wholesale and retail trade, and public administration. Agriculture, as a complex system, consists of several components: the cultivation of grain, industrial, fodder, and vegetable crops, fruits, berries, and other plant production; and livestock production.

Unlike other industries, which are less dependent on seasonal factors, agriculture is sensitive to environmental conditions and subject to the laws of nature and seasonality. Among the indicators of these influences, price is the most responsive in the Ukrainian market economy — it reflects production costs and also signals shortages, surpluses, or sufficiency of output, and responds to changes in population demand. The main principle of a market economy is equality among business participants and freedom of competition: both large and small farms or enterprises have equal rights to produce and sell. The way they balance the market is illustrated here through the dairy industry, which maintains deterministic price dynamics over a long period despite exogenous and endogenous influences.

The analysis used data from official statistical sources, including the State Statistics Service of Ukraine, the World Bank Data portal, FAOSTAT, and others. Specialized Python libraries and tools were applied for econometric modeling, mapping, spatial analysis, and forecasting.

Price as a signal

Price is the most elastic indicator in the market — capturing costs, shortages, surpluses, and shifts in demand.

Seasonality rules

Agriculture answers to the laws of nature: harvest cycles, temperature, and daylight all leave their mark on prices.

Deterministic dairy

Milk and dairy hold the steadiest, most predictable rhythm of all categories — the focus of this study.

02 · Introduction & Review of Literature

What other scholars found

Analysis of economic systems uses different approaches, chosen by the goal of the research. Across recent work, regression analysis is the most applicable approach, with price treated as one of the most representative indicators in the economy. Studies range across farms, industries, single economies, and the world — increasingly relying on machine-learning algorithms to process large data sets.

[2]Regression · Ukraine

Internal grain prices form under the influence of world prices; weaker export ability and seasonal volatility negatively affect producers' profitability.

[3]Utility function · USA

Elasticity of substitution between domestic and imported fruits, berries, and vegetables, and the effect of import growth on domestic prices and farm profits.

[4]Regression · Ukraine

Lags in milk-price changes drive fluctuations in dairy-product prices; the model helped predict cost indicators.

[5]Marginal productivity

Productivity dispersion within farms across 26 European countries, using production output plus weather and soil conditions.

[6]Investment equations

Investment policy in dairy farms of transition economies (Estonia, Hungary, Slovenia); high discount rates raise dairy-farm sales.

[7]Farm size · Ethiopia

Larger farms hold more resources for effective operation — a relationship drawn between farm size and productivity.

[8·9]Digitalization

Digital technologies support stable, effective agriculture — but may be exclusive to small farms, risking inequality in development conditions.

[10]Markov model

Changes in product prices and quota restrictions may lead to expansion and strengthening of the milk industry.

[11]Supply-chain power · EU

Market structure and the EU unfair-trading directive: small firms dominate, yet greater productivity sits with large farms.

[12]System approach

Macroeconomic volatility from EU accession and the single currency in five Eurozone members; the 2008 crisis disrupted dynamics.

[13]Vector autoregression

Milk-cost fluctuations in France and Germany show asymmetric dynamics and sensitivity to external shocks.

[14]Megatrends

Wars, pandemics, and bankruptcies — plus innovation, climate change, demographics, and globalization — drive structural shifts.

[15]Machine learning

SVM, ridge/linear regression, and decision trees extract food-security factors; 104 indicators across political, military, economic, healthcare spheres.

[16]Autoregression · Italy

Risks in agriculture shape food security over time and space; regional diversification and productivity play a leading role.

[17]Regression · cluster

Regression and cluster analysis are frequently used in studies of agricultural growth stability.

[18]Economic security

Economic security is a key factor of competitiveness for farms — especially for countries facing military aggression.

[19]Econometrics · Ukraine

Econometric study of the structure and dynamics of Ukraine's agricultural exports.

[20]Logistics modeling

Optimization of logistics activities plays an important role for agricultural enterprises.

[21]Decomposition

GDP, consumer, and oil-price fluctuations decomposed into trend, seasonal, and random components to improve forecasts.

[22]Harmonic analysis

A universal way to reveal cycles of ups and downs in business activity within economic systems.

[23]Stochastic frontier

FADN data on 4,500 crop farms across 24 European countries over 14 years; data aggregation determines result quality.

[24]ML forecasting

Labor-market data in Colombia: optimal model selected via component/regression analysis, neural networks, and SVM.

[25]ESG · Bayesian

147 European agricultural companies: generalized least squares plus Bayesian networks link ESG investment to profitability.

Synthesis

Together these works reveal the complexity of economic systems and the range of characteristics for reconstructing their state and instability.

