International price dispersions of the Big Mac and economic integration
Bibliographic record
Abstract
Abstract McDonald's Big Mac hamburger is available all over the world, and its recipe and quality are almost identical around the world and have changed little over time. However, Big Mac prices are widely disparate even across countries with more similar per capita incomes. This fact would be amazing because world tariff levels have been falling steadily and world trade volumes have been increasing dramatically in recent decades. We pay attention to the situation of international goods markets' integration and attempt to clarify why the deviations from absolute Big Mac parity are common across countries. To summarize our main results, global price dispersion of the Big Mac did not decrease although per capita income dispersion reduced. On the other hand, price dispersions of the Big Mac decreased within countries where trade ties are strong. These results suggest that Big Mac prices of countries in the world converge to several levels and that existence of trading bloc accounts for deviations from absolute Big Mac parity to some extent. Keywords: Big Mac paritydispersionprice convergenceeconomic integrationJEL Classification: F15F40 Acknowledgements I am grateful to Professors Ryuzo Miyao, Yoshihiko Seoka, Hayato Nakata, Eiji Ogawa, Shingo Iokibe, Shigeto Kitano and Tomoko Kinugasa for their helpful comments. I also thank editor and anonymous referees for their valuable comments. Notes 1 Clements et al. (Citation2011) reviewed many literature on the Big Mac index. 2 Parsley and Wei (Citation2007) described the advantages of using Big Mac prices as a benchmark of price index in detail. 3 Pakko and Pollard (Citation2003) added data that The Economist does not report. 4 We deal with countries having less than three missing values, and treat Belgium, France, Germany, Italy, the Netherlands and Spain as the euro area from 1999 to 2007 because of data restriction. 5 European countries include Belgium, Denmark, France, Germany, Italy, the Netherlands, Spain, Sweden and the United Kingdom. 6 Non-European countries include Australia, Canada, Hong Kong, Japan, Singapore, South Korea and the United States. 7 Considering more segmented groups might help us to understand convergence of Big Mac prices more elaborately. We divide the whole sample into only two groups because available countries are limited. 8 For countries whose prices in 1986 are not reported, we use the oldest available local-currency-based Big Mac prices. 9 Ong (Citation1997) indicated that the nontradable component in a Big Mac accounts for approximately 94% of its price. Parsley and Wei (Citation2007) suggested that the share of nontradable inputs in the Big Mac price is from 55% to 64%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".