January 2026
When comparing compensation across cities, the salary figure alone doesn't tell the whole story. The relative buying power of the U.S. dollar in a location and how far a new law graduate's paycheck will stretch is an important consideration as well. For example, a law student choosing between Washington, DC and San Francisco might wonder: Which city provides greater purchasing power? A location with stronger buying power can offer greater lifestyle flexibility, more discretionary income, and the opportunity for new lawyers to reach personal milestones, such as paying off student debt, purchasing a home, or starting a family, more quickly.
To illustrate purchasing power differentials, NALP has analyzed salary data from the Class of 2024 Employment Report and Salary Survey in conjunction with cost-of-living data from the Council for Community & Economic Research (C2ER) to rank cities based on a Buying Power Index (BPI). The BPI was calculated using New York City's Class of 2024 median private practice salary and cost of living as a benchmark. New York City's BPI is thus 1.00. BPIs for other cities demonstrate how much buying power the median law firm salary for the Class of 2024 in that location provides compared with the New York City median. Table 1 below shows the BPI calculated for 117 cities for which at least ten law firm salaries were reported for the Class of 2024, and for which cost-of-living information was available for the 2024 calendar year. The 69 cities with a BPI greater than 1.0 offer more purchasing power compared to New York City and the 47 cities with a BPI below 1.0 provide less purchasing power. Thus, in nearly 60% of cities included in the table, the buying power of the median salary exceeds that of New York City's when the relative cost of living is factored in. For example, while the median law firm salaries in Jackson, MS and Indianapolis, IN are approximately 60% of the New York City median, they provide about 50% more buying power. Similarly, the median salaries in Omaha, NE and Las Vegas, NV are less than half that of New York City's, yet their purchasing power still surpasses that of New York.
Additionally, compensation in any two cities with similar median salaries but different BPIs can be compared. For example, the median private practice salaries in San Francisco, CA and Washington, DC were both $225,000 for the Class of 2024; however, the BPI in San Francisco is 1.382 and in Washington is 1.625. This means that the Washington salary offers 18% more purchasing power than the identical salary in San Francisco [1.625/1.382] = 1.18 or 18%. Viewed the other way around, the San Francisco salary offered about 85% of the purchasing power of the Washington salary [1.382/1.625] x 100 = 85%.
Likewise, the BPI can be used to compare any salary in a listed city (not just the median) with that for New York City since the amount needed to match the purchasing power of a $225,000 New York City salary does not change. For example, in Austin, TX, a comparable level of buying power can be achieved with a salary of approximately $95,000. This means that a new law graduate earning $190,000 in Austin would have nearly double the purchasing power of a graduate earning $225,000 in New York City, as shown by the calculation: [$190,000/$95,000] = 2.0 or 100% more purchasing power.
Table 1. Class of 2024 Buying Power Index for Cities with at Least 10 Reported Law Firm Salaries
| City | Class of 2024 Median Law Firm Salary ($) | Salary ($) Required to Yield New York City Buying Power | Buying Power Index | # of Law Firm Salaries Reported |
| Houston, TX | $215,000 | $91,912 | 2.339 | 468 |
| Minneapolis, MN | 180,000 | 91,327 | 1.971 | 118 |
| Chicago, IL | 215,000 | 112,305 | 1.914 | 791 |
| Dallas, TX | 187,500 | 99,230 | 1.890 | 426 |
| Philadelphia, PA | 190,000 | 100,791 | 1.885 | 202 |
| Wilmington, DE | 190,000 | 101,767 | 1.867 | 68 |
| St. Louis, MO | 160,000 | 86,936 | 1.840 | 53 |
| Atlanta, GA | 167,500 | 93,669 | 1.788 | 290 |
| Roseland, NJ | 197,500 | 111,329 | 1.774 | 22 |
