Are food prices in position to make us eat healthier? The effects of taxes and subsidies on consumer’s food choices

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Are food prices in position to make us eat

healthier? The effects of taxes and

subsidies on consumer’s food choices

Lyuboslav Ivaylov Ivanov

University of Groningen | Faculty of Economics and Business | MSc Marketing Management Supervisor: Prof. Dr. Koert Van Ittersum

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ABSTRACT

Exhibiting healthy and varied diet is imperative to one’s health and well-being. Diet-related diseases such as diabetes and obesity are at all time high and present an ever growing threat in the developed world, especially among people with lower socio-economic status. This is large part due to the overconsumption of cheaper, sugar rich and calorie-dense unhealthy foods that offer little to no nutritious value on the one hand and the higher cost of foods that constitute healthier diets. As prices are one of the most important determinants for food choices, fiscal measures, such as imposing taxes on unhealthy foods and providing subsidies for healthier alternatives, are one approach aimed at improving the quality of people’s diet. This research investigates the effects taxes and subsidies have on consumer’s choices for healthy products and the moderating effect income level has on that relationship.

Using an online survey, the study simulated a shopping trip across sixteen common product categories in a 2 (taxes on unhealthy foods vs. no taxes) by 2 (subsidies on healthy foods vs. no subsidies) design. Furthermore income level was measured for each respondent in order to observe if it moderates the effect of our variables. The results show that only taxing unhealthy foods did not result in higher purchases of healthy foods, whereas only subsidizing the healthier foods did increase the share of healthy products participants purchased. Contrary to our expectations presenting taxes alongside subsidies did not produce significant increase in the amount of healthy products purchased. Additionally, income level had no moderating effect on the strength of taxes and subsidies, as both high and low income level consumers purchased similar number of healthy foods.

The findings of this study are in favor of subsidizing the healthier products as a mean to increase consumer’s healthiness of shopping basket.

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PREFACE

The master thesis is the final step in obtaining a Master’s degree at the University of Groningen. The topic is written within the field of Marketing Management and focuses upon consumer well-being and how fiscal measures can help consumers obtain a healthier diet.

I want to express my gratitude towards several people during this process. First, I want to thank my family as they have always supported me. Next, special gratitude goes to my supervisor, Prof. Dr. Koert Van Ittersum, with whom I had the chance not only to discuss relevant to the topic ideas, but also provided me to invaluable lessons in work organization along the way. Last, but certainly not least I want to express my deep gratitude to my friends and close-ones which were with me during those times.

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1. Introduction

The overconsumption of foods, especially those high in their sugar count and saturated fats are responsible to the growing trend of chronic diseases such as cardiovascular problems, diabetes and obesity (WHO, 2009). Obesity is recognized as the single most serious health threat in the developed world according to the World Health Organization (WHO, 2000). As a clinical condition, obesity is defined as the excess fat reserves accumulated in one’s body to an extent that can have negative health effects (James et al. 2000). The magnitude of the issue is revealed when estimates indicate that around one billion people worldwide are overweight, with as much as 400 million of which are obese (Finucane et al. 2011) and obesity rates are continuously rising (Ogden et al., 2012, Flegal et al. 2002).

Generally gaining weight can be due to variety of factors including inherited biological traits e.g simply being prone to weight gain, but the most common factor for being overweight is behavioral: bad eating habits related to unhealthy food and overconsumption. (M.J.Morris et al.2015).

One of the main ways, by which a person can influence his body weight, apart from engaging in physical activity, is by exhibiting a varied and healthy diet, an imperative for good health (WHO, 2004). Food consumption can be manifested in variety of ways, from eating out for to preparing a home cooked meal. With the recent economic recession people have begun to place more emphasis on the value of their money and as a result going out for a dinner has undergone a significant decline when compared to shopping at a grocery store (Sloot., Food Retail Outlook, EFMI 2015) which is just one of the reasons that places store bought food as the number one calorie intake provider for most people. Having the biggest contribution to one’s consumption, thorough understanding of consumer’s groceries shopping behavior and the determinants of their choices for healthy food is needed.

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healthier food options, are aimed at changing consumption patterns at aggregate level and operate on the basis of economic theory, specifically the law of demand and supply (Caraher, 2005; Giesen et al., 2012). Even though research in fiscal measures as incentives to improving people’s diet is still emerging, there is growing evidence of its effectiveness (Waterlander et al.2013, Giesen et al. 2012; Nedekoorn et al. 2011).

The objective of this paper is to shed more light on consumer’s shopping behavior with a focus on their healthy food choices, as the overall healthiness of the shopping basket serving as the main point of interest. The main goal of the study is to find whether consumer’s choices for healthy foods can be influenced by different fiscal measures such as taxes imposed upon unhealthy products or subsidies granted for healthier alternatives and whether their income level moderates that relationship. Both taxes on unhealthy products and subsidies for healthier alternatives are included in the study as the aim is not only to investigate their effects individually, but also their simultaneous effect on consumer’s shopping behavior. The focus on income level is introduced in order reflect real life situation more accurately- that is products that constitute a healthier diet are usually more expensive and not available to everyone (Mooney, 1990; Lang & Caraher, 1998; Rose, 2010; Jetter et al. 2006).

The paper employs a 2x2 between subjects design (taxes on unhealthy foods vs. no taxes and subsidies for healthier foods/no subsidies) in a virtual shopping environment across sixteen product categories, each category consisting of three levels of products: relatively unhealthy choice, neutral and relatively healthy alternative of the same product type. The main research questions that the paper sets to answer are:

1. Can taxing unhealthy foods be used as an effective measure to promote healthier food choices?

2. Can subsidizing healthy foods be used as an effective measure to promote healthier food choices?

3. Is the effect of presenting taxed unhealthy products alongside subsidized healthier products stronger influencer on consumer’s choices compared to their individual effects?

