1 Data Preprocessing

A total of 98 cities exhibited some level of missing data across RTCI’s crime statistics, FBI arrest records, or demographic data from the Census Bureau.

  • 57 cities were missing monthly theft or motor vehicle theft data for more than one month.

  • 68 cities lacked yearly arrest rate data for over a year.

  • 10 cities were missing demographic information specifically for the year 2017.

Change 1: We removed 98 cities due to missing data and left with 300 cities.

98 Cities Removed Due to Missing Data
agency_state
Los Angeles, CA
Columbus, OH
Albuquerque, NM
Milwaukee, WI
Pittsburgh, PA
Kettering, OH
Worcester, MA
Lowell, MA
Cuyahoga Falls, OH
Hamilton, OH
Youngstown, OH
El Paso, TX
Lakewood, OH
Baton Rouge, LA
Framingham, MA
Lubbock, TX
Middletown, OH
Barnstable, MA
Clinton Township, MI
Medford, OR
Kalamazoo, MI
Weymouth, MA
Newark, NJ
Fort Wayne, IN
Toledo, OH
New Bedford, MA
Newton, MA
Flagstaff, AZ
Des Plaines, IL
Green Township, OH
Miami Beach, FL
Washington, DC
Atlanta, GA
Arlington Heights, IL
Bolingbrook, IL
Champaign, IL
Cicero, IL
Decatur, IL
Evanston, IL
Moline, IL
Mount Prospect, IL
Normal, IL
Oak Lawn, IL
Palatine, IL
Schaumburg, IL
Springfield, IL
Tinley Park, IL
Tucson, AZ
Chicago, IL
Skokie, IL
Lawrence, MA
Omaha, NE
New York City, NY
Bensalem, PA
Haverford, PA
Lancaster, PA
State College, PA
Glendale, AZ
Phoenix, AZ
Tempe, AZ
Antioch, CA
Bakersfield, CA
Burbank, CA
Fremont, CA
Glendale, CA
Long Beach, CA
Milpitas, CA
Riverside, CA
San Bernardino, CA
San Francisco, CA
San Jose, CA
Vallejo, CA
Flint, MI
Kentwood, MI
St Charles, MO
North Bergen Township, NJ
Mount Vernon, NY
Raleigh, NC
Euclid, OH
Allentown, PA
Lower Paxton, PA
Millcreek, PA
Bethlehem, PA
Abington, PA
Lower Merion, PA
Erie, PA
Harrisburg, PA
Reading, PA
York, PA
Allen, TX
Mission, TX
Colerain Township, OH
West Chester Township, OH
Clarksville, TN
Hendersonville, TN
Johnson City, TN
Kingsport, TN
Spring Hill, TN
Cities In the Final Panel Data
agency_state fbi_population_covered new_population_rank
Houston, TX 2304406 1
Philadelphia, PA 1550843 2
San Antonio, TX 1490047 3
San Diego, CA 1378349 4
Dallas, TX 1304989 5
Honolulu, HI 987546 6
Charlotte, NC 979304 7
Austin, TX 978816 8
Fort Worth, TX 973722 9
Indianapolis, IN 887131 10
Seattle, WA 753786 11
Denver, CO 712222 12
Nashville, TN 690495 13
Louisville, KY 669468 14
Boston, MA 642823 15
Portland, OR 626146 16
Memphis, TN 616061 17
Detroit, MI 615501 18
Baltimore, MD 565192 19
Mesa, AZ 515848 20
Kansas City, MO 509855 21
Colorado Springs, CO 489254 22
Virginia Beach, VA 453991 23
Minneapolis, MN 422341 24
Aurora, CO 396976 25
Arlington, TX 394799 26
New Orleans, LA 364197 27
Cleveland, OH 358146 28
Stockton, CA 322220 29
Lexington, KY 319994 30
Corpus Christi, TX 315340 31
Cincinnati, OH 309484 32
Greensboro, NC 303237 33
St. Paul, MN 300368 34
Durham, NC 295788 35
Lincoln, NE 293155 36
Plano, TX 291140 37
Chandler, AZ 282419 38
Chula Vista, CA 280748 39
St Louis, MO 280108 40
Gilbert, AZ 278495 41
Buffalo, NY 275922 42
Laredo, TX 256542 43
Irving, TX 255203 44
