2019年全球生活成本和生活质量报告-德勤-2019.5-44页_405kb

报告摘要

2019 Global Prices and Living Standards Report Summary

Core Content

This report is the 8th annual survey of global prices and living standards, analyzing data from 56 cities across various countries. The focus is on the impact of the US dollar's strength on global currencies and the changes in living standards and prices across different cities over the last 12 months and 5 years.

Key Findings

Currency Trends

USD Strength: The US dollar has strengthened against all but the Egyptian Pound over the last 12 months.
Biggest Losers: The Turkish Lira (-31%) and the Argentine Peso (-55%) have been the most affected.
Long-Term Trends: Over the past 5 years, the dollar has outperformed all these currencies, with several currencies falling by 20% or more versus the USD, including the Norwegian Krone (-31%), Swedish Krona (-31%), Mexican Peso (-31%), Brazilian Real (-43%), Russian Rouble (-44%), Nigerian Naira (-55%), Egyptian Pound (-59%), Turkish Lira (-64%) and Argentine Peso (-82%).
Sterling and Euro: The British Pound (-23%) and the Euro (-20%) have also seen significant drops.

Cities and Living Standards

San Francisco: Has overtaken Zurich as the city with the highest salaries and disposable incomes, climbing 7 and 21 places respectively over the last 5 years.
Zurich: Drops to second place in salaries and disposable incomes.
Quality of Life: San Francisco also improved its position in the quality of life index, climbing 7 places over the last year and 21 over the last 5 years.
New Entries: Several cities and countries were added this year, including Buenos Aires, Dhaka, Cairo, Rome, Lagos, Riyadh, and Seoul, with the addition of these cities covering all G20 countries and increasing representation from emerging markets.

Main Points

Income and Disposables

San Francisco: Leads in salaries and disposable incomes, with a 5-year increase of 21 places.
New York, Boston, Chicago: Have entered the top 5 in terms of salaries and disposable incomes due to the US economy's growth.
London: Has the lowest disposable income, with a significant drop in both 1-year and 5-year comparisons.

Cost of Living

Rent: The cost of a 2-bedroom apartment has increased in most cities, with San Francisco only behind Hong Kong in rent.
Consumer Goods: Prices for consumer goods vary significantly, with some cities being much cheaper than others.
Public Transport: Cities like Singapore, Copenhagen, and Oslo have expensive public transport, while London is the most expensive.

Other Expenses

iPhone Prices: iPhones are 25-65% more expensive in countries like Brazil, Turkey, Argentina, India, and Greece.
Cigarettes and Beer: The "Bad Habits" index is most expensive in Melbourne, with Sydney, Auckland, and Dubai also in the top 5.
Cleaners: Stockholm and Oslo have the most expensive hourly rates for cleaners, while cities like Cape Town, Buenos Aires, Lagos, and Istanbul are the cheapest.
Haircuts: Haircuts in Copenhagen, Oslo, and Zurich are 10-15 times more expensive than in cities like Dhaka, Bangalore, Manila, and Cairo.
Internet: Moscow and Istanbul have the cheapest internet.
Coffee: Milan has the best coffee prices, with cappuccino prices being three times higher in cities like Copenhagen, Dubai, Hong Kong, and Oslo.
Car Rentals and Ownership: In cities like Singapore, Copenhagen, and Oslo, car ownership is very expensive due to policy, while car rentals are also costly.

Key Information

Methodology

Data Sources: Most data is collected through crowdsourcing, with some data from Expatistan and Numbeo.
Currency Conversion: Prices are converted back to USD for comparison.
Consistency: Efforts are made to ensure uniformity in product and service selection and to include price distortions such as taxes and discounts.
Data Collection Time: Data is collected from the same point in time each year (April) to control for seasonality.

Notes on Data

Variability: Some data points may be inconsistent over time, with adjustments made for outliers.
Representative Data: Prices, changes, and ranks are considered representative but subject to measurement and sampling errors.
Comparisons: Changes are compared to both 2014 and 2018, with the 5-year cumulative change also noted.

Table of Exhibits

Figure 1: Quality-of-Life Indices (ranks)
Figure 2: Monthly Salary (Net of Taxes)
Figure 3: Monthly Rent for Mid-Range 2 Bedroom Apartment
Figure 4: Disposable Income Index after Rents
Figure 5: Weekend Getaway Index
Figure 6: Cheap Date Index
Figure 7: Bad Habits Index
Figure 8: iPhone XS
Figure 9: Daily Car Rental
Figure 10: Five Star Hotel Rooms with a View
Figure 11: 2 Litres of Coca-Cola
Figure 12: Beer in a Neighbourhood Pub
Figure 13: 1 Pair of Sport Shoes
Figure 14: 1 Pair of Levis Jeans
Figure 15: Monthly Ticket Public Transport
Figure 16: New Mid-Size Car
Figure 17: 1 Liter of Gas
Figure 18: Taxi Trip on a Business Day
Figure 19: 1 Ticket to the Cinema
Figure 20: 1 Month of Gym Membership
Figure 21: Men's Standard Haircut
Figure 22: 1 Pack of Marlboro Cigarettes
Figure 23: Basic Dinner at a Neighbourhood Pub for Two
Figure 24: Full Course Dinner for Two at an Italian Restaurant
Figure 25: Hourly Rate for Cleaning
Figure 26: 1 Month of Internet (8 Mbps)
Figure 27: Cappuccino in Expat Area
Figure 28: 1 Summer Dress
Figure 29: Annual Subscription of the Economist
Figure 30: Foreign Exchange Rates
Figure 31: Relative Price Levels as Implied by PPP
Figure 32: Changes in Consumer Price Indices

Acknowledgments

Expatistan: Provided most of the price data.
Numbeo: Provided Quality-of-Life and salary data.
Apurv Chaudhari: Contributed to the report.

Data and Methodology Notes

Crowdsourcing: Data is collected through crowdsourcing techniques, which may lead to inconsistencies.
Adjustments: Outliers are adjusted for to ensure more consistent data.
Comparability: Data is collected from the same point in time each year to improve comparability across periods.
Revisions: 2018 data was revised to provide a more fair comparison with 2019 data.

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