**1. Introduction**

The dairy sector is one of the major contributors to the agri-food economy in the European Union (EU). According to Eurostat (2021a), milk production represents 14% of total agricultural output and the manufacture of dairy products contributes 18% to the total food production value and 17% to the total food industry turnover (Cechura and ˇ Kroupová 2021). Poland is one of the five major European milk producers, accounting for 8% of total European milk production (Eurostat 2021a) and contributing 5% to European dairy production (Eurostat 2021b). Since supply exceeds consumption in the Polish dairy market, Poland is one of the European member states considerably contributing to the EU dairy export (Ministry of Agriculture, Nature and Food Quality 2018). Polish exports are mainly oriented towards the European market and among member states; Germany, with 19% of the Polish dairy export value, the Czech Republic (6%), and Italy (5%) are the main recipients of Poland's dairy products (Ministry of Agriculture, Nature and Food Quality 2021). For the Czech Republic, imports of Polish milk and dairy products account for 25% of all imports of milk and dairy products. Moreover, 6% of Czech exports of milk flows to Poland. With these shares, Poland is the Czech Republic's second most important foreign partner (after Germany) on the milk market. Cheese dominates the volume and the value of imports from Poland to the Czech Republic (Ministry of Agriculture of the Czech Republic 2021) and in the value of exports to Poland from the Czech Republic, while milk dominates in volume (Czech Statistical Office 2021).

Similarly to Poland, milk and dairy products historically generate a significant proportion of the Czech agri-food sector output (Zdráhal and Beˇcvárov ˇ á 2018). Moreover, the dairy sectors in Poland and Czechia were shaped by the same major events; namely the adoption of the market mechanism in 1989, the accession to the EU in 2004, and the

**Citation:** Roman, Monika, and Zde ˇnka Žáková Kroupová. 2022. Spatial Market Integration: A Case Study of the Polish–Czech Milk Market. *Economies* 10: 25. https:// doi.org/10.3390/economies10010025

Academic Editor: Sajid Anwar

Received: 18 December 2021 Accepted: 7 January 2022 Published: 13 January 2022

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abolishment of the dairy quota in 2015 (Sobczy ´nski et al. 2015). The adoption of the market mechanism in 1989 fundamentally changed the dairy sector, and both countries faced an initial contraction of milk production; it decreased from 15,860 ths tonnes in Poland, and 4946 ths tonnes in Czechia, in 1989, to 11,927 ths tonnes in Poland, and 2725 ths tonnes in Czechia, in 2003 (Eurostat 2021c). After the accession to the EU on 1 May 2004, milk production began to increase slowly within the limits permitted by the Common Agricultural Policy (CAP). Production reached 13,002 ths tonnes in Poland and 2934 ths tonnes in Czechia in 2014. After the abolition of the milk quotas in April 2015, production continued to increase, reaching 14,831 ths tonnes in Poland, and 3268 ths tonnes in Czechia, in 2020 (Eurostat 2021c). All of this period can be characterized by a considerable decrease in the number of dairy cows. Since 1999 the number of dairy cows has decreased by 35% in both countries (Eurostat 2021d). Despite this considerable decrease in the dairy cow herd, the level of milk production confirms that the yield per cow has been steadily increasing since 1990 (Cechura et al. 2021 ˇ ).

However, the Polish and Czech dairy sectors are quite heterogeneous regarding size and industrial structure (Philippidis and Waschik 2019). In the Czech Republic, milk production is carried out by large farms. According to Farm Accountancy Data Network (FADN 2021), the average Czech farm specializing in milk production had 117.2 LU (livestock unit) of cows, with a milk yield of 7872 kg/cow, in 2019. Conversely, in Poland, the average farm specializing in milk had 17.3 LU of cows with a milk yield of 5901 kg/cow. It should be noted that more than 2/3 of Czech milk production is produced by farms with mixed production (crops and livestock). While the high degree of diversification allows minimization of the potential risks arising from the dynamics of development on individual commodity markets ( Bórawski et al. 2020a highlighted the price volatility in the milk market), specialization of farms can bring the advantage of more knowledge and a higher level of skills (Trnková and Kroupová 2020; Zdráhal and Beˇcvárov ˇ á 2018). The low specialization, together with the predominant localization of Czech milk production to less favorable areas, is considered to be the reason why Czech milk production is characterized by significantly higher technical inefficiency than Polish production (Trnková and Kroupová 2020; Rudinskaya et al. 2019). Furthermore, the catching up of Polish best practice is leading to an increase of Polish competitiveness on the international milk and dairy market (Sobczy ´nski et al. 2015), while Czech milk production exhibits a decreasing trend in productivity and competitiveness (Cechura et al. 2021 ˇ ). Technical efficiency and productivity are also important for facing price volatility, which has gained momentum as a result of market liberalization (Thorsøe et al. 2020). According to Bórawski et al. (2020b), the prices for milk paid to farmers have become the most important element of the market, shaping the production of milk and dairy products after the quota abolishment. Milk production has developed well in countries and regions that have met the requirements of the common market and have been competitive.