Chesapeake, VA 254051 45
Scottsdale, AZ 243644 46
Garland, TX 240051 47
Boise, ID 236949 48
Norfolk, VA 230849 49
Richmond, VA 230789 50
Spokane, WA 230648 51
Frisco, TX 228527 52
Tacoma, WA 222828 53
Mckinney, TX 212716 54
Fayetteville, NC 209262 55
Rochester, NY 208452 56
Salt Lake City, UT 206692 57
Sioux Falls, SD 206559 58
Grand Prairie, TX 205487 59
Little Rock, AR 202986 60
Amarillo, TX 201684 61
Peoria, AZ 200886 62
Knoxville, TN 198132 63
Grand Rapids, MI 196019 64
Brownsville, TX 190590 65
Providence, RI 189590 66
Akron, OH 187705 67
Chattanooga, TN 185370 68
Newport News, VA 183600 69
Salem, OR 178276 70
Eugene, OR 178191 71
Oceanside, CA 171348 72
Springfield, MO 170521 73
Fort Collins, CO 168886 74
Murfreesboro, TN 166916 75
Killeen, TX 161968 76
Surprise, AZ 159346 77
Lakewood, CO 156065 78
Denton, TX 155215 79
Springfield, MA 154218 80
Alexandria, VA 153897 81
Escondido, CA 149837 82
Bridgeport, CT 148483 83
Mesquite, TX 147926 84
Rockford, IL 145873 85
Pasadena, TX 145850 86
Waco, TX 145741 87
McAllen, TX 145684 88
Thornton, CO 143838 89
New Haven, CT 141481 90
Hampton, VA 138533 91
Stamford, CT 136512 92
Warren, MI 136121 93
Midland, TX 135253 94
Meridian, ID 135239 95
Dayton, OH 135181 96
Carrollton, TX 134261 97
Lewisville, TX 133694 98
Sterling Heights, MI 131801 99
Round Rock, TX 129898 100
Columbia, MO 129602 101
Abilene, TX 128387 102
Pearland, TX 127433 103
College Station, TX 126136 104
Rochester, MN 122035 105
Concord, CA 121331 106
Hartford, CT 120710 107
Independence, MO 120326 108
Arvada, CO 120200 109
Richardson, TX 119008 110
Cambridge, MA 118960 111
Ann Arbor, MI 118072 112
Nampa, ID 116116 113
League City, TX 115791 114
Waterbury, CT 115380 115
Manchester, NH 114963 116
Carlsbad, CA 113796 117
Westminster, CO 113660 118
Richmond, CA 113282 119
Lansing, MI 112529 120
Buckeye, AZ 112048 121
New Braunfels, TX 111942 122
Odessa, TX 111922 123
Pueblo, CO 111240 124
Tyler, TX 110824 125
Beaumont, TX 110671 126
Gresham, OR 110225 127
Goodyear, AZ 109929 128
Greeley, CO 109183 129
Brockton, MA 108938 130
Sugar Land, TX 108718 131
Hillsboro, OR 107459 132
Conroe, TX 106904 133
Dearborn, MI 106747 134
Edinburg, TX 106137 135
Bend, OR 105099 136
Centennial, CO 104724 137
Lee’s Summit, MO 104402 138
Boulder, CO 104232 139
El Cajon, CA 103569 140
South Bend, IN 102999 141
Wichita Falls, TX 102740 142
Quincy, MA 102465 143
Lynn, MA 101144 144
Suffolk, VA 100598 145
Yuma, AZ 99610 146
Tracy, CA 99347 147
Canton Township, MI 98915 148
San Angelo, TX 98642 149
Longmont, CO 98444 150
Roanoke, VA 96925 151
Beaverton, OR 96840 152
Portsmouth, VA 96649 153
Bellingham, WA 94968 154
O’Fallon, MO 94702 155
Fall River, MA 93879 156
Asheville, NC 93471 157
Temple, TX 93073 158
Livonia, MI 93042 159
Avondale, AZ 92661 160
Norwalk, CT 91639 161
Nashua, NH 91145 162
Franklin, TN 88315 163
Georgetown, TX 87871 164
Danbury, CT 87327 165
Troy, MI 87265 166
Bloomington, MN 86793 167
Duluth, MN 86570 168
Upper Darby, PA 84468 169
Baytown, TX 83809 170
Castle Rock, CO 83546 171
Westland, MI 83463 172
Warwick, RI 83369 173
