This webpage describes the nature, uses, method, limitations, and potential future works related to the IIMA-SFarmsIndia Agri Land Price Index (ISALPI) launched during the second quarter of 2022. It also provides a brief primer on popular indices. After several rounds of discussion, SFarmsIndia, a Hyderabad-based Agri Land (Online) marketplace, signed a memorandum of understanding (MoU) with the Indian Institute of Management Ahmedabad (IIMA) on 25 November 2021. The MoU laid out the blueprint for a collaborative research project on pricing of Agri Land parcels listed on the SFarmsIndia platform. SFarmsIndia agreed to share new land listing data with IIMA on a regular frequency. IIMA agreed to explore the idea of developing an Agri Land Price Index for India based on the SFarmsIndia data. The first batch of data included over 6,000 listings across several states of India starting the January of 2019. For a meaningful index, we selected data from the six states: Andhra Pradesh, Karnataka, Maharashtra, Tamil Nadu, Telangana, and Uttar Pradesh. These states offered a critical mass of listings adequate to be included in the index formation. Currently, the aggregate of these six states is posited as the National ISALPI. As more data is generated, ISALPI will be expanded for wider and more granular geographic coverage. The ISALP index is based on a hedonic pricing model on a monthly frequency of land listing data and could be treated as a “quality controlled Agri land price Index for India.”
Land stays central to agricultural activities. In 2016, India was home to nearly 200 million hectares of cropped land with an average landholding of 1 hectare (2.5 acres approx.) per household. Although agriculture contributes less than 20% to the national GDP, it claims to employ nearly 60% of the population in India. Also, the gross value added (GVA) of agriculture is growing roughly at 3-4% per year. Beyond production, agriculture also contributes to capital formation. According to NABARD, agriculture contributed over 7% of gross capital formation (GCF) during 2019-2020. The National Sample Survey Organization (NSSO) Report 587 on agricultural land possessed by Indian households suggests that nearly 80% of the agricultural households are self-employed, with most (70%) involved in crop production. This statistic broadly matches the NSSO report. In some parts of India such as Varanasi, the agricultural land area increased by 40% between 1993 and 2013 (S. K. Patel et al., 2019).
Importance of Agri Land
The pace of growth in agriculture is surpassed by the growth in the manufacturing and service sectors. However, although India contributes only 2.3% of the world’s land area, it feeds 17% of the world’s population (A. Patel, 2015). The latest trends in agri-business posit Agri land as an important asset class.
Development of farm land supports entrepreneurship in numerous allied areas: agricultural engineering, crop protection technology, precision farming, food technology, supply chain management, green energy, and agricultural education, among others (Bhooshan & Sharma, 2021). This trend is espoused by world-class educational programs. For example, IIM Ahmedabad’s agribusiness program is globally ranked one, and two other Indian-based programs rank among the top 50.
The green revolution of India during the later half of the twentieth century was blamed for the widespread use of chemical fertilizers and genetically modified crops (Prabhu, 2012). As a result, several states, such as Andhra Pradesh and Kerala, came up with policies to support organic farming. An increased awareness and government support policies towards the Environmental, Social and Corporate Governance (ESG) goals has led to increased enthusiasm for organic farming in India and has opened new doors for innovative Agri entrepreneurship. Thus, the interest in Agri land is expanding from agricultural households to a new breed of new-age entrepreneurs.
Depletion of vegetation lends as much importance to Agri land as to real estate development. For example, In Varanasi, an 86% decrease in vegetation meant a 40% increase in Agri land, but a 350% increase in built-up area (S. K. Patel et al., 2019). Besides, in peri-urban areas agricultural land conversion (ALC) to urban land has led to several studies that call for Agri land protection (Govindaprasad & Manikandan, 2016).
The Need for Tracking Agri Land Prices
“Buy land, they're not making it anymore” – Mark Twain
For agricultural households, the land possessed is a critical component of wealth. In financial terms, however, operating Agri land may not create adequate additional wealth. For example, the annual yield from crop farming is often as small as 1-2%. On the other hand, land, as a resource, gets scarcer with the increase in population. Thus, land price appreciation is the dominant way for landowners to track their wealth. As the majority of the Indian population is still agriculturally based, the question of tracking land prices over time is an important policy goal.
