Econometric Modelling in Logistics

Econometric Modelling in Logistics

Igor B. SEVASTIANOV, PhD, New Mexico State Uni

Abstract

Nowadays, the logistic infrastructure is running at its limit, as trade flows are mostly focused on Asia. Previous studies on this topic are generally aimed at examining the functioning of logistics infrastructure and its impact on the economy of the country. This research focuses on the interaction between the state of transport infrastructure, the dynamics of logistics costs, and export trade volumes to the Asia-Pacific region. The purpose of this study is to explore how the shortage of transport infrastructure in the Far East increases logistics costs for raw material exports (coal) and hampers trade cooperation with the countries of the Asia-Pacific region. By evaluating this on real world data, this study intends to test the following hypotheses: (1) a lack of logistic infrastructure leads to an increase in transportation costs; (2) there is a correlation between high transportation costs and new investments in transport infrastructure; (3) an exceeding share of logistics costs in the price of raw materials leads to a reduction in their export volumes to the countries of the Asia-Pacific region. To this end, based on econometric panel data modelling, the industry’s trends from 2014 to 2024 will be identified, using the example of a major bulk commodity – coal.

Key words: coal, logistics, railway, transport, APR, costs, CIF, shipping

Article

Nowadays, the advancement of railway and maritime infrastructure is becoming a significant strategic imperative for Russia. Due to complicated geopolitical conditions and consequent trade blocking sanctions, the country was forced to turn their economy and trade cooperation from the West (EU countries) to the East. The key foreign economic partners of the Russian Federation along its Eastern border are the countries of the Asia-Pacific region (APR) (e.g., China, South Korea, Vietnam). Therefore, extensive logistics systems are required to ensure the growing cargo flows with APR countries and to recover lost benefits from reduced trade with the EU market.

The limiting factor for the efficient work of exporters and importers is the shortage of existing capacities of the ports and railways (including railway sidetracks to ports) in the Far East of Russia, since the growing freight traffic congests the transport infrastructure. As a result, logistics costs are growing in the key Far Eastern ports, which induces suppliers to increase the prices of goods or decrease their margin. The high share of the logistics component in the final price of a product reduces the competitiveness of Russian raw materials (e.g., coal, gas, oil).

In this respect, well-developed and cost-efficient transport infrastructure is a central element in the strategy of supporting export-oriented industries in Russia. It is necessary to expand and modernise existing logistics routes, as well as to create new ways for trade cooperation with the countries of the Asia-Pacific region.

Hence, the relevance of this work is substantiated by the need for a comprehensive assessment of the relationship between the state of transport infrastructure, the dynamics of logistics costs, and Russian export trade volumes to the Asia-Pacific region for further use of the results in determining the priorities of government and corporate investment policy in the field of freight transportation.

Methodological Aspects

The shortage of transport infrastructure in the Far East increases logistics costs for products (raw materials), which reduces the trading benefits for export-oriented industries in Russia and hampers trade cooperation with the countries of the Asia-Pacific region itself.

Research questions:

1. Does a shortage of transport infrastructure (or assets) directly lead to an increase in transportation costs?
2. Is there a direct correlation between high transportation costs and new investments in transport infrastructure?
3. Does exceeding a threshold share of logistics costs in the price of raw materials, due to infrastructure constraints, lead to a reduction in its export volumes to the countries of the Asia-Pacific region?

The goal of the paper upon which a project is scheduled for February 2026 is to identify, quantify and analyse the nature of the relationship between the parameters of the logistics infrastructure, the level of transportation costs and the volume of Russian export cargo flow to the countries of the Asia-Pacific region using econometric modelling, taking into account country specifics and product group (using the example of a major bulk commodity — coal).

The research objectives of the paper are:

• to calculate and analyse the structure and dynamics of transportation costs for key export routes to the APR countries;
• to identify and evaluate the impact of infrastructure constraints on the growth of logistics costs;
• to build and evaluate an econometric model that establishes the relationship between infrastructure development, cost levels, and trade volume;

The professional significance

The results of the work can be used by government authorities to substantiate investment policy priorities in the transport industry and to develop tariff regulation measures; by logistics companies to optimise supply chains and assess risks associated with logistical constraints; by the scientific and expert community to conduct further research in the field of transport and international trade.

