India’s wheat market

In India, wheat holds a significant position as a main staple and principal food grain crop. India cultivates wheat across a vast area of 26.34 million hectares, resulting in a substantial production of 109.59 million metric tons (MMT) (FAO 2021). India plays a significant role in the global wheat market, being the second-largest producer of wheat worldwide. It contributes more than 13% to global wheat production. Through the implementation of yield-enhancing green revolution technology and market interventions, there has been a significant increase in wheat production in India on a sustained basis. This has been achieved by carefully balancing the interests of both producers and consumers. Four broad policy instruments have played a significant role, including producer price support, trade policies, input subsidies, and food distribution subsidies (OECD 2014).

Wheat market intervention by the government consists of minimum support price and procurement, buffer stock maintenance, the public distribution system, and open market operations. In addition, the wheat trade is subject to several restrictions, including a license and permit system, multi-tiered tariff structure, quota, and trade prohibition. Wheat is subject to state trading requirements in India (WTO 2015). However, the enforcement mechanism is contingent upon domestic supplies and prices. The primary government agency responsible for implementing food policy is the Food Corporation of India (FCI). It procures grain from farmers and distributes it to consumers, working in collaboration with state agencies. Additionally, the FCI manages the government’s “central pool” of stocks through transactions in both international and domestic markets.

The FCI conducts open-ended procurement of wheat at a pre-announced minimum support price (MSP).Footnote ⁷ The pre-announced MSP, defended by public procurement, places an effective floor on domestic prices, especially when the corresponding market prices fall. A recent study (Tripathi Reference Tripathi2024) found that implementing a price floor policy reduces the probability of significant price declines by truncating the lower end of the price distribution and has a price-enhancing effect. The implementation of a price floor policy could potentially lead to a situation where domestic prices exhibit no correlation with the international market beyond a specific threshold or to a nonlinear relationship where the domestic level quickly absorbs rise in global prices and falls in international prices are passed on at a comparatively slower pace (Ghoshray Reference Ghoshray2011).

In addition to the above policies, there are also restrictive trade policies that use a mix of tariffs and non-tariff barriers to keep prices and supplies stable in the domestic market. Despite significant liberalization, wheat trade policy in India remains complex. Wheat trade is managed through a combination of instruments such as permit and licensing requirements, quotas, taxes, state trading requirements, and tariff structure with multiple rates. Whether these instruments are enforced or not depends on domestic supply and prices. The role of state trading enterprises was emphasized as a canalizing agency for wheat trade. In this case, the government establishes a quota, determines the quantity of a commodity to be exported or imported, and insulates domestic prices from fluctuations in trade prices and exchange rates (see Ackerman and Dixit Reference Ackerman and Dixit1999).

The government adjusted its trade policy instruments from time to time, considering factors such as domestic production, price dynamics, and the global landscape. Since 1998, there has been a recurring pattern of accumulating large stocks of wheat, exporting them, depleting the stocks, and then importing large quantities again (Chand Reference Chand2009). In the case of wheat, Tripathi (Reference Tripathi2013) showed that, under an exportable scenario, during the period 2001–2004, poor transmission of changes (with a transmission elasticity of 30%) in trade prices and exchange rates on domestic prices has precluded much of the potential price change. The trade policy response to low world prices, which involved raising export subsidies, has largely neutralized the impact of low world prices on Indian wheat exports.

In 2005–06, the real-world price of wheat started picking up (from 180.71 $/t) and reached a peak in 2007–08 (337.11$/t). High world prices have made wheat imports less attractive. Wheat imports fell from 6 MMT in 2006–07 to 1.8 MMT in 2007–08. Additionally, high world prices forced India to reduce import duty from 50% in 2006–07 to zero in 2007–08 (Figure 2). Figure 2 illustrates the trend in the real-world price of wheat.Footnote ⁸ By December 2016, the world price had dropped more than 50% from its peak in November 2012. However, after reaching their lowest level (i.e., 175.7 $/t in 2016–17Footnote ⁹ ), prices started picking up slowly and hovered between 185.5 $/t and 206.6 $/t during 2017–18 and 2019–20 but remained much lower than the level reached in 2012–13 (i.e., 318.2 $/t). As a result, imports started picking up, and within two years, beginning in 2015–16, India imported more than 6 MMT of wheat. A low level of world prices forced the country to impose an import duty starting in August 2015, varying from time to time (Figure 2).