| Nashville, TN | 170,000 | 96,303 | 1.765 | 101 |
| Greenville, SC | 160,000 | 90,839 | 1.761 | 25 |
| Huntsville, AL | 155,000 | 88,595 | 1.750 | 12 |
| Austin, TX | 165,000 | 95,035 | 1.736 | 141 |
| Denver, CO | 180,000 | 105,963 | 1.699 | 158 |
| Cleveland, OH | 145,000 | 89,180 | 1.626 | 105 |
| Washington, DC | 225,000 | 138,454 | 1.625 | 922 |
| Indianapolis, IN | 135,000 | 86,644 | 1.558 | 51 |
| Santa Monica, CA | 225,000 | 145,772 | 1.544 | 29 |
| Detroit, MI | 152,500 | 100,791 | 1.513 | 32 |
| Boston, MA | 215,000 | 142,357 | 1.510 | 471 |
| Salt Lake City, UT | 160,000 | 106,353 | 1.504 | 75 |
| Jackson, MS | 130,000 | 87,424 | 1.487 | 12 |
| Los Angeles, CA | 215,000 | 145,772 | 1.475 | 674 |
| Madison, WI | 150,000 | 102,157 | 1.468 | 38 |
| Birmingham, AL | $130,000 | 89,571 | 1.451 | 78 |
| Richmond, VA | 130,000 | 91,912 | 1.414 | 55 |
| Costa Mesa, CA | 215,000 | 152,504 | 1.410 | 31 |
| Columbus, OH | 130,000 | 93,083 | 1.397 | 82 |
| Menlo Park, CA | 225,000 | 162,749 | 1.382 | 32 |
| Redwood City, CA | 225,000 | 162,749 | 1.382 | 37 |
| San Francisco, CA | 225,000 | 162,749 | 1.382 | 402 |
| Norfolk, VA | 125,000 | 91,717 | 1.363 | 12 |
| Kansas City, MO | 120,000 | 88,888 | 1.350 | 101 |
| Milwaukee, WI | 130,000 | 98,059 | 1.326 | 60 |
| Morristown, NJ | 140,000 | 106,841 | 1.310 | 10 |
| Amarillo, TX | 105,000 | 81,277 | 1.292 | 11 |
| Stamford, CT | 160,000 | 124,209 | 1.288 | 11 |
| Palo Alto, CA | 225,000 | 176,312 | 1.276 | 160 |
| Miami, FL | 147,000 | 117,866 | 1.247 | 200 |
| Wichita, KS | 106,500 | 86,644 | 1.229 | 14 |
| Fort Worth, TX | 115,000 | 93,766 | 1.226 | 45 |
| Phoenix, AZ | 125,000 | 103,719 | 1.205 | 63 |
| Omaha, NE | 105,000 | 89,668 | 1.171 | 61 |
| Charleston, WV | 96,000 | 82,058 | 1.170 | 14 |
| Newark, NJ | 130,000 | 111,329 | 1.168 | 17 |
| Chattanooga, TN | 100,000 | 86,448 | 1.157 | 11 |
| Plano, TX | 124,000 | 107,329 | 1.155 | 13 |
| Winston-Salem, NC | 105,000 | 91,132 | 1.152 | 16 |
| Las Vegas, NV | 110,000 | 96,108 | 1.145 | 51 |
| Rochester, NY | 107,500 | 96,791 | 1.111 | 18 |
| Jacksonville, FL | 100,000 | 90,644 | 1.103 | 34 |
| Louisville, KY | 100,000 | 91,815 | 1.089 | 23 |
| Cincinnati, OH | 102,000 | 93,766 | 1.088 | 45 |
| Seattle, WA | 152,500 | 141,576 | 1.077 | 118 |
| Dayton, OH | 100,000 | 94,157 | 1.062 | 13 |
| Hartford, CT | 105,000 | 98,938 | 1.061 | 31 |
| Boise, ID | 105,000 | 99,523 | 1.055 | 13 |
| Des Moines, IA | 88,000 | 83,716 | 1.051 | 19 |
| Tampa, FL | 100,000 | 95,230 | 1.050 | 94 |
| Oklahoma City, OK | 84,000 | 80,301 | 1.046 | 63 |
| Pittsburgh, PA | 100,000 | 95,815 | 1.044 | 114 |
| Columbia, SC | 90,000 | 86,936 | 1.035 | 24 |
| New Orleans, LA | 112,520 | 109,670 | 1.026 | 64 |
| San Diego, CA | 145,000 | 141,771 | 1.023 | 133 |
| Baltimore, MD | 100,000 | 97,962 | 1.021 | 30 |
| Scottsdale, AZ | 105,000 | 103,719 | 1.012 | 10 |
| San Antonio, TX | 90,000 | 88,985 | 1.011 | 51 |
| Fort Lauderdale, FL | 120,000 | 118,745 | 1.011 | 31 |
| Knoxville, TN | 85,000 | 84,302 | 1.008 | 14 |
| New York City, NY | 225,000 | 225,000 | 1.000 | 2,883 |
| Lafayette, LA | 85,000 | 85,082 | 0.999 | 11 |
| Baton Rouge, LA | 90,000 | 90,546 | 0.994 | 51 |
| Fort Wayne, IN | 87,500 | 88,107 | 0.993 | 12 |
| Virginia Beach, VA | 90,000 | 91,717 | 0.981 | 13 |
| Overland Park, KS | 87,000 | 88,888 | 0.979 | 23 |
| Orlando/Winter Park, FL | 92,000 | 94,059 | 0.978 | 62 |
| Tulsa, OK | 80,000 | 82,643 | 0.968 | 41 |
| Savannah, GA | 88,500 | 91,522 | 0.967 | 16 |
| Toledo, OH | 90,000 | 93,278 | 0.965 | 11 |
| Buffalo, NY | 90,000 | 93,376 | 0.964 | 49 |
| Spokane, WA | 90,000 | 94,059 | 0.957 | 16 |
| Raleigh, NC | 90,000 | 94,840 | 0.949 | 85 |
| Edwardsville, IL | 82,000 | 86,936 | 0.943 | 10 |
| Tyler, TX | 86,000 | 91,620 | 0.939 | 12 |
| Tallahassee, FL | 85,000 | 90,742 | 0.937 | 10 |
| Portland, OR | 105,000 | 113,768 | 0.923 | 57 |
| Little Rock, AR | 84,100 | 91,132 | 0.923 | 32 |
| Waukesha, WI | 89,750 | 98,059 | 0.915 | 10 |
| Memphis, TN | 80,000 | 87,619 | 0.913 | 19 |
