Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential

Utami, Anisa Dwi; Harianto, Harianto; Krisnamurthi, Bayu Article Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Utami, Anisa Dwi; Harianto, Harianto; Krisnamurthi, Bayu (2023) : Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-17, https://doi.org/10.1080/23322039.2023.2178123 This Version is available at: https://hdl.handle.net/10419/303979 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential Anisa Dwi Utami, Harianto Harianto & Bayu Krisnamurthi To cite this article: Anisa Dwi Utami, Harianto Harianto & Bayu Krisnamurthi (2023) Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential, Cogent Economics & Finance, 11:1, 2178123, DOI: 10.1080/23322039.2023.2178123 To link to this article: https://doi.org/10.1080/23322039.2023.2178123 © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 26 Feb 2023. Submit your article to this journal Article views: 1375 View related articles View Crossmark data Citing articles: 2 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential Anisa Dwi Utami 1 *, Harianto Harianto 1 and Bayu Krisnamurthi 1 Abstract: Being the main food commodity, the dynamics of rice prices is one of the most important issues for Indonesian economy. The prices at the retail level and at the farm level are influenced not only by the demand and supply in each of these markets but also by price behavior at the wholesale market. This study aims to analyse the dynamics of the relationship and behaviour of the prices of various varieties and qualities of rice in the wholesale market. The dynamics of rice prices are investigated by employing multivariate vector error correction model (VECM) and using daily price series at wholesale level during the period of 1 October 2014 until 12 February 2018. The results show a strong price relationship between premium-quality rice and medium-quality rice and between medium-quality rice and low-quality rice. Changes in the price of premium-quality rice and changes in the price of low-quality rice will have a large influence on the price of medium quality rice, but not vice versa. Furthermore, regarding the price stabilization policy, the results suggested that the policies aimed at regulating medium-quality rice prices are estimated to have relatively weak effects on the prices of premium-quality rice and low-quality rice. Subjects: Microeconomics; Econometrics; Industry & Industrial Studies ABOUT THE AUTHORS Anisa Dwi Utami is a permanent lecturer in the Department of Agribusiness, Faculty of Economic and Management, IPB University. She is interested in doing research in the areas of agricultural market analysis, efficiency and productivity analysis, gender development and the application of quantitative model. Harianto Harianto is a professor in the Department of Agribusiness, Faculty of Economic and Management, IPB University. He is interested in doing research in the areas of macroeconomics, agricultural policy in developing countries, and politics and agribusiness development. Bayu Krisnamurthi is an associate professor in the Department of Agribusiness, Faculty of Economic and Management, IPB University. He is interested in doing research in the areas of agribusiness, trade and agricultural policy, institutional economic and strategic and management business. PUBLIC INTEREST STATEMENT As the strategic food commodity for Indonesian economy, the rice market has been commonly assumed to be homogeneous in terms of product and quality. However, along with the changing socioeconomic condition, the situation may require to be further clarified. This paper aims to explore the interdependence of prices among the different quality of rice products. To this end, this paper used wholesale prices in a specific market in Indonesia with the period of 1 October 2014 until 12 February 2018. The findings generally suggested that different quality and characteristics of the rice products in Indonesia have different price behaviour. Furthermore, it can be concluded that the substitution relationship between the premium-quality rice and the lowquality rice is lower than the substitution relationship between the premium-quality rice and the medium-quality rice as well as lower compared to the substitution relationships of lowquality rice with medium-quality rice. Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 1 of 17 Received: 06 October 2022 Accepted: 04 February 2023 *Corresponding author: Anisa Dwi Utami, Department of Agribusiness, Faculty of Economic and Management, IPB University, Bogor Indonesia E-mail: [email protected] Reviewing editor: Muhammad Shafiullah, Economics, BRAC University, Dhaka Bangladesh Additional information is available at the end of the article © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Keywords: Food price; Price transmission; Rice; Wholesale market; VECM JEL Classification: Q110; Q130; C320 1. Introduction The dynamics of rice prices has been widely discussed within the existing economics literatures around the world. As one of the most consumed food products globally, rice is a strategic commodity which attracts much attention from many developing countries, especially in Asia. In several rice-producing countries, rice generally accounts for half of farmers’ income, though with declining trend of its share due to nonfarm economy that has overtaken rural economies (Bandumula, 2018). Meanwhile, at the consumer side, rice accounts for 25–40% of households’ expenditure (Dawe & Timmer, 2012; Timmer, 2010). Therefore, changes in rice prices will likely lead to large changes in purchasing power and nutrition of the poor (Akhter, 2017; Bekkers et al., 2017; Block et al., 2004; Dawe & Timmer, 2012; Elleby & Jensen, 2019; Haile et al., 2016; Hasan, 2016). The global rice market has been generally found to be thin and volatile during some recent periods. This relates to the situation in which nearly one-half of the world population has consumed rice as their staple food, but only 7 percent are traded across the borders (Gibson & Kim, 2013). Furthermore, after global food price spikes in 2007–2008, people are more aware of the existence of food price instability and thus, some governments revise their policy to maintain their food security. During this period, within 4 months in the early of 2008, the world’s largest rice exporters, i.e., Vietnam and India (the second and the third world largest exporters), banned rice export, followed by panic buying by the Philippines as the largest rice importer. This export bans by Vietnam and India, which have driven to the increasing world rice prices, reflected political goals of protecting domestic consumers from the rice price inflation, but the situation was contradictory. The local rice prices were reported to being doubled in Ho Chi Min City as rice disappeared from the city market for over 2 days (Slayton, 2009). Volatile market has discouraged governments to rely on the global market for maintaining their domestic consumption, thus making the thinner world market become more unstable (Timmer, 2010). Being the fourth most populous country in the world, Indonesia has played a strategic role in the global rice market, considering rice as the staple food of the people. Playing as consumer and producer at the same time, Indonesian economy heavily relies on the dynamics of rice prices. Many studies have emphasized this situation. Grabowski and Self (2016) found that rice price stability was one of the main drivers of structural change in Indonesia. The shifting labor from agriculture sector to manufacturing sector is critically dependent on the existence of food price stability. Therefore, rice is considered not only as an economic commodity but also as a political commodity. For decades, Indonesian government has maintained many policies regularizing the rice market. Rice price stabilization, for example, is one of the most highlighting political issues especially during the political momentum such as presidential and general election in the country. In addition, the rice self-sufficiency has become the main agenda for every president. The government of Indonesia has claimed achieving rice self-sufficiency in some periods, i.e., 2005, 2010, and 2014. However, there are still growing debates on the validity of the data regarding whether the rice production is sufficient while at the same time, the rice prices tend to increase over time. Following this issue, the debates are more complex when the government conducts import for rice. Studies of price transmission between market levels along the marketing chain have been widely conducted (Aguiar & Santana, 2002; Çamoğlu et al., 2015; Cao & Mohiuddin, 2019; Chavas & Mehta, 2004; Deb et al., 2020; Fousekis et al., 2016; Kinnucan & & [With reply from Tim Lloyd], 2019; Ngango & Hong, 2020; Zanin et al., 2020). Those studies also assume that the quality of products traded at each level along the marketing chain is the same. However, studies of the price relationship of similar but different quality of agricultural products or varieties in one market are relatively rare. This study attempts to fill this gap. This study aims to analyze the behavior of rice Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 2 of 17 prices at the wholesale market in Indonesia by investigating the interdependence among rice products and learning whether there are differences among rice products in the market. Furthermore, the price interdependency was investigated by estimating the cross price elasticity for the varieties of rice products. The next session explains the literature review and methods of analysis. Then, it is followed by the empirical results and discussion. Finally, the last session will be the conclusion as well as the policy implications. 