The Challenges with Creating a Land Price Index
There are centralized marketplaces for goods (e.g. Amazon), services (e.g. Fiverr), or assets (e.g. Bombay Stock Exchange). Some items being sold may be homogeneous, e.g. toothpaste tubes of a specific brand and batch, or securities (e.g. common stocks of a company). Yet, several goods (e.g. computers) or assets (e.g. homes, artworks, land parcels, etc.) of the same type sold within a market may be different from each other significantly.
Consider some examples. No two homes are exactly alike: They may differ in orientation, location, and several other characteristics. Even within a brand and make, a buyer may customize her car to differentiate from other buyers. Two paintings by the same painter will not be the same even if the painter endeavours to replicate his work: It may differ in the quality of canvas (or paint), brush strokes, or in more abstract terms (e.g., the first one may have the “novelty/premier” status while others will not). Similarly, two land parcels can never be identical: They will differ in their geographic coordinates, access to amenities (e.g. roads, views, sunlight) even if they are sub-plotted from the same parcel. Pricing homogeneous assets (e.g. stocks, bonds), therefore, is a different type of exercise compared to pricing heterogeneous assets (e.g. land, artwork, homes, etc.). As the assets are not identical, one may easily argue that the price differential observed between two items is due to differences in the attributes between these assets, and not because the underlying supply-demand conditions for the asset class have fundamentally changed.
Applications of ISALPI
The index should be of interest to existing agri-land owners, prospective buyers, financiers, policymakers, local governments, environmentalists, and agri-entrepreneurs. Existing landowners may use the index to assess how the valuation of their holdings have evolved over time. Sellers and buyers could use this information to assess the historical risk and return and predict these metrics for the future to prudently decide on their buying/selling decision. ISALPI may be useful in reducing litigation cost in some situations, e.g. when agri-land is acquired for public use (e.g., highway) or private interests (e.g., a manufacturing facility) by informing the price movements over time.
Uncertainty in price movements increase the cost of financing or insuring the underlying assets. The transparency offered by the land price index may not only reduce the landowners’ underwriting costs, the financial market products (insurance, mortgage, etc.) the availability and cost of financial products will also improve.
Researchers could use this information to study how economic events and factors are associated with price movements in a specific asset class. Benchmarking land price movements in rural or semi-urban areas to a standard land price index will signal the potential conversion of agricultural land into real estate. Policymakers may use it to modulate their policies.
FAQs about the ISALP Index
What is ISALPI?
ISALPI stands for IIMA-SFarmsIndia Agri Land Price Index. It is a monthly, “Constant-Quality” price index of Agri Land Price in India.
Who develops and maintains the ISALP Index?
ISALPI is developed by IIM Ahmedabad (IIMA), the premier management school of India in collaboration with SFarmsIndia, a Hyderabad-based Agri Land Market place. On 25th November 2021, Dr. Errol D’Souza, Director IIMA, and Mr. Kamesh Mupparaju, CEO SFarmsIndia signed an MoU to jointly maintain and update the index. The programming algorithm for the index development was ideated and first executed in 2022 by Prof. Prashant Das.
How to Use the ISALP Index?
ISALPI provides a big picture idea of how the Agri Land prices are evolving in India. The price index levels in January 2019 are standardized at 100. Suppose the index moves up to 125 in January 2020. This implies that on average, Agri land has appreciated by 25% between these twelve months.
Can ISALPI be used as a discount rate for Agri Land Valuation?
ISALPI provides a big picture idea of how the Agri Land prices are evolving in India and focuses solely on capital appreciation. The discount rate estimate must also include the projected income yield from the crops (or farmland rental). Usually, this yield is small and varies in the range of 1-2.5 percent per year.
What is the Methodology behind the ISALPI?
ISALPI is based on the hedonic pricing method that involves developing a regression model from the past listings data. The regression output leads to a unique index value for each period. These early-stage index values are spikier than expected. We expect that the quality of the index will improve with the arrival of new data over time.
What is the big deal (about the ISALP Index method)?