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7 1.2 Contribution and Relevance

This paper makes contribution to academic literature by investigating the consumer’s shopping behavior under the influence of different price levels due to taxation and subsidization and integrating the moderating effect of income level in the construct. The paper also takes into account the matter of “tax salience” and “subsidy salience”—that is consumers are aware that the reasons for the price adjustments on the products is due to health and diet related taxes or subsidies. To the author’s knowledge, this is the first study investigating the effects of taxes and subsidies on food purchases that presents them as such rather than price discounts or price increases.

1.3 Thesis Outline

The rest of the paper is organized as follows: First off, a theoretical background detailing the variables and hypothesis formulation is given. In the third chapter the methodology of the study is introduced. Next, chapter four presents the results of the study. Lastly, the paper concludes with a discussion of the results and future research directions.

2. Theoretical Background

This chapter contains the literature review for the main variables of the study: (2.1) taxation, (2.2) subsidies and (2.3) the role of income level, followed by the (2.4) conceptual model of the paper.

2.1 Taxation

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activities that can generate negative externalities such as the environmental pollution from gasoline powered cars or the cigarette smoke that can be inhaled from non-smoker1

(

Agnar, 2008

).

In the context of this paper a special attention is given to the so called sin tax which is a sumptuary tax2 levied on goods and services such as tobacco, fast foods and soft drinks, coffee, gambling among others.

The focus in this paper falls onto taxation on foods and drinks that can be considered as unhealthy for one’s consumption needs, as the overconsumption of those foods that are high in their sugar count and saturated fats are found to contribute to obesity (Ludwig et al. 2001, WHO, 2009). The most important way in which taxation can be utilized lies in its effect of food prices, one of the key determinants for food choices, especially among low income level customers (Steenhuis, Waterlander,& de Mul, 2011).

Health related food taxation and subsidization have been discussed as potential strategies to combat weigh related problems and diseases (McCarthy, 2004).The notion of taxation as a restrictive measure lies within the concept that increasing the price of a commodity, all else being equal, should decrease consumption of that commodity, a term known as same-price elasticity (Bickel, Madden, and Petry, 1998). In fact, taxes on goods like alcohol and tobacco have been successful in reducing their consumption ().

The concept of taxation on unhealthy food products and its subsequent effects on purchasing and consumption behavior has also received attention in the academic literature. Epstein et al. (2010) carried an experimental purchasing study that used common food categories, taxing high-calorie product categories such as hot dogs, French fries and M&M’s among others and subsidizing the low-calorie products like eggs, nonfat yoghurt and skim milk. The results indicated that taxation is useful in reducing overall energy (calories) intake, whereas subsidizing healthier options led to increased calorie count. Another study examined the effects taxes have on lunch menu offerings, reporting that increasing the prices of the unhealthy menu by 150% results in significant decrease in purchasing that option (Giesen et al., 2012). Nederkoorn et al. (2011) reports similar findings of decreased calorie intake when energy-dense foods are being taxed by using a virtual-based shopping environment, however the study also reports that people substitute the taxed unhealthy foods with cheaper alternatives that do not fall under taxation. Product specific taxation effects have also received academic attention, namely the product category of sugar sweetened beverages (SSB). The main reason is that consumption of sweetened beverages comprises the biggest share of

1

See Sandmo, Agnar (2008). "Pigouvian taxes,"

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energy intake amongst US population (Duffey & Popkin, 2007) and their established link to obesity (Vartanian et al., 2007).

T. Andreyeva et al. (2011) estimate that taxes on sweetened beverages can decrease caloric intake by 25% if consumers don’t substitute the taxed products with other unhealthy alternatives. Another study carried out in a virtual-shopping store carried out by Waterlander et al. (2014) reports that increasing the prices on SSB due to taxes significantly decreases their consumption when compared to a control condition where prices are not adjusted.

In conclusion the results of taxation on unhealthy (or calorie-dense) products indicate that taxation can be an effective mechanism for decreasing calorie intake among consumers. One key difference is that most of the studies that examine taxation effects, as remarked by Edwards (2011) do not take substitution of products into account—that is they present taxed options alongside relatively unhealthy items that are not subjected by tax which can cause customers to pick the untaxed alternative, which was supported by the study of Nederkoorn et al. (2011). Another one is the issue of ‘tax salience’ (Chetty et al. 2009) as discussed by Waterlander et al. (2014). What this means is that customers are presented with the higher priced unhealthy products but are unaware of the reasons behind it. In this paper respondents are made aware that some products have their prices adjusted due to tax on unhealthy foods, and taxes are presented as an additive to the regular price, to emphasis their effects.

Based on the previous findings about taxation effects and the adoption of tax salience this paper hypothesizes that:

H1: Taxing unhealthy food decreases the purchasing of those options amongst consumers, thus resulting in an increase on the healthiness of the shopping basket.

2.2 Subsidies

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paper is towards subsidies aimed at the consumer, or consumption subsidies, specifically in the context of healthier food choices that have the goal of reducing acquisition costs of them.

Food subsidy systems have been introduced to varied success in the past as part of governmental measures to provide essential foods to the population in need (Gutner et al, 1999). Some of the countries that have food subsidy systems include Egypt, Mexico and Bangladesh among others (Gutner et al., 1999; Lustig, 1986; Adams Jr. 1998). For example Egypt included four basic food products as part of their subsidy system – bread, wheat flour, sugar and oil (Ali & Adams Jr., 1996). Ali & Adams Jr. (1996) report that even though Egypt’s food subsidy system does not target specific population, i.e. the poor it is essentially “self-targeted” because it includes “inferior foods” 3

and that the food subsidy system has a positive effect on income distribution. Similar is the situation of food subsidies in Mexico— predominately basic, cheap, calorie-dense foods such as tortillas, flour, oil and beans are being subsidized in order to ensure that the population has access to them (Lustig, 1986).