Figure 2.

Trend in international wheat price and India’s basic custom duty on wheat, 2001M01–2024M03 (prices in real terms).

The heatwaves in major wheat-producing states in India during the 2014–15 crop season resulted in a decline in wheat production by more than 9 MMT over the previous year. Consequently, in 2016, wheat procurement witnessed a significant decrease, and wheat stock with public agencies was reduced to 30 MMT by July 2016. Along with this, the falling world prices (world wheat prices dropped by more than 50% by December 2016 from their peak in November 2012) made wheat importation an attractive proposition. For three years, starting in 2015–16, India imported about 8 MMT of wheat. Low world prices in 2016–17 forced India to impose a tariff on wheat imports (Figure 3). To prevent cheap imports, the government increased import duty to 28.33% in 2018–19 and further to 39.17% in the subsequent year. As a result, wheat imports dropped to 1.6 MMT in 2018–19, down from 5.7 MMT in 2017–18.

Figure 3.

Trend in wheat export, import, and stock at the central pool from 2000–01 to 2022–23.

A relatively low but stable trajectory of global wheat prices from 2017 to mid-2020 made Indian wheat uncompetitive in the global market. Additionally, the increase in domestic productionFootnote ¹⁰ resulted in the accumulation of wheat stocks in the country, much more than the buffer stock norms. The wheat stock in the central pool reached 60.36 MMT on July 01, 2021, much above the stocking norm of 27.6 MMT. Following a substantial rise in the global prices of wheat after mid-2020, Indian wheat regained its competitiveness. As a result, between mid-2020 and May 2022, India shipped around 12 MMT of wheat before implementing a ban on wheat exports (Figure 3).

Literature review

Many studies have investigated market integration and transmission of price signals by deploying various analytical techniques. These studies highlight several factors that limit the transmission of price signals. Import tariffs, TRQs, export subsidies or taxes, and intervention mechanisms are examples of agricultural policy instruments that can influence domestic markets in addition to exchange rate policies. These policies have the potential to disrupt the transmission of world price signals by affecting the domestic market’s excess supply and demand schedules (Quiroz and Soto Reference Quiroz and Soto1993; Rapsomanikis, Hallam, and Conforti Reference Rapsomanikis, Hallam and Conforti2003; Timmer Reference Timmer2008; Baffes and Gardner Reference Baffes and Gardner2003; Imai, Gaiha, and Thapa Reference Imai, Gaiha and Thapa2008; Keats et al. Reference Keats, Wiggins, Compton and Vigneri2010; Ghoshray Reference Ghoshray2011; Ianchovichina, Loening, and Wood Reference Ianchovichina, Loening and Wood2014; and IMF 2011). However, only a small number of studies have formally evaluated the impact of policy interventions on domestic price variability and price transmission. In this study, we present a review of the studies that quantify the effect of policy interventions on price transmission exclusively.

In their study, Rapsomanikis, Hallam, and Conforti (Reference Rapsomanikis, Hallam and Conforti2003) analyzed the spatial price transmission in developing countries in various cash and food crop markets. The study suggests that depending on specific agricultural policy instruments, it can either impede or facilitate market integration. In the case of the Rwandan coffee market, they found that the coffee market was disconnected from the global coffee market due to government regulation with predetermined price levels. Additionally, the research offers insight into the Egyptian wheat market, demonstrating that floor price policies did not hinder market integration. However, it did lead to a gradual and uneven response to fluctuations in international prices. In general, regulated markets showed relatively low-price transmission in terms of both degree and speed.

Liefert (Reference Liefert2011) decomposed the changes in real agricultural producer prices for the major emerging market economies of Brazil, China, and South Africa. For each country, the authors decomposed the changes in the real producer price for beef, pork, and poultry, as well as one other commodity specific to each country. Findings revealed that the transmission from border/landed prices to domestic producer prices was high. Changes in both world prices and exchange rates would cause a large movement in real domestic prices. The results also showed that incomplete transmission, caused not by policies but rather by market conditions such as weak agricultural market infrastructure, prevented much of the potential fluctuation in producer prices in the domestic country.

