CLOCK STAGE ANALYSIS: Auction 108 Summary (2500 MHz Band)
General Auction Statistics at End of Round
46:
County-Level Statistics at the End of Round 46:
| Qualified Bidders (Clock Phase): | 82 |
| Products with Demand > Supply: | 355 |
| Products with Demand = Supply: | 7515 |
| Products with Demand < Supply: | 147 |
|
Products with No Demand:
(subset of Products with Demand < Supply) |
147 |
| Total Provisionally Sold Products: | 7870 |
| Total Unsold Products: | 147 |
County-Level Statistics at the End of Round 46:
| Counties with Demand > Supply: | 301 |
| Counties with Demand = Supply: | 2444 |
| Counties with Demand < Supply: | 59 |
|
Counties with No Demand:
(subset of Counties with Demand < Supply) |
44 |
| Largest County (by Population) with Demand Change: | Oneida |
Nationwide Gross Proceeds by Category at End of Round
46:
Minimum Proceeds Required to Purchase One Block Nationwide at End of Round 46:
Nationwide Price Per MHz-POP Statistics at End of Round 46:(1)
Price Comparison Only in Counties with All Categories Available at End of Round 46:
| All Categories | $371,914,990 |
| Category C1: | $136,594,470 |
| Category C2: | $181,581,150 |
| Category C3: | $53,739,370 |
Minimum Proceeds Required to Purchase One Block Nationwide at End of Round 46:
| Any Category: | $56,969,240 |
Nationwide Price Per MHz-POP Statistics at End of Round 46:(1)
| Based on 2010 Census Data | Based on 2020 Census Data(2) | |
| Average Across All Categories: | $0.016260 | $0.015205 |
| Category C1: | $0.014619 | $0.013666 |
| Category C2: | $0.017374 | $0.016238 |
| Category C3: | $0.017457 | $0.016238 |
(1) The prices per MHz POP provided on this site assumes that the all POPs within these county-sized licenses are unencumbered.
As an overlay auction, this is the approach the FCC took. This is not the price per MHz-POP based on truly unencumbered POPs.
Please read the section below called "Deep Dive: Channel Availability in 2.5 GHz Overlay Licenses" for additional details on
the level of encumbrances found in each license.
As an overlay auction, this is the approach the FCC took. This is not the price per MHz-POP based on truly unencumbered POPs.
Please read the section below called "Deep Dive: Channel Availability in 2.5 GHz Overlay Licenses" for additional details on
the level of encumbrances found in each license.
(2) Because the FCC released its data for this auction using 2010 Census Data,
we use 2010 Census population estimates except where explicitly stated otherwise (as is the case here).
we use 2010 Census population estimates except where explicitly stated otherwise (as is the case here).
Price Comparison Only in Counties with All Categories Available at End of Round 46:
| Based on 2010 Census Data | |
| Category C1: | $0.015915 |
| Category C2: | $0.019899 |
| Category C3: | $0.017302 |
Snapshot of Aggregate Demand
20 Most Expensive Products by Price Per MHz-POP after Round 46: (any category)
(A Preview of Demand Analysis Below)
Price Per MHz-POP Analysis
Average Price Per MHz-POP in Each County after Round 46: (average across all categories in each county)
Average Price Per MHz-POP in Each County after Round 46: (average across all categories in each county)
Click Here for Interactive Map & Prices for Each Category
Price Per MHz-POP for All Products in 20 Largest Counties by Population after Round
46:
| fips_code | county_name | state | population | category | aggregate_demand | posted_price | supply | gross_proceeds | price_mhz_pop |
|---|---|---|---|---|---|---|---|---|---|
| 06037 | Los Angeles | CA | 9,818,605 | C3 | 1 | $900,000 | 1 | $900,000 | $0.005238 |
| 06037 | Los Angeles | CA | 9,818,605 | C1 | 1 | $2,900,000 | 1 | $2,900,000 | $0.005967 |
| 06037 | Los Angeles | CA | 9,818,605 | C2 | 1 | $2,900,000 | 1 | $2,900,000 | $0.005849 |
| 17031 | Cook | IL | 5,194,675 | C1 | 0 | $1,500,000 | 1 | $0 | $0.000000 |
| 17031 | Cook | IL | 5,194,675 | C2 | 0 | $1,500,000 | 1 | $0 | $0.000000 |
| 17031 | Cook | IL | 5,194,675 | C3 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 48201 | Harris | TX | 4,092,459 | C2 | 0 | $1,200,000 | 1 | $0 | $0.000000 |
| 48201 | Harris | TX | 4,092,459 | C3 | 0 | $400,000 | 1 | $0 | $0.000000 |
| 48201 | Harris | TX | 4,092,459 | C1 | 0 | $1,200,000 | 1 | $0 | $0.000000 |
| 04013 | Maricopa | AZ | 3,817,117 | C1 | 1 | $1,100,000 | 1 | $1,100,000 | $0.005822 |
| 04013 | Maricopa | AZ | 3,817,117 | C2 | 1 | $1,100,000 | 1 | $1,100,000 | $0.005706 |
| 04013 | Maricopa | AZ | 3,817,117 | C3 | 1 | $300,000 | 1 | $300,000 | $0.004491 |
| 06073 | San Diego | CA | 3,095,313 | C1 | 0 | $900,000 | 1 | $0 | $0.000000 |
| 06073 | San Diego | CA | 3,095,313 | C2 | 0 | $900,000 | 1 | $0 | $0.000000 |