So far the above-mentioned programs emphasize basic food options which are almost exclusively calorie-dense (white breads, wheat flour, vegetable oils) and can easily be considered as unhealthy to one’s diet (McCarthy, 2004). As discussed above one of the objectives of the paper is to examine the effects of subsidization on foods that are relatively healthier when compared to the basic alternatives. The rationale behind subsidizing those options is to promote their selection, especially amongst low-income level consumers since these foods are generally more expensive compared to the basic unhealthy alternatives (Jetter & Cassidy, 2006) especially with regards to the fact that there has been an established link between low-income levels and obesity (Drewnowski and Specter, 2004).

With regards to academic literature few studies examine the effects of subsidies on healthier food options upon consumer’s choices. A study carried out by Ni Mhurchu et al.(2010) investigated the effects price discounts (i.e.. subsidies) and nutritional knowledge have on consumer’s choices for healthy foods, by the use of randomized control trial in eight New Zealand supermarkets. The results indicated that while nutritional knowledge does not have a significant effect on nutrients purchased, the effects of price discounts (subsidies) can be a viable tool to promote healthier diets as it led to significant increase in purchase (Ni Mhurchu et al.2010). More recent study reports that healthy foods that are given a subsidy (or a price

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discount) of 50% are purchased significantly more than healthy options that have 25% of their prices subsidized or no subsidy at all (Waterlander et al. 2012). The authors compared different levels of subsidies on healthy foods (50%, 25% discounts and no) and different levels of taxes on unhealthy food choices (5%,10%,25% increase) using a virtual grocery store that carried out 38 product categories (Waterlander et al. 2012). While the most heavily subsidized healthy options were purchased significantly more than the other options, the shopping basket of consumers in that condition contained the highest number of calories, whereas the effects of taxation on unhealthy food choices were insignificant (Waterlander et al. 2012). A study carried by the same authors a year later, this time examining the effects of subsidization alongside health labels confirms the findings—heavily promoting healthy foods leads to higher purchases, but also to increases the overall calorie count, while health labeling had no effect on food choices (Waterlander et al. 2013)

Single product categories subsidies have also been investigated. French et al. (2001) investigated the effect different price discounts have on low-fat snacks distributed via vending machine. The study reports that price reduction with 10%, 25 % and 50% all result in increased sales of the snacks, with the highest discount rate being the most effective at promoting healthier purchases (French et al. 2001).

Even though academic literature is scarce on the subject matter, there is evidence that subsidizing healthier food options via price discounts is an effective way to promote them. Nevertheless, potential drawback of subsidizing healthier foods are that the consumers could use the money they have saved due to the price discounts and use them to buy more products, that could be unhealthy (Giesen et al., 2012), or just buy more of the subsidized products which increases the overall calorie count, and paradoxically can lead to obesity (Epstein et al.2010). In order to tackle those issues and better examine the effects of subsidies, the study focuses on single choices amongst a product category, i.e. a consumer can pick only one item per product category, thus this paper hypothesizes that:

H2: Subsidies on healthy foods would result in higher purchasing of those items, increasing the healthiness of the shopping basket.

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12 H3: The presence of both subsidies and taxes has a stronger impact on the healthiness of the shopping basket, compared to the case where only taxes or subsidies are present.

2.3 Income level

One of the many negative implications of the recent economic recession was and still is the phenomenon of ‘belt tightening’ or simply reduction in spending that many consumers had to undergo in order to cope with their financial situation. However, the negative implications extend further than just the reduction in spending, as academic research suggest that the rising costs of food due to the financial crisis reduced the access to nutritious food and led to the deterioration of consumer’s diets, jeopardizing their health (Brinkman et al., 2010). Especially vulnerable to those threats are individuals and households of lower socio-economic status (SES) for which the access to healthy and nutritious is already limited (Mooney, 1990). Furthermore academic evidence establishes a link between poverty level and obesity rates, caused by exhibiting unhealthy diet (Drewnowski and Specter, 2004). By setting up budgets such as one designated to grocery shopping, consumers can tackle this issue and make sure that their spending is optimal. Generally speaking a budget allocates a portion of one’s income for precise use (Bénabou and Tiróle, 2004)

One concept that can be used in aid of that is by employing specifically designated budgets for their various expenses by the means of mental budgeting (Heath and Soll, 1996). By mental budgeting Heath and Soll (1996) state that consumers set up different budgets for various expense accounts—e.g household purchases, clothing, food, etc. Once the budget for a certain category is near depletion, consumers refrain themselves from further spending. The authors propose that mental budgeting is comprised of two parts: “setting a budget” and “expense tracking”

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no need for. Tracking expenses is the second concept in the mental accounting model, which in the consumer context differs from that of an investor’s context where expenses are salient and rightfully categorized (Heath 1995). Consumers on the other hand have to rely on self-discipline and control to record and assign their expenses.

As mentioned above, mental budgeting is one way that households can utilize in order to cope with their financial situation. Of course, various households and consumer have different purchasing power- while someone that fall into the low-income category would have smaller explicit budget, those of higher income levels could have less strict budgeting rules apply to them (Thaler, 1999).

