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Status, Impact, and Architecture

Electronic Agricultural Spot Markets

The electronic spot market has introduced technological innovations to agricultural commodity market trading through the electronic National Agriculture Market. To assess the role of the electronic spot market in price discovery, this paper explores the price efficiency test between select commodities’ spot and futures markets. While we find that the spot plays an instrumental role in price formation and transmission in selected markets, eNAM is yet to augment price-setting for farmers. We propose improvisations in the spot market design that align institutional structures, governance mechanisms and incentives and strengthen spot market infrastructure to enhance farmer participation.

Electronic spot markets are said to play an important role in agricultural market development. It can be argued that it helps derive a theoretical price for the futures/options contract, especially in the exchange-traded derivatives market (O’Hara 1995). In other words, if price discovery is found to be opaque or insufficiently transparent in the spot market, the pricing of derivative contracts may be affected, which can be detrimental to agricultural market transparency and development. In India, the organised futures market was introduced in 2002–03, whereas the national-level private spot exchanges were set up in 2007–08. Post 2011–12, information and communication techno­logy (ICT)-enabled large-scale electronic screen-based agricultural spot trading was initiated, following the introduction of the Karnataka model and electronic National Agriculture Market (eNAM). This development is attributed to digitalisation, technological innovations, the orchestrated roles of market institutions, and development policies (Chand 2016; Dey 2016; ­Aggarwal et al 2017; Reddy 2018). In the agricultural commodities market landscape, the enactment of the Model Agriculture Produce and Livestock Marketing (Promotion and Facilitation) Act, 2017 paved the way for electronic (secondary) spot market development to integrate local mandis (large markets) or agricultural produce marketing committees (APMCs) to improve price-setting and remove intra-state trade barriers. However, the lack of a competitive environment and adequate support infrastructure has arrested the growth of the electronic spot market and hindered its potentially instrumental role in price discovery and market development (Department of Economic Affairs 2018).

Our paper contributes to discussions on the status and ­design issues of the electronic spot in the agriculture market setting and its role in price discovery and market integration. It has gained ground against the backdrop of the union finance mini­ster’s deliberations on the adoption of an eNAM (integrated 1,000 APMCs in 18 states and three union territories) over archaic APMCs, where collusive trade practices are prevalent and beleaguered marketing systems often force smallholders to restrain from voluntary exchange. While reviewing the literature on the impact of the electronic spot market on price-setting and market arrival, Aggarwal et al (2017) and Reddy (2018) must be acknow­ledged; their work explored the impact of electronic spot auctions on price realisation and stakeholders’ participation concerning the Karnataka model named Rashtriya e-Market ­Services (ReMS). Nevertheless, their analyses fall short in terms of inve­sti­gating how the electronic spot market can be a potential avenue to alleviate distress sales and farm poverty. Does it score higher than the futures market in price discovery or has it registered a low entry barrier to participation?

Translating the technological opportunities offered by eNAM into socio-economic development for smallholders remains an area of concern for agriculture and food policy in developing countries. Since information search costs constitute a bottleneck for smallholder participation in market-based transactions, mobile phones with active internet facilities are considered an effective medium to harness the benefits of electronic spot markets (Chadha 2020). Thus, mobilising and collectivising smallholders in producer companies can help them overcome digital literacy constraints, enhance their collective barg­aining, and prevent distress sales. Electronic spots can enhance the utility function of small farmers with reduced transaction costs, improved price realisation, and increased market social capital (Meijerink et al 2014; Aker and Ksoll 2016).

With this in mind, we engage in price efficiency tests of commodities between the spot and futures markets. These help us draw some insights into the spot and futures temporal price relationship and determine which market is (informationally) efficient in impounding new information and reflec­ting the true or fair value of commodities in a given period (O’Hara 1995). Empirical evidence reveals that agriculture fut­ures markets are driven by speculators and the lack of broad-based and liquid contracts has outlived its vitality (Sahadevan 2012, 2014). Additionally, the poor execution of policy-determined minimum support prices has left many smallholders in the lurch (Chand 2017). So, what options are farmers left with? How can they avert the spiralling of distress sales? Can they improve their holding capacity to store the marketable surplus and sell/trade them on the electronic spot platform (such as eNAM, ReMS, or BSE Electronic Agricultural Market [BEAM]) by capturing seasonality? What design and processes should electronic spots adopt?

