Choosing brands: fresh produce versus other products.

student (0.02) (0.03) (0.04) (0.02) IG: Gender = female 0.06 *** 0.06 *** 0.06 ** 0.06 ***

(0.02) (0.02) (0.03) (0.01) Black and African 0.20 *** 0.24 *** 0.24 *** 0.20 ***

American (0.04) (0.04) (0.06) (0.03) Asian 0.04 ** 0.05 ** 0.05 * 0.03

(0.02) (0.02) (0.03) (0.02) Hispanics 0.07 ** 0.09 ** 0.09 * 0.06 *

(0.03) (0.04) (0.06) (0.03) Other races -0.03 -0.08 -0.09 -0.02

(0.06) (0.07) (0.10) (0.06) hsize: Household size -0.02 *** -0.02 *** -0.02 ** -0.02 ***

(0.01) (0.01) (0.01) (0.01) Constant 0.38 *** 0.37 *** 0.38 *** 0.35 ***

(0.06) (0.07) (0.10) (0.06) Log likelihood -163 -396 -304 -117 Pseudo R-square 0.08 0.13 0.15

Estimated Coefficients

Tobit RE-Tobit Marginal

Effects IPREF.. Strong brand 0.20 *** 0.19 *** 0.16

preference = 8,9,10 -0.02 -0.02 [0.01] IP = E: Electronic 0.06 *** 0.06 *** 0.05

(0.03) (0.02) [0.01] IP = C: Clothing 0.08 *** 0.08 *** 0.06

(0.02) (0.02) [0.01] IP = P: Packaged food 0.04 * 0.04 ** 0.05

(0.02) (0.02) [0.01] INC: Income per capita 0.002 * 0.002

(0.00) (0.00) 0.001 INC: Income square -0.00 -0.00 [0.00]

(0.00) (0.00) age: Age -0.01 *** -0.01 *

(0.00) (0.01) -0.002 [age.sup.2]: Age square 0.00 ** 0.00 * [0.00]

(0.00) (0.00) edu1: College and -0.09 *** -0.09 ** -0.07

above (0.03) (0.04) [0.01] edu2: Current college 0.04 0.03 0.03

student (0.02) (0.04) [0.00] IG: Gender = female 0.06 *** 0.06 ** 0.05

(0.02) (0.03) [0.01] Black and African 0.22 *** 0.22 *** 0.19

American (0.04) (0.06) [0.02] Asian 0.04 * 0.04 0.03

(0.02) (0.03) [0.00] Hispanics 0.08 ** 0.08 [0.06 ]

(0.04) (0.06) [0.01] Other races -0.06 -0.07

(0.07) (0.10) hsize: Household size -0.02 *** -0.02 *** -0.02

(0.01) (0.01) [0.00] Constant 0.33 *** 0.34 ***

(0.07) (0.10) Log likelihood -346 -250 Pseudo R-square 0.24 Note: Figures in parentheses are White heteroskedastic consistent standard errors and figures in brackets are standard errors of the estimated marginal effects. Single, double, or triple asterisks (*, **, ***) represent significance at the 1%, 5%, and 10 levels, respectively. Table 5. Estimation Results and Marginal Effects of the Ordered Probit Models on the Stated WTP Ranges ([IW.sub.ik])

Estimated Marginal Effects On

Coefficients The OPROBIT Model

with Brand Preference Independent P P Variables: OPROBIT OPROBIT (IW = 1) (IW = 2) IPREF Brand 0.70 *** -0.27 0.05

preference > 7 / (0.08) [0.03] [0.01] IP=E: Electronic 0.58 *** 0.34 *** -0.14 0.03

(0.07) (0.08) [0.03] [0.01] IP=C: Clothing 0.33 *** 0.33 *** -0.14 0.03

(0.08) (0.08) [0.02] [0.01] IP=P: Packaged 0.07 * 0.13 ** -0.05 0.01

food (0.06) (0.06) [0.03] [0.01] INC: Income per 0.01 0.01 -0.0016 0.0004

capita (0.01) (0.01) [INC.sup.2]: Income -0.00 -0.00 [0.00] [0.00]

square (0.00) (0.00) age: Age -0.04 * -0.04 ** 0.0036 0.0007

(0.04) (0.02) [age.sup.2]: Age square 0.00 * 0.00 * [0.01] [0.00]

