Product-level data from the Nevo (2000) study of the US ready-to-eat cereal market. Contains 2256 product-market observations across 94 markets (47 cities x 2 quarters).
Format
A data frame with 2256 rows and the following columns:
- market_ids
Market identifier (city-quarter combination)
- city_ids
City identifier
- quarter
Quarter (1 or 2)
- product_ids
Product identifier within market
- firm_ids
Firm identifier
- brand_ids
Brand identifier
- shares
Market share
- prices
Product price (dollars per serving)
- sugar
Sugar content (grams per serving)
- mushy
Mushiness indicator (0/1)
- demand_instruments0
Excluded demand-side instrument 0
- demand_instruments1
Excluded demand-side instrument 1
- demand_instruments2
Excluded demand-side instrument 2
- demand_instruments3
Excluded demand-side instrument 3
- demand_instruments4
Excluded demand-side instrument 4
- demand_instruments5
Excluded demand-side instrument 5
- demand_instruments6
Excluded demand-side instrument 6
- demand_instruments7
Excluded demand-side instrument 7
- demand_instruments8
Excluded demand-side instrument 8
- demand_instruments9
Excluded demand-side instrument 9
- demand_instruments10
Excluded demand-side instrument 10
- demand_instruments11
Excluded demand-side instrument 11
- demand_instruments12
Excluded demand-side instrument 12
- demand_instruments13
Excluded demand-side instrument 13
- demand_instruments14
Excluded demand-side instrument 14
- demand_instruments15
Excluded demand-side instrument 15
- demand_instruments16
Excluded demand-side instrument 16
- demand_instruments17
Excluded demand-side instrument 17
- demand_instruments18
Excluded demand-side instrument 18
- demand_instruments19
Excluded demand-side instrument 19
References
Nevo, A. (2000). A Practitioner's Guide to Estimation of Random-Coefficients Logit Models of Demand. Journal of Economics & Management Strategy, 9(4), 513-548.
Examples
nevo_products <- load_nevo_products()
head(nevo_products)
#> market_ids city_ids quarter product_ids firm_ids brand_ids shares
#> 1 C01Q1 1 1 F1B04 1 4 0.012417212
#> 2 C01Q1 1 1 F1B06 1 6 0.007809387
#> 3 C01Q1 1 1 F1B07 1 7 0.012994511
#> 4 C01Q1 1 1 F1B09 1 9 0.005769961
#> 5 C01Q1 1 1 F1B11 1 11 0.017934141
#> 6 C01Q1 1 1 F1B13 1 13 0.026601892
#> prices sugar mushy demand_instruments0 demand_instruments1
#> 1 0.07208794 2 1 -0.2159728 0.04057341
#> 2 0.11417849 18 1 -0.2452393 0.05474226
#> 3 0.13239066 4 1 -0.1764587 0.04659597
#> 4 0.13034408 3 0 -0.1214013 0.04876037
#> 5 0.15482331 12 0 -0.1326114 0.03962835
#> 6 0.13704921 14 0 -0.1534998 0.04298842
#> demand_instruments2 demand_instruments3 demand_instruments4
#> 1 -3.247948 -0.523937690 -0.23246005
#> 2 -19.832461 -0.180519690 0.01468859
#> 3 -2.878531 -0.284219000 -0.21553691
#> 4 -2.059918 -0.328412260 -0.22206995
#> 5 -6.137598 -0.138625100 -0.18936521
#> 6 -8.417332 0.007829087 -0.13850121
#> demand_instruments5 demand_instruments6 demand_instruments7
#> 1 0.0068326605 3.1397395 -0.57478633
#> 2 0.0007988026 0.2876539 0.03293960
#> 3 -0.0318693280 2.8862741 -0.74976495
#> 4 -0.0314740400 4.4531096 0.25567529
#> 5 -0.0437471020 -3.5546508 0.13882114
#> 6 -0.0210582270 -2.7594799 0.05020052
#> demand_instruments8 demand_instruments9 demand_instruments10
#> 1 0.2062201 0.1774656 2.1163580
#> 2 0.1051208 -0.2875618 -7.3740909
#> 3 -0.4789565 0.2147389 2.1878721
#> 4 -0.4729673 0.3560980 2.7045762
#> 5 -0.6886784 0.2602726 1.2612419
#> 6 -0.2734440 0.1273060 0.3375543
#> demand_instruments11 demand_instruments12 demand_instruments13
#> 1 -0.15470824 -0.0057964065 0.01453801
#> 2 -0.57641176 0.0129908540 0.07614324
#> 3 -0.20734643 0.0035092777 0.09178117
#> 4 0.04074801 -0.0037242656 0.09473168
#> 5 0.03483558 -0.0005676374 0.10245147
#> 6 0.02351037 0.0002637777 0.08627983
#> demand_instruments14 demand_instruments15 demand_instruments16
#> 1 0.12624398 0.06734464 0.06842261
#> 2 0.02973565 0.08786672 0.11050060
#> 3 0.16377308 0.11188073 0.10822551
#> 4 0.13527378 0.08809001 0.10176745
#> 5 0.13063951 0.08481820 0.10107461
#> 6 0.07233581 0.02225051 0.10564387
#> demand_instruments17 demand_instruments18 demand_instruments19
#> 1 0.03480046 0.12634612 0.03548368
#> 2 0.08778380 0.04987192 0.07257905
#> 3 0.08643905 0.12234707 0.10184248
#> 4 0.10177748 0.11074119 0.10433204
#> 5 0.12516923 0.13346381 0.12111110
#> 6 0.11603699 0.09965064 0.10572660