2. Literature Review Within the existing economics literature, rice is usually treated as one single commodity (Anggraeni et al., 2019; Chaudhary et al., 2019; Onumah et al., 2022; Putra et al., 2021; Rahman et al., 2020; Śmiech et al., 2019). (Shively & Thapa, 2017); (Korale Gedara et al., 2016); (Valera & Lee, 2016); (Keho & Camara, 2012). In the estimation technique, mainly because of data availability issue, most of the studies have not accounted for the type and quality differences in the price analysis. This empirical way to some extent may lead to the unclear conclusion in explaining the real market behavior and the price dynamics and in explaining the policy implication. In the case of Indonesian rice industry, for instance, as studied by Rachmat et al. (2016), along with the variation of consumer preferences, the consumers of rice in Indonesia are becoming more discriminating on the rice quality. In addition, following the changing of socioeconomic condition, especially among the people from upperand middleincome classes, the correlation between price and quality difference is becoming more important in the consumption behavior (Cuevas et al., 2016; Mottaleb et al., 2017). Price behavior in the wholesale rice market needs to be analyzed so that any policy intended to influence the price level in retailers or the price at the farmer level can be formulated appropriately. The wholesale market connects the market at the farm level with the retail market. Price movement behavior at the retail level and at the farm level will be largely determined by the role of every trader in the wholesale market in setting the price. Therefore, the wholesaler’s behavior will determine whether or not the changes in the retail price level will be transmitted perfectly to the market at the farm level, or vice versa. Traders or wholesalers in the wholesale rice market can be classified as multi-product firms which sell more than one quality grades of rice products. Rice sold in the wholesale market is categorized as premium-quality, medium-quality, and low-quality rice. Quality differences between rice occur because of differences in varieties and differences in rice characteristics, such as levels of broken rice, off color, chalkiness, and the absence or presence of dirt (Cuevas et al., 2016). Medium-quality rice can be further processed to become premium-quality rice. Similarly, lowquality rice can be improved to have medium-quality rice characteristics. This process of changing characteristics certainly requires additional costs. The quality differences of rice products reflect the condition of both production and consumption sides, which can be different from each other. Consequently, according to this assumption, how strong the price relationships among the rice products of different qualities will depend on the interaction of both supply and demand side characteristics? On the demand side, rice with different quality or characteristics has a relationship to substitute one another. Consumers determine the choice of the quality of rice they like based on preferences. Consumers’ willingness to pay for each unit of rice they buy depends on the characteristics of rice. Hedonic price function theory has shown that consumers provide certain implicit prices for each change in the characteristics of a product (Lancaster, 1966; Rosen, 1974; Hendler, 1975; Lancaster, 1966). Several studies of the characteristics of agricultural products and their implicit prices have been done (Ahmad & Anders, 2011; Chang et al., 2010; Espinosa & Goodwin, 1991; Misra & Bondurant, 2000). Following Midrigan (2011) and Alvarez and Lippi (2012) who examined pricing in multi-product companies, this study assumed that trader or firm in the wholesale rice market can be categorized as not fully acting as the price taker. The sales amount of each firm in the wholesale market is Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 3 of 17 relatively large compared to the volume of rice sold in one day on the market. Accordingly, it was assumed that there is one firm in the wholesaler rice market, which can represent the behavior of all wholesalers in the rice market. This firm sells different quality of rice. The firm was assumed to employ technology that is linear with the use of labor (l i,t ) to produce output of rice with quality i (q i,t ) in period t as follows: q i,t = αl i,t . Assuming the firm as a price taker in the labor market and given technology, the marginal cost of firm for rice i is MC i,t = W t where W t is nominal wage. The firm faces the demand for every variety of rice (i) it produced as follows: qi;t¼f p1;t;p2;t;. . . ;pn;t  �;i¼1;2...;n(1) Qt¼q1þq2þ. . . þqn(2) where p i,t is the price of rice i and Q t is the aggregate rice demand that is faced by firm. Therefore, marginal revenue of firm for each additional unit of rice of quality i is MRi;t¼qi;tð@pi;t @qiþ∑ i�j @pj;t @qj;t @qj;t @qi;tÞ:(3) The marginal revenue of each additional one-unit sale of rice i will be determined not only by the value of the own price elasticity of rice of quality i but also by the magnitude of cross price elasticity of rice with quality i and that of rice with quality j, where i ≠ j. The lower the value of own price elasticity of demand for rice of quality i is, the higher the marginal revenue for each additional one unit of rice of