IFCN Methods

1. IFCN Monthly Public Indicators (Milk price & feed price)

2. IFCN Standardization

3. IFCN Typical Farm Approach

1. IFCN Monthly Public Indicators

IFCN Combined World Milk Price Indicator

The Combined IFCN World Milk Price Indicator reflects the global market price level for milk. It represents the theoretical milk price that a processor could pay to farmers if products were sold on the world spot market while operating at standardized production costs.

A significant gap between IFCN World Milk Price Indicators can signal economic stress for specialized dairy producers, particularly if their primary dairy product trades at the lower end of the price range.

This indicator is calculated as a weighted average of three IFCN global milk price benchmarks:

1. 1. Skim Milk Powder (SMP) & Butter (~32%)
   2. Cheese & Whey (~51%)
   3. Whole Milk Powder (WMP) (~17%)

The weightings are updated quarterly based on the latest global trade shares of these dairy commodities.

Latest update: 01.04.2025

Data table: IFCN World Milk Price Indicator in USD / 100 kg SCM*
(*Solid Corrected Milk: 4.0% fat, 3.3% protein)

 IFCN World Feed Price Indicator in USD / 100 kg

The IFCN World Feed Price Indicator reflects the global market price level for animal feed. It is calculated based on the prices of soybean meal and corn, weighted according to their proportions in a simplified compound feed ration.

This indicator provides valuable insights into feed cost trends, which directly impact dairy and livestock production costs worldwide.

Calculation of IFCN World Milk Price Indicators

The IFCN World Milk Price Indicators are calculated based on a weighted average of three key dairy commodity bundles:

1. 1. Skim Milk Powder (SMP) & Butter
   2. Cheese & Whey
   3. Whole Milk Powder (WMP)

Evolution of the Weighting Method

• Before June 2019: The weights were fixed based on global trade shares, with 45% Cheese & Whey, 35% SMP & Butter, and 20% WMP.

• Since June 2019: A dynamic weighting approach was introduced, where the share of each commodity in total dairy trade is updated quarterly based on actual trade data.

Oceania Export Prices & Market Precision

The IFCN World Milk Price is derived from Oceania commodity export prices, now weighted using quarterly trade shares for greater accuracy. This market-oriented method reflects shifts in global dairy import demand and seasonal trade patterns, ensuring a more precise representation of real-world milk prices. The IFCN Trade Database serves as the primary data source for these calculations.

Standardization with Solid Corrected Milk (SCM)

To ensure comparability, all milk data is converted to Solid Corrected Milk (SCM), which standardizes milk content at 4.0% fat and 3.3% protein using the formula:

$$SCM = \text{milk production} \times \frac{(\text{fat \%} + \text{true protein \%})}{7.3}$$

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This standardization allows for more accurate price comparisons across different milk compositions.

Milk: feed price ratio indicator

The milk:feed price ratio is a key economic indicator in dairy farming, calculated as:

$$\text{Milk:Feed Price Ratio}=\frac{\text{IFCN Combined World Milk Price Indicator}}{\text{IFCN World Feed Price Indicator}}$$

This ratio represents the purchasing power of farmers in terms of concentrated feed (kg) per 1 kg of milk sold.

Interpreting the Milk:Feed Price Ratio

• • A milk:feed price ratio >1.5 is considered favorable, indicating that high-yield, high-input dairy systems are economically viable.
  • In simple terms, a higher ratio means it is more cost-effective for farmers to use concentrated feed in milk production.

This ratio serves as a critical benchmark for evaluating farm profitability, feed affordability, and production efficiency in the dairy sector.

2. IFCN Standardization

To ensure global data comparability, IFCN applies the following standardization methods in its annual analysis:

• • Energy-Corrected Milk (SCM) Adjustment: Converts natural milk composition into energy-corrected milk (SCM) standardized at 4.0% fat and 3.3% protein for accurate comparisons.
  • Milk Equivalents (ME) Conversion: Determines how much raw milk is required to produce a given unit of a dairy commodity, using IFCN’s fat-and-protein-based conversion method.
  • Litres to Kilograms Conversion: IFCN uses metric weight measurements rather than volume, applying a standard conversion of 1 litre = 1.033 kg.

These standardization measures enhance data accuracy and enable reliable global dairy market comparisons.

3. IFCN Typical Farm Approach

The IFCN Typical Farm Approach is a key methodology used in IFCN’s annual farm comparison studies. It is based on three core elements:

• • • The Typical Farm Approach
    • The Panel Approach
    • Analysis using the TIPI-CAL Model

Defining a Typical Dairy Farm

In IFCN research, a typical dairy farm represents a specific production system, farm size, and technology level, as well as the average milk output in a given country or dairy region. The IFCN model typically evaluates:

1. 1. A medium-sized farm with average management performance.
   2. A larger farm (also with average management performance) to analyze economies of scale.

The Typical Farm Approach, combined with the Panel Approach—which involves 1–5 farmers, an advisor, and a scientist—enables practical and in-depth farm-level analysis. Compared to traditional statistical methods, this approach allows for more detailed insights into dairy farm economics and management.

The TIPI-CAL Model: A Dairy Farm Analysis Tool

The TIPI-CAL Model (Technology Impact and Policy Impact Calculations) is a comprehensive analytical tool used to assess production, economic, and environmental factors in dairy farming. Originally developed by Torsten Hemme (2000), it has been continuously refined by IFCN to address emerging challenges.

The model includes optional modules for:

• • • Greenhouse gas analysis

    • Feed and water efficiency

    • Risk assessment

    • Farm supply response analysis

    • Scenario modeling

Global Comparisons & Dairy Development Insights

The TIPI-CAL Model allows for global comparisons of dairy farm data across different regions, farm sizes, legal structures, and policy environments.
By ranking the impacts of anticipated policies and farm strategies, it serves as a valuable decision-making tool for dairy sector development.