Longview, TX 82981 174
Cranston, RI 82484 175
Leander, TX 82228 176
Farmington Hills, MI 82223 177
Brooklyn Park, MN 81920 178
Rapid City, SD 80850 179
Pharr, TX 80359 180
Woodbury, MN 80153 181
Shelby Township, MI 79545 182
Flower Mound, TX 79513 183
Somerville, MA 79513 183
Lynchburg, VA 79509 185
Alhambra, CA 79087 186
Parma, OH 78913 187
Mansfield, TX 78788 188
Loveland, CO 78656 189
Plymouth, MN 77576 190
Missouri City, TX 77560 191
Cedar Park, TX 77464 192
Broomfield, CO 77072 193
Lakeville, MN 76929 194
Wyoming, MI 76712 195
Scranton, PA 75687 196
Pawtucket, RI 75100 197
Southfield, MI 74960 198
New Britain, CT 74609 199
Redlands, CA 74147 200
Blaine, MN 72384 201
Harlingen, TX 71581 202
San Marcos, TX 71413 203
North Richland Hills, TX 70853 204
Maple Grove, MN 70729 205
Maricopa, AZ 70355 206
St Joseph, MO 69925 207
St. Cloud, MN 69922 208
Grand Junction, CO 69240 209
Canton, OH 69164 210
Waterford Township, MI 69153 211
Plymouth, MA 68771 212
Caldwell, ID 68731 213
Idaho Falls, ID 68662 214
Jackson, TN 68470 215
Medford, MA 68280 216
Commerce City, CO 67851 217
Haverhill, MA 67133 218
Eagan, MN 66943 219
Rowlett, TX 66671 220
Novi, MI 66482 221
Albany, GA 66281 222
Pflugerville, TX 65599 223
Oshkosh, WI 65548 224
Lorain, OH 65436 225
Victoria, TX 65298 226
West Bloomfield Township, MI 64904 227
West Hartford, CT 64423 228
Cheyenne, WY 64307 229
Malden, MA 64291 230
Kyle, TX 63931 231
Waltham, MA 63797 232
Greenwich, CT 63777 233
Burnsville, MN 63650 234
Fairfield, CT 63588 235
Casa Grande, AZ 63228 236
Brookline, MA 62639 237
Wylie, TX 62539 238
Parker, CO 62431 239
Coon Rapids, MN 62391 240
Bellevue, NE 62372 241
Taylor, MI 61781 242
Eden Prairie, MN 61645 243
Bristol, CT 61609 244
Corvallis, OR 61474 245
Dearborn Heights, MI 61420 246
Springfield, OR 61185 247
Battle Creek, MI 60969 248
Hamden, CT 60691 249
Taunton, MA 60356 250
Meriden, CT 60054 251
La Mesa, CA 60008 252
Little Elm, TX 59954 253
Blue Springs, MO 59896 254
Euless, TX 59722 255
Lake Havasu City, AZ 59720 256
Manchester, CT 59408 257
St Peters, MO 58937 258
Pocatello, ID 58390 259
Smyrna, TN 58096 260
Springfield, OH 57866 261
Marana, AZ 57718 262
Coeur D Alene, ID 57653 263
Texas City, TX 57448 264
St. Clair Shores, MI 57257 265
Royal Oak, MI 57233 266
Southaven, MS 57135 267
Revere, MA 57132 268
Albany, OR 57002 269
Bartlett, TN 56324 270
Burleson, TX 56307 271
Desoto, TX 56257 272
Tigard, OR 56142 273
Twin Falls, ID 55447 274
Port Arthur, TX 55371 275
National City, CA 55270 276
Chicopee, MA 55043 277
Apple Valley, MN 54995 278
West Haven, CT 54791 279
Peabody, MA 53841 280
Methuen, MA 53558 281
Rockwall, TX 53433 282
Elyria, OH 53024 283
Milford, CT 53011 284
Joplin, MO 52881 285
Galveston, TX 52810 286
Stratford, CT 52596 287
Dunwoody, GA 52505 288
Grand Island, NE 52264 289
Edina, MN 51980 290
Minnetonka, MN 51791 291
Collierville, TN 51686 292
Grapevine, TX 51458 293
Newark, OH 51147 294
Florissant, MO 51045 295
Harrisonburg, VA 50928 296
East Hartford, CT 50625 297
Prescott Valley, AZ 50166 298
Everett, MA 49740 299
Dublin, OH 48827 300