Methods

We suggest the following methodological approaches should one study the link between logistic infrastructure and transportation costs while assessing trade and economic cooperation in the Asis Pacific for Russia. By evaluating this on real world data, this study intends to test the following hypotheses: (1) a lack of logistic infrastructure leads to an increase in transportation costs; (2) there is a correlation between high transportation costs and new investments in transport infrastructure; (3) an exceeding share of logistics costs in the price of raw materials leads to a reduction in their export volumes to the countries of the Asia-Pacific region.

Well, total transportation costs were calculated for the major commodity which is traded eastwards (coal) in order to figure out the portion of the commodity export price attributed to transportation costs. The following parameters were calculated for specific APR countries (China, South Korea, Vietnam, India – are major importers of Russian coal), covering a period from 2014 to 2024, to use in panel data modelling:

— railway and maritime transportation costs from Russia to APR countries (USD);

— CIF price for Russian coal export calculated from benchmark Newcastle FOB price for APR countries (USD per ton);

— transportation costs as a percentage of the CIF price (integrated and separate for railway and maritime) for each year (%).

Also, some basic statistics data were gathered:

— export flows of Russian coal to APR countries (APR imports as mirror data) from Trade Map database (mln tons and mln USD);

— volume of coal transshipment in Far Eastern ports from the RZD Research Centre (tons);

— throughput capacity of the Vostochny polygon railway network from the RZD website (tons);

— average exchange rate (USD/RUB);

— GDP growth rate (%);

— unemployment rate (%);

— inflation rate (%);

— key rate (%).

For the first hypothesis, the Pooled OLS model is going to be used, as it describes the initial data the most adequately, passed the statistical tests (Wald test, Breusch-Pagan test and Hausman test, which indicated no panel effect between countries) and passed the Gauss-Markov theorem conditions.

A correlation matrix is going to be build for the second hypothesis. Pearson’s correlation coefficients are going to be checked for statistical significance using the Student t-test.

As for the third hypothesis, the Fixed effect model is going to be used, as it describes the initial data the most appropriately (takes into account panel effect — country differences in transportation costs) and passed the abovementioned statistical tests. Standard robust errors in White form were used in adjusting the model, as it did not pass the Wald test (heteroskedasticity) and the Wooldridge test (autocorrelation).

The Pooled OLS model results (see Appendix 2) showed that with a 1% increase in the Vostochny polygon throughput capacity, the integrated logistics costs as a percentage of the CIF price decrease by 0.509 percentage points on average, all other things being equal.

The final equation of the Pooled OLS regression model includes:

- – integrated (maritime and railway) transportation costs as a percentage of the CIF coal price;

- – natural logarithm of the throughput capacity of the Vostochny polygon railway network;

- – average exchange rate;

- – GDP growth rate;

- – unemployment rate;

- – inflation rate;

- – key rate.

The tested hypotheses may provide a clear understanding of what transportation costs and its share in product price are favourable for international trade and what level of transportation costs restraints trade in the light of different coal prices. These conclusions are of great importance for infrastructure development in various scenarios of coal consumption and price.

This study reveals several key findings, based on the results of the correlation analysis and the econometric models. Preliminary correlation analysis (see Appendix 1) indicated a strong positive correlation between the coal transshipment volume in the Far East, the throughput capacity of the Vostochny polygon and Russian coal exports to APR countries in USD and in tons. Multicollinearity was found between integrated transportation costs as a percentage of the CIF price, maritime and railway transportation costs as a percentage of the CIF price, the CIF coal price, and the exchange rate. Hence, they were not considered in the model to avoid endogeneity. For the further analysis, some indicators (export in USD and in tons, transshipment volume in the Far East, throughput capacity of the Vostochny polygon, and maritime and railway transportation costs in USD) were converted to a natural logarithm to simplify the interpretation of coefficients and determine elasticity.

For more details, please contact me in person.

Igor B. SEVASTIANOV

PhD, Solid Mechanics

New Mexico State Uni

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