Tag: Tax system

A Potential Broadening of the Excise Tax on Food Products High in Sugar and Salt: The Case of Latvia

Posted on June 9, 2025 | Policy Brief

Woman holding a burger with fried chicken, donuts, and sugary foods – concept image for excise tax on sugar and salt.

Overweight and obesity are significant public health issues, contributing to various chronic diseases such as cardiovascular diseases, diabetes, and certain cancers. Latvia’s second-highest share of overweight adults in the EU is a compelling reason for public health measures. These should aim to discourage excessive consumption of high-calorie foods and beverages. Excise tax is one of the tools in a complex approach to encourage a balanced diet and promote positive health