quality i becomes. The lower the substitution relationship between rice of quality i and rice of quality j is, or the smaller the magnitude of cross price elasticity of rice of these two qualities is, the higher the marginal return obtained for each additional one unit of rice of quality i will be. Furthermore, the profits obtained by the firm in a certain period are as follows: πt¼∑ i¼1 n πi;t¼∑ i¼1 n TRi;tTCi;t:(4) The problem faced by the firm is to determine the price of rice of each quality to obtain maximum profits in each period t. The maximum profit of the firm will be obtained if the marginal cost of rice of quality i will be equal to its marginal revenue, i.e., MC i,t = MR i,t or W t = MR i,t . In the equilibrium condition, the total amount of rice (q 1,t + q 2,t + . . .+q n,t ) sold is the same as the aggregate demand for rice received by the firm (Q t ). The optimal determination of price of rice of quality i will affect the determination of the price of rice of other quality j. With constant quantity of total demand for rice (Q t ), each price increase in one quality of rice i will be followed by a decrease in the price of the other quality of rice (j), so that the total of all variety of rice sold is the same as the total demand. The closer the substitution relationship between two qualities of rice is, the greater the effect of changes in rice price of one quality (i) on the rice prices of other quality (j). 3. Research Methodology 3.1. Data This study used daily price series obtained from Cipinang Wholesale Rice Market in Jakarta during the period of 1 October 2014 until 12 February 2018 (n = 1225 observations). Cipinang Wholesale Market (PIC) is the main wholesale rice market located in Jakarta that distributes most of rice Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 4 of 17 products from several producing areas in Java Island and supplies rice products to several regions outside Java Island. This study covered 11 rice products that are mostly traded in Cipinang Market based on the type and quality, as summarized in Table 1. All price series were then transformed into the logarithmic form. 3.2. Methods of Analysis The dynamics of rice prices were investigated by employing a multivariate vector error correction model (VECM). A VECM can give information about how the reactions among investigated prices are both in the long run and in the short run. We first presumably asked whether the investigated rice prices in PIC shared the same long-run information. According to this assumption, we tested the existence of one common cointegrating factor. Suppose that we have n x 1 vector of nonstationary price series, i.e., I(1) P t = P 1 , P 2 , . . ., P nt at time t for the i rice product. This P t can be written as: Pt ¼Anxsftþ,Pt(5) where Pt is an s x 1 vector of s (s < n) common unit root vectors and ~P t is an 1 x n nonstationary components. This equation implies the common factor representation if and only if there are n-s cointegrating vectors among the elements of the vector of Pt as depicted in the Engel-Granger representation theorem. Based on this theorem, a cointegrated system can be explained by a vector of error correction model as follows: ΔPt ¼μþnPt 1þT1ΔPt 1þT2ΔPt 2þ. . . þTp 12ΔPt pþ1þεt;(6) where π and T are the coefficient of matrices of n x n and π has reduced ranks of n-s. The matrix of π can also be written as π = αβ΄, where α is an n x n (n < s) cointegrated vector. Accordingly, we have П Pt1 = αβ’ Pt-1 = α Zt-1. The interest point here is the error correction term as Zt-1 = β’ Pt-1 with α called as adjustment coefficient from the long-run disequilibrium. With this framework, the market integration was held when s = 1 since we searched for markets which share the same longrun information. Therefore, searching the common factor representation as in Equation 15 is equivalent with the searching for n-1 cointegrating vectors. The search for n-1 cointegrating vectors was conducted in a multivariate framework proposed by Johansen (1998), i.e., the reduced rank of VAR cointegration testing. Table 1. Description of investigated rice prices in IDR Rice variety Quality category Mean Standard deviation Minimum Maximum Cianjur Kepala (CK) Premium 13,366 496.6 12,000 15,600 Cianjur Slyp (CS) Premium 12,171 486.7 11,000 14,925 Setra (SE) Premium 12,219 583.3 10,900 13,825 Saigon (SA) Medium 11,117 602.7 9900 13,200 Muncul 1 (M1) Medium 10,465 734.6 9000 13,675 Muncul 2 (M2) Low 9656.8 719.9 8200 12,400 Muncul 3 (M3) Low 8938.3 704.1 7500 11,825 IR 641 Medium 9990.3 649.1 8800 12,650 IR 642 Low 9091.8 713.2 8100 12,075 IR 643 Low 8198.2 488.16 7200 10,300 IR 42 Medium 10,486 730.4 9000 12,600 Source: Cipinang Market Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 5 of 17 In addition, to capture the effect of policy during the period of investigation, which was between 2014 and 2017, we augmented the long-run equation with the dummy variables representing the implementation of rice policy. Therefore, for this purpose, the normalized cointegrating vector for each