Using data from 2003 to 2007 from selected Asian economies, Dawe (Reference Dawe2008) analyzed the transmission of increased global cereal prices to domestic prices. The author found that the transmission of international food prices was mostly incomplete. The author argued that the increase in the currency value, compared to the US dollar, offset a significant portion of the global price increases in the local markets. In Asian countries, local policies regarding specific agricultural commodities, particularly rice, are effectively stabilized and protect domestic prices from fluctuations in global prices.

In the Indian context, Sekhar (Reference Sekhar2012) investigated spatial integration in specific commodity markets in India. The author found that commodity markets, such as gram and edible oils, with no inter-state trade restrictions, were well-integrated. Conversely, rice markets with inter-state movement restrictions lacked national integration. Similarly, Baylis et al. (Reference Baylis, Jolejole-Foreman and Mallory2014) analyzed the integration between specific wheat and rice markets in India both before and during the export bans. The authors found that the export ban resulted in a separation between the domestic and global markets for both rice and wheat. Furthermore, there was a noticeable absence of market integration between the producing and consuming regions within India. In addition, the findings indicated that the export ban led to a rise in domestic price fluctuations caused by disruptions in domestic supply.

In another study, Elleby et al. (Reference Elleby, Hansen and Yu2015) investigated the impact of India’s export ban during the global food price crisis on domestic market prices and, subsequently, consumer welfare. The authors found that the export ban did indeed exert a substantial impact on the domestic retail price of rice and wheat. The domestic price of wheat dipped approximately 40% lower than it would have been without the export ban. Tripathi (Reference Tripathi2013) analyzed the effects of trade prices, the exchange rate, and agricultural trade policies on changes in domestic prices of wheat, rice, sugar, and edible oils. The author found that wheat and rice fell under the exportable hypothesis (covering the 2001–2004 period). The author argued that in most cases, the price transmission elasticity between the domestic price and the landed price was between 30% and 50%. Therefore, it prevented many changes in domestic prices. The trade policy response to low world prices annulled the effect of a rise or fall in world prices on domestic prices. A combination of both government policies and underdeveloped market infrastructure was accountable for the incomplete transmission of changes in trade prices and exchange rates to domestic prices.

Theoretical and econometric framework

The law of one price suggests that price transmission is complete, with the prices for an identical good at different locations differing by no more than the costs of trading the good between those locations (Fackler and Goodwin Reference Fackler, Goodwin, Gardner and Rausser2001). A complete price pass-through is attained by trade. Profitable trade arbitrage will swiftly erase any price difference across spatially separate marketplaces above transaction cost by physically moving the goods between the markets until the disparity is below transaction costs. And is given by:

(1) $${P^d} = {P^e} + T = \;{P^w}$$

where ${P^d}$ is the price in the domestic (importing) market, ${P^e}$ is the price in the exporting market, $T$ is the transport and other transfer costs involved in moving goods between the markets, and ${P^w}$ is the trade price of imported goods. If a country imposes no transmission-impeding policies, the domestic price for a good ( ${P^d}$ ) in the importing country is determined by the trade price ( ${P^w}$ ) times the exchange rate (X) and ad valorem tariff; that is, ${P^d}$ = ${P^l}$ , where ${P^l}$ is duty included in the landed price expressed in local currency.

(2) $${P^d} = \;{P^l} = \left[ {{P^w}X\left( {1 + t} \right)} \right]$$

The value for the price transmission elasticity ( $\varepsilon $ ) between the domestic and landed prices, that is, the percentage change in ${P^d}$ with a 1% change in ${P^l}$ , can be expressed as:

(3) $$\varepsilon = {{\mathop {{P^d}}\limits^ \bullet } \over {\overbrace {\left[ {{P^W}X\left( {1 + t} \right)} \right]}^ \bullet }}$$

where a “dot” above the variable in equation (3) indicates a percentage change; we follow the methodology developed by Liefert (Reference Liefert2011) to decompose the changes in the domestic market prices in equation (3) into the effect of changes in trade prices of wheat, exchange rates, and agricultural trade policies (e.g., ad valorem tariffs in the case of imports). To isolate the effect of incomplete transmission from equation (3), following Liefert (Reference Liefert2011), we expand the price transmission elasticity from $\varepsilon \;$ to $\left( {\varepsilon + k - k} \right)$ , where $k = 1 - \varepsilon $ , such that $\varepsilon + k = 1$ . This gives us:

(4) $$\eqalign{{\mathop{{P^d}}\limits^\bullet} & = \overbrace {\left[ {{P^W}X\left( {1 + t} \right)} \right]}^ \bullet - k\overbrace {\left[ {{P^W}X\left( {1 + t} \right)} \right]}^ \bullet \cr & {\bf{ \quad \quad \quad \quad A \quad \quad \quad \quad \quad \quad B}}}$$

The term B in equation (4) becomes zero if the transmission from a change in the landed price ${P^l}$ to ${P^d}$ were complete ( $\varepsilon = 1,\;\;such\;that\;k = 0$ ). Equation (4) isolates and measures the effect on ${P^d}$ assuming that transmission is complete (as measured by term A), as well as the effect on ${P^d}$ arising from incomplete transmission (the term B of the Equation). The term B in equation (4) measures the degree to which incomplete transmission cuts into the potential change in ${P^d}$ . The sum of these two parts (i.e., A and B of equation (4)) gives the net effect based on the actual value of $\varepsilon $ (transmission elasticity). To measure the share of percentage change in ${P^d}$ caused by and attributed to the percentage change in ${P^w},\;X,\;and\;t\;$ in the final form of the decomposition equation, no term should contain the percent change of either a sum or product of two or more of the above variables. One can break the term A in equation (4) by using the expression $\mathop {{\rm{ }}X}\limits^ \bullet = {{\Delta X} \over {{X_1}}}.$ This gives the following equation:

$$\overbrace {\left[ {{P^W}X\left( {1 + t} \right)} \right]}^ \bullet = {{\Delta \left[ {{P^W}X\left( {1 + t} \right)} \right]} \over {{P^W}X\left( {1 + t} \right)}}$$

And further,

(5) $$\eqalign{ {{\Delta \left[ {{P^W}X\left( {1 + t} \right)} \right]} \over {{P^W}X\left( {1 + t} \right)}} & = {{\Delta \left( {{P^W}X} \right)} \over {{P^W}X\left( {1 + t} \right)}} + {{\Delta \left( {{P^W}t} \right)} \over {{P^W}X\left( {1 + t} \right)}} \cr & \quad\quad\quad{\bf{ C \quad\quad\quad\quad\quad\quad D}} \cr} $$

The term C of equation (5) can be further simplified by using the following mathematical rule:

$$\eqalign{ {\Delta \left( {XY} \right)} & \!= {\bar X\Delta Y + \Delta X\bar Y} \hfill \cr & \,{{\rm{ = }}\left( {{{\left( {{X_1} + {X_2}} \right)\mathop {{\rm{ }}Y}\limits^ \bullet {Y_1}} \over 2}} \right) + \left( {{{\left( {{Y_1} + {Y_2}} \right)\mathop {{\rm{ }}X}\limits^ \bullet {X_1}} \over 2}} \right)} \hfill \cr } $$

Applying the above rule to equation (5) results in the following expression:

(6) $${{\Delta \left( {{P^W}X} \right)} \over {{P^W}X\left( {1 + t} \right)}} = {{\mathop {{P^W}}\limits^ \bullet {P^W}\left( {{X_1} + {X_2}} \right)} \over {2\left[ {{P^W}X\left( {1 + t} \right)} \right]}} + {{\mathop {{\rm{ }}X}\limits^ \bullet X\left( {P_1^W + P_2^W} \right)} \over {2\left[ {{P^W}X\left( {1 + t} \right)} \right]}}$$

Equation (6) measures the change in ${P^d}$ from the direct price effect that occurs from $\Delta {P^w}$ and $\Delta X$ . Similarly, the term D of equation (5) can also be broken into the following:

(7) $$\eqalign{& \small{{{\Delta \left( {{P^W}X} \right)} \over {{P^W}X\left( {1 + t} \right)}} = {{\mathop {{\rm{ }}t}\limits^ \bullet t\left( {P_1^W + P_2^W} \right)\left( {{X_1} + {X_2}} \right)} \over {2 \bullet 2\left[ {{P^W}X\left( {1 + t} \right)} \right]}} + {{\mathop {{\rm{ }}X}\limits^ \bullet X\left( {P_1^W + P_2^W} \right)\left( {{t_1} + {t_2}} \right)} \over {2 \bullet 2\left[ {{P^W}X\left( {1 + t} \right)} \right]}} + {{\mathop {{P^w}}\limits^ \bullet {P^W}\left( {{X_1} + {X_2}} \right)\left( {{t_1} + {t_2}} \right)} \over {2 \bullet 2\left[ {{P^W}X\left( {1 + t} \right)} \right]}}} \cr & {{\bf{\quad \quad\quad\quad\quad\quad\quad\quad E \quad\quad \quad\quad\quad\quad\quad\quad\quad F \quad\quad\quad\quad\quad\quad\quad\quad\quad G}}} \hfill \cr } $$