Rationale and Status

The rationale for electronic screen-based trading is well documented in the financial economics literature (Harris 1990). Derivative exchanges were introduced in 2002–03, while spot exchanges were promoted in 2007–08. The importance of screen-based trading is as follows: first, electronic spot trading reduces the fixed costs of running a physical or floor-based trading centre (Harris 1990) and expedites the participation of informed traders, or market participants operating on privileged or useful information, which can accelerate the price discovery process in the spot market and seamlessly transmit the price information to the futures market. Second, the electronic spot market can minimise the trade time required to process an order (through the electronic limited order book as in the case of an exchange-traded derivatives market), route it to the market, and execute the trade (Grossman 1990). Third, it provides rapid price information capture and dissemination (Hasbrouck and Sosebee 1992). Fourth, electronic screen-based trading can provide more useful information to market participants than a floor-trading market (Grunbichler et al 1994). The eNAM or ReMS, a joint venture of the National eMarkets Limited (NeML) and the Karnataka State Agricultural Marketing Board, and private electronic spot markets, such as BEAM and NeML, are promoted in light of these reasons (Chand 2016; Dey 2016). The Department of Economic Affairs (2018: 258) also noted the need for an electronic spot:

The electronic spot markets for commodities could play a crucial role in the integration of localised physical markets, establishing a direct link between the buyer and seller and providing a transparent mechanism of price discovery. Further, being electronic, the value addition offered by the electronic spot exchanges is also scalable.

The Model Agriculture Produce and Livestock Marketing (Promotion and Facilitation) Act, 2017 made several provisions to improve the spot market institutional design, align its design with incentives, and enable market infrastructure for farmer participation. For example, direct marketing now all­ows farmers to sell their produce at the farm gate or the warehouse platform. While agricultural marketing is proposed to be divorced from the ambit of the APMCs as per the act, Section 4(a) made a provision for the entire state to be declared as a unified market. Section 13 of the act empowers farmers through the process of demo­cratisation, Section 17 reduces the mandi cess from 2.5% to 2% (while it is 1% for perishable produce), of which 1.5% can be used for operation and development. Section 19 gives autonomy to APMC officials, and Sub-sections 33 (e, f, and d) stress improvisation in licensing. The act also specifies a ceiling on commissions (2% for non-perishable and 4% for perishable commodities) (Singh 2018).

It is worth noting that eNAM has accommodated diverse stakeholders as of 31 May 2021—1.71 crore farmers, 1.69 lakh traders, 92,079 commission agents, and 2,097 farmer producer organisations (FPOs) (accessed data from the eNAM portal). Out of the 1,000 APMCs integrated with the eNAM structure, Rajasthan (144), Uttar Pradesh (UP) (125), Gujarat (122), and Maharashtra (118) account for more than 50% (Table 1, p 46). Rajasthan ranks first in terms of the total number of traders registered with eNAM, followed by UP and Madhya Pradesh (mP). Rajas­than and Maharashtra were the states with the highest number of FPOs registered with eNAM. However, at an individual farmers’ level, the highest turnout rate (number of farmers registered with eNAM) is seen in mP, followed by UP and ­Gujarat. Karnataka, Kerala, and West Bengal reported the lowest turnout of far­mers. Table 2 presents a statewise quantity transacted and traded value on eNAM in 2017–18.