In the context of our paper grocery shopping is one of the most important accounts that should be assigned a budget. That holds especially true for lower-income households and consumers who have to optimize their value-for-money purchasing behavior as expenditures for nutritious and healthier diet can constitute up to 40% of low-income consumers (Jetter and Cassady, 2006)

The focus of this paper falls upon customer’s monthly household income, used as a proxy measurement for shopping on a budget, as a moderator of the strength of taxes and subsidies have on consumer’s choices for healthy foods. Taxation especially is reasoned to distress lower income households and act as a restraint against unhealthy purchases, as their grocery expenditures constitute a larger share of all household expenditures, compared to higher income households (Edwards, 2011; Drewnowski and Specter, 2004). Furthermore, subsidizing healthier foods is also reasoned to be primarily effective among lower-income groups, as those groups have the largest share of diet-related disease and are often times financially restrained in taking up healthier diets (Waterlander et al., 2012; Darmon and Drewnowski, 2008). As healthier foods are generally more expensive than the basic alternatives (Jetter et al. 2006) and purchasing power is a function of income this paper hypothesizes that:

H4a: Taxes on unhealthy food has a stronger effect on the healthiness of shopping basket, when consumer’s income level is low.

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14 2.4 Conceptual model

The conceptual model of the paper, illustrating the relationship between the main variables is depicted below.

Figure 1. Conceptual model

3. Methodology

In the following section the research design of the paper will be presented. The chapter starts with the (3.1) research method, followed by the description of the (3.2) study design, (3.3) procedure and (3.4) measurement approach. The chapter concludes with a description of the (3.5) data collection method. The analysis and results of the study are presented in the next chapter.

3.1 Research Method

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taxation) by 2 (subsidies on healthy products versus no subsidies) between participants design. Participants in the online survey are randomly assigned to a condition, with the same probabilities of ending up in one of the four conditions (Aronson et al. 1998). Participants are asked to shop for groceries in an online store environment.

3.2 Study design

In order to observe the effects that taxation and subsidies have on consumer’s food choices a simulated online shopping environment was created consisting of sixteen common product categories. The product categories (see table 1.) are partially based on USDA’s Thrifty Meal Plan (usda.gov, Jetter & Cassady, 2006), alongside with product categories that are not included in the plan, to encompass more products, thus suiting it better for an online shop simulation (Van Ittersum et al. 2013). Each of the sixteen product categories contains three variations of the same product – relatively healthy and unhealthy versions of the product, coupled with a neutral option amongst them. Rationale for the inclusion of the neutral option is to enrich and balance out the product options for the consumers, avoiding the contrasting scenario of only relatively healthy versus relatively unhealthy products. Differentiating between the levels of healthiness of the different products was done with the help of the UK Food Standards Agency Traffic Lights system guidelines (Food Standards Agency,eatwell.gov.uk/trafficlights) which details the necessary levels of fats, saturated fats, salts and sugars a product should contain to be given green, yellow or red symbol, indicating its respectful level of healthiness (Food Standards Agency). Some of the product categories do not adhere to those guidelines, most notably the cookies, peanut butter and ice cream, so for those product categories the distinction is based on their intrinsic nutritional information differences.

Product type:

Product categories Unhealthy Neutral Healthy

Bread* Great value white Bread Great Value Brown Bread Great Value Whole Wheat Bread

Milk Great Value Fat 2% Milk Great Value Low Fat 1%

Milk Great Value 0% Fat Milk

Yoghurt* Mountain High Original _{Plain Style yoghurt} Mountain High Plain _{Lowfat Yoghurt} Mountain High Plain Lowfat _Yoghurt Cookies* _{Chocolate Chip Cookie}Chips Ahoy! Chunky _{Chocolate Chip Cookie}Chips Ahoy! Original Chips Ahoy! Oatmeal Chocolate _{Chip Cookie} Cold Cereal* Great Value Sugar _{Frosted Flakes} Great Value Corn Flakes Great Value Bran Flakes

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16 Peanut Butter Skippy Creamy Peanut Skippy Natural Creamy Skippy Reduced Fat Creamy

Chips* Pringles Original Potato _Crisps Pringles Original Reduced _{Fat Potato Crisps} Pringles Original Fat Free Potato _Crisps

Cola Pepsi Cola Pepsi Next Pepsi Diet

Ice cream * Ben & Jerry’s Chocolate _{Ice Cream} Ben & Jerry's Greek _{Frozen Yoghurt} Ben & Jerry's Frozen Yoghurt _{Half Baked}

Macaroni & Cheese * Hospitality Mac & _{Cheese Dinner}

Kraft Premium Three Cheese Macaroni & Cheese Dinner

Annie’s Homegrown Organic Classic Mild Cheddar Macaroni & Cheese

Spaghetti* Great Value Spaghetti Great Value Whole Wheat

Spaghetti Barilla Whole Grain Spaghetti

Pasta Sauce Newman's Own Pasta _Sauce _{Traditional Sauce}Bertolli Organic _{Gina Rispoli All Natural Sauce} Beef Patties Ground Beef Patties _{73% Lean} Ground Beef Patties 85% _Lean Ground Beef Patties 93% Lean

Salad Dressing _{Ranch Salad Dressing}Great Value Creamy Great Value Classic Ranch _{Light Dressing} Great Value Fat Free Creamy _{Ranch Salad Dressing} Breakfast Biscuits belVita Chocolate _Biscuits belVita Golden Oat _Biscuits _{belVita Mixed Fruits Biscuits} *product categories subjected to taxation and subsidization

The products used in the survey are retrieved from Wal-Mart’s online store – 48 real products were used, complete with their pictorial information and current prices expressed in USD. Product details used in the questionnaire consist of: name of the product (e.g. Great Value White Bread), 200x200px picture, pricing in $ and nutritional information comprised of calorie count (expressed in Cal), levels of fat, saturated fat, sodium and sugars, all per 100g., making sure that respondents are presented with enough information to make well-considered decisions. To minimize on brand selection bias, product categories consist of a single brand within them, with only three product categories not conforming to this rule as a single brand could not provide enough assortment. Preview of the questions is available at the Appendix. To test the effect of taxes and subsidies eight out of the sixteen product categories are selected to have their price adjusted in the respected experimental conditions. In order to compare the differences between them, across all experimental conditions the product categories that are price adjusted are kept constant. The range of price discount and price increase falls within the 20% range which was found to be the optimal by (Waterlander et al. 2012, Andreyeva et al. 2011), as taxes and subsidies below that level often do not produce desired results (Waterlander et al. 2013), whereas increasing the price adjustments to 50% has shown to produce desirable outcomes, but taxing or subsidizing products with half their price is strictly experimental condition and not plausible long-term solution in real life (Waterlander et al. 2013; 2014).