03 · Purpose & Data

The aim, and how it was reached

The purpose consists of several subgoals: examine the main trends in agricultural price fluctuations in Ukraine; study the dairy sector, whose prices stay deterministic despite destructive factors; and identify the causes behind these trends. Understanding sustainability in one sector may help improve others.

Step 01

General dynamics

Reconstructed from average monthly agricultural producer prices, 2003–2023.

Step 02

Animals & milk

Animal numbers and milk volume studied to reveal milk-productivity trends over the years.

Step 03

Enterprises & farms

Output of dairy enterprises and farms analysed for their role in milk-market stability.

Step 04

Spatial view

A spatial comparison of farm and enterprise contributions across the regions of Ukraine.

Official statistics

State Statistics Service of Ukraine, World Bank Data, FAOSTAT, and other official sources.

252 months · 1,764 values

Average prices across seven product categories over 252 months from 2003 to 2023.

Python toolchain

Specialized Python libraries for econometric modeling, mapping, spatial analysis, and forecasting.

Seven categories

Cereals & legumes, oilseeds, potato, vegetables, cattle & poultry, milk & dairy, and eggs.

04 · Results — Price Seasonality

Every product keeps its own calendar

Over 2003–2023, prices oscillate in rhythms of ups and downs on a steadily rising trend, with clear annual seasonality. Vegetable prices swing the most; grain and oilseed dynamics are similar, with a sharp 2022 surge after the full-scale invasion. Milk and dairy show the narrowest range — changing without catastrophic declines or sharp rises.

Grains & oilseeds

Prices usually rise in spring; harvest volumes from July to October push producers to cut prices during harvest months.

Potatoes & vegetables

The highest peak comes in mid-summer, when old stocks fall and fresh produce just begins to appear — then prices decline as harvest completes.

Cattle & poultry

Cheaper in late winter and spring; meat is more caloric and in demand during the cold season, and spoils quickly, so prices rise in warmer periods.

Fig. 2 — Heat map of seasonal price fluctuations
Normalized producer prices by month and category, 2003–2023. Lighter cells = higher average price for that month; darker = lower.
Low priceHigh price
Analyzed and compiled by the author based on data [26].
Seasonal rhythm, side by side
The same normalized index plotted as curves — note how milk & dairy and eggs peak in winter and bottom out in summer, mirror-imaging cattle & poultry.
Analyzed and compiled by the author based on data [26].

Milk & dairy and eggs fall to their lowest at the end of summer — driven by warmth, longer daylight, fresh plant feed, and physiological cycles that lift productivity. Of all categories, milk shows the smallest amplitude and the steadiest dynamic over two decades.

05 · Results — Milk & Herds

Fewer cows, less milk — but more per cow

Why is dairy so predictable? From 1990 to 2023, milk production declined in step with a shrinking dairy herd. Yet productivity per cow nearly doubled, even though profitability only turned reliably positive in the 2010s.

24,508 → 7,430
Gross milk production, thsd tons (1990 → 2023)
8,528 → 1,353
Number of cows, thsd heads (1990 → 2023)
2.87 → 5.49
Milk per cow, tons / year (1990 → 2023)
20.4%
Dairy profitability by 2020 — positive only since 2012 (2.3%)
Fig. 3 — Cow population vs. milk volume
The author's fitted regression line, with the 1990 and 2023 endpoints from official data. A polynomial fit would approximate better, but a linear function makes the dependence clear.
y = 1.4859*x + 6711.3814
Analyzed and compiled by the author based on data [28].
The long decline, 1990 → 2023
Herd and output both fell sharply over three decades.
Analyzed and compiled by the author based on data [28].

Modern animal-care technologies, high-quality feed, and improved living conditions lifted yield per cow from 2.87 to 5.49 tons. Even so, the profitability of the dairy business was not consistently high — it reached a stable positive trend only from 2012 (2.3%), rising to 20.4% by 2020.

06 · Results — Enterprises vs. Households

Two kinds of producer, one balanced market

Both large enterprises and individual households produce milk. The comparison uses end-of-2021 data — the most complete year, and the last before the full-scale invasion, allowing a reliable read under stable conditions. Until 2022, official statistics distinguished two groups (enterprises and households); from 2023, three (enterprises, farms, households).

Blue area · Fig. 4–5

Enterprises

  • Sell their products at higher prices
  • Distribution peaks at lower production volumes
  • Price–volume link is far weaker — prices stay flatter as output changes
Higher price · lower volume
Yellow area · Fig. 4–5

Households

  • Produce more and sell at lower prices
  • More volume drives their offered prices down
  • A significant, region-varying share of total milk output
Lower price · higher volume
07 · Results — Regional Map

Where households carry the dairy market

Households' share of total regional milk productivity in 2021. Their advantage is strongest in the south-central and western regions; the highest contributions — over 85% — appear in Rivne, Lviv, Ivano-Frankivsk, Zakarpattia, Chernivtsi, and Odesa Oblasts. Crimea is conditionally marked 0%: under occupation, it could not provide representative statistical reporting.