| 06073 | San Diego | CA | 3,095,313 | C3 | 1 | $300,000 | 1 | $300,000 | $0.005538 |
| 12086 | Miami-Dade | FL | 2,496,435 | C1 | 0 | $700,000 | 1 | $0 | $0.000000 |
| 12086 | Miami-Dade | FL | 2,496,435 | C2 | 1 | $700,000 | 1 | $700,000 | $0.005552 |
| 12086 | Miami-Dade | FL | 2,496,435 | C3 | 1 | $294,000 | 1 | $294,000 | $0.006730 |
| 06065 | Riverside | CA | 2,189,641 | C2 | 1 | $600,000 | 1 | $600,000 | $0.005426 |
| 06065 | Riverside | CA | 2,189,641 | C1 | 0 | $600,000 | 1 | $0 | $0.000000 |
| 06065 | Riverside | CA | 2,189,641 | C3 | 1 | $200,000 | 1 | $200,000 | $0.005219 |
| 06071 | San Bernardino | CA | 2,035,210 | C1 | 1 | $600,000 | 1 | $600,000 | $0.005956 |
| 06071 | San Bernardino | CA | 2,035,210 | C3 | 1 | $200,000 | 1 | $200,000 | $0.005615 |
| 06071 | San Bernardino | CA | 2,035,210 | C2 | 1 | $600,000 | 1 | $600,000 | $0.005838 |
| 32003 | Clark | NV | 1,951,269 | C3 | 1 | $100,000 | 1 | $100,000 | $0.002928 |
| 32003 | Clark | NV | 1,951,269 | C2 | 1 | $500,000 | 1 | $500,000 | $0.005074 |
| 32003 | Clark | NV | 1,951,269 | C1 | 1 | $500,000 | 1 | $500,000 | $0.005177 |
| 53033 | King | WA | 1,931,249 | C2 | 1 | $500,000 | 1 | $500,000 | $0.005127 |
| 53033 | King | WA | 1,931,249 | C1 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 53033 | King | WA | 1,931,249 | C3 | 1 | $100,000 | 1 | $100,000 | $0.002959 |
| 06085 | Santa Clara | CA | 1,781,642 | C1 | 1 | $500,000 | 1 | $500,000 | $0.005669 |
| 06085 | Santa Clara | CA | 1,781,642 | C2 | 1 | $500,000 | 1 | $500,000 | $0.005557 |
| 12011 | Broward | FL | 1,748,066 | C1 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 12011 | Broward | FL | 1,748,066 | C3 | 0 | $100,000 | 1 | $0 | $0.000000 |
| 12011 | Broward | FL | 1,748,066 | C2 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 48029 | Bexar | TX | 1,714,773 | C1 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 48029 | Bexar | TX | 1,714,773 | C2 | 0 | $500,000 | 1 | $0 | $0.000000 |
| 48029 | Bexar | TX | 1,714,773 | C3 | 1 | $100,000 | 1 | $100,000 | $0.003332 |
| 25017 | Middlesex | MA | 1,503,085 | C1 | 0 | $400,000 | 1 | $0 | $0.000000 |
| 25017 | Middlesex | MA | 1,503,085 | C3 | 1 | $100,000 | 1 | $100,000 | $0.003802 |
| 25017 | Middlesex | MA | 1,503,085 | C2 | 0 | $400,000 | 1 | $0 | $0.000000 |
| 36103 | Suffolk | NY | 1,493,350 | C1 | 1 | $400,000 | 1 | $400,000 | $0.005411 |
| 36103 | Suffolk | NY | 1,493,350 | C2 | 1 | $400,000 | 1 | $400,000 | $0.005304 |
| 36103 | Suffolk | NY | 1,493,350 | C3 | 1 | $100,000 | 1 | $100,000 | $0.003826 |
| 06067 | Sacramento | CA | 1,418,788 | C2 | 0 | $400,000 | 1 | $0 | $0.000000 |
| 06067 | Sacramento | CA | 1,418,788 | C1 | 0 | $400,000 | 1 | $0 | $0.000000 |
| 12099 | Palm Beach | FL | 1,320,134 | C3 | 1 | $100,000 | 1 | $100,000 | $0.004329 |
| 12099 | Palm Beach | FL | 1,320,134 | C1 | 1 | $300,000 | 1 | $300,000 | $0.004591 |
| 12099 | Palm Beach | FL | 1,320,134 | C2 | 1 | $300,000 | 1 | $300,000 | $0.004500 |
| 26125 | Oakland | MI | 1,202,362 | C3 | 1 | $100,000 | 1 | $100,000 | $0.004753 |
| 26125 | Oakland | MI | 1,202,362 | C1 | 1 | $300,000 | 1 | $300,000 | $0.005041 |
| 26125 | Oakland | MI | 1,202,362 | C2 | 1 | $300,000 | 1 | $300,000 | $0.004941 |
| 12095 | Orange | FL | 1,145,956 | C1 | 1 | $300,000 | 1 | $300,000 | $0.005289 |
| 12095 | Orange | FL | 1,145,956 | C2 | 1 | $300,000 | 1 | $300,000 | $0.005184 |
| 06013 | Contra Costa | CA | 1,049,025 | C1 | 1 | $300,000 | 1 | $300,000 | $0.005777 |
| 06013 | Contra Costa | CA | 1,049,025 | C2 | 1 | $300,000 | 1 | $300,000 | $0.005663 |
20 Most Expensive Counties by Price Per MHz-POP after Round
46: (ave. for all categories)
| fips_code | county_name | population | price_mhz_pop |
|---|---|---|---|
| 48443 | Terrell | 984 | $1.280055 |
| 46021 | Campbell | 1,466 | $1.114046 |
| 46049 | Faulk | 2,364 | $0.960867 |
| 49009 | Daggett | 1,059 | $0.945894 |
| 46089 | McPherson | 2,459 | $0.923745 |
| 46107 | Potter | 2,329 | $0.759709 |
| 60040 | Swains Island | 17 | $0.750939 |
| 46045 | Edmunds | 4,071 | $0.721031 |
| 20017 | Chase | 2,790 | $0.706719 |
| 29103 | Knox | 4,131 | $0.701297 |
| 40025 | Cimarron | 2,475 | $0.701139 |
| 69120 | Tinian | 3,136 | $0.618758 |
| 20111 | Lyon | 33,690 | $0.574354 |
| 28055 | Issaquena | 1,406 | $0.552647 |
| 69100 | Rota | 2,527 | $0.516296 |
| 46129 | Walworth | 5,438 | $0.497523 |
| 20195 | Trego | 3,001 | $0.481825 |
| 35006 | Cibola | 27,213 | $0.471614 |
| 40139 | Texas | 20,640 | $0.469652 |
| 20031 | Coffey | 8,601 | $0.468031 |
20 Most Expensive Products by Price Per MHz-POP after Round 46: (any category)
| fips_code | county_name | state | population | category | aggregate_demand | posted_price | supply | gross_proceeds | price_mhz_pop |
|---|---|---|---|---|---|---|---|---|---|
