Regional Cost Data
Some large news, to me at least: The Bureau of Economic Analysis is straightaway producing "regional cost parities" information that let yous to compare the cost of living inward i identify inward the U.S.A. to another. The BEA news unloose release is here; coverage from the taxation foundation here (HT the ever interesting Marginal Revolution). In the past, yous could meet regional inflation -- changes over fourth dimension -- but yous couldn't compare the degree of prices inward dissimilar places.
The states differ widely. It is inward fact every bit if nosotros alive inward dissimilar countries amongst dissimilar currencies. Hawaii (116.8) vs. Mississippi (86.7) is bigger than paying inward dollars vs Euros (118) Yen (times 100, 1.01) too almost every bit large every bit pounds (1.30)
The variation across city/country too across cities is fifty-fifty higher:
San Francisco-Oakland-Hayward, CA
All items 121.3
Goods 108.4
Services: Rents 183.9
Services: Other 109.6
San Jose-Sunnyvale-Santa Clara, CA
All items 122.9
Goods 108.2
Services: Rents 200.7
Services: Other 109.3
Beckley, WV
All items 79.7
Goods 92
Services: Rents 52.8
Services: Other 92.5
There is all the same a 20% departure inward the cost of goods too other services, but the variation inward rents is truly big. When yous consider that the cost of existent estate drives upwardly other costs, its number may locomote fifty-fifty larger: If the barbershop pays higher rent, too the hairdresser pays higher rent, you're going to pay to a greater extent than for haircuts. And this is only rents. Since houses receive got sparse rental markets, the truthful departure may locomote larger still. Also, rents are ofttimes controlled or poorly measured. I don't know how BLS deals amongst that.
You tin post away meet many uses for fifty-fifty to a greater extent than granular data. But since identify cost too rent are slow to get, yous powerfulness teach a expert approximation past times adding granular housing cost information to regional cost data.
There are a lot of interesting issues here.
One query it raises is the truthful pic of inequality. Poor people, particularly those who don't work, tend to alive inward low-rent areas. Relative to local prices, inequality may non locomote every bit bad every bit it seems. (I presume the BLS does something to conform rents for character of housing.)
One tin post away also imagine that congresspeople from high cost areas volition shortly enquire for higher cost of living adjustments for benefits to their constituents.
This information ought to focus to a greater extent than attending on housing provide restrictions -- the master copy argue that rents vary too thus much.
It raises some puzzles too. I respect that the marketplace position for academics gives surprisingly picayune weight to cost of living variations. If yous compare offers from a European too U.S.A. university, nobody expects yous to compare "100,000" inward each identify without converting currency. But nominal academic salaries are quite similar across chasms of cost of living. To some extent universities teach far upwardly amongst absurdly complex too inefficient housing subsidies, but that doesn't brand much feel either. I'm curious to what extent this phenomenon occurs inward other markets.
And... who knows? New information ever leads to interesting novel research. Kudos to the BEA for making this available.
Comments from people who know how this information is constructed, amongst expert parts too pitfalls, are particularly welcome.
Update
Influenza A virus subtype H5N1 colleague who knows a lot nearly these issues sent some useful information:
From which I take: 1) This is really of import 2) The BLS took a useful stab at it amongst the numbers they receive got but 3) sympathise the large limitations of the BLS numbers earlier yous utilisation them 4) teach to work, big-data economists, on using scanner data, twitter feeds, amazon purchases, zillow, too everything else yous tin post away teach your hands on, to compass 21st century granular cost indices!
Update 2:
Enrico Moretti has already written a really overnice paper, Real wage inequality (Also here) adjusting inequality measures for local cost of living.
The states differ widely. It is inward fact every bit if nosotros alive inward dissimilar countries amongst dissimilar currencies. Hawaii (116.8) vs. Mississippi (86.7) is bigger than paying inward dollars vs Euros (118) Yen (times 100, 1.01) too almost every bit large every bit pounds (1.30)
The variation across city/country too across cities is fifty-fifty higher:
In 2014, the metropolitan expanse amongst the highest RPP was Urban Honolulu, HI (123.5). Metropolitan areas amongst RPPs inward a higher identify 120.0 also included San Jose-Sunnyvale-Santa Clara, CA (122.9), New York-Newark-Jersey City, NY-NJ-PA (122.3), Santa Cruz-Watsonville, CA (121.8), San Francisco-Oakland-Hayward, CA (121.3), too Bridgeport-Stamford-Norwalk, CT (120.4). The metropolitan expanse amongst the lowest RPP was Beckley, WV (79.7), followed past times Rome, GA (80.7), Danville, IL (81.1), Morristown, TN (81.9), too Jonesboro, AR (82.0).No surprise, much of the variation is due to housing. Breaking it out, (look upwardly your town here!)
San Francisco-Oakland-Hayward, CA
All items 121.3
Goods 108.4
Services: Rents 183.9
Services: Other 109.6
San Jose-Sunnyvale-Santa Clara, CA
All items 122.9
Goods 108.2
Services: Rents 200.7
Services: Other 109.3
Beckley, WV
All items 79.7
Goods 92
Services: Rents 52.8
Services: Other 92.5
There is all the same a 20% departure inward the cost of goods too other services, but the variation inward rents is truly big. When yous consider that the cost of existent estate drives upwardly other costs, its number may locomote fifty-fifty larger: If the barbershop pays higher rent, too the hairdresser pays higher rent, you're going to pay to a greater extent than for haircuts. And this is only rents. Since houses receive got sparse rental markets, the truthful departure may locomote larger still. Also, rents are ofttimes controlled or poorly measured. I don't know how BLS deals amongst that.