Change 2: We identified 20 negative values with magnitudes of -1, -2, and -3 and replaced them with 0.

Summary:

All cities in the panel:
Dimensions of dataset: 25200 x 174
Number of cities included: 300
Number of cities in the treatment group: 165
Number of cities in the control group: 135

Displayed in the map below:

State Level Online Launch Summary
state is_ever_treated online_market_launch_month launch_running_semiyear agency_count
PA 1 2019-05-01 3 3
RI 1 2019-09-01 4 4
IN 1 2019-10-01 4 2
OR 1 2019-10-01 4 11
NH 1 2019-12-01 4 2
CO 1 2020-05-01 5 19
IL 1 2020-06-01 5 1
TN 1 2020-11-01 6 10
MI 1 2021-01-01 7 23
VA 1 2021-01-01 7 12
AZ 1 2021-09-01 8 15
WY 1 2021-09-01 8 1
CT 1 2021-10-01 8 19
LA 1 2022-01-01 9 1
NY 1 2022-01-01 9 2
AR 1 2022-03-01 9 1
MD 1 2022-11-01 10 1
OH 1 2023-01-01 11 11
MA 1 2023-03-01 11 20
KY 1 2023-09-01 12 2
NC 1 2024-03-01 13 5
CA 0 NA NA 14
GA 0 NA NA 2
HI 0 NA NA 1
ID 0 NA NA 8
MN 0 NA NA 19
MO 0 NA NA 12
MS 0 NA NA 1
NE 0 NA NA 3
SD 0 NA NA 2
TX 0 NA NA 67
UT 0 NA NA 1
WA 0 NA NA 4
WI 0 NA NA 1

2 Model Results

2.1 Benchmark Semi-year

The analysis covers the period spanning three years before and six years after the state-level legalization of the online sports betting.

Effect of Online Sports Betting Legalization on Theft and Motor Vehicle Theft
Motor Vehicle Theft: All Cities Motor Vehicle Theft: Top 50 Cities Motor Vehicle Theft: 51–150 Cities Motor Vehicle Theft: 151–300 Cities Theft: All Cities Theft: Top 50 Cities Theft: 51–150 Cities Theft: 151–300 Cities
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Post Launch 34.823* 60.880 48.994* 19.934** 59.560* 107.871* 76.867* 33.885
(14.845) (47.528) (22.082) (6.236) (25.188) (38.536) (34.757) (24.811)
(0.025) (0.214) (0.037) (0.004) (0.024) (0.010) (0.037) (0.185)
Num.Obs. 3966 647 1342 1977 3966 647 1342 1977
R2 0.813 0.783 0.797 0.828 0.913 0.909 0.908 0.903
R2 Within 0.018 0.022 0.034 0.023 0.016 0.053 0.024 0.005
RMSE 70.66 111.56 72.37 35.93 132.02 126.53 135.14 128.85
Std.Errors by: state by: state by: state by: state by: state by: state by: state by: state
FE: running_semiyear X X X X X X X X
FE: agency_state X X X X X X X X

2.2 Synthetic Control

MVT: Average ATT Estimates from fect Model
ATT SE CI.lower CI.upper P.value
2.5% 43.49868 13.06478 24.76155 69.64723 0