(0.00) (0.00) edu1: College and -0.38 ** -0.30 * 0.12 -0.02

above

(0.17) (0.17) [0.06] [0.01] edu2: Current 0.13 0.14 -0.06 0.01

college student (0.14) (0.14) [0.05] [0.01] IG:Gender= 0.25 ** 0.26 ** -0.10 0.03

female (0.11) (0.11) [0.04] [0.01] Black & African 0.96 *** 0.93 *** -0.31 -0.02

American

(0.21) (0.22) [0.06] [0.03] Asian 0.19 * 0.15 -0.06 0.01

(0.13) (0.13) [0.05] [0.01] Hispanics 0.47 ** 0.44 ** -0.17 0.02

(0.20) (0.22) [0.08] [0.01] Other races -0.29 -0.24 0.10 -0.03

(0.61) (0.40) [0.16] [0.06] Hsize: Household -0.10 -0.06 0.02 -0.01

size (0.40) (0.04) [0.02] [0.00]

Marginal Effects On The OPROBIT Model

with Brand Preference Independent P P P P Variables: (IW = 3) (IW = 4) (IW = 5) (IW = 6) IPREF Brand 0.08 0.06 0.04 0.04

preference > 7 [0.01] [0.01] [0.01] [0.01] IP=E: Electronic 0.04 0.03 0.02 0.02

[0.01] [0.01] [0.01] [0.01] IP=C: Clothing 0.04 0.03 0.02 0.02

[0.01] [0.01] [0.01] [0.01] IP=P: Packaged 0.01 0.01 0.01 0.01

food [0.01] [0.00] [0.00] [0.00] INC: Income per 0.0004 0.0003 0.0002 0.0003

capita [INC.sup.2]: Income [0.00] [0.00] [0.00] [0.00]

square age: Age -0.001 -0.0007 -0.0005 -0.007 [age.sup.2]: Age square [0.00] [0.00] [0.00] [0.00] edu1: College and -0.04 -0.02 -0.02 -0.02

above

[0.02] [0.02] [0.01 [0.01] edu2: Current 0.02 0.01 0.01 0.01

college student [0.02] [0.01] [0.01] [0.01] IG:Gender= 0.03 0.02 0.01 0.01

female [0.01] [0.01] [0.01] [0.00] Black & African 0.09 0.08 0.07 0.09

American

[0.02] [0.02] [0.02] [0.04] Asian 0.02 0.01 0.01 0.01

[0.02] [0.01] [0.01] [0.01] Hispanics 0.05 0.04 0.03 0.03

[0.02] [0.02] [0.02] [0.02] Other races -0.03 -0.02 -0.01 -0.01

[0.05] [0.02] [0.01] [0.01] Hsize: Household -0.01 -0.00 -0.00 -0.00

size [0.00] [0.00] [0.00] [0.00] Cut Estimated Points Cut Points [C.sub.1] -0.65 -0.52

(0.43) (0.44) [C.sub.2] 0.24 0.41

(0.42) (0.44) [C.sub.3] 0.74 0.93

(0.42) (0.43) [C.sub.4] 1.11 1.32

(0.42) (0.43) [C.sub.5] 1.50 1.74

(0.41) (0.42) No. of OBS 1208 1207 Pseudo [R.sup.2] 0.05 0.07 Cut Probability Points [C.sub.1] prob([IW.sub.ik] = 1) = prob(0 [less than or

equal to] [W.sup.*.sub.ik] < [C.sub.1]) [C.sub.2] prob([IW.sub.ik] = 2) = prob([C.sub.1] [less than or

equal to] [W.sup.*.sub.ik] < [C.sub.2]) [C.sub.3] prob([IW.sub.ik] = 3) = prob([C.sub.2] [less than or

equal to] [W.sup.*.sub.ik] < [C.sub.3]) [C.sub.4] prob([IW.sub.ik] = 4) = prob([C.sub.3] [less than or