Transportation and Public Safety
Objectives of the action plan and background information
The United Nations Economic Commission for Europe (UNECE) Sustainable Mobility and Smart Connectivity initiative is to help ECE member States move towards sustainable transport and better connectivity.
Renewal of the registered vehicles
The need to rejuvenate the vehicle fleet in Montenegro is based on the need to lower the average age of registered vehicles. The current situation in Montenegro is unsatisfactory, largely due to the purchasing power of the population and the vehicle users’ habits concerning the acceptable safety and technical standards for vehicles.
Action plan
This chapter contains the content of the project with the implementation plan for the necessary activities and goals to be achieved.
Sustainable Transport Action Plan for Montenegro
Determining Road Use Fee and Promoting Vehicle Renewal for Environmental Sustainability
This report is part of Sustainable Mobility and Smart Connectivity initiative, aimed at supporting selected countries in Central Asia, Caucasus and the Western Balkans in transitioning towards sustainable transport and better connectivity. It outlines national action plans designed to build the capacity of national stakeholders to implement sustainable mobility and smart connectivity policies. In collaboration with the Ministries, national stakeholders, and a national consultant, UNECE conducted an in-dept analysis to assess the current state of mobility sustainability and connectivity. The analysis identified key areas for improvement and, in agreement with national authorities, established priority areas for action. Based on these findings, the report proposes tailored actions plans and recommendations for Montenegro to follow in order to improve sustainability of transport sector.
Data sources
The T&T dataset is built from international merchandise trade data from UN Comtrade, combined with GIS-based freight transport network models.
Final remarks
Expanding the availability of detailed official trade data, leveraging additional data sources, refining the statistical models and further accuracy checking and cross-validation can lead to considerable further enhancements of the dataset.
Constructing the dataset
For the construction of the dataset, the pre-processed UN Comtrade data are combined with the Time Distance Matrix, filled up by model-based estimates, broken down by route segments, and aggregated by MoT. Gaps in trade data reporting are filled up by imputations.
Acknowledgments
This technical report provides detailed documentation of the content, concepts, sources and methods for the Trade-and-Transport Dataset developed by UNCTAD and the World Bank.
Introduction
The Trade-and-Transport Dataset provides rich new opportunities for analysis in the light of growing disruptions and fundamental longer-term changes in the global logistics system.
Preparing the UN Comtrade data for use
To prepare the UN Comtrade data for use, they are: acquired, filtered, harmonized, filled up with estimations, reformatted, and cleaned
Econometric models
Data cleaning and compilation of the output data rely on two econometric models: the Transport Cost and the Route Split Model.
Overview of the dataset
The T&T Dataset records main indicators of international merchandise trade and its transport, globally, broken down by origin, destination, commodity and transport mode.
Overview of the compilation process
The compilation of the T&T Dataset involves: pre-processing of source data; data cleaning; econometric modelling; building of the output; and imputation for non-reported trade.
The Trade-and-Transport Dataset
Technical Documentation
This paper describes the sources and methods behind the new Trade-and-Transport (TnT) Dataset, developed by UNCTAD and the World Bank, recording bilateral international merchandise trade, in value and quantity, alongside its associated transport work and costs, broken down by commodity group and mode of transport (air, sea, rail, road, and other modes), from 2016 to 2021. Its compilation has been made possible by the availability of new variables in a recent upgrade of the UN Comtrade database and of enhanced data on transport distances obtained from geographic information systems. Gaps in the primary data on transport costs and transport mode have been filled with model estimates to obtain global coverage. The TnT Dataset builds on the methods developed for the predecessor, the Global Transport Costs Dataset of International Trade, which have been further refined to achieve higher accuracy and allow a more informed adjustment for inter-modal transshipment.