Price Efficiency: Spot versus Futures

In this section, we explore the price efficiency of spot and ­futures markets. The test aims to assess whether the spot price is informationally efficient to the futures price or vice versa in price discovery. As testing the efficiency of the spot and futures prices is essential to help farmers select the right market to access real-time price information and manage (hedge) price risks, we conducted a secondary-level analysis, the data for which was extracted from the Reuters Eikon database from 2006–07 to 2017–18.1 We used standard econometric models to perform linear co-integration (to investigate a long-run equilibrium price relation) between (1) the spot and futures prices (adjusted for seasonality in each case) and (2) the short-run causality between the spot and futures returns (Engle and Granger 1987). The specification for the vector error correction model (VECM) contains information on short- and long-run adjustments to changes in the non-stationary time series. Sometimes, “Granger” causality2 is conducted to explore any short-run causality between the spot and futures returns. The equations for estimating the price efficiency of selected futures and spot markets are given below:

Rs,t ds + asECTt–1 + ∑ βs,t Rs,t–1 + ∑ yf,tRf,t–1 + εs,t ... (1)

Rf,t d+aECTt–1 ∑ βf,t Rf,t–1 ∑ ys,tRs,t–1 + εf,t ... (2)

Rst or ∆St are the spot return and Rft is the futures return; βsi, γsj, βFi, and γfj are the short-run coefficients; Ω (St-1–Ft-1) is the error correction term (ECT); and εs,t and εf,t are the residuals, as explained above. The magnitude of the coefficients αs and αf determines the speed at which the long-run equilibrium is restored following a “unit shock”—from the spot to the fut­ures, within the spot, within the futures, and from the futures to the spot—which can be captured through impulse response analysis. When these coefficients are large, the adjustment is rapid; Ω is highly stationary, and reversion to the long-run equilibrium is also rapid where ζ is the error coefficient adjusted through ECT (denoted by Ω).

We tested the price efficiency of the spot and futures prices of a few commodities, namely castor seed, cumin seed, rapeseed–mustard (RM) complex, coriander, and soybean largely grown and traded in the spot markets of Gujarat, Rajasthan, and mP, and the futures exchanges of the Nati­onal Commodity and Derivatives Exchange (NCDEX) and Multi Commodity Exchange of India (MCX). More than half of the cultivated area in Gujarat is used to grow cotton and cumin and a similar share in mP is used to grow soybean. Also, brokers and members of commodity exchanges have a higher concentration in these states, in which such high-value commodities as cumin, castor, RM complex, and soybean have active spot markets, and their corresponding futures markets have been operational since 2005–06. The selected commodities are reported to have a high futures trade multiplier (the ratio of futures trade volume to net [physical] availability in a year); for example, in 2015–16, the castor seed futures trade multiplier was 20.07, followed by that of coriander (17.99), cumin (5.22), RM complex (2.65), and soybean (2.36). We excluded cotton and its derivatives and guar seed because of limited observations and the absence of liquid futures after 2012–13.

Table 3 shows the descriptive statistics of the commodity spot and futures returns of selected commodities. The futures price of castor fetched the highest average returns, followed by rapeseed spot returns and soybean spot and futures returns; the latter also showed the highest negative average returns (for both spot and futures). RM futures returns showed maximum risk (as captured by the standard deviation), followed by the castor and coriander markets, whereas cumin spot returns entailed the lowest risk. The spot and futures returns of rapeseed and castor showed maximum skewness, suggesting frequent small gains and sudden extreme losses (Kang et al 2017). The excess kurtosis for all markets and commodities was more than three, with the spot and futures returns of rapeseed showing the highest kurtosis. All kurtosis was leptokurtic, that is, with a marked peak and a fat tail. These patterns of skewness and kurtosis suggest that all returns follow a non-linear process. We converted commodity futures and spot prices into futures and spot returns by taking the first difference of logarithmic prices of the period and (t−1)Rt = (Pt /Pt–1 ) because the prices were non-stationary.3

The spot and futures prices of castor responded to error correction (referred to as basis) instantaneously (Table 4, p 48), as is evident from their statistically significant error correction terms (ECTs). In the case of castor, the ECT value and its statistical significance (p-value) indicate the average speed of news adjustment through the co-movement of the castor spot price and castor futures price towards convergence—the spot price follows the futures price and the futures price also responds to the spot price, but the latter response is stronger. The co-integration or co-movement of the castor futures price and spot price restores the long-run equilibrium in the relationship between the two markets. However, the castor fut­ures price is not informationally efficient to its spot price, as can be seen from the statistically significant p-value of the ECT of the futures price. In the short run, there is a bidirectional “Granger” causality, that is, from the futures return to the spot return and the spot return to futures return at the respective first lag of return series. Therefore, in the short run, both the returns series respond to innovation or shocks and show bidirectional causality. Some of these results are in contrast to those reported by Karnade (2006). However, this may be bec­ause the study considered a small sample and two castor markets, Ahme­dabad and Mumbai, to explore long-run relationships in prices.