| 48443 | Terrell | TX | 984 | C3 | 1 | $51,000 | 1 | $51,000 | $2.961672 |
| 60040 | Swains Island | AS | 17 | C3 | 1 | $500 | 1 | $500 | $1.680672 |
| 49009 | Daggett | UT | 1,059 | C2 | 2 | $85,000 | 1 | $85,000 | $1.589394 |
| 46021 | Campbell | SD | 1,466 | C3 | 1 | $36,900 | 1 | $36,900 | $1.438316 |
| 28055 | Issaquena | MS | 1,406 | C2 | 2 | $85,000 | 1 | $85,000 | $1.197133 |
| 46021 | Campbell | SD | 1,466 | C2 | 2 | $85,000 | 1 | $85,000 | $1.148137 |
| 48443 | Terrell | TX | 984 | C2 | 1 | $51,000 | 1 | $51,000 | $1.026322 |
| 29087 | Holt | MO | 4,912 | C3 | 2 | $85,000 | 1 | $85,000 | $0.988832 |
| 46049 | Faulk | SD | 2,364 | C1 | 1 | $115,000 | 1 | $115,000 | $0.982755 |
| 29103 | Knox | MO | 4,131 | C3 | 2 | $70,000 | 1 | $70,000 | $0.968289 |
| 46021 | Campbell | SD | 1,466 | C1 | 1 | $70,000 | 1 | $70,000 | $0.964626 |
| 46049 | Faulk | SD | 2,364 | C2 | 2 | $115,000 | 1 | $115,000 | $0.963294 |
| 46089 | McPherson | SD | 2,459 | C1 | 1 | $115,000 | 1 | $115,000 | $0.944787 |
| 48443 | Terrell | TX | 984 | C1 | 1 | $46,000 | 1 | $46,000 | $0.944403 |
| 46089 | McPherson | SD | 2,459 | C2 | 2 | $115,000 | 1 | $115,000 | $0.926079 |
| 20017 | Chase | KS | 2,790 | C1 | 2 | $127,000 | 1 | $127,000 | $0.919590 |
| 17171 | Scott | IL | 5,355 | C3 | 2 | $85,000 | 1 | $85,000 | $0.907029 |
| 46107 | Potter | SD | 2,329 | C3 | 1 | $36,900 | 1 | $36,900 | $0.905355 |
| 20003 | Anderson | KS | 8,102 | C3 | 2 | $127,000 | 1 | $127,000 | $0.895722 |
| 46049 | Faulk | SD | 2,364 | C3 | 1 | $36,900 | 1 | $36,900 | $0.891951 |
Deep Dive: Channel Availability in 2.5 GHz Overlay Licenses
The FCC is selling county-sized overlay licenses in the 2.5 GHz (2496–2690 MHz) band in this auction. In each county, up to three categories of licenses will be made available. Category C1 licenses total 49.5 MHz in size, currently consisting of nine 5.5 MHz channels. Category C2 licenses total 50.5 MHz in size, currently consisting of twenty channels between 0.33 MHz, 5 MHz and 6 MHz in size. Category C3 licenses total 17.5 MHz in size, consisting of three 0.33 MHz-channels and three 5 MHz-channels. The 5 MHz-channels are discontiguous from the 0.33 MHz-channels in these Category C3 licenses.
The FCC is selling these county-sized overlay licenses in each category unless the current incumbents cover 100% of the area of the county. The FCC considers these licenses as "fully-encumbered" and not for sale. Roughly 72% of the U.S. population will have at least one overlay license available for sale in this auction. However, as overlay licenses, winning bidders may not get full access to these spectrum licenses. Because incumbents still have a right to operate in these bands, the winning bidders will either have to avoid and protect incumbent operations or negotiate for their removal. This is why this auction is sometimes called a "white space" auction and the FCC calls these "encumbered" licenses.
The FCC has provided very nice maps of the current incumbents in each category of the 2.5 GHz band and the number of channels encumbered. We show them below, but interactive versions these maps and helpful legends can be found on the FCC's Auction 108 Mapping Tool.
We took this excellent data (including tribal applications) to do our own GIS analysis. In particular, we intersected the shape files of the licenses held by incumbents in each category and the shape files created by the tribal applications with 2 x 2 km cell population data (2010 Census)(3) to determine the population-weighted average number of channels in each county license that would be encumbered. We used the population-weighted number of channels encumbered to classify licenses in each category into "encumbrance classifications" that we can then use in more granular pricing analysis.(4)
It should be noted that encumbrance classifications are conservative because we assume that every tribal application will be granted regardless of current status. It should also be noted that winner of these overlay licenses in this auction made available in this auction have the right to negotiate with incumbents to further reduce the size of these encumbrances.
More specifically, these encumbrance classifications are:
To help visualize the level of encumbrances in each county based on population (which the FCC maps did not analyze), we have mapped this data into an interactive map which allows you to see the population-weighted number of channels that are encumbered for each category in a county-sized license area. Keeping in mind the caveats above (including about different licenses sizes as noted in footnote 4), these visualizations make clear those areas where wireless operations may not be possible for the winners of these overlay licenses.