Theft: Average ATT Estimates from fect Model
ATT SE CI.lower CI.upper P.value
2.5% 71.70892 22.03667 29.83076 115.9978 0

3 Heterogeneity

Interaction Effects on Theft Rates
Top 10 City Top 50 City Nearby Most Championships Sports League Franchise High % Age 18–30
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Post Launch 58.296* 36.303 56.261* 53.186* 66.244*
(25.430) (24.079) (25.678) (25.605) (24.481)
(0.028) (0.141) (0.036) (0.046) (0.011)
Post Launch × Top 10 City 243.156***
(22.267)
(<0.001)
Post Launch × Top 50 City Nearby 54.627**
(18.737)
(0.006)
Post Launch × Most Championships 215.471***
(48.572)
(<0.001)
Post Launch × Franchise 79.183
(53.667)
(0.150)
Post Launch × % Age 18–30 -13.812
(28.613)
(0.632)
Num.Obs. 3966 3966 3966 3966 3966
R2 0.913 0.913 0.913 0.913 0.913
R2 Within 0.017 0.020 0.020 0.019 0.016
RMSE 131.89 131.69 131.74 131.82 132.00
Std.Errors by: state by: state by: state by: state by: state
FE: running_semiyear X X X X X
FE: agency_state X X X X X
Interaction Effects on Motor Vehicle Theft Rates
Top 10 City Top 50 City Nearby Most Championships Sports League Franchise High % Age 18–30
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Post Launch 33.919* 44.172** 33.738* 19.408 14.608
(15.012) (15.813) (15.044) (13.706) (17.007)
(0.031) (0.009) (0.032) (0.166) (0.397)
Post Launch × Top 10 City 173.873***
(15.479)
(<0.001)
Post Launch × Top 50 City Nearby -21.961
(13.775)
(0.120)
Post Launch × Most Championships 70.821
(53.522)
(0.195)
Post Launch × Franchise 191.499***
(33.424)
(<0.001)
Post Launch × % Age 18–30 41.769**
(12.715)
(0.002)
Num.Obs. 3966 3966 3966 3966 3966
R2 0.814 0.814 0.813 0.825 0.815
R2 Within 0.022 0.021 0.020 0.081 0.029
RMSE 70.53 70.55 70.60 68.38 70.28
Std.Errors by: state by: state by: state by: state by: state
FE: running_semiyear X X X X X
FE: agency_state X X X X X

Summary:

In the top 10 US cities, both mvt and theft had an increase of 243 thefts and 173 mvt per 100,000 people post sports betting legalization relative to prior.

MVT:

Cities with sport league franchise in big four show a significant increase of 162 mvt per 100,000 people post relative to prior.

For mvt, area with high young population concentration (18-30) experienced an additional increase of 41 motor vehicle thefts per 100,000 people. This phenomenon does not exist in theft.

Theft:

Cities won most championships in big four show a significant increase of 215 theft crime per 100,000 people post relative to prior.

Cities within 50 km of US top 50 cities show significance for theft, increasing 55 theft per 100,000 people.

4 Regression

Effect of Post Launch on Arrest Rates by Gender
MVT: Age 18–30 Theft: Age 30–34
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Post Launch 27.823** -16.937
(7.844) (44.925)
(0.001) (0.709)
Female -52.757*** -157.223***
(5.468) (18.977)
(<0.001) (<0.001)
Post Launch × Female -27.434** -107.833*
(9.298) (48.011)
(0.006) (0.032)
Num.Obs. 3600 3600
R2 0.542 0.699
R2 Within 0.204 0.074
RMSE 61.11 345.94
Std.Errors by: state by: state
FE: agency_state X X
FE: running_year X X

Note: The whole 2024 arrest data and population are NA.

The legalization of online sports betting was associated with an 28 arrest rate increase in MVT among males aged 18 to 30. In contrast, females at this age group did not have change in MVT arrest rates during the post-legalization period relative to pre_legalization, indicating a gender-specific differential effect.

Among individuals aged 30 to 34, the arrest rate of theft was 107 units lower foe females than that of their male counterparts in the post-legalization period relative to the pre-legalization baseline.