Cumin spot and futures prices also respond to error correction with almost the same magnitude as in the case of castor. The futures price and spot price co-movements are instantaneous, although we did not find the cumin futures market to have any influential role in spot price formation and dissemination (as can be seen from the significant coefficient value of error correction for the futures price in Table 4). In the short run, the futures return and spot return respond to each other, which is why a return spillover occurs at the first lag and shows a bidirectional “Granger” causality. The cumin spot market is more mature than its futures market and shows enhanced participation, thanks to the Unjha APMC in Gujarat. Though futures trading started in 2005–06, an actively traded cumin spot market is critical to market integration and improved market efficiency.

Coriander prices showed a pattern that was different from that shown by any of the other four commodities—owing to non-stable explosive error correction, the futures price and spot price of coriander showed no restoration of a co-integrating relationship. In other words, both the price series remained divergent or departed from the long-run equilibrium relationship to such an extent that a natural convergence was highly unlikely to be attained. It is evident that the coriander futures price responded to the spot price in the long run while the spot price did not show any such response. A positive sign of the ­error correction vectors for the spot and futures prices cannot hold a stable relationship in the long run, which may result in illiquid contracts and ineffective hedging against price risks. This phenomenon is characterised by the lack of information spillover between the spot and futures market contemporaneously. The plausible reason could be the coriander backwarded market or the existence of a relatively thinly traded futures market that hardly contains any quality information to discover a true or fair value of coriander for the spot.

For RM complex, the co-movement of the rapeseed futures and spot prices has restored the co-integrating relationship in the long term. However, the spot price appears to lead the futures price, as can be seen from the ECTs and their res­pective sign and p-values. In the short run, information spillover in the returns equation from futures to spot is pronounced, as can be seen from Table 4. The futures return Granger–causes the spot return and the spot return Granger–causes the futures return at only the first lag—we can, therefore, infer a bidirectional causality between rapeseed futures and spot returns.

Soybean spot and futures prices held a long-run equilibrium relationship as they responded to each other. However, the fut­ures price showed a pronounced response to the spot price, as can be seen from the magnitude of the ECT of the futures price. In the short run, there was a return spillover from spot to spot and from spot to futures, although we found no response from futures to spot returns. Therefore, we can infer that the spot return at its first lag Granger–causes the futures return or that there is unidirectional causality from spot to fut­ures. This also indicates a relatively weak form of futures market efficiency in the case of soybean.

What are the implications of these findings for farmers and their organisations? We wondered whether co-integration could help us understand the pattern or the degree of convergence between the futures and spot prices. For example, the co-integrating relation in the case of castor spot and fut­ures was restored in 40 days, which means both the price ­series would naturally converge in more than a month. Also, by and large, both the futures and spot price played an equal role in price formation—neither can overshadow the other in terms of price discovery. Therefore, farmers should consider both the prices in real-time and then decide how to use both the markets. With cumin, the restoration only took 14 days, indicating mature and liquid spots and futures markets. However, a spot market for cumin has been operational in Gujarat for a long time, trader involvement and export potential have made the spot efficient, and bidirectional causality observed between the two prices has restored the futures and spot price co-movement. Therefore, farmers should use the spot price to set more realistic expectations or sell a major portion of their produce in the spot market. In the case of rapeseed, the restoration took less than four days and showed a rapid convergence throughout the contract period. Because the futures price is informationally efficient, farmers can take a short (sell) position but should cautiously watch the market since any speculative pressure on buying and selling can distort the futures price, making it deviate from its fundamental or economic value. In the case of coriander, because no co-integrating relationship was observed, farmers need not consider acc­essing the futures price or rely on the spot price otherwise. In the case of soybean, the restoration took approximately 69 days, indicating that a natural convergence can take longer than two months. Therefore, farmers should observe and speculate on the spot price and futures price evolution by taking a short position in the spot (as spot return Granger-causes the futures return) and a long position in the futures (if they are interested) and match the contract period with the underlying cash market. They should realise a return using an intra-commodity spread strategy or reverse cash-and-carry arbitrage.