Equation (7) gives the policy effect on ${P^d}$ and has three parts. The sub-term (E) associated with $\dot tt$ in equation (7) measures the change in ${P^d}$ resulting from changes in the tariff (i.e., explicit policy effects). The sub-terms 7 (F) and (G) are associated with $\dot XX$ and ${\dot P^w}{P^w}$ and measure the change in ${P^d}$ resulting from changes in trade prices ( $\Delta {P^w})$ and exchange rates ( $\Delta X$ ) interacting with the tariff rates (i.e., implicit policy effects). The magnitudes of both the direct price and policy effect assume a complete transmission of change in the landed price ${P^l}$ to domestic prices ${P^d}$ . Similarly, the incomplete transmission effect on domestic prices ( ${P^d})$ is given by the term B in equation (4). It measures the change in domestic prices ( ${P^d})$ resulting from changes in trade prices ( $\Delta {P^w})$ , changes in exchange rates ( $\Delta X$ ), and changes in the ad valorem tariff rates ( $\Delta t)\;$ interacting with market conditions, resulting in an incomplete price transmission to domestic prices ( ${P^d})$ .

Data description

We apply the decomposition model to the real domestic market prices ( ${P^d}$ ) for Indian wheat. The 2006/07–2008/09 and 2017/18–2019/20 period was chosen for several reasons. First, both periods involved a fair amount of movement in real trade prices. For instance, during 2006/07–2008/09, wheat trade prices (in real terms) increased by 12%. Similarly, it witnessed a marginal decrease of around 5% from 2017/18–2019/20. Second, the periods witnessed a substantial movement in the effective rate of basic customs duty. For instance, the basic customs duty rate on imported wheat decreased (increased) by 100% (176%), from 50% to zero (14.17% to 39.17%) in response to rise (decline) in trade prices during 2006/07–2008/09 (2017/18–2019/20). Third, India’s wheat imports reduced substantially, approximately 1.65 MMT, between 2017/18 and 2019/20 due to increased tariff rates.

The data on domestic market prices ( ${P^d}$ ) were collected from the report on Agricultural Prices in India, published by the Directorate of Economics and Statistics, the Ministry of Agriculture, and the Government of India. The prices refer to the month-end wholesale market price of the average quality of wheat in Uttar Pradesh (Kanpur). We determine the real value of domestic prices by dividing the nominal prices by the Consumer Price Index, using a base of 2010 = 100 for all Indian items. The international wheat price refers to free-on-board the US Gulf price of Hard Red Winter (HRW) No. 2. We collected the data from the Global Information and Early Warning System database of the Food and Agriculture Organization. We determined the real values by dividing the nominal prices by the Consumer Price Index for all items in the USA, using a base of 2010 = 100. We collected data on monthly average exchange rates (national currency per US dollar) from the International Financial Statistics of the International Monetary Fund. We determine the real value of the exchange rate by multiplying the nominal values by the ratio of the USA to India’s consumer price indices, using a base of 2010 = 100. We compiled data on the effective rate of basic customs duty (ad valorem import tariff) on wheat from the Directorate of Economics and Statistics, the Ministry of Agriculture, and the Government of India.

To estimate the trade price for imported wheat, we added the international ocean freight charges (from the US Gulf port to the Indian port, i.e., Visakhapatnam) to the FOB US Gulf price for US HRW No. 2. We have adjusted the domestic price for domestic transport and transaction costs under the importable hypothesis, assuming that these costs are same to both imports and domestic output by following the methodology developed by Pursell, Gulati, and Gupta (Pursell, Gulati, and Gupta Reference Pursell, Gulati, Gupta, Anderson and Martin2009) and Saini and Gulati (Reference Saini and Gulati2017). We took the domestic marketing costs and traders’ margins to be 6% of the domestic price.