You tin post away meet many uses for fifty-fifty to a greater extent than granular data. But since identify cost too rent are slow to get, yous powerfulness teach a expert approximation past times adding granular housing cost information to regional cost data.
There are a lot of interesting issues here.
One query it raises is the truthful pic of inequality. Poor people, particularly those who don't work, tend to alive inward low-rent areas. Relative to local prices, inequality may non locomote every bit bad every bit it seems. (I presume the BLS does something to conform rents for character of housing.)
One tin post away also imagine that congresspeople from high cost areas volition shortly enquire for higher cost of living adjustments for benefits to their constituents.
This information ought to focus to a greater extent than attending on housing provide restrictions -- the master copy argue that rents vary too thus much.
It raises some puzzles too. I respect that the marketplace position for academics gives surprisingly picayune weight to cost of living variations. If yous compare offers from a European too U.S.A. university, nobody expects yous to compare "100,000" inward each identify without converting currency. But nominal academic salaries are quite similar across chasms of cost of living. To some extent universities teach far upwardly amongst absurdly complex too inefficient housing subsidies, but that doesn't brand much feel either. I'm curious to what extent this phenomenon occurs inward other markets.
And... who knows? New information ever leads to interesting novel research. Kudos to the BEA for making this available.
Comments from people who know how this information is constructed, amongst expert parts too pitfalls, are particularly welcome.
Update
Influenza A virus subtype H5N1 colleague who knows a lot nearly these issues sent some useful information:
...it’s my agreement from conversations amongst a few people too brief reading on methodology (https://www.bea.gov/regional/pdf/RPP2015.pdf) that they are truly pretty misfortunate measures of local prices. Essentially all of the variation comes from relatively poorly measured housing prices, almost past times construction.
That’s because the exclusively local retail cost information going into the BEA indices comes from the BLS CPI data, which covers less than xxx cities (and non fifty-fifty on identical products across locations). They’re extrapolating from this pocket-size number of cities to all cities inward the U.S.A. past times only taking the nearest metropolis amongst CPI information too re-weighting it amongst local expenditures shares. So for example, in that location is no retail pricing information collected for Columbus, but they exhibit upwardly inward the BEA subway scheme expanse cost parities. So where are they getting cost information from? They only receive got the prices collected inward Cleveland (where BLS collects data) too assume that are the same inward Columbus amongst potentially slightly dissimilar weights inward the consumption basket. So fifty-fifty if in that location is broad heterogeneity across cities inward prices... this is for the most purpose non going to teach picked upwardly inward their local cost measures, since they’re imputing prices inward most cities using pricing information from other cities. Since most states receive got either 0 or 1 BLS cost collection cities, this way that only about 100% of the within-state variation inward their cost levels is coming from housing. So to only about a get-go approximation, these purchasing powerfulness indices are truly only identify cost indices since they basically aren’t using information on local prices for anything except housing.
But the housing cost information is coming from ACS amongst diverse hedonic adjustment. That is notoriously challenging, particularly across locations. It’s much easier but all the same difficult to compute identify cost changes across fourth dimension using repeat sales indices similar inwardness logic, but the housing stock is fundamentally heterogeneous across infinite which puts huge measure errors on trying to create the cost for an equivalent unit of measurement of housing across space, too thus I receive got the exact numbers in that location amongst a large grain of salt.
So overall I shout out back these indices basically only tell yous that housing is to a greater extent than expensive inward san francisco too NYC than inward oklahoma, but I shout out back their quantitative usefulness is pretty limited. I shout out back to truly mensurate cost degree differences across locations, scanner information is much to a greater extent than useful since nosotros tin post away mensurate identical products every bit good every bit production availability too varieties. (A weakness is that this can’t capture differences inward service prices across space, but it’s difficult to conform for character in that location only similar for housing, fifty-fifty if nosotros had a census of all service providers prices everywhere inward the country). Jessie Handbury too David Weinstein’s 2014 restud newspaper is the best written report I know of trying to receive got seriously measure retail cost levels across locations using that form of data. I receive got no persuasion how it lines upwardly amongst the BEA numbers.
From which I take: 1) This is really of import 2) The BLS took a useful stab at it amongst the numbers they receive got but 3) sympathise the large limitations of the BLS numbers earlier yous utilisation them 4) teach to work, big-data economists, on using scanner data, twitter feeds, amazon purchases, zillow, too everything else yous tin post away teach your hands on, to compass 21st century granular cost indices!
Update 2:
Enrico Moretti has already written a really overnice paper, Real wage inequality (Also here) adjusting inequality measures for local cost of living.
At to the lowest degree 22% of the documented growth inward college premium is accounted for past times spatial differences inward the cost of living.He creates local cost indices. He also takes on the query whether higher prices inward hot cities stand upwardly for to a greater extent than housing -- improve amenities -- or only higher prices which yous receive got to pay inward social club to operate high -productivity jobs.
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