The Electronic Spot in Price-setting

We explored the impact of the electronic spot on price formation and present the findings below drawing evidence from a survey.


The role of the electronic spot in price realisation: NCDEX eMarkets (NeML)—as the technology partner to ReMS—integrated 170 APMCs into a unified market platform in 2012 that offers automated auction and post-auction facilities, assaying facilities, facilitation of warehouse-based sales, and price dissemination by leveraging technology. Gradually, Guj­arat, Telangana, and Andhra Pradesh partnered with NCDEX eMarkets for mandi modernisation, which was held outside the eNAM ambit, although the objective remains unchanged. Both private and public initiatives aim to improve spot trading and help in spot price discovery by integrating local/primary APMCs into a unified market platform.

Therefore, we conducted a study to assess the impact of the electronic spot market on price realisation for farmers. We selected a group of commodities that have a high share in trade volume and liquidity in the local markets of Gujarat, mP, Rajasthan, and UP. We conducted the investigation from January 2007 to November 2019 to capture the structural break as a sign of eNAM (2016 onward) considered as a pulse dummy in the equation. While we did not find any significant impact of eNAM in price-setting for selected commodities,5 Reddy (2018) reported that ReMS has a positive impact on price realisation and market arrival and showed that participating farmers from Karnataka benefited from higher prices due to the online auction for copra and groundnut and traders benefited from higher market arrivals. The emergence of the electronic spot market buoyed competition and discouraged collusive trade practices. Aggarwal et al (2017) put forward that the enterprise of marketing reform is to be achieved by institutional reforms, incentives, and infrastructure.


Farmers’ opinions on market performance: To capture farmers’ opinions on the comparison between the electronic spot and futures markets, the Centre for Management in Agriculture (CMA), Indian Institute of Management (Dey et al 2019), conducted a field survey with a majority of small and marginal farmers (about 200 farmers as the sample) associated with farmer producer companies and the cotton growers’ association that had been involved in futures and spot trading in Gujarat, mP, and Raja­sthan. A large number of high-value agriculture commodities grown in the region have matured and liquid primary agriculture markets and exchange officials often draw reference prices from such markets, such as northern Gujarat and the Agar-Malwa region of mP—especially for castor seed, cumin seed, RM complex, coriander, soybean, and cotton.

Table 5 reports the responses of farmers associated with producer organisations, recorded and computed on a five-point Likert scale (based on a survey questionnaire presented in Appendix 1, p 52) showing the comparison between electronic spot market and futures market attributes, namely market role in price discovery, pay-off, margin (money) requirement, standardised contract, compliance, liquidity, risk of losses in trading, and certainty equivalent income (CEI). Findings reveal that 45.2% of respondents agreed with the instrumental role of the futures market as compared to the spot market in price discovery, while 49.2% remained indifferent or partially in agreement. Of the respondents, 41.2% stated that pay-offs from spot markets are relatively more secure compared to futures as one can immediately take (buy/sell) a position in the spot and deliver the assayed produce at relatively lower transaction costs. Regarding the margin money requirement for participating in electronic trade, 59.8% of the respondents were ­indifferent, while only 15.6% maintained that the margin money requirement is significantly higher in futures compared to the spot due to the nature of the market and the nuances of contract and exchange management. However, 46.2% of the respondents accepted that futures contracts are more standardised relative to the spot, but supplying the basis/tradable variety is difficult as most farmers grow local varieties of crops. Concerning compliance and liquidity, more than 50% of the respondents partially agreed that the futures market enh­ances liquidity in the market, brings surveillance in place, and reinforces compliance with member/participants’ activities. As far as the risk of losses is concerned, 42.7% of the respondents agreed that the futures market is riskier than spot, and that in the spot market, one can delimit losses by extending the sales period and storing the assayed produce in the storage/warehouse until local prices improve. As consu­mption assets or agricultural commodities are likely to exhibit a backwardation market pheno­menon, futures prices overstate the bias in determining the expected future spot prices; in that condition, producers can exp­loit the spot market to a greater ext­ent (for more details on reverse cash-and-carry arbi­trage strategy, see ­Geman [2009]), and in the absence of basis risk in the spot market, farmers need to manage the price risk of commodities only.