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The questionnaire is divided in two main parts: (1) the first part contains the sixteen product categories that serve as the online shopping environment from which consumer’s select their groceries, (2) and the second part contains demographic questions about the respondents: age, gender, household size and income.

In the control condition of the study (C1) with no price adjustments, the respondents are presented with the product’s real prices and are required to select only one out of the three products available. After making their choices through all the sixteen categories, respondents are asked demographic questions regarding their age, gender and monthly income. The only difference, apart from the respective price adjustments, in the other three conditions is the introductory question which details that the price adjustments of certain products is due to health related taxes and/or subsidies, making sure that the adjustment is salient to consumers (Chetty et al., 2009). An overview of the experimental conditions is presented in table 2.

Control Subsidies

Control C1 (no price adjustments on the

products)

C2 (subsidies on the healthier

products, no price adjustments on the unhealthier products)

Taxes C3 (taxes on the unhealthier

products, no price adjustments on the healthier alternatives)

C4 (subsidies on the healthier

products, taxes on the

unhealthier products)

3.3 Procedure 3.3.1 Pre-test

Prior to the launch of the final survey, a pre-test was carried out with a sample of nine respondents. The goal of pre-testing was to establish that participants understood the task they were given, to shop online for groceries, and to check if the price adjustments in the tax and subsidies conditions are clearly acknowledged by them. Further, pre-testing served to estimate the completion time of the questionnaire and whether the demographics questions were correctly enquired. Based on the feedback of the respondents in the pre-test it was estimated that completion time of the survey is approximately seven minutes. Additionally, the price adjustments due to taxes and subsidies were given a wider spacing and bold font, to aid respondent’s comprehension.

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18 3.3.2Control Variables

Respondents are asked to provide their monthly income (expressed in USD, self-reported), which is going to be assessed whether it has a moderating effect on our independent variables. Age (expressed in years, continuous), gender (1=male, 2=female) and household size (continuous) also serve as a control variables in our study.

3.4 Measurement Approach

The main dependent variable of our study is the healthiness of a consumer’s shopping basket. Several methods for measuring it have been considered, however due to feasibility reasons a singular was chosen. Epstein et al. (2010) adopts the total number of calories contained in the shopping basket as dependent variable, however due to the intrinsic differences amongst our product categories in terms of calories (e.g even the most healthy ice-cream version contains more calories than some of the unhealthiest product categories like milk and yoghurt), another approach was chosen. The main outcome measurement is the total number of purchases of healthy items, expressed as a share of the sixteen product categories, which is in line with the research carried out by Waterlander et al. (2012).

3.5 Data collection method

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4. RESULTS

In this section the results of our study will be presented and examined in detail. The chapter starts with descriptive statistics of the sample, followed by testing of the control variables to analyze whether they introduce significant effects on the results. Finally, the hypotheses are tested and reported.

4.1 Descriptive statistics

A total of 196 respondents participated in the study, of which a total of three didn’t meet the criteria of being the primary household shopper and were not assigned to a condition, reducing the sample to 193 participants. Missing values analysis reveals that of all 193 respondents that have completed the main condition that is selecting groceries among the sixteen product categories 47 have not provided demographic details (age, gender, weight, height, household size and income), forming a complete sample of 146 respondents.

Out of the 146 respondents, 47 (32%) are males and 99 (68%) are females. The average age of the respondents is 47 years old, whereas the average values for household size and monthly household income are 2.9 people and $ 19,683, respectively. An overview of the distribution of respondents per condition is presented in table 3.

Overall N C1.Control Condition C2. Tax condition C3. Subsidy condition C4. Taxes and subsidies Completed the shopping trip 193 41 47 55 50 Percentage 100% 21.2% 24.35% 28.5% 26% Missing demographic data 47 4 11 19 13 Average household size 2.9 2.97 2.75 2.67 3.08

Table 3. Distribution of respondents

4.2 Measurement of the main variable

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computed: the share of relatively healthy products within a respondent basket (Share_of_HP). The variable is created by dividing the total number of relatively healthy purchases a respondent has made within the shopping trip on the number of all product options, thus assigning a share ranging from 0% (no healthy purchases) to 100% (only healthy purchases). The dependent variable is measured on a continuous level, thus ANOVA (Analyses of variance) tests are employed to compare the mean differences across the conditions.

4.2.1 Control variables 4.2.1.1 Age

In order to see if participant’s age differs per condition, a One-way ANOVA is performed with age per condition. The results from the test, indicate that there are no significant differences between respondent’s age across the four conditions (F=1.468, p=0.266). The highest mean age of participants is in the 2nd condition with 49.94 years, whereas the lowest falls into the 1st with an average of 44.22 years. Since there are no significant differences, age is not expected to influence the results, thus not taking it into account for further analyses. Table 4 shows the complete age distribution per condition.