Below is some analysis based on these encumbrance classifications. While not a recalculation of MHz-POPs, the data demonstrates how level of impairment can impact pricing.
Gross Proceeds and Price Per MHz-POP By Encumbrance Classification after Round 46:
Tracking Auction 108's Progress Toward Completion after Round 46
Comparing Auction 108's Progress to Prior FCC Auctions after Round 46
The FCC is selling these county-sized overlay licenses in each category unless the current incumbents cover 100% of the area of the county. The FCC considers these licenses as "fully-encumbered" and not for sale. Roughly 72% of the U.S. population will have at least one overlay license available for sale in this auction. However, as overlay licenses, winning bidders may not get full access to these spectrum licenses. Because incumbents still have a right to operate in these bands, the winning bidders will either have to avoid and protect incumbent operations or negotiate for their removal. This is why this auction is sometimes called a "white space" auction and the FCC calls these "encumbered" licenses.
The FCC has provided very nice maps of the current incumbents in each category of the 2.5 GHz band and the number of channels encumbered. We show them below, but interactive versions these maps and helpful legends can be found on the FCC's Auction 108 Mapping Tool.
FCC Encumbrance Maps
Here is the FCC's map of Category C1 (or Block 1) licenses color coded by the number of channels encumbered by current incumbents.
Here is the FCC's map of Category C2 (or Block 2) licenses color coded by the number of channels encumbered by current incumbents.
Here is the FCC's map of Category C3 (or Block 3) licenses color coded by the number of channels encumbered by current incumbents.
Finally, the FCC also provided information regarding pending Rural Tribal Applications, whose applications if accepted, would further reduce the spectrum available in counties that cover tribal areas.
We took this excellent data (including tribal applications) to do our own GIS analysis. In particular, we intersected the shape files of the licenses held by incumbents in each category and the shape files created by the tribal applications with 2 x 2 km cell population data (2010 Census)(3) to determine the population-weighted average number of channels in each county license that would be encumbered. We used the population-weighted number of channels encumbered to classify licenses in each category into "encumbrance classifications" that we can then use in more granular pricing analysis.(4)
(3) Using 2020 Census data, we found that the percentages are very similar so we stuck with the same data as the FCC is using.
(4) Because not all channels are of the same MHz in size, using the FCC's shape files, which are classified by number of channels encumbered, does not perfectly translate to MHz-POPs. However, when I applied the unencumbered channel percentages to MHz-POPs, the resulting nationwide number was in line with the 16.5% "white space" discount that FCC previously applied to spectrum in this band for spectrum screen purposes. Because of this fact, and the fact that I am using these encumbrance classifications strictly for categorical reasons rather than specific calculations, this approach should be sufficient.
It should be noted that encumbrance classifications are conservative because we assume that every tribal application will be granted regardless of current status. It should also be noted that winner of these overlay licenses in this auction made available in this auction have the right to negotiate with incumbents to further reduce the size of these encumbrances.
More specifically, these encumbrance classifications are:
| Category | Min % of Channels Encumbered (weighted by POPs) | Max % of Channels Encumbered (weighted by POPs) | Encumbrance Classification |
| Category C1 | 0% | 0% | C1 - 0 |
| Category C1 | > 0% | < 50% (or 4.5 channels) | C1 - 50 |
| Category C1 | >= 50% (or 4.5 channels) | < 75% (or 6.75 channels) | C1 - 75 |
| Category C1 | >= 75% (or 6.75 channels) | <= 100% (or 9.0 channels) | C1 - 100 |
| Category C2 | 0% | 0% | C2 - 0 |
| Category C2 | > 0% | < 50% (or 10.0 channels) | C2 - 50 |
| Category C2 | >= 50% (or 10.0 channels) | < 75% (or 15.0 channels) | C2 - 75 |
| Category C2 | >= 75% (or 15.0 channels) | <= 100% (or 20.0 channels) | C2 - 100 |
| Category C3 | 0% | 0% | C3 - 0 |
| Category C3 | > 0% | < 50% (or 3.0 channels) | C3 - 50 |
| Category C3 | >= 50% (or 3.0 channels) | < 75% (or 4.5 channels) | C3 - 75 |
| Category C3 | >= 75% (or 4.5 channels) | <= 100% (or 6.0 channels) | C3 - 100 |
To help visualize the level of encumbrances in each county based on population (which the FCC maps did not analyze), we have mapped this data into an interactive map which allows you to see the population-weighted number of channels that are encumbered for each category in a county-sized license area. Keeping in mind the caveats above (including about different licenses sizes as noted in footnote 4), these visualizations make clear those areas where wireless operations may not be possible for the winners of these overlay licenses.
Below is some analysis based on these encumbrance classifications. While not a recalculation of MHz-POPs, the data demonstrates how level of impairment can impact pricing.