The correlation structure of variables (ordinal) used to compare the spot market with futures is presented in Table 6. The coefficients of correlations are relatively higher and significant between the market functioning and margin money and compliance. On the other hand, a standardised contract (spot and futures) correlates with liquidity, which implies that when a contract is uniform or homogeneous, participation improves the trading volume and brings liquidity to the market. However, the risk of losses in trading and income variability is not correlated with other variables significantly. It is attributed to outcome-related issues that are not similar to operational or regulation-based ones, such as standardised contracts and margin money.

Electronic Spot Architecture: Design and Implementation

Based on the findings on price efficiency, the role of an electronic spot in price-setting, and farmers’ opinions, we argue that the utility of the electronic spot market platform can be realised by farmers if its design and implementation are aligned with social and economic processes and process stakeholder analysis (Reddy 2018). An organised, transparent electronic spot market seamlessly interacts with futures, improves market integration by removing trade barriers, and introduces liquidity and transparency, as may be observed in ReMS. With the recent introduction of BEAM, the price-polling exercise can be improved. The coexistence of public and private electronic spot markets can augment the price discovery process through competitive price polling, improve decision-making among farmers and traders, and curb agents’ cartelisation and collusive trade practices that affect market functioning. Although multiple electronic spot markets encourage (spatial) arbitrage opportunities, arbitraging leads to efficient spot price discovery and improves market efficiency.


Social and economic processes: The framework proposed by Ribbers et al (2002) classifies the complex socio-economic processes that determine the success (or failure) of an electronic spot market according to the foll­owing process elements or determinants: (i) producers/manufacturers, (ii) traders, (iii) commodities, (iv) market organisation, (v) market quality, (vi) electronic market success, and (vii) competition with other market formats (Figure 1). Among the seven determinants, market organisation and product quality are critical to electronic spot market deve­lopment. While commodities need standardisation in terms of quality standards and assaying facilities available in the marketplace, market organisation involves overseeing the performance of various operations, such as the price discovery mechanism (like the bidding process), information dissemination, logistics arrangement (storage, assaying, etc), and coordination (Dey 2016). Market organisation influences the quality of a range of products and services, fair price discovery based on demand and supply, low transaction costs, and governance mechanisms. Given the competition in the oligopolistic market, the electronic spot market can augment producer price realisation, infuse more market social capital, and formalise the trading network. A detailed survey of the seven elements of socio-economic processes may be conducted to assess the impact of the electronic spot market on price realisation, arrivals, and governance, among other important parameters (Reddy 2018). The electronic spot market can establish a real-time inf­ormation flow between primary regulated APMCs and a centralised information system where the market arrival, trade, and price data are maintained.

Process stakeholder analysis: Electronic spot trading needs to be standardised and process-oriented. Process stakeholder analyses for trade processes, namely searches, valuation, logistics, clearing and settlement, and authentication and trade context processes, including communications, product representation, legitimation, influence, and dispute resolution (compliance and legal issues) are the key considerations for spot market development (Kambil and van Heck 1998). Table 7 presents the salient characteristics of trade processes and trade context processes.