Age in years Overall C1 C2 C3 C4

N 146 37 36 36 37

Mean 47.21 44.22 49.94 45.67 49.03

Minimum 20 25 23 20 27

Maximum 82 71 80 74 82

Table 4. Age distribution per condition

4.2.1.2 Gender

The sample is comprised of more females (99), than men (47). In all the conditions females are prevalent, especially condition 2. Full distribution per condition is available in the table below.

Gender Overall C1 C2 C3 C4

Male 32% 40.5% 13.9% 38.9% 35.1%

Female 68% 59.5% 86.1% 61.1% 64.9%

Total 100% 100% 100% 100% 100%

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Chi-square test is performed in order to see if respondent’s gender varies significantly between our four conditions (Table 6). The results show that gender differences are marginally significant between the scenarios, result likely caused by the overrepresentation of females in the second condition.

Pearson Chi-square Degrees of freedom p-value

Gender 7,593a 3 0.055

Table 6. Chi-square test, df and p-value for gender per condition

Following, in order to see if there are any significant differences in the healthiness of basket between males and females, One-way ANOVA test for gender is performed (table 7).

Dependent variable

Male Female Means male

Means female

F-test P-value

Share_of_HP 47 99 .3098 .3213 .090 .765

Table 7. Gender results on share of healthy products

The results reveal that there no significant differences in the means between males and females with respect to the main dependent variables. When measuring the share of healthy products, the average of healthy products bought by females is at 32%, whereas for males it is 30%, with a (F=.090, p-value=.765), making the differences not significant.

4.2.1.3 Household size

The average household size in our sample consists of 2.9 people. To see if household size differs per condition we have performed a One-Way ANOVA with it per condition. The results indicate that there are no significant differences between household size across the four conditions, thus is not expected to influence our results further (F=.576, p=.632). Full distribution is presented in the table below:

Household size Overall C1 C2 C3 C4

N 146 37 36 36 37

Mean 2.87 2.97 2.75 2.67 3.08

Standard Deviation 1.523 1.323 1.962 1.287 1.460

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22 4.3 Hypothesis testing

4.3.1 Hypothesis overview

H1 Taxation on unhealthy food products decreases the purchasing of those options amongst consumers, resulting in an increase on the healthiness of the shopping basket.

H2 Subsidies on healthy foods would result in higher purchasing of those items, increasing the healthiness of the shopping basket.

H3 The presence of both subsidies and taxes has a stronger impact on the healthiness of the shopping basket, compared to the case where only taxes or subsidies are present.

Table 9. Hypothesis overview

First, in order to analyze whether there are significant differences across the means of the share of healthy product for the experimental conditions, a Two-Way ANOVA between groups analysis is performed for our main dependent (Table 10).

Two-Way ANOVA across conditions

Mean share of healthy products

F-test p-value

Taxes .2972 (29.72%) 2.787 .097

Subsidies .3798 (37.98%) .767 .382

Taxes and Subsidies .3018 (30.18%) .540 .463

Table 10. Two-Way ANOVA across conditions

The results across conditions reveals that the mean share of healthy products for participants who were subjected to only taxed unhealthy products is significantly different at 90% confidence level (F=2.787, p=.097), however they negatively influence the share of healthy products as it is clearly illustrated by having the lowest average of only 29.72% healthy products. The means for the subsidies and taxes and subsidies conditions report insignificant differences with p=0.382 (F=.767) for subsidies and p=0.436 (F=.540) for the combination of both taxes and subsidies, respectively.

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overview of the results comparing the conditions are provided in the following table, while Graph 1 illustrates the share of healthy purchases per condition

C1 C2 C3 C4

Mean F-test p-value F-test p-value F-test p-value F-test p-value C1 .3276 (32.76%) x .386 .536 1.189 .278 .353 .554

C2 .2972 (29.72%) x x 3.021 .085 .011 .917

C3 .3798 (37.98%) x x x

3.281 .073

C4 .3018 (30.18%) x x x x

Table 11. Between conditions results on the share of healthy products

Graph 1. Share of healthy products per condition

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subsidies alone have stronger influence on purchasing healthy items than presenting taxes alongside subsidies (F=3.281, p=0.73). When looking at the share of healthy products of respondents in the third condition against our control condition with no price adjustments, we observe that there is a marginal increase in the purchases of healthy items caused by subsidies (32.76% versus 37.98%), however the differences are not statistically significant (F=1.189, p=.278).

While subsidies alone were found to increase the share of healthy products purchased, that is not the case for the remainder of our experimental conditions. Looking at the graph reveals that respondents in the condition of taxes alone (C2) have the lowest average of healthy products in their shopping basket with 29.72%, albeit as mentioned above those differences are only significant when compared to the share of healthy products in the third condition (C3). Rather surprisingly the effects of presenting both taxes and subsidies (C4) were found not significant in increasing the share of healthy products. In fact participant’s healthy products in that condition constituted only 30.18% of their shopping basket, significantly less than participants who received only subsidies, and a marginal decrease compared to our control condition with no price adjustments.

4.4 Hypothesis results

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25 4.5 The effects of income

4.5.1 Hypothesis overview

H4a Taxation of unhealthy products has a stronger effect on the healthiness of the shopping basket, when consumer’s income level is low.

H4b Subsidies on healthy products have a stronger effect on the healthiness of the shopping basket, when consumer’s income level is low

Table 12. Income level hypothesis overview

Respondents had to self-report their monthly household income level in the questionnaire. After performing missing value analyses it is revealed that 52 respondents did not provide their income data, leaving a complete sample of 141 respondents. The sample was analyzed for outliers, which revealed six cases of extreme values, four with income below $100 which are most likely due to typo errors when filling in the questionnaire and two values above $250000. Average income was assessed without factoring the outliers and those cases were substituted with the average income of $19 683. Overview of the income distribution per condition is presented in table 13.

