Base Model: CL Estimates and WTP

In the base model (equation 4.6 in Chapter 4), the effects of the main attributes in the choice experiment are measured, including full labelling, partial labelling, verification organization, presence of Omega-3 and Price. Table 5.2 presents the CL and WTP results for the base model. The value of the Log Likelihood Function is -5275.028 and the Pseudo-R2 is 0.25, indicating that the goodness of fit of this model is moderately good. All coefficients are statistically significant at the 1% level and with the expected signs. The WTP values of all attributes are also statistically significant at 1% and with the expected signs. WTP estimates

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provide a useful basis on which to compare the relative strength of preferences for the examined attributes.

Table 5.2: Base Model: CL Estimations and WTP

Variable Coefficient t-ratio WTP

($/2 Litres)

t-ratio

Price -1.461*** -47.618 - -

Function Claim .298*** 2.915 .204*** 2.913

Risk Reduction Claim .679*** 6.652 .465*** 6.694

Disease Prevention Claim .532*** 5.300 .364*** 5.299

Heart Symbol .177*** 3.901 .121*** 3.895

Government Verification .336*** 5.184 .230*** 5.173

Third Party Verification .319*** 4.969 .219*** 4.977

Omega-3 .321*** 3.512 .220*** 3.558

No Purchase -6.12*** -58.395 -4.187*** -66.370

Log Likelihood Function = -5275.028; Pseudo-R2 = 0.25

*,** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Specifically, the variables capturing full labelling: Function Claim, Risk Reduction Claim and Disease Prevention Claim, all have positive and significant coefficients which imply that consumers prefer these three types of health claims to be present on food labels compared with no health claim (base level). The variable Heart Symbol (partial labelling), has a positive and significant coefficient, indicating that consumers prefer a heart symbol to be present on Omega-3 milk products, compared with the no symbol (base level). Of interest for this study is which labelling format consumers are more likely to prefer, partial labelling or full labelling. Since the

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coefficients of the CL model are marginal utilities which are not comparable, Table 5.2 also presents the WTP results.

Comparing consumers‘ WTP for full labelling with their WTP for partial labelling in Table 5.2 shows that, on average, consumers are willing to pay an additional 12 cents for the heart symbol (partial labelling) for a two-litre carton of milk, compared with no symbol (base level). However, consumers are willing to pay 20 cents for a function claim relative to no health claim, which is almost twice the value of their WTP for a heart symbol. Consumers‘ WTP for a risk reduction claim is 47 cents, almost four times the value of their WTP for a heart symbol (12 cents), while the WTP for a disease prevention claim is 36 cents. The WTP results indicate that on average, consumers are more likely to prefer full labelling relative to partial labelling, and within full labelling, consumers are more likely to prefer a risk reduction claim.

The WTP for the variables Government Verification and Third Party Verification are both positive and significant, which implies that compared to having no verification by any outside party (the base level), consumers are willing to pay more when the labels include government or third party verifications of health claims. More specifically, consumers are willing to pay almost identical amounts: 23 cents extra for the government verification and 22 cents for the third party verification on a two-litre carton of milk, compared with no verification (base level).

The presence of Omega-3 (an alternative specific constant variable) has a positive and significant coefficient, indicating that, holding other variables constant, on average consumers prefer milk products enriched with Omega-3 compared with conventional milk. Consumers are willing to pay 22 cents more for the presence of Omega-3 per two-litre carton of milk. No Purchase (an alternative specific constant variable) has a negative and statistically significant

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coefficient, which implies that not purchasing any milk product in a given choice set, has a negative impact on consumer‘s utility. The unrealistic negative ‗WTP‘ for No Purchase indicates how much consumers dislike not purchasing any milk product. Price also has a negative and significant coefficient which is consistent with economic theory: the higher the product‘s price, the lower the consumer‘s utility.

Table 5.3 shows the WTP differences between full labelling and partial labelling, and also between the government and third party verifications. A Wald test is used to test the significance of WTP differences among attributes. The coefficients of the first three ‗WTP- difference‘ variables are positive and significant, indicating that consumers prefer a risk reduction claim relative to a disease prevention claim, they prefer a risk reduction claim relative to a function claim and they also prefer a disease prevention claim relative to a function claim. The insignificant coefficients of the last two ‗WTP-difference‘ variables show that there is no statistical difference in consumers‘ preferences for a function claim and a heart symbol, and between the two types of verification organizations (Government and Third Party).

Table 5.3: Wald Test for Difference in WTP

Variable Coefficient St. Err. T-ratio Prob.

WTPRRC - WTPDPC 0.101 0.043 2.32 0.020

WTPRRC - WTPFC 0.261 0.044 5.872 0.000

WTPDPC - WTPFC 0.160 0.043 3.704 0.000

WTPFC - WTPHS 0.083 0.074 1.123 0.262

WTPGOV – WTPTP 0.012 0.045 0.257 0.797

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According to the estimation results in Tables 5.2 and 5.3, consumers are more likely to prefer full labelling relative to partial labelling. Canadian consumers might believe that full labelling conveys more accurate health information about a product‘s health benefits than partial labelling. Recall that no statistically significant difference was found between a function claim and a heart symbol, suggesting that respondents, on average, regard a function claim such as ―Good for your heart‖, as similar to a red heart symbol. Among the three full health claims, on average, consumers prefer a risk reduction claim and a disease prevention claim relative to a function claim. This could occur if consumers believe a function claim is relatively general and fairly weak (e.g. ―this product is good for your heart‖), and perhaps does not carry enough information about the product‘s health benefit.

It was clear from the results that, on average, respondents preferred a risk reduction claim relative to a disease prevention claim, even though the latter is a stronger claim. Perhaps consumers perceive a disease prevention claim as a drug claim and are wary of this claim on a food label. Also, Canadian consumers might be more familiar with a risk reduction claim on certain functional foods in the actual market place (e.g. in Canada, products enriched with calcium has been already labelled as ‗reducing the risk of osteoporosis‘) compared with a disease prevention claim which is not permissible.

The results also show that respondents prefer to see verification of health claims, either by the government or a third party. Consumers‘ preferences between government verification (Health Canada) and a credible third party verification (Heart and Stroke Foundation) are similar, and they are willing to pay price premiums for these verifications. These results suggest that verification of health claims increases the credibility of health claims for Canadian consumers. Put differently, Canadian consumers‘ trust in functional foods could be increased by the presence

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of verifications of health claims on food labels. This has implications for how food manufacturers might best market a new functional food. However, it will remain important for government regulatory agencies to balance the needs of the food industry with the importance of protecting consumers from misleading health claims or false or unsubstantiated verifications by irresponsible third-party organizations or food companies.

As described in Chapter 4, the CL model in Table 5.2 provides a basic starting point for analysis using more advanced discrete choice models, such as the Random Parameter Logit model and the Latent Class Model. These models can explore different aspects of the consumer choice framework.