Research Article: The price is right!? A meta-regression analysis on willingness to pay for local food

Date Published: May 29, 2019

Publisher: Public Library of Science

Author(s): Iryna Printezis, Carola Grebitus, Stefan Hirsch, Zhifeng Gao.


We study the literature on willingness to pay (WTP) for local food by applying meta-regression analysis to a set of 35 eligible research papers that provide 86 estimates on consumers’ WTP for the attribute “local.” An analysis of the distribution of WTP measures suggests the presence of publication selection bias that favors larger and statistically significant results. The analyzed literature provides evidence for statistically significant differences among consumers’ WTP for various types of product. Moreover, we find that the methodological approach (choice experiments vs. other approaches) and the analyzed country can have a significant influence on the generated WTP for local.

Partial Text

Local food production systems are one of agribusinesses’ major innovations in the last decades [1: 2]. According to Mintel’s Locavore report, consumers in the U.S. are highly motivated to purchase local food, with almost 50% of them stating that they are buying local foods at least on a weekly basis [3]. Moreover, in 2019, Mintel released a report looking specifically at private label food and beverage trends in the US. Testing the priorities for food shopping Mintel asked consumers, which attributes encourage them to buy store brands. Nearly 22% mentioned locally sourced products as a reason [4]. Similarly, in Europe, in 2017, German consumers were asked how often they purchase locally produced foods. Approximately 42% stated ‘very often’, and 45% answered ‘sometimes’ [5]. These examples from across the globe show that local food purchases are a global phenomenon.

We present our meta-regression results in Tables 3 and 4. As described above, we use sqrt(n) and n as precision measures and apply three different approaches to correct for intra-study error correlations. Table 3 presents WLS results for the simple model without additional study design covariates (Eq 2). Columns (3) and (4) display the results for the main specification, WLS with cluster robust standard errors. The significant and negative coefficients of sqrt(n) and n confirm the presence of publication bias already detected by the funnel plot. This finding is consistent across the remaining methods used to control for intra-study error dependence (robust standard errors in columns (1) and (2) as well as Wild bootstrapped standard errors in columns (5) and (6)).

The body of research on local food continues to grow, with many articles investigating the premium consumers are willing to pay for local. This literature, however, provides a range of estimates for the local attribute that appears to vary significantly based on, for example, the type of “local” labeling employed [38, 48, 35, 32, 39] or the product category used [15, 26, 22, 17, 11]. Therefore, the objective of this paper is to determine a holistic estimate of the WTP for the local attribute. In order to do so, we utilize an MRA, which is a quantitative method used to evaluate the effect of study-specific characteristics on published empirical results. Collecting all relevant evidence on this topic and utilizing a systematic review methodology, we find that there is a significant mean estimate for products labeled as “local” that ranges between $1.70/lb and $2.08/lb (0.414 and 0.522 when the percentage WTP premium is used). As such, this research contributes to the broad literature that studies consumer demand for local food by deriving a proxy for “true” WTP for local.




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