The electronic agricultural spot market has a long way to go, entailing several policy measures ranging from regulation to market design issues and the creation of a support infrastructure. The institutional design, governance mechanism, and incentive structure for market agents/actors need to be aligned to promote spot market transparency and introduce a unified trading architecture for the spot market. From the price efficiency test, we find that agricultural spot markets (cumin, castor, RM, soybean) score higher than their derivatives in price discovery and transmission, which can influence farmer decision-making regarding market participation and investment in resource allocation. Price information transmission and returns spillover from the spot market to the futures market heavily depend on spot-market efficiency, and co-integration between the spot and futures prices helps restore long-run relationships. For market integration, spot and futures price convergence is important to hold, and we provide some empirical evidence based on the findings of the price efficiency test. However, we could not find any significant impact of eNAM on price-setting.

We propose the following policy recommendations against the backdrop of institutional design, incentives, and market infrastructure facilities to promote the electronic spot market. First, institutional design and governance set the rules of the game for market participants and infuse buoyancy in regulation and compliance mechanisms. For example, risk management, clearing, and settlement for electronic spot trading should receive the utmost attention. A SPAN-based margining system can be adopted for the spot market, which can calculate margins at a predetermined timing; and different types of margins—such as pre-exposure and expiry, and delivery margins—can be imposed on the exchange members (Dey 2019). We can draw some lessons from the best practices of spot exchanges that charge the “full amount” or risk collateral setting the upper bound on the trade volume. For dispute resolution in agricultural spot trading, the adjudicating authority can be the concerned state agencies or the Directorate of Marketing Inspection, which will monitor the eNAM integrated APMCs. Second, market infrastructure institutions need to promote electronic spot trading based on electronic negotiable warehouse receipts (eNWR) and facilitate bank financing against eNWR (collateral) in consultation with the Warehousing Development Regulatory Authority and affiliated repositories. Delivery standards and trading architecture should be unified for the development of electronic spot markets. Third, product standardisation is necessary for electronic spot trading, which should be in sync with derivative markets as much as possible. Trade-based delivery should be held in exchange accredited warehouses, which should exist in high concentrations in the vicinity of production centres. Competing products and a basis variety of commodities for spot trading should help arrive at a benchmark or reference prices for secondary agriculture markets.


1 The data is from the Eikon data licensed from Reuters by IIM Ahmedabad.

2 In an endogenous system, “Granger” causality means the causal mechanism between the two variables, X and Y. In this case, “futures returns” and “spot returns” are considered two variables in an endogenous system and the objective is to find out whether “futures returns” “Granger”—causes spot returns or spot returns “Granger”—causes futures returns. In other words, which market in the short run is instrumental in impounding available information in the asset price and engaging in a lead-lag relationship.

3 The unit root test of prices for non-stationarity can be obtained on request.

4 We have employed Bai and Perron (2003) break point tests as well as examined the effects of eNAM by taking a year dummy. In both the cases, the effects of eNAM introduction are not significant. In the interest of brevity, results are not reported; however, they are available on request.


Aggarwal, N, S Jain and S Narayanan (2017): “The Long Road to Transformation of Agricultural Markets in India: Lessons from Karnataka,” Economic & Political Weekly, Vol 52, No 41, pp 47–55.

Aker, Jenny C and Christopher Ksoll (2016): “Can Mobile Phones Improve Agricultural Outcomes? Evidence from a Randomised Experiment in ­Niger,” Food Policy, Vol 60, pp 44–51.

Bai, Jushan and Pierre Perron (2003): “Computation and Analysis of Multiple Structural Change Models,” Journal of Applied Econometrics, Vol 18, No 1, pp 1–22.

Chadha, Kashika (2020): “Digital Literacy in India: Structural Constraints and the NEP 2020,” Social and Political Research Foundation,

Chand, Ramesh (2016): “e-platform for National Agricultural Market,” Economic & Political Weekly, Vol 51, No 28, pp 15–18.

Dey, Kushankar (2016): “National Agricultural Market: Rationale, Roll-out, and Ramifications,” Economic & Political Weekly, Vol 51, No 19, pp 35–39.

— (2019): “Electronic Commodity Spot Markets: Potential, Design, and Integration,” Commodity Insights Yearbook, Mumbai: Multi Commodity Exchange and National Institute of Securities Markets, pp 32–38.