Gross Proceeds and Price Per MHz-POP By Encumbrance Classification after Round 46:
| Encumbrance Classification | Gross Proceeds | Price MHz POP |
|---|---|---|
| C1 - 0 | $18,814,770 | $0.051351 |
| C1 - 50 | $50,830,150 | $0.032917 |
| C1 - 75 | $22,343,540 | $0.016067 |
| C1 - 100 | $44,606,010 | $0.007382 |
| C2 - 0 | $22,440,920 | $0.067307 |
| C2 - 50 | $70,026,530 | $0.047736 |
| C2 - 75 | $30,896,520 | $0.023815 |
| C2 - 100 | $58,217,180 | $0.007917 |
| C3 - 0 | $13,869,850 | $0.044101 |
| C3 - 50 | $20,165,480 | $0.038735 |
| C3 - 75 | $4,971,390 | $0.026615 |
| C3 - 100 | $14,732,650 | $0.007164 |
Additional Round-by-Round Analysis
3D Map of Gross Proceeds by Category in Each County after Round
46
Click Here for Interactive 3D Map
Treemap of Gross Proceeds in Highest Grossing Counties (Above $500K Threshold) after Round
46: (sum across all categories)
Demand Analysis
Excess or Net Demand (Demand-Supply) in Each County after Round
46:
(across all categories in each county)
(across all categories in each county)
Click Here for Interactive Map & Category Data
Change in Demand in Round
46 from Prior Round in Each County:
(across all categories in each county)
(across all categories in each county)
Click Here for Interactive Map & Category Data
20 Counties with the Largest Excess Demand after Round
46:
(across all categories in each county)
(across all categories in each county)
| fips_code | county_name | population | aggregate_demand | supply | excess_demand |
|---|---|---|---|---|---|
| 66010 | Guam | 159,358 | 6 | 3 | 3 |
| 69110 | Saipan | 48,220 | 6 | 3 | 3 |
| 21035 | Calloway | 37,191 | 6 | 3 | 3 |
| 21083 | Graves | 37,121 | 6 | 3 | 3 |
| 21157 | Marshall | 31,448 | 6 | 3 | 3 |
| 02130 | Ketchikan Gateway | 13,477 | 6 | 3 | 3 |
| 54075 | Pocahontas | 8,719 | 6 | 3 | 3 |
| 21039 | Carlisle | 5,104 | 6 | 3 | 3 |
| 21105 | Hickman | 4,902 | 6 | 3 | 3 |
| 69120 | Tinian | 3,136 | 6 | 3 | 3 |
| 36019 | Clinton | 82,128 | 5 | 3 | 2 |
| 36033 | Franklin | 51,599 | 5 | 3 | 2 |
| 01031 | Coffee | 49,948 | 5 | 3 | 2 |
| 01047 | Dallas | 43,820 | 5 | 3 | 2 |
| 36031 | Essex | 39,370 | 5 | 3 | 2 |
| 01039 | Covington | 37,765 | 5 | 3 | 2 |
| 01109 | Pike | 32,899 | 5 | 3 | 2 |
| 28001 | Adams | 32,297 | 4 | 2 | 2 |
| 01099 | Monroe | 23,068 | 5 | 3 | 2 |
| 56041 | Uinta | 21,118 | 5 | 3 | 2 |
20 Counties with Largest Absolute Change in Demand after Round
46
from Prior Round:
(across all categories in each county)
from Prior Round:
(across all categories in each county)
| fips_code | county_name | population | aggregate_demand | demand_change |
|---|---|---|---|---|
| 02130 | Ketchikan Gateway | 13,477 | 6 | 3 |
| 36019 | Clinton | 82,128 | 5 | 2 |
| 19089 | Howard | 9,566 | 5 | 2 |
| 36065 | Oneida | 234,878 | 4 | 1 |
| 25001 | Barnstable | 215,888 | 4 | 1 |
| 23031 | York | 197,131 | 4 | 1 |
| 53005 | Benton | 175,177 | 4 | 1 |
| 19163 | Scott | 165,224 | 3 | 1 |
| 33017 | Strafford | 123,143 | 4 | 1 |
| 30063 | Missoula | 109,299 | 4 | 1 |
| 41019 | Douglas | 107,667 | 4 | 1 |
| 19061 | Dubuque | 93,653 | 3 | -1 |
| 19155 | Pottawattamie | 93,158 | 4 | 1 |
| 24001 | Allegany | 75,087 | 4 | 1 |
| 41035 | Klamath | 66,380 | 4 | 1 |
| 36043 | Herkimer | 64,519 | 4 | 1 |
| 41011 | Coos | 63,043 | 4 | 1 |
| 55111 | Sauk | 61,976 | 4 | 1 |
| 72005 | Aguadilla | 60,949 | 3 | 1 |
| 33001 | Belknap | 60,088 | 4 | 1 |
Change in Aggregate Demand in 100 Largest Counties by Round: (across all categories)
(Double click on legend to switch to a different county)
(Double click on legend to switch to a different county)
20 Counties with Largest Absolute Change in Demand in Category C1 after Round
46
from Prior Round:
from Prior Round:
| fips_code | county_name | category | population | aggregate_demand | demand_change |
|---|---|---|---|---|---|
| 25001 | Barnstable | C1 | 215,888 | 2 | 1 |
| 23031 | York | C1 | 197,131 | 2 | 1 |
| 53005 | Benton | C1 | 175,177 | 2 | 1 |
| 19163 | Scott | C1 | 165,224 | 2 | 1 |
| 33017 | Strafford | C1 | 123,143 | 2 | 1 |
| 41019 | Douglas | C1 | 107,667 | 2 | 1 |
| 19155 | Pottawattamie | C1 | 93,158 | 2 | 1 |
| 36019 | Clinton | C1 | 82,128 | 2 | 1 |
| 24001 | Allegany | C1 | 75,087 | 2 | 1 |
| 41035 | Klamath | C1 | 66,380 | 2 | 1 |
| 41011 | Coos | C1 | 63,043 | 2 | 1 |
| 55111 | Sauk | C1 | 61,976 | 2 | 1 |
| 72005 | Aguadilla | C1 | 60,949 | 2 | 1 |
| 33001 | Belknap | C1 | 60,088 | 2 | 1 |
| 55135 | Waupaca | C1 | 52,410 | 2 | 1 |
| 36033 | Franklin | C1 | 51,599 | 2 | 1 |
| 72023 | Cabo Rojo | C1 | 50,917 | 2 | 1 |
| 49003 | Box Elder | C1 | 49,975 | 2 | 1 |
| 33003 | Carroll | C1 | 47,818 | 2 | 1 |
| 49021 | Iron | C1 | 46,163 | 2 | 1 |
20 Counties with Largest Absolute Change in Demand in Category C2 after Round
46
from Prior Round:
from Prior Round:
| fips_code | county_name | category | population | aggregate_demand | demand_change |
|---|---|---|---|---|---|
| 30063 | Missoula | C2 | 109,299 | 2 | 1 |
| 49003 | Box Elder | C2 | 49,975 | 1 | -1 |
| 19191 | Winneshiek | C2 | 21,056 | 2 | 1 |
| 49041 | Sevier | C2 | 20,802 | 1 | -1 |
| 35053 | Socorro | C2 | 17,866 | 1 | -1 |
| 02130 | Ketchikan Gateway | C2 | 13,477 | 2 | 1 |
| 49027 | Millard | C2 | 12,503 | 1 | -1 |
| 19089 | Howard | C2 | 9,566 | 2 | 1 |