Developing a price index for liquid asset classes (such as stocks) follows a relatively simple method (e.g. weighted average), as the asset-quality remains broadly constant over time. Thus, changes in price over time may be directly attributed to the change in the supply-demand factors for assets of constant quality.
On the other hand, developing price index for heterogeneous asset classes (e.g. land) is a challenge: When we observe a price differential across two time periods, it may be a result of two factors: (1) the quality of the assets transacted during the two time periods are different; and (2) the supply-demand factors may have changed. An index should focus on the latter, so that the price trend could be applied to any specific asset with a specific (“constant”) set of quality-attributes.
Simpler models that summarize the land price per acre (e.g., average price, median price) are more prone to sampling biases. E.g. some time periods may be dominated by land parcels with a specific set of attributes while others by a different set of attributes. Thus, the difference in the average across these time periods may be due to the difference in the sampled attributes rather due to the difference in supply and demand factors for the core asset (i.e., Agri Land) common across these parcels. Hedonic pricing models used in ISALPI control for (filter out) the difference in quality-attributes across the land parcels sold in different time periods, and teases out the trend attributed to supply-demand factors.
How often is the ISALP Index updated?
As of 2022, the two parties (IIMA and SFarmsIndia) have agreed to publish monthly price indices updated once a year. Thus, ISALPI, as originally planned, is recorded on a monthly frequency, but updated annually. The first release came out in June 2022. The second release was developed in August 2022.
What is the geographic coverage of the ISALP Index?
Originally, ISALPI was based on land listing data from six states: Andhra Pradesh, Karnataka, Maharashtra, Tamil Nadu, Telangana, and Uttar Pradesh. The data from these six states were aggregated into a national index. In the second release, 26 states (and union territories) were included in the index creation of which 18 had critical mass for ranking them.
What are the appropriate uses of the index?
The index could be used as a broad tracker of Agri Land prices in India over time. It is useful as an input for estimating the discount rate for valuation. The index could be juxtaposed with other price indices to study the relative movement in land prices with respect to other asset classes. Stakeholders could develop their expectations of how the Agri land prices have evolved over time.
What are the limitations of the ISALP Index?
The hedonic pricing method is based on some assumptions that may not always be highly reflective of reality. For example, a basic assumption is that the pricing function for different attributes of the land parcels stays the same over time. Over long enough time horizons, this assumption may be violated. A major limitation with the hedonic pricing models is that with the arrival of new data, the past index values may have to be retrospectively updated. Often, the relative (percent) difference between the index value across consecutive time periods does not change materially.
In early releases, the index may not be the most optimal national-level indicator of Agri Land prices. In the second release, the top seven states states (Telangana, Andhra Pradesh, Maharashtra, Tamil Nadu, Karnataka, Uttar Pradesh, Madhya Pradesh) represented over 85% of the listings. The next six states (Gujarat, Rajasthan, Haryana, Kerala, Punjab, West Bengal) represented additional 10% of the data. With superior data coverage, more geographic granularity is desirable.
Another limitation of the index is that it is based on listing data rather than transactions data. However, the quality of the reported transactions data has been questioned for its accuracy in India. Besides, the ISALPI hedonic model exhibits a high degree of fit (65-67%) that renders it fit for being used in the index creation.
Where should the index not be used?
The index provides a reliable, yet broad-based measure of how land prices have evolved in the past. Individual land parcels may be subject to their own specificities such that their price movement may deviate from what the index suggests.
The landholding per household has almost halved in the last fifty years. In 1970-71, it was around 2.28 hectares.
Data sourced from https://nabard.org/auth/writereaddata/tender/2901194931Average%20Size%20of%20Land%20Holding.pdf
GVA reflects the state of the supply side (producers) of an economy whereas GDP relates to the demand (consumer) side.
GCF is a measure of the net new fixed capital formation in an economy. GCF = Gross fixed capital formation + ΔInventory + (Acquisition – Disposition) of valuables
However, we recommend avoiding using this index for performance appraisal of such managers. See the FAQ section for more details.
Note that this graphic, although complete is presented here for illustrative purposes. The latest (and updated) index value can be seen on the Index website.