Overall C1 C2 C3 C3

Average income

$ 19682.9 $ 21725.8 $ 17940.1 $ 19388.7 $ 19618.7

Table 13. Average income distribution per condition

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26 28.30% 33.80% 32% 29.40% 33.10% 30.30%

Taxes Subsidies Direct Effect of

Income S ha re of he al thy produc ts

Low Income High Income

C1 C2 C3 C4 Total

Income group low income

18 19 14 16 67

high income

18 16 21 19 74

Total 36 35 35 35 141

Table 14. Income groups per condition

After the dichotomous variable for income is created, the hypothesis can be tested. A Three-Way ANOVA with the effects of taxes, subsidies and income level, on the main dependent variable is performed (See Appendix, Table A2). Overview of the mean differences for healthy products between high and low income groups is presented in the following graph:

Graph 2. Share of healthy products per income level

The results of the three-way ANOVA indicate that there are no significant differences in the average share of healthy products of participants that received taxes or subsidies that can be attributed to income level.

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received subsidies are not significant (F=0.70, p-value=.791). Respondents who received subsidies and fall in the low income group have a share of 33.8%, less than 1% increase compared to the high income group’s average of 33.1%, therefore we reject hypothesis H4b. The three-way ANOVA also reveals that there is no significant direct effect of income level on the healthiness of the shopping basket (F=0.209, p-value=.648).

Likely reasoning that can explain those results is the insignificant differences between real income distributions among the different conditions (Table 13). Furthermore, a cross table with Chi-square for the categorical variable of income level (high vs. low) also reveals that there are no significant differences between people with high and low income across the conditions (See Appendix, Table A3)., further explaining the insignificant effect income has.

4.6 Additional findings-The effects of shopping on a budget

Income level failed to produce any significant results when used as a proxy measurement for shopping on a budget. However another approach was considered: in our questionnaire participants were asked to rate themselves on the following statement “More often than not, I shop for groceries on a budget” on a scale of 1”strongly disagree” to 7 “strongly agree”. (Van Ittersum et al., 2013). Even though it is not as an objective measure as analyzing their income, the scale details respondents subjective judgments about whether they shop on a budget or not (Van Ittersum et al., 2013)

First, descriptive statistics are run to determine what the mean and median scores are for respondents on the statement (See Appendix, table A4) showing mean score of 5.27 and median score of 6 out of 7. Next, based on the median score the respondents are grouped into a new variable: participants rated lower than the median (does not shop on a budget) and respondents whose score is higher than the median (shops on a budget). Following, to see if the new variable moderate the effect of taxation and subsidies, a three-way ANOVA test is performed (See Appendix, Table A5).

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28 27.72%

36.17%

Shops on a budget Does not shop on a budget

Share of healthy products

N Mean F-test P-value

Does shop on a budget

76 .2772 (27.72%) 5.819 .017

Does not shop on a budget

71 .3617 (36.17%)

Table 15. One-way ANOVA for share of healthy products

The results illustrate that respondents that have stated that they often times shop on a tight budget have purchased significantly less healthy products (27.72%) than those who are not budget restricted (M=36.17%, F=5.819, p=0.17). An overview is presented in Graph 1.

Graph 3. Direct effect of shopping on a budget

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5. Conclusion and Discussion

5.1 Conclusion

Obesity is rapidly becoming one of the serious health threats in the developed world (World Health Organization, 2009) with bad eating habits related to unhealthy food and overconsumption regarded as the primary cause for its ever-growing increase (Ogden et al. 2012). Even though healthier food options are considered to be more abundant than ever before, access to them due to their higher prices is not always available and lower income consumers are often times forced to substitute those for cheaper, often times unhealthier alternatives (Mooney, 1990;, Jetter et al. 2006; Rose, 2010). To combat this issue, further research into the determinants of healthy purchases is required.

The goal of our paper was to examine consumers shopping behavior for healthy products under the influence of price adjustments due to taxes and subsidies. We investigated the influences imposing taxes on unhealthy food products and subsidizing the healthier alternatives have on consumer’s choices. In addition to that we have also investigated the influence that household income has on moderating those choices. Based on the results from our study we can answer the main research questions of our paper:

1. Taxing unhealthy foods did not produced significant results on the purchases of the healthier alternatives, even more so respondents who were presented with only taxed unhealthy products had the smallest share of healthy products in their basket, thus we reject our first hypothesis.

2. Subsidizing the healthier alternatives resulted in an overal increase in the number of healthy items purchased, significant when compared to the other price adjusted conditions and marginal increase when compared to the control condition with no price adjustmensts, thus we partially accept our hypothesis.

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products. Furthermore no direct effect of income level was found, on the share of healthy products.

Overview of the results is presented in table 16.

H1 Taxation on unhealthy food products decreases the purchasing of those options amongst consumers, resulting in an increase on the healthiness of the shopping basket.

Rejected

H2 Subsidies on healthy foods would result in higher purchasing of those items, increasing the healthiness of the shopping basket.

Partially Accepted

H3 The presence of both subsidies and taxes has a stronger impact on the healthiness of the shopping basket, compared to the case where only taxes or subsidies are present.