| 08113 | San Miguel | C2 | 7,359 | 2 | -1 |
| 08065 | Lake | C2 | 7,310 | 2 | 1 |
| 29171 | Putnam | C2 | 4,979 | 2 | 1 |
| 69120 | Tinian | C2 | 3,136 | 2 | 1 |
| 38037 | Grant | C2 | 2,394 | 2 | 1 |
| 49033 | Rich | C2 | 2,264 | 1 | -1 |
| 38065 | Oliver | C2 | 1,846 | 2 | 1 |
| 38083 | Sheridan | C2 | 1,321 | 2 | 1 |
20 Counties with Largest Absolute Change in Demand in Category C3 after Round
46
from Prior Round:
from Prior Round:
| fips_code | county_name | category | population | aggregate_demand | demand_change |
|---|---|---|---|---|---|
| 36065 | Oneida | C3 | 234,878 | 2 | 1 |
| 19061 | Dubuque | C3 | 93,653 | 1 | -1 |
| 36019 | Clinton | C3 | 82,128 | 2 | 1 |
| 36043 | Herkimer | C3 | 64,519 | 2 | 1 |
| 08037 | Eagle | C3 | 52,197 | 1 | -1 |
| 49043 | Summit | C3 | 36,324 | 1 | -1 |
| 08097 | Pitkin | C3 | 17,148 | 1 | -1 |
| 32013 | Humboldt | C3 | 16,528 | 1 | -1 |
| 35057 | Torrance | C3 | 16,383 | 2 | 1 |
| 02130 | Ketchikan Gateway | C3 | 13,477 | 2 | 1 |
| 19133 | Monona | C3 | 9,243 | 1 | -1 |
Tracking Auction 108's Progress Toward Completion after Round 46
NOTE: Because the prior non-logarithmic chart is somewhat skewed by the large excess demand in the early rounds, we have repeated the chart above taking the log (base 10) of the values on both axeses:
NOTE: This next chart looks at changes in excess demand in dollars after removing the impact of round price increases. Please note negative scale. Also, this chart is not relevant for Round 1 because there are no prior rounds.
Comparing Auction 108's Progress to Prior FCC Auctions after Round 46
The chart below tracks auction progress (using the metric of excess demand as a percent of aggregate demand) against other recent prior FCC auctions.
NOTE: Any comparison between Auction 97 (the AWS-3 auction and an SMRA auction) and the other auctions shown (which are all clock auctions) needs several important caveats. SMRAs have a fundamentally different structures from clocks auctions (e.g., SMRAs allow bidders to bid for specific licenses whereas in clock auctions you bid for generic blocks; SMRAs determine provisional winners after reach round whereas clock auctions just determine aggregate demand at the end of each round). Participants in an SMRA also face different rules regarding the exiting of accepted bid (e.g., a provisionally winning bidder in an SMRA is allowed to submit a withdrawal bid subject to a withdrawal penalty whereas in a clock auction a bidder may not withdraw a bid once demand equals supply). Finally, in SMRAs, bidders do not need to affirmatively bid in every round for licenses that they have provisionally won as they will have an opportunity to bid again in the next round if their provisionally winning bid is outbid in the current round. These differences make any direct comparisons difficult. Nevertheless, with all these caveats in mind and using a simple moving average to “smooth” the variations in demand that you see from round-to-round in an SMRA, I thought that it might still be interesting to make a comparison between Auction 97 and this auction.
NOTE: Any comparison between Auction 97 (the AWS-3 auction and an SMRA auction) and the other auctions shown (which are all clock auctions) needs several important caveats. SMRAs have a fundamentally different structures from clocks auctions (e.g., SMRAs allow bidders to bid for specific licenses whereas in clock auctions you bid for generic blocks; SMRAs determine provisional winners after reach round whereas clock auctions just determine aggregate demand at the end of each round). Participants in an SMRA also face different rules regarding the exiting of accepted bid (e.g., a provisionally winning bidder in an SMRA is allowed to submit a withdrawal bid subject to a withdrawal penalty whereas in a clock auction a bidder may not withdraw a bid once demand equals supply). Finally, in SMRAs, bidders do not need to affirmatively bid in every round for licenses that they have provisionally won as they will have an opportunity to bid again in the next round if their provisionally winning bid is outbid in the current round. These differences make any direct comparisons difficult. Nevertheless, with all these caveats in mind and using a simple moving average to “smooth” the variations in demand that you see from round-to-round in an SMRA, I thought that it might still be interesting to make a comparison between Auction 97 and this auction.
Fun: Comparing Current County Prices to Predicted Prices at the PEA-Level Based on Prior FCC Auctions after Round
46
Using this Overprice Ratio, we can then identify the licenses that represent the best "deals" at the close of each round. (5)
Deals Following Round 46: Most Underpriced Counties (Above 500K in Population) Relative to their Predicted Prices at the PEA-LEVEL:
In the bubble graph below, we attempt to track how current prices of the 100 largest counties mapped into their corresponding PEAs (on a price per MHz pop basis) compare to their "Predicted Price" based on past FCC auctions. To accomplish this comparison, we need to introduce the concept of the "Overprice Ratio". This Overprice Ratio is the current price of each county's PEA divided by the Predicted Price for that PEA.