| Manchester, NH | 100,000 | 109,866 | 0.910 | 19 |
| Lubbock, TX | 80,000 | 88,205 | 0.907 | 10 |
| Syracuse, NY | 90,000 | 100,401 | 0.896 | 24 |
| Newport Beach, CA | 130,000 | 145,772 | 0.892 | 31 |
| Albuquerque, NM | 82,500 | 92,693 | 0.890 | 21 |
| Albany, NY | 90,000 | 102,255 | 0.880 | 25 |
| Lincoln, NE | 80,000 | 92,010 | 0.869 | 23 |
| Glendale, CA | 125,000 | 145,772 | 0.858 | 27 |
| St. Paul, MN | 78,500 | 91,717 | 0.856 | 12 |
| Mt. Pleasant, SC | 85,000 | 99,425 | 0.855 | 19 |
| Irvine, CA | 130,000 | 152,504 | 0.852 | 111 |
| St. Petersburg, FL | 81,000 | 95,230 | 0.851 | 16 |
| Coral Gables, FL | 100,000 | 117,866 | 0.848 | 37 |
| Providence, RI | 91,500 | 109,475 | 0.836 | 24 |
| Southfield, MI | 82,500 | 100,791 | 0.819 | 16 |
| Charleston, SC | 81,250 | 99,425 | 0.817 | 40 |
| Portland, ME | 85,000 | 109,378 | 0.777 | 19 |
| Oakland, CA | 100,000 | 134,356 | 0.744 | 30 |
| North Charleston, SC | 71,400 | 99,425 | 0.718 | 12 |
| Alexandria, VA | 86,000 | 121,086 | 0.710 | 10 |
| Tacoma, WA | 87,500 | 123,916 | 0.706 | 10 |
| Long Beach, CA | 100,000 | 145,772 | 0.686 | 18 |
| Pasadena, CA | 100,000 | 145,772 | 0.686 | 21 |
| Beverly Hills, CA | 96,800 | 145,772 | 0.664 | 16 |
| Orange, CA | 100,000 | 152,504 | 0.656 | 13 |
| San Jose, CA | 115,000 | 176,312 | 0.652 | 15 |
| Honolulu, HI | 100,000 | 182,361 | 0.548 | 21 |
| Brooklyn, NY | 85,000 | 157,188 | 0.541 | 23 |
Sources: Cost-of-living information comes from the Council for Community & Economic Research (C2ER) and its calendar year 2024 Cost of Living Index. Median law firm salary data is from NALP's Jobs & JDs, Class of 2024.
Notes on Resources and Methodology for Calculating the Buying Power Index
The Buying Power Index (BPI) uses as its benchmark New York City's median starting salary and cost of living. Cost-of-living information was obtained from the Council for Community & Economic Research (C2ER) and its Cost of Living Index for the 2024 calendar year. C2ER is a non-profit professional organization of research staff of chambers of commerce, economic development organizations and agencies, and related organizations. C2ER obtains information through the participation of local Chambers of Commerce or similar organizations. C2ER uses this information to develop a cost-of-living index relative to a U.S. average of 100. The index measures differences in the costs of goods and services; however, C2ER does not attempt to incorporate tax differentials into its index. The index is not available for metropolitan areas whose Chamber(s) of Commerce do not participate. Median salary information for each city was obtained from analysis included in NALP's Jobs & JDs, Class of 2024 report.
These indices were used to create an adjusted cost-of-living index for each city, with New York City, rather than the U.S. average, set as 1.00. This adjusted index thus indicates the dollar amount equivalent to a dollar in New York City when the cost-of-living differential is considered. For example, the C2ER Cost of Living index for Indianapolis, IN is 88.8. Comparing this to New York City's index of 230.6 means that about $0.39 is needed in Indianapolis to obtain purchasing power equal to that of $1.00 in New York City (88.8/230.6 = 0.3851).
This adjusted index was then used to determine how the New York City median private practice salary would need to be scaled to provide comparable purchasing power in each city. Using the Indianapolis example, the lower cost of living means that a salary of approximately $86,650 is equivalent in purchasing power terms to the $225,000 salary in New York ($225,000 x 0.3851 ≈ $86,650).
This purchasing power equivalent was then compared to the actual median reported private practice salary in each city to determine a BPI. The closer the BPI is to 1.00, the closer the salary comes to providing purchasing power on par with New York City. Continuing with the Indianapolis example, the BPI of 1.558 means that the $135,000 median salary has about 56% more purchasing power than the New York salary ($135,000/$86,644 = 1.558).