Fig. 6 — Households' contribution to milk production by region, 2021
Share of total regional milk productivity (%), shaded by contribution band.
≥ 85% — highest
66–84%
30–65% — moderate
No representative data
Analyzed and constructed by the author based on data [31; 32].
≥ 85%
Rivne, Lviv, Ivano-Frankivsk, Zakarpattia, Chernivtsi, Odesa
66–84%
Volyn, Zhytomyr, Ternopil, Khmelnytskyi, Vinnytsia, Kirovohrad, Mykolaiv, Dnipropetrovsk, Kherson, Zaporizhia, Luhansk
30–65%
Kyiv, Chernihiv, Sumy, Poltava, Cherkasy, Kharkiv, Donetsk
0%
Autonomous Republic of Crimea — under occupation; occupied parts of Donetsk & Luhansk excluded
08 · Results — Forecast

Steady growth, amid the same seasonal swing

A forecast of average dairy sales prices for 2003–2024 was built with a Fourier function applied to 252 months of data (Fig. 7). It points to continued steady growth amid seasonal fluctuations, with price growth anticipated in 2025 under similar conditions.

Fourier function

Seasonal price fluctuations reconstructed and projected from 252 monthly observations.

Price growth in 2025

The expected trajectory: steady upward dynamics with the familiar seasonal rhythm preserved.

Risks ahead

Specialists note falling domestic consumption and accumulating surpluses, plus war-related risks for domestic dairy.

By analysing price volatility, experts suggest mitigating further risks by improving relations between supply-chain partners — producers, manufacturers, retailers, and consumers. Mapping how that chain functions, and where it is weak or strong, could be the next stage of investigation.

09 · Conclusions

What the dairy market teaches us

The core finding

Competition keeps dairy in equilibrium

Enterprises sell at higher prices while households supply more milk at lower prices. This competition partially establishes a balance in the milk and dairy market — protecting it and consumers from catastrophic fluctuations in production volumes and prices.

01

Across 2003–2023, different sectors show their own price oscillations — but the most stable, seasonal dynamics belong to milk and dairy, dearer in winter and cheaper in summer.

02

Long-term trends in animal numbers and milk production reveal a clear reduction in the dairy-cattle population over the decades.

03

Comparing efficiency, enterprises command higher prices while households deliver more volume at lower prices — two complementary roles.

04

Households make a significant, region-varying contribution to milk production; under similar conditions, a price increase is expected in 2025.

References

Sources

As cited in the original article. Statistical sources marked (in Ukrainian).