The regional differences are visible in milk production and processing in both countries. Thorsøe et al. (2020) considers the regional polarization a consequence of dairy market liberalization. Since quotas had limited structural adjustment—in other words, limits to the market mechanisms that force milk production to move to regions with favorable environmental and economic conditions—milk production began to concentrate in regions with a mild climate and a high proportion of grassland after quotas were abolished, as these regions have a comparative advantage. In recent years, 79% of milk production has taken place in six regions (voivodships) from 16 regions of Poland: Mazowieckie (22%), Podlaskie (21%), Wielkopolskie (13%), Warmi ´nsko-Mazurskie (8%), Kujawsko-Pomorskie (8%), and Łódzkie (7%) (Statistics Poland 2021), see Table 1. These voivodships have developed processing capacity (dairies and dairy cooperatives are concentrated there according to Zuba-Ciszewska 2018), the transportation distance from farmers to processors is relatively short, and they are located close to major cities with considerable consumption capacities (Sobczy ´nski et al. 2015). In the Czech Republic, 71% of milk production is gained from six regions (see Table 1), namely: Vysoˇcina (19%), Prague and Central Bohemia (13%),

South Bohemia (11%), Pilsen (11%), Pardubice (9%), and Hradec Králové (8%) (Ministry of Agriculture of the Czech Republic 2020). Similarly to Poland, these are regions characterized by short distances to processing capacities, close to agglomerations and also to the border, especially with Germany and Poland.


**Table 1.** Raw milk production (the percentage share of total raw milk production in 2020).

Source: own study based on Statistics Poland (2021) and Ministry of Agriculture of the Czech Republic (2020).

This paper empirically explores the linkages existing between the Polish and Czech milk and dairy product markets, i.e., between markets that are characterized by geographic proximity; this proximity leads to significant foreign trade flows not only in a homogeneous raw material such as milk, but also in homogeneous dairy products (butter, Edam, SMP). The spatial integration of these markets, which can be understood as the flow and transmission of goods and price information across spatially separated markets (Pan and Li 2019), takes place through two channels: (i) the trade flow of unprocessed raw milk and (ii) the trade flow of processed goods—dairy products. The horizontal type of integration has received substantial attention among academics and policymakers over the past decades. The interest in the analysis of the interrelations between geographically separated objects is motivated by the potential welfare and policy implications (Roman 2020). The spatial price behavior of the homogenous product is an important indicator of overall market performance (Kumar and Mishra 2017). Since producer decisions are based on market price information, poorly integrated markets may convey inaccurate price information, leading to inefficient product movements and sub-optimal allocation of resources (Goodwin and Schroeder 1991); this is connected with a reduction in the possibility for a full specialization of countries or regions (Jacks et al. 2011). Poorly integrated markets also choke on the prospective gains from technological change, since without good access to distant markets that can absorb excess local supply, firms' adoption of improved production technologies will tend to cause producer prices to drop; this erases the gains from technological change and thereby dampens incentives for firms to adopt new technologies that can stimulate economic growth (Barrett 2008; Hou and Song 2021). In contrast, strong spatial integration brings benefits. A well-integrated market allows for efficient movement of trade flow that

stabilizes market prices and reduces the price risk, thanks to flows of surplus to locations characterized by deficits (Gitau and Meyer 2018). According to Hamulczuk et al. (2019), the factor-price equalization theorem stemming from the Heckscher–Ohlin model argues that the full integration of spatially separate product markets should lead to the spatial integration of markets of production factors; consequently, there should be equalization in the wages of workers, rents earned on capital, and prices of land throughout geographically separated objects (e.g., regions or countries). Serra et al. (2006) sum up the benefits of spatial market integration as improvement in the efficiency of resource allocation, reduction in social costs, and maximization of social welfare. Contrarily, spatial market segmentation represents self-sufficiency without trade, has negative effects on the healthy development of markets, increases the deadweight loss incurred by society, and reduces overall economic efficiency (Pan and Li 2019). The benefits of market integration have also been recognized by policymakers and, to facilitate the spatial integration of agri-food markets within the individual member states, enhancing price discovery mechanisms has become one of the most important targets of the European Union's (EU) Common Agricultural Policy (CAP) (Bakucs et al. 2019).