This Predicted Price for any county license is calculated by first identifying its relevant PEA and then classifying each PEA into its relevant REAG (an FCC licensing schema that divides the country into 6 regions) and then identifying a "Reference Market" for that REAG. Typically, the Reference Market for each REAG is the largest PEA by population (with the exception of the Southeast REAG where we selected Atlanta as its Reference Market rather than Washington DC, which we have reclassified as being in the Northeast REAG). For those PEAs that are Reference Markets, we use the New York PEA (the "Nationwide Reference Market") as their Reference Market. We then take the current price for each Reference Market and multiply it by the historical ratio of auction prices between each PEA and its Reference Market to get the Predicted Price.
The y-axis on the left shows the log (base 10) of the "Overprice Ratio." We take the log of the Overprice Ratio to lessen the impact of outliers. By definition, the New York PEA (shown in the graph as the biggest bubble in dark blue below), as the Nationwide Reference Market, will always remain at y=0 (the horizontal green line in the graph below). The y-axis on the right side of the graph tracks the current price for New York PEA (based on all the counties that fall into it) after the latest round and is adjusted so that New York PEA's price always remains on the green horizontal line in the graph below.
The x-axis shows aggregate demand in each county (regardless of category) after the latest round. There is a vertical green line where aggregate demand equals 3. This the maximum number of licenses available for sale in each county. Thus, if the bubble shows up to the right of this green vertical line, aggregate demand in this county is greater than supply. The bubbles representing the counties are sized based on their population and color-coded based on the PEA that they fall in.
Example:
Pick San Diego County. It falls into the San Diego PEA (which only has one county in the PEA ). Its Reference Market is Los Angeles.
Suppose
San Diego County current aggregate demand = 10
San Diego current price (average across categories) = $0.50
Los Angeles current price (average across categories) = $0.75
Historical ratio (San Diego/Los Angeles) = 1.09784
Compute
San Diego current Predicted Price = $0.75 * 1.09784 = $0.82338
San Diego Overprice Ratio = $0.50 / $0.82338 = 0.607253
San Diego logarithmic-scaled Overprice Ratio = Log10(0.607253) = -0.21663
Interpretation
In the logarithmic-scaled chart below, San Diego would be represented by a bubble with coordinates (x,y) = (10,-0.21663). That means San Diego is underpriced. All bubbles with negative values are underpriced; conversely, all bubbles with positive values are overpriced with respect to their Reference Market's current price. Before the Reference Market's price converges, any underpriced PEA is a valid prediction due to the non-decreasing price property; however, the converse may not be true until the Reference Market's price converges.
To get the complete list of Reference Markets, Predicted Prices and Overprice Ratios for any county see the table at the bottom of this web page.
This Predicted Price for any county license is calculated by first identifying its relevant PEA and then classifying each PEA into its relevant REAG (an FCC licensing schema that divides the country into 6 regions) and then identifying a "Reference Market" for that REAG. Typically, the Reference Market for each REAG is the largest PEA by population (with the exception of the Southeast REAG where we selected Atlanta as its Reference Market rather than Washington DC, which we have reclassified as being in the Northeast REAG). For those PEAs that are Reference Markets, we use the New York PEA (the "Nationwide Reference Market") as their Reference Market. We then take the current price for each Reference Market and multiply it by the historical ratio of auction prices between each PEA and its Reference Market to get the Predicted Price.
The y-axis on the left shows the log (base 10) of the "Overprice Ratio." We take the log of the Overprice Ratio to lessen the impact of outliers. By definition, the New York PEA (shown in the graph as the biggest bubble in dark blue below), as the Nationwide Reference Market, will always remain at y=0 (the horizontal green line in the graph below). The y-axis on the right side of the graph tracks the current price for New York PEA (based on all the counties that fall into it) after the latest round and is adjusted so that New York PEA's price always remains on the green horizontal line in the graph below.
The x-axis shows aggregate demand in each county (regardless of category) after the latest round. There is a vertical green line where aggregate demand equals 3. This the maximum number of licenses available for sale in each county. Thus, if the bubble shows up to the right of this green vertical line, aggregate demand in this county is greater than supply. The bubbles representing the counties are sized based on their population and color-coded based on the PEA that they fall in.
Example:
Pick San Diego County. It falls into the San Diego PEA (which only has one county in the PEA ). Its Reference Market is Los Angeles.
Suppose
San Diego County current aggregate demand = 10
San Diego current price (average across categories) = $0.50
Los Angeles current price (average across categories) = $0.75
Historical ratio (San Diego/Los Angeles) = 1.09784
Compute
San Diego current Predicted Price = $0.75 * 1.09784 = $0.82338
San Diego Overprice Ratio = $0.50 / $0.82338 = 0.607253
San Diego logarithmic-scaled Overprice Ratio = Log10(0.607253) = -0.21663
Interpretation
In the logarithmic-scaled chart below, San Diego would be represented by a bubble with coordinates (x,y) = (10,-0.21663). That means San Diego is underpriced. All bubbles with negative values are underpriced; conversely, all bubbles with positive values are overpriced with respect to their Reference Market's current price. Before the Reference Market's price converges, any underpriced PEA is a valid prediction due to the non-decreasing price property; however, the converse may not be true until the Reference Market's price converges.
To get the complete list of Reference Markets, Predicted Prices and Overprice Ratios for any county see the table at the bottom of this web page.
Using this Overprice Ratio, we can then identify the licenses that represent the best "deals" at the close of each round. (5)
(5) Because these deals are based on historical comparisons at the PEA-Level, some caution is necessary. For example, a county that sits at the edge of a large PEA may look underpriced when comparing to the predicted price for the larger PEA in which it resides.