  1. 1State Statistics Service of Ukraine (2023). Gross domestic product at current prices of 2023. (in Ukrainian)
  2. 2Zhybak M., Khrystenko H. (2024). Grain market in Ukraine: price situation and problems of development in the conditions of war. Agrosvit, 6, pp. 23–29. DOI
  3. 3Khanal, A., Poudel, D., & Gopinath, M. (2024). The Imported Challenge: Economic Impact of Fresh Fruit and Vegetable Imports on U.S. Producers. Journal of Agricultural and Applied Economics, 56(4), pp. 544–574. DOI
  4. 4Shyian, N., Moskalenko, V., Shabinskyi, O., & Pechko, V. (2021). Milk price modeling and forecasting. Agricultural and Resource Economics: International Scientific E-Journal, 7(1), pp. 81–95. DOI
  5. 5Wimmer, S., Finger R. (2025). Productivity Dispersion and Persistence in European Agriculture. American Journal of Agricultural Economics, pp. 1–28. DOI
  6. 6Fertő, I., Bojnec, Š., Fogarasi, J., & Viira, A. H. (2021). The investment behaviour of dairy farms in transition economies. Baltic Journal of Economics, 21(1), pp. 60–84. DOI
  7. 7Ameye, H., Bachewe, F.N., Minten, B. & Tamru, S. (2025). Farm size and agricultural productivity of nutritious foods: Evidence from Ethiopia. Journal of Agricultural Economics, 00, pp. 1–42. DOI
  8. 8Finger, R. (2023). Digital innovations for sustainable and resilient agricultural systems. European Review of Agricultural Economics, 50(4), pp. 1277–1309. DOI
  9. 9Cui, Y., Zhao, C., & Zhang, Q. (2024). Impact of digital transformation in agribusinesses on total factor productivity. International Food and Agribusiness Management Review, 27(5), pp. 843–857. DOI
  10. 10Ben Arfa, N., Daniel, K., Jacquet, F., & Karantininis, K. (2015). Agricultural policies and structural change in French dairy farms: A nonstationary Markov model. Canadian Journal of Agricultural Economics, 63(1), pp. 19–42. DOI
  11. 11Nes, K., Colen, L., & Ciaian, P. (2024). Market structure, power, and the unfair trading practices directive in the EU food sector: a review of indicators. Agricultural and Resource Economics Review, 53(3), pp. 454–477. DOI
  12. 12Hegerty, S. W. (2020). Macroeconomic volatility, monetary union, and external exposure: evidence from five Eurozone members. Baltic Journal of Economics, 20(2), pp. 117–138. DOI
  13. 13Fousekis, P. (2025). A time-varying and frequency-dependent network of conventional and organic milk markets in France and Germany. Australian Journal of Agricultural and Resource Economics, 69, pp. 43–58. DOI
  14. 14Garretsen, H., Kitson, M., & Yang C. (2025). Global forces and local impacts: megatrends in regional development. Cambridge Journal of Regions, Economy and Society, 18(1), pp. 1–16. DOI
  15. 15Shan, Sh. (2024). Unveiling Socioeconomic Factors Shaping Global Food Prices and Security: A Machine Learning Approach. Asian Journal of Agriculture and Development, 21(2), pp. 1–24. DOI
  16. 16Chavas, J. P., Rivieccio, G., Di Falco, S., De Luca, G., & Capitanio, F. (2022). Agricultural diversification, productivity, and food security across time and space. Agricultural Economics, 53, pp. 41–58. DOI
  17. 17Abad-Segura, E., Castillo-Díaz, F. J., Batlles-delaFuente, A., & Belmonte-Ureña, L. J. (2024). Enhancing competitiveness and sustainability in Spanish agriculture. Business Strategy & Development, 7(4), e70021. DOI
  18. 18Volyk, S., Orel, A., & Senchyk, I. (2023). The role of economic security in ensuring competitive economic development of agricultural enterprises. Baltic Journal of Economic Studies, 9(5), pp. 73–80. DOI
  19. 19Kryvenko, N., Radziyevska, S., & Us, I. (2023). Ukraine in the global trade of agricultural products. Baltic Journal of Economic Studies, 9(4), pp. 148–160. DOI
  20. 20Nuzhna, S., Karimov, H., and Karimov, I. (2023). Economic and mathematical modeling in logistics activities of agricultural enterprises. Economic analysis, 33(1), pp. 258–269. DOI
  21. 21Yunus Emre Gur (2024). Development and application of machine learning models in US consumer price index forecasting. Data Science in Finance and Economics, 4(4), pp. 469–513. DOI
  22. 22Karmalita, V. (2024). Stochastic model of economic cycles and its econometric application. Data Science in Finance and Economics, 4(4), pp. 615–628. DOI
  23. 23Makieła, K., Marzec, J., Pisulewski, A., & Mazur, B. (2025). Are European Farms Equally Efficient? What Do Regional FADN Data on Crop Farms Tell Us? Journal of Agricultural and Applied Economics, 57(1), pp. 157–181. DOI
  24. 24Orozco-Castañeda, J. M., Sierra-Suárez, L. P., & Vidal, P. (2024). Labor market forecasting in unprecedented times: A machine learning approach. Bulletin of Economic Research, 76, pp. 893–915. DOI
  25. 25Cristea, M., Noja, G. G., Drăcea, R. M., Iacobuță-Mihăiță, A.-O., & Dorożyński, T. (2024). ESG investment strategies and the financial performance of European agricultural companies. Journal of Business Economics and Management, 25(6), pp. 1283–1307. DOI
  26. 26State Statistics Service of Ukraine (2024). Average sale prices for agricultural products sold by enterprises. (in Ukrainian)
  27. 27Dmytriieva, V., & Sviatets, Yu. (2023). Agricultural business in independent Ukraine: thirty-year dynamics of the reorganization process. Agricultural and Resource Economics, 9(2), pp. 136–162. DOI
  28. 28State Statistics Service of Ukraine (2024). Livestock (1990–2023). (in Ukrainian)
  29. 29State Statistics Service of Ukraine (2021). Profitability level of agricultural production in enterprises (1990–2020). (in Ukrainian)
  30. 30State Statistics Service of Ukraine (2024). Production (gross yield) of milk in 2023, by region. (in Ukrainian)
  31. 31State Statistics Service of Ukraine (2023). Production of animal products in 2022. (in Ukrainian)
  32. 32State Statistics Service of Ukraine (2022). Sale of agricultural products by enterprises and households in January 2022. (in Ukrainian)
  33. 33Fastieiev M. (2025). The situation in dairy exports highlights the large-scale problems of falling domestic consumer demand. InfAgro, March 28, 2025. (in Ukrainian)