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Record W2298954934 · doi:10.14288/1.0058223

The economic evaluation of public investment in transportation in underdeveloped countries

2011· article· en· W2298954934 on OpenAlexaboutno aff
William Henry Griffiths

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsDeveloping countryInvestment (military)Public investmentBusinessEconomic growthEconomicsDevelopment economicsPolitical scienceEconomic policyPublic welfare

Abstract

fetched live from OpenAlex

Public investment in transportation forms a large part of the capital budget of many developing countries. In view of the scarcity of development capital, it is essential that the available capital be used to the best advantage. This indicates the need for careful analyses of proposed public investments in transportation. Until quite recently, transportation investment evaluation in underdeveloped countries was almost entirely within the preserve of engineers, with economists taking little active interest in the spatial aspects of economic activity. Economists have recently taken a much more active interest, and new methods of evaluation are constantly being developed and older ones improved. However, there are still some unresolved methodological problems in the evaluation of public transportation investment, and a number of deficiencies in the application of the concepts and methods which have been developed. The objective of this thesis is to describe and evaluate the methods of transportation investment analysis now in use, identify the deficiencies in the existing methods and in their applications, and to propose methods of overcoming the deficiencies. The research which has resulted in this thesis has been in three forms. One was a review of the published literature pertaining to public investment in transportation in underdeveloped countries. The second was in the author's experience in transportation investment analysis in Canada and overseas, for agencies such as the Government of Canada and the World Bank. This experience presented the opportunity of reviewing unpublished writings on the subject, and of reviewing the methodology used and results produced by various consultants and study groups in a wide range of transportation investment analyses in underdeveloped countries. Much of this material, particularly the consultants' reports, is held confidential by the World Bank and by the governments of the countries involved, and therefore cannot be specifically cited in references. The third source of information was in discussions with consultants working in this field, both in Canada and abroad; with representatives of the governments receiving foreign aid for transportation investments, and with the personnel of the World Bank. Chapter I of the thesis is a general introduction to the subject. It deals with the relative importance of transportation investment in underdeveloped countries, and states the objective of the thesis. In Chapter II the objective of public transportation analysis is established, and some of the principles which are basic to all analyses of public investment are considered. In considering the principles, some problems in their applications are identified and the recommended procedures are indicated. All acceptable analyses of public transportation investments must ultimately result in some form of comparison of the costs and benefits of the proposed investment or investments. In Chapter III the methods of measuring costs and benefits are described, and deficiencies in the current methods and their applications are identified. In the cases of relatively minor deficiencies, the correct methods and applications are shown in Chapter III. Possible solutions to the major problems identified are proposed in Chapter IV. The major deficiencies noted in Chapter III are the common failure to relate a proposed transportation investment on an individual link of the system, to the system as a whole, and the failure to relate the transportation system to the economy of the country. These deficiencies will almost invariably result in the incorrect measurement of costs and benefits. In Chapter IV, methods of overcoming these deficiencies are described and evaluated. The most recent published method of conducting a comprehensive analysis which takes account of these factors is the Harvard Model, which consists of two parts: a transportation model and a macro-economic model. The difficulty of applying this approach is considered, and it is concluded that, although the Harvard Model is conceptually the best approach which has thus far been developed, it cannot be applied as a practical method of evaluation at this time. An alternative approach is suggested, based on the methodology used in a recent land transportation study of Dahomey, Africa. The analysis of traffic flows is based on the transportation portion of the Harvard Model, while the economic methodology was developed primarily by the author while engaged in the Dahomey study. The conclusions are presented in Chapter V. It is concluded that transportation investment analyses could be greatly improved, and that most of the necessary improvements are incorporated in the Harvard Model. However, the Harvard Model has not yet been applied successfully, and this will probably be the case for at least the next five to ten years. The methodology used in the Dahomey study is recommended for use as a less sophisticated, but workable alternative, which is also more appropriate to the evaluation of specific investment proposals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.010
Science and technology studies0.0010.002
Scholarly communication0.0060.004
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.113
GPT teacher head0.210
Teacher spread0.097 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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