Deals Following Round 46: Most Underpriced Counties (Above 500K in Population) Relative to their Predicted Prices at the PEA-LEVEL:
| County | County Name | FIPS Code | Population | Supply | Aggregate Demand | Gross Proceeds | County Price MHz Pop | PEA | PEA Name | PEA Price MHz Pop | Reference PEA | Reference PEA Name | PEA Predicted Price | Overprice Ratio (Log Base 10) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TN-037 | Davidson | 47037 | 626,681 | 2 | 2 | $620,000 | $0.009893 | PEA032 | Nashville, TN | $0.010578 | PEA030 | Kansas City, MO | $0.067278 | -0.803476 |
| TX-121 | Denton | 48121 | 662,614 | 3 | 3 | $358,000 | $0.004598 | PEA008 | Dallas, TX | $0.005329 | PEA001 | New York, NY | $0.010061 | -0.275984 |
| TX-085 | Collin | 48085 | 782,341 | 2 | 2 | $400,000 | $0.005113 | PEA008 | Dallas, TX | $0.005329 | PEA001 | New York, NY | $0.010061 | -0.275984 |
| CA-111 | Ventura | 06111 | 823,318 | 3 | 3 | $668,000 | $0.006905 | PEA002 | Los Angeles, CA | $0.005944 | PEA001 | New York, NY | $0.009428 | -0.200332 |
| CA-029 | Kern | 06029 | 839,631 | 3 | 3 | $706,000 | $0.007156 | PEA002 | Los Angeles, CA | $0.005944 | PEA001 | New York, NY | $0.009428 | -0.200332 |
| CA-037 | Los Angeles | 06037 | 9,818,605 | 3 | 3 | $6,700,000 | $0.005807 | PEA002 | Los Angeles, CA | $0.005944 | PEA001 | New York, NY | $0.009428 | -0.200332 |
| CA-065 | Riverside | 06065 | 2,189,641 | 3 | 2 | $800,000 | $0.005373 | PEA002 | Los Angeles, CA | $0.005944 | PEA001 | New York, NY | $0.009428 | -0.200332 |
| CA-071 | San Bernardino | 06071 | 2,035,210 | 3 | 3 | $1,400,000 | $0.005854 | PEA002 | Los Angeles, CA | $0.005944 | PEA001 | New York, NY | $0.009428 | -0.200332 |
| FL-086 | Miami-Dade | 12086 | 2,496,435 | 3 | 2 | $994,000 | $0.005855 | PEA009 | Miami, FL | $0.005753 | PEA011 | Atlanta, GA | $0.008479 | -0.168415 |
| FL-099 | Palm Beach | 12099 | 1,320,134 | 3 | 3 | $700,000 | $0.004513 | PEA009 | Miami, FL | $0.005753 | PEA011 | Atlanta, GA | $0.008479 | -0.168415 |
| NC-183 | Wake | 37183 | 900,993 | 2 | 2 | $400,000 | $0.004440 | PEA045 | Raleigh, NC | $0.004881 | PEA011 | Atlanta, GA | $0.007070 | -0.160890 |
| AL-073 | Jefferson | 01073 | 658,466 | 3 | 3 | $260,000 | $0.003360 | PEA040 | Birmingham, AL | $0.004871 | PEA011 | Atlanta, GA | $0.007015 | -0.158463 |
| OH-061 | Hamilton | 39061 | 802,374 | 2 | 2 | $400,000 | $0.004985 | PEA025 | Cincinnati, OH | $0.005619 | PEA003 | Chicago, IL | $0.007458 | -0.123010 |
| FL-095 | Orange | 12095 | 1,145,956 | 2 | 2 | $600,000 | $0.005236 | PEA013 | Orlando, FL | $0.004758 | PEA011 | Atlanta, GA | $0.005827 | -0.087988 |
| FL-105 | Polk | 12105 | 602,095 | 2 | 2 | $200,000 | $0.003322 | PEA013 | Orlando, FL | $0.004758 | PEA011 | Atlanta, GA | $0.005827 | -0.087988 |
| FL-009 | Brevard | 12009 | 543,376 | 2 | 2 | $200,000 | $0.003681 | PEA013 | Orlando, FL | $0.004758 | PEA011 | Atlanta, GA | $0.005827 | -0.087988 |
| AZ-013 | Maricopa | 04013 | 3,817,117 | 3 | 3 | $2,500,000 | $0.005574 | PEA015 | Phoenix, AZ | $0.005574 | PEA002 | Los Angeles, CA | $0.006681 | -0.078666 |
| NV-003 | Clark | 32003 | 1,951,269 | 3 | 3 | $1,100,000 | $0.004798 | PEA026 | Las Vegas, NV | $0.005131 | PEA002 | Los Angeles, CA | $0.005903 | -0.060932 |
| CA-073 | San Diego | 06073 | 3,095,313 | 3 | 1 | $300,000 | $0.005538 | PEA018 | San Diego, CA | $0.005538 | PEA002 | Los Angeles, CA | $0.006211 | -0.049750 |
| GA-121 | Fulton | 13121 | 920,581 | 3 | 3 | $510,000 | $0.004715 | PEA011 | Atlanta, GA | $0.006974 | PEA001 | New York, NY | $0.007787 | -0.047924 |
Download to Excel or View Details on All Counties After Round
46
Selected County Details(6)
(6) Calculations in the table below are based on 2010 Census figures unless designated with a "2020" in the column title.
| County | County Name | FIPS | Category | Population | Population 2020 | Bidding Units | Supply | Aggregate Demand | Excess Demand | Demand Change | Posted Price | Gross Proceeds | Price Per MHz POP (for product) | Price Per MHz POP 2020 (for product) | Encumbrance Class | PEA | PEA Name | Price Per MHz POP for PEA | Reference Market | Reference Market Name | Predicted Price for PEA | Overprice Ratio (Log Base10) |
|---|