Rejected

H4a Taxation of unhealthy products has a stronger effect on consumer’s

choices, when their income level is low

Rejected

H4b Subsidies on healthy products have a stronger effect on consumer choices, when their income level is low

Rejected Table 16. Hypothesis results

5.2 Discussion

First, when observing the effects of only taxing unhealthy foods as a measure to stimulate the purchases of the healthier alternatives and increase consumer’s healthiness of the shopping basket we see that the results are not significant. This results are not in line with the either the findings of Epstein et al.(2010), nor Giesen (2012) which reports that taxing unhealthier products is an effective way to promote healthier purchases. In our study participants who were presented with only taxes had the smallest share of healthy products in their baskets: 29 %, a significant difference compared to the average share of healthy products in the other conditions. However our results are not that uncommon as price increases (taxes) on unhealthy items also have shown to be ineffective at increasing the healthiness of the shopping basket. One study reports that 25% price increase of unhealthy products does not significantly affect groceries purchases (Waterlander et al. 2012)

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biggest share of healthy items in their shopping basket with 38%. Our findings are in-line with the findings of French et al. (2001) and Waterlander et al. (2013) who report that subsidizing healthier food products results in increased purchasing of them and higher healthiness of basket. Our study shows that even 20% price reduction on the healthy items is an effective measure to promote healthier food choices, whereas previous literature suggest that effective discount rate is at 50%

Third, we found no statistically significant results when taxed unhealthy products are presented alongside subsidized healthier alternatives. To our knowledge only one study investigates the simultaneous effect of presenting both taxes and subsidies (Waterlander et al.2012). Their study does report statistically significant effect of subsidization on healthy foods, however no significant results were found for the simultaneous effect of taxes and subsidies, which is in accordance with our findings.

Additionally, income level was found not significant at moderating the effects of taxes and subsidies, neither it was as a direct effect on increasing the share of healthy products. No significant differences between the higher and lower income group were found in the number of healthy products purchased across the experimental conditions. Those findings are most likely caused by the very small differences of average income between the participants in each condition, coupled with almost equal distribution of participants in both high and low income groups. Nedekoorn et al. (2011) reports similar findings to our study, although the focus of that research falls upon daily budgets instead of monthly income, the results suggest that daily budget does not moderates the effect taxes have on restricting unhealthy products.

Finally, although not part of the main research framework of our paper, we have found that participants who have self-identified to shop on a tight budget purchased significantly less healthy products than those who reported they were not shopping under budget constraint, irrespective of price adjustments. While these findings contradict the ones when assessing income level, they potentially illustrate respondent’s subjective reasoning as to why pick the cheaper, unhealthy alternative.

5.3 Managerial Implications

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et al. 2000, Gupta 1988). Our study shows that even a twenty percent discount, presented in the form of subsidies on healthy products, resulted in sales increase of those products. This is an important finding that can be utilized by marketing managers that position their brands as healthier food alternatives. For example, when coordinating their price promotional campaigns, marketeers can present the set price promotion as a health discount aimed at enriching consumer’s healthy diet. By presenting their price discounts as a health related initiative, marketing managers can potentially build stronger brand loyalty towards their brand within their customer base, allowing for not only short term sales increase due to price promotions, but also long term effects.

5.4 Limitations and future research directions

This research has been subjected to several limitations that could explain the insignificant results of some of the hypothesis.

First, our sample was relatively small given that between participants design and four conditions. Secondly, the product categories set can be considered rather small for a full featured grocery shopping simulation, not including basic food categories such as rice, potato and beans just to name a few, whilst over emphasizing on sweetened products like ice-creams, cookies and breakfast biscuits. Featuring more product categories, alongside more products within them might allow for different results on our main dependent variable.

Third, monthly household income displayed very little variance in our sample across the experimental conditions. Next to that, the use of median split on income to differentiate between high and low income groups created almost equal subgroups across the conditions, which coupled with the little variance of crude income might explain that our results regarding income are not significant.

Fourth, the effects of tax and subsidy salience were not thoroughly measured in our paper. While respondents in the conditions where taxes and subsidies were given an introductory statement that price adjustments are due to health related taxes and subsidies, it would have been possible for a group of them not to receive this statement in order to compare if any differences in their shopping basket occur.

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be used. Tax and subsidies salience should be properly measured by presenting to one group of respondents the reason for price adjustments, while leaving it out for the other.

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APPENDICES

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41 Appendix B: Results output

Table A1. One-Way ANOVA results for income distribution

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound 1 36 21725.8056 27551.54820 4591.92470 12403.7028 31047.9083 900.00 82000.00 2 ₃₅ _17940.0571 _{32334.96046 5465.60588} _6832.6096 _29047.5047 _{800.00 150000.00} 3 ₃₅ _19388.7429 _{28114.61277 4752.23692} _9731.0355 _29046.4502 _{800.00 125000.00} 4 ₃₅ _19618.7143 _{27232.59553 4603.14880} _10263.9904 _28973.4382 _{1000.00 100000.00} Total 141 19682.9220 28593.96116 2408.04593 14922.0858 24443.7582 800.00 150000.00

Table A1.1Descriptive statistics for income distribution, based on one-way ANOVA

Sum of Squares df Mean Square F Sig.

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42 Table A2. Three Way ANOVA results with income level

Dependent Variable: Share of Healthy Products

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model ,290a 7 ,041 ,884 ,521 Intercept 13,496 1 13,496 287,648 ,000 Income Level ,010 1 ,010 ,209 ,648

Taxes ,074 1 ,074 1,579 ,211

subsidies ,074 1 ,074 1,574 ,212 Income Level * Taxes ,028 1 ,028 ,599 ,440 Income Leve * subsidies ,003 1 ,003 ,070 ,791 Taxes * subsidies ,004 1 ,004 ,093 ,761 Income Level * Taxes *

subsidies ,081 1 ,081 1,731 ,191 Error 6,240 133 ,047 Total 20,180 141 Corrected Total 6,531 140 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 1,571a 3 ,666 Likelihood Ratio 1,577 3 ,665 Linear-by-Linear Association ,515 1 ,473 N of Valid Cases 141

Table A3. Chi-Square Tests for Income level (high vs. low)

Are food prices in position to make us eat healthier? The effects of taxes and subsidies on consumer’s food choices