pair is defined as follows: P1t ¼β0þβ1P2t þβ3POL2016 þβ4POL2017 þut(7) where P 1t and P 2t are the price pairs of the respective rice products, while POL 2016 is the dummy variable with value of 1 representing the implementation of the price reference policy in 2016 and POL 2017 represents the implementation of the ceiling price policy in 2017. According to these results, the estimation of cross price elasticities of rice products is calculated by referring to the magnitude of β 1 for each pair of rice product prices. Subsequently, the investigation of interdependency among the rice prices is conducted by referring to the magnitude of error correction coefficients, i.e., α resulted from the MVECM. The VEC in Equation 6 contains the short-run dynamics of the vector Pt as a function of α past disequilibrium and the lags of P t-1 for every ∆ Pt. The matrix of speed of adjustments provides information about the structure of the market, which can be observed by referring to which coefficient is statistically significant. For instance, if all α are found to be statistically significant, it implies the reactions of one rice product to every disequilibrium of any other rice products. In addition, an investigation of the presence of exogenous rice product that dominate the long-run behavior of the system was conducted. Furthermore, to capture the structure of interdependency among the rice prices, the estimated half-life time adjustments were then calculated to picture the reactions among the rice prices. The estimated half-life time adjustments provide the information about the time required for the effect of 50% of price shocks to stop gradually. In brief, our empirical technique is summarized as follows: 1) We checked the time-series properties by testing the stationary of the price variables using augmented Dickey–Fuller (ADF) unit root test; 2) For the price variables which have the same order of integration at the first difference, i.e. I(1), we tested the existence of cointegration relationships by employing Johansen multivariate cointegration test; 3) After finding the number of cointegration rank, we employed multivariate error correction model (MVECM) with several modifications in normalizing the cointegrating vector for each rice product; and 4) Finally, the robustness of the estimation was tested to evaluate the possibility of model misspecification by employing Lagrange Multiplier test for serial correlation, the RESET test for functional form, White test for heteroscedasticity, and Chow test for the model stability. 4. Results As common procedure in the time-series analysis, first we checked the time-series properties to investigate whether or not the investigated variables were stationary. To do this, we employed ADF unit root test with both constant and trend in the test specification. According to the results of ADF test as summarized in Table 2, most price variables were stationary at the first difference, i.e. I(1), except IR 643, which was stationary at the level. This finding has confirmed the unique behavior of IR 643, which has the lowest price among the other rice products. The Indonesian government uses IR 643 as rice aid for the poor, which is called beras miskin (raskin) or rice for the poor. The government subsidizes this rice product and, therefore, IR 643 has different market than other rice products. Furthermore, after finding that all price variables have the same order of integration at the first difference (excluding IR 643), the cointegration test was conducted by employing the Johansen cointegration test. The results suggested the existence of nine cointegration ranks for the ten price variables being investigated, as shown in Table 3. Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 6 of 17 After finding the existence of cointegrating relationships among the 10 investigated price products, we employed multivariate VECM using normalized Johansen cointegrating methods to estimate the cross price elasticity of rice products. To explore the pattern of interdependence among rice products, we conducted several modifications in normalizing the cointegrating vector for each rice product. The results of estimated cross product price elasticity are presented in Table 4. When we normalize the cointegrating vector by CK rice product, for instance, we will have nine cointegrating vectors: 1) CS = −3.5CK + 0.05 POL 2016–0.38 POL 2017 + u t , 2) SE = −2.11CK + 0.02 POL 2016 + 0.2 POL 2017 + u t , 3) SA = −3.31CK + 0.01 POL 2016 + 0.37 POL 2017 + u t , 4) M1 = −8.05CK + 0.18 POL 2016 + 1.08 POL 2017 + u t , 5) M2 = −6.33 CK + 0.13POL 2016 + 0.83 POL 2017 + u t , 6) M3 = −1.12 CK + 0.02POL 2016 + 0.02 POL 2017 + u t , 7) IR 641 = −4.40 CK + 0.06 POL 2016 + 0.52 POL 2017 + u t , 8) IR 642 = 3.59 CK—0.10 POL 2016–0.75 POL 2017 + u t , and 9) IR 42 = 14.88 CK + 0.29 POL 2016 + 2.23 POL 2017 + u t . Table 2. Corresponding p-value of ADF unit root test Price variables Level First difference Constant Constant and trend Constant Constant and trend CK 0.9066 0.9254 0.0000 0.0000 