Agri-food market integration has been discussed extensively in the economic literature (e.g., Serra et al. 2006; Frederico 2007; Ihle et al. 2012; Gitau and Meyer 2018; Sobczak et al. 2018; Hamulczuk et al. 2019), both because of the specific nature of agri-food products— which are characterized by seasonality, perishability, and specific production requirements— and because of the importance of agri-food market integration, as the market efficiency associated with integration enhances the development of rural areas. For example, seasonal production of milk cause seasonality of milk and dairy product prices. According to Kussaiynor and Zhakupova (2019), the prices of milk and dairy products remain high in autumn and winter and decrease in spring and summer. Milk market integration was previously analyzed, especially at the level of vertical market integration (e.g., Fallert et al. 1978; Fałkowski 2010; Serra and Goodwin 2003; Reziti 2014; Kharin 2018; Antonioli et al. 2018; Bełdycka-Bórawska et al. 2021; Bórawski et al. 2021). Research on the spatial integration of the milk market is relatively less frequent (e.g., Goodwin et al. 1999; Jha et al. 2013; Fousekis and Trachanas 2016; Fousekis 2018; Chalmers et al. 2019; Jaramillo-Villanueva and Palacios-Orozco 2019; Xue et al. 2021). Moreover, the results of these studies cannot be generalized, due to their diversity in terms of methodology, commodities, periods, and countries.

The most important studies that evaluated the spatial integration of milk and dairy product markets in the EU are listed in Table 2. The majority of these studies evaluate market integration employing the price method based on the Law of One Price (LOP) and national price data.

A focus on Poland's milk market (Bakucs et al. 2010) investigated the retail milk price integration in Poland and Hungary between April 1997 and March 2009, employing a Vector Error Correction Model (VECM) and a Threshold Error Correction Model (TECM). Their results confirm neither strong nor weak conditions of the Law of One Price, suggesting that milk price integration between Hungary and Poland is not perfect. More recently, Bakucs et al. (2019) confirmed this result by employing Vector Autoregression Models (VAR) to analyze the spatial integration of the milk market based on a monthly series of raw cows' milk prices from January 2000 to February 2014 in 20 European member states; they found that the so-called New Member States were less integrated compared to the Old Member States and Euro Area member states. Their results also revealed that milk price cointegration is less pronounced than cointegration in other agricultural sectors (e.g., pork prices), and also raised questions about the applicability of national price data. Although the authors believe that regional prices would almost certainly change the results, few studies employed regional price data to analyze spatial market integration of milk and dairy products. One of these studies is by Roman (2020), and assesses the processes of spatial integration on the Polish raw milk market in the period 1999–2018. Her results confirmed a long-term balance between prices in various voivodeships in Poland

and the role of distance—the closer the voivodeships are to one another, the greater the co-variability of prices is between them. Moreover, she found that Poland's integration processes were associated with: a strong concentration of milk production; the elimination of the smallest farms; investments to improve the competitiveness of dairy farms and processing enterprises; and the association of farmers in producer organizations, in the analyzed period.


**Table 2.** Empirical studies of spatial milk market integration in Europe.

Note: AT = Austria, BE = Belgium, BG = Bulgaria, CH = Switzerland, CY = Cyprus, CZ = Czechia, DE = Germany, DK = Denmark, EE = Estonia, EL = Greece, ES = Spain, FI = Finland, FR = France, HU = Hungary, IE = Ireland, IT = Italy, LV = Latvia, LT = Lithuania, LU = Luxembourg, NL = the Netherlands, OC = Oceania, PL = Poland, PT = Portugal, RO = Romania, SI = Slovenia, SK = Slovakia, SW = Sweden, UK = the United Kingdom.

Instead of the monthly prices used by Roman (2020); Klepaˇcka et al. (2021) used weekly observations from 3 January 2010 to 5 November 2017, to test butter and curd market integration between two neighboring regions with large dairy sectors in Poland (Northern and Central region). Butter and curd have been chosen for their contrasting characteristics: high storability of butter and high perishability of curd. Employing VECM they found that both regions (the surplus-producing North, and the Central with its deficit) were highly integrated in the butter market. Furthermore, based on impulse response analysis, they revealed that the effect of shocks on butter prices was mostly absorbed in two weeks, and prices returned to full equilibrium in about four to five weeks. Contrary to butter, the adjustment of curd prices in one region in reaction to prices in the other region was almost unnoticeable, and the prices of curd seem not to be integrated. The causes of the observed lack of spatial curd price integration could be related to the relatively low price of curd as compared to butter. It seems that the dairy processors adjust curd production after allocating raw milk to the production of butter or other, relatively higher value products.

The relationship between the Polish and the Czech milk markets was investigated by Tłuczak (2012) who also explored the trade linkages existing between the Polish and the Slovakian/German/French raw milk markets. Applying Vector Autoregressive Models to data from May 2004 to October 2010, she found that milk prices in Poland were dependent on prices in the Czech Republic, Germany, France and Slovakia, while milk prices in the Czech Republic were not dependent on Polish prices. The relationship between the Polish and the Czech raw milk markets (among 24 other member states) was also investigated by Roman and Roman (2020). Employing the VAR model on monthly raw milk prices in 2005– 2018, the authors revealed that the Polish and the Czech raw milk markets were integrated and this linkage was strengthening over time. Moreover, contrary to Tłuczak (2012), they confirmed the bidirectional causality of raw milk prices in Poland and Czechia; however, the key countries determining the price variation in Poland were Germany, Ireland, France, and Slovakia. Integration of the Czech and the Polish markets can also be observed at the level of dairy products. The degree of association between butter prices in Poland and the Czech Republic among 10 selected EU countries using monthly prices was examined by Roman (2017) for the period 2007–2016. Her results confirmed the strong integration of the Czech and the Polish butter prices in the period 2012–2016, and also revealed evidence for the bidirectional causality of butter prices in Poland and Czechia.

It is clear that there is a gap in the research on the assessment of market integration between neighboring EU countries such as Poland and the Czech Republic, where milk production is a traditional part of agri-food production. Filling this research gap requires an analysis of market integration based on regional data, as existing research highlights that the degree of integration is influenced by geographical distance. At the same time, it is appropriate to analyze integration at multiple levels of the value chain. On this basis, this paper attempts to fill a gap in the research on spatial market integration by (i) analyzing spatial market integration between neighboring countries based on regional data; (ii) analyzing market integration on both levels of the value chain—the raw milk market and the processed milk market. The results of this analysis provide important information for the decision-making sphere. Knowing the level of regional market integration allows policy instruments to be targeted to support the building of regional comparative advantage and to promote regional economic development.

The aim of this paper is to assess the spatial integration processes on the milk and dairy product market between Poland and the Czech Republic. As part of the main aim, the authors have sought answers to the following questions: What is the long-run dependence between milk and milk product prices in Poland and the Czech Republic? Is there a longrun balance of milk prices in different regions of Poland and the Czech Republic? In which regions do milk prices have a dominant influence on prices in other areas of Poland and the Czech Republic? What is the direction of the dependence of dairy product prices?

The rest of the paper is organized as follows: Section 2 provides the theoretical background of the spatial market integration; Section 3 introduces the research methodology and datasets; Section 4 presents the results of this study and its discussion; and Section 5 summarizes our findings and provides concluding remarks.

#### **2. Theoretical Background**

Market integration is a multi-dimensional concept that relates to the flow of goods and information across space, time, and form (González-Rivera and Helfand 2001). The first definition of this concept is attributed to Cournot ([1838] 1897) who stated that an integrated market is an entire territory, the parts of which are so connected by relations of unrestricted trade that prices readily and quickly take the same level throughout the territory. In line with the definition, market integration has three dimensions: vertical (along the supply chain), horizontal (between locations) and intertemporal (between the spot and future or forward markets) (Hamulczuk et al. 2019; Goodwin et al. 2021).

The concept of horizontal or spatial market integration, which is what this paper focuses on, is based on the spatial arbitrage theory and the Law of One Price (McNew

1996). The process of spatial arbitrage between two spatially separated competitive markets each having their own supply and demand for a homogenous good is described by Van Campenhout (2007) as a process of clearing a common market. If local prices of the homogenous good (*Pi* and *Pj*) differ between the two markets by more than the cost of transferring the goods between these markets (*Tij*): *Pi* − *Pj* > *Tij*, where *i* and *j* indicate two spatially separated markets, arbitrageurs will exploit the profit-making opportunities by shipping the good from the market with the low price (*Pj*) to the market with the high price (*Pi*). This transfer of goods will increase the demand for goods in the low-price market while increasing supply in the high-price market. The increase in demand with unchanged supply in the low-price market will drive up the price (*Pj*), while the increased supply at a given level of demand will decrease the price (*Pi*) in the high-price market. The process of arbitrage will continue until actual prices differ by exactly *Tij* (Van Campenhout 2007) and arbitrage opportunities are zero (García-Hiernaux et al. 2016). That is, the spatial arbitrage ensures a reaching of unique equilibrium, where local prices in spatially separated markets differ by no more than transportation and transaction costs (Goodwin and Schroeder 1991); these may be determined by, for example, the distance between markets, quality and quantity of transport infrastructure, search costs, and market risk (Svanidze et al. 2021), and no profiting opportunities that would be exploited by arbitrageurs exist (Listorti and Esposti 2012). The lack of arbitrage opportunities is reflected in market efficiency (Dwyer and Wallace 1992). As Frederico (2007) adds, the market is defined as efficient if prices take into account all publicly available information, and there are no opportunities for profit from the exploitation of some information.

The consequence of spatial arbitrage is the Law of One Price, defining that homogeneous goods tend to have the same net price of transportation and transaction costs, when the prices are expressed in the same currency, in markets linked by trade and arbitrage (Fetter 1924). As Hamulczuk et al. (2019) added, the definition of the LOP presented above can be viewed as a weak (relative) notation of the LOP, that can be defined as *Pi*,*<sup>t</sup>* − *Pj*,*<sup>t</sup>* = *Tij*,*t*, where *t* denotes time (Baulch 1997). The strong (absolute) notation does not take into account transfer costs, and assumes full and immediate price transmission with zero price differences, that is: *Pi* = *Pj* in any time *t* (Hamulczuk et al. 2019; García-Hiernaux et al. 2016). The LOP can be viewed as a criterion of market integration (Gluschenko 2021), and an important condition for the efficient functioning of markets under assumptions of the lack of: trade barriers, market power, product heterogeneity and perishability, exchange rate risks, and imperfect flow of information (Listorti and Esposti 2012). A violation of the LOP is an instance of inefficiency which may delay specialization according to the comparative advantage and, thus, cause welfare losses (Frederico 2007).

In this paper, the LOP is applied to analyze the spatial integration of Poland and Czech milk and dairy product markets. According to Van Campenhout (2007) and Frederico (2007) we define these markets as integrated if prices in these countries are determined simultaneously in the long-run, since the dynamics of economic processes can lead to temporary deviations from equilibria (e.g., due to seasonality of agricultural commodities McNew 1996); this means that in the short-run, price differences may exceed the transfer costs in competitive markets (Roman 2020). Two relevant mechanisms are behind this price adjustment: physical trade of the good, and information flow that occurs between the locations (Hamulczuk et al. 2019); according to Listorti and Esposti (2012), the information flow might explain price transmission even more than physical trade flows.

Empirical analyses use several methods to evaluate spatial market integration based on price adjustment between markets. According to Van Campenhout (2007), the first attempts at this evaluation were based on the strong notation of the LOP and took price correlation coefficient as a measurement of the degree of market integration. This simple regression and correlation analysis has been criticized due to two main conceptual and practical problems: the endogeneity of prices and the dynamism of price adjustments associated with temporary deviations from equilibrium (Fackler 1996). As a reaction to this criticism, dynamic regression models gained increasing attention because they allow representation of contemporaneous and lagged price linkages, and take price endogeneity into account (Van Campenhout 2007). The dynamic model framework (e.g., Ravallion 1986) applied in this study assesses market integration employing cointegration analysis. In addition, the authors used the Error Correction Model (ECM), the Granger causality test to examine the direction of the relationship, and the Impulse Response Function (IRF) to determine the response to price shocks of individual dairy products. This allowed us to investigate the short-run dynamics that are consistent with the long-run relationship (Goodwin et al. 2021).

The analysis of market integration can provide a lot of economically and politically important information. The measurement of market integration is an essential tool for understanding the functioning of markets (Ravallion 1986). Knowledge of spatial integration helps economists explain whether the market moves commodities towards their higher value users, whether it is able to absorb large shocks without breakdown, and whether the market fosters development through specialization (Fackler 1996). With the knowledge of market integration, it is possible to evaluate the speed of transmission, which makes it easier to forecast prices in particular markets (Roman 2020). Moreover, the understanding of spatial markets also increases the knowledge of price relationships in a vertical chain, since spatial transformations are representative of input/output relationships (Fackler 1996). Cognition of the level and strength of market integration is also essential for economic policy aimed at creating the conditions to achieve an efficient market system (Hamulczuk 2020) and for the building of comparative advantages (Hou and Song 2021). An efficient agricultural and food market is a prerequisite for food security (Habte 2017; Svanidze et al. 2021) as it reduces the exposure of producers and consumers to unexpected fluctuations in local supplies of raw materials and processed products (Hamulczuk 2020).
