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Record W7096261000

The Impact of Real Exchange Rate Movements on Service Sector Firms

2008· article· en· W7096261000 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsLeverage (statistics)Profitability indexTertiary sector of the economyExchange rateManufacturing sectorService (business)
DOInot available

Abstract

fetched live from OpenAlex

There is a growing literature addressing the effect of exchange rate movements on the survival and performance of manufacturing firms. With international trade in services expanding tremendously, the international environment is also becoming increasingly important to service sector firms. To date, however, the implications of the international economy for firms in the service sector are vastly understudied. This paper sets out to investigate this important, yet unexplored, issue. We analyze the effects of industry specific real exchange rate movements on the profitability, survival, sales and leverage of Canadian service sector firms. We use firm level data from 1986 to 1997 combined with service trade data from 1990 to 2005. Our empirical results show that real appreciations of the Canadian dollar reduce firm probability of survival, sales and profitability while depreciations have the opposite effect. Leverage decreases with appreciations and increases with depreciations. This paper is among the first in the literature that analyze the impact of exchange rate movements on the behaviour of service firms. Overall, our findings suggest a significant exchange rate effect on service firms and the direction of which is similar to that for manufacturing firms.

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)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.252
Teacher spread0.187 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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