Dey, Kushankar, Vasant P Gandhi and Kanish Debnath (2019): “Farmers’ Participation in India’s Futures Markets: Potential, Experience, and Constraints,” Research Report, Centre for Management in Agriculture, Indian Institute of Management Ahmedabad.

Department of Economic Affairs (2018): “Report of Expert Committee on Integration of Commo­dity Spot and Derivatives Markets,” Ministry of Finance, Government of India, New Delhi.

Engle, Robert F and C W J Granger (1987): “Co-­integration and Error Correction: Representation, Estimation and Testing,” Econometrica, Vol 55, No 2, pp 251–76.

Geman, Hélyette (2009): Commodities and Commodity Derivatives: Modelling and Pricing for Agriculturals, Metals and Energy, West Sussex, England: John Wiley & Sons.

Granger, Clive W J (1969): “Investigating Causal Relations by Econometric Models and Cross-spectral Methods,” Econometrica, Vol 37, No 3, pp 424–38.

Grossman, S J (1990): Report of the Market Volatility and Investor Confidence Panel, New York Stock Exchange, G2–1–17.

Grunbichler, Andreas, Francis Longstaff and Eduardo S Schwartz (1994): “Electronic Screen Trading and the Transmission of Information: An Empirical Examination,” Journal of Financial Intermediation, Vol 3, pp 166–87.

Harris, Lawrence E (1990): Liquidity, Trading Rules, and Electronic Trading Systems, New York: New York University Salomon Centre.

Hasbrouck, Joel and Deborah Sosebee (1992): ­“Orders, Trade, Reports and Quotes at the New York Stock Exchange at the New York Stock ­Exchange,” NYSE Working Paper, pp 93–101.

Jadhav, Radheshyam (2021): “14% of APMC Manids, Farmers Have Joined e-NAM,” Hindu Business Line, viewed on 29 June 2021,

Johansen, Søren (1992): “Cointegration in Partial Systems and the Efficiency of Single-equation Analysis,” Journal of Econometrics, Vol 52, No 3, pp 389–402.

Kambil, Ajit and Eric van Heck (1998): “Reengineering the Dutch Flower Auctions: A Framework for Analysing Exchange Organisations,” Information System Research, Vol 9, No 1, pp 1–19.

Kang, Sang Hoon, Ron McIver and Seong-Min Yoon (2017): “Dynamic Spill-over Effects Among Crude Oil, Precious Metal, and Agricultural Commodity Futures Markets,” Energy Economics, Vol 62, pp 19–32.

Karande, K (2006): “A Study of Castor Seed Futures Market in India,” Doctoral Dissertation, Indira Gandhi Institute of Development Research, Mumbai.

Meijerink, G, E Bhulte and D Alemu (2014): “Formal Institutions and Social Capital in Value Chains: The Case of the Ethiopian Commodity Exchange,” Food Policy, Vol 49, pp 1–12.

O’Hara, M (1995): Market Microstructure Theory, London: Blackwell Publishing House.

Reddy, A A (2018): “Electronic National Agricultural Markets: The Way Forward,” Current Science, Vol 115, No 5, pp 826–37.

Ribbers, P M A, A M Fairchild, E van Heck and J P C Kleijnen (2002): “Creating Alternative Electronic Trading Mechanisms in Time-sensitive Transaction Markets,” Trust in Electronic Commerce, Kluwar Law International, J E J Prins, P M A Ribbers, H C A van Tilburg, A F L Veth, J G L van der Wees (eds), Hague: Kluwer Law International, pp 147–70.

Sahadevan, K G (2012): “Commodity Futures and Regulation,” Economic & Political Weekly, Vol 47, No 52, pp 106–12.

— (2014): “Economic Benefits of Futures: Do Speculators Play Spoilsport in Agricultural Commodity Markets?” Economic & Political Weekly, Vol 49, No 52, pp 45–53.

Singh, Sukhpal (2018): “Reforming Agricultural Markets in India: A Tale of Two Model Acts,” Economic & Political Weekly, Vol 53, No 52, pp 44–49.

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Updated On : 29th Jul, 2022
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