CS 0.9660 0.9668 0.0000 0.0000 SE 0.2139 0.2489 0.0000 0.0000 SA 0.7147 0.4243 0.0000 0.0000 M1 0.5061 0.6154 0.0000 0.0000 M2 0.2484 0.2964 0.0000 0.0000 M3 0.3257 0.4363 0.0000 0.0000 IR 641 0.4352 0.1142 0.0000 0.0000 IR 642 0.6897 0.6641 0.0000 0.0000 IR 643 0.0025 0.0147 0.0000 0.0000 IR 42 0.6144 0.7241 0.0000 0.0000 Annotation: The lag selection in the unit root test is based on the AIC. Null hypothesis is the existence of unit root. (Source: Author’s conception) Table 3. Results of Johansen Cointegration Test Rank of cointegration Constant Constant and trend Trace-test P-value Trace-test P-value 0 314.11 0.0000 382.70 0.0000 1 235.57 0.0001 268.53 0.0001 2 165.92 0.0218 192.40 0.0282 3 111.98 0.2588 137.10 0.2315 4 78.770 0.4156 103.03 0.2988 5 48.965 0.6870 72.907 0.4047 6 29.367 0.7563 43.131 0.7334 7 13.154 0.8815 23.712 0.8478 8 4.6736 0.8394 8.2297 0.9724 9 0.14233 0.7067 2.1733 0.9430 Annotation: Number of lags was selected by AIC. (Source: Author’s conception) Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 7 of 17 Table 9. Estimated coefficient of price policy in 2017 from long-run equation Normalization Dependent variables CK CS SE SA M1 M2 M3 IR 641 IR 642 IR 42 CK POL 2017 0.38** 0.20** 0.37** 1.08** 0.83** 0.02 0.52** −0.75** 2.23** CS POL 2017 −0.11** −0.03 0.00 0.21** 0.14** −0.10** 0.04 −0.36** 0.61** SE POL 2017 −0.09** 0.04 0.05 0.32** 0.23** −0.09** 0.09 −0.41** 0.81** SA POL 2017 −0.11** −0.00 −0.03 0.19** 0.13** −0.11** 0.03 −0.35** 0.58** M1 POL 2017 −0.13** −0.09** −0.08** −0.08** −0.02 −0.13** −0.07** −0.26** 0.22** M2 POL 2017 −0.13** −0.08** −0.07** −0.07** 0.03 −0.13** −0.06** −0.28** 0.28** M3 POL 2017 −0.01 0.32** 0.17** 0.31** 0.95** 0.73** 0.45** −0.69** 1.99** IR 641 POL 2017 −0.11** −0.03 −0.05 −0.02 0.14** 0.08** −0.11** −0.33** 0.48** IR 642 POL 2017 −0.21** −0.35** −0.24** −0.32** 0.32** −0.49** −0.21** −0.04** 0.09** IR 42 POL 2017 −0.15** −0.14** −0.11** −0.13** −0.12** −0.12** −0.15** −0.14** −0.21** Note: Annotation: *significant at 10% level, ** significant at 5% level, *** significant at 1% level (Source: Author’s conception) Utami et al., Cogent Economics & Finance (2023), 11: 2178123 https://doi.org/10.1080/23322039.2023.2178123 Page 14 of 17 substitution relationships among the rice products of different qualities and characteristics. This substitution relation may reflect that the trader in the market will adjust their decision on trading, and maybe pricing, depending on the dynamics of each rice product. For example, traders may decide to mix some rice products to exploit more profit due to price differences. As a consequence, it will lead to substitution relations among the different rice products. However, an exception was found in the case of the IR 642 rice price, which is categorized as the low-quality rice product. The IR 642 was found to have positive sign of cross price elasticity with the prices of all other rice products. The results of this study have important implications for the policy formulation, especially in the food sector in Indonesia. In the context of agricultural policy in Indonesia, where rice market has been quite highly intervened, the understanding of market dynamics needs to be improved. Differentiation by considering the behavior of each rice products and the behavior of each actor along the commodity’s value chain in more detail is then crucial in the policy formulation process. Furthermore, policy to stabilize rice prices in the market needs to pay attention to the linkages between prices of rice of various varieties and qualities in the market. The policies aimed at regulating medium-quality rice prices are estimated to have relatively weak effects on the prices of premium-quality rice category and low-quality rice. However, if there is a change in the price of premium-quality rice or a change in the price of low-quality rice, it will have a major impact on the price of medium-quality rice. Despite the contribution of this study in investigating the presence of quality differentials in the market dynamics especially in rice market sector in Indonesia, this study still has limitations that we should be aware of. This study has only relied on the behavior of prices at wholesale level at a specific market in Jakarta. This may not be directly reflecting the firm’s behavior specifically. Additionally, this may be insufficient to capture the whole dynamics of rice markets in Indonesia with various geographic and physical situations. Acknowledgements The authors are grateful to Department of Agribusiness, Faculty of Economics and Management, IPB University, for providing the funding to support this study. Funding The authors received no direct funding for this research. Author details Anisa Dwi Utami 1 E-mail: [email protected] Harianto Harianto 1 Bayu Krisnamurthi 1 1 Department of Agribusiness, Faculty of Economic and Management, IPB University, Bogor Indonesia. Disclosure statement No potential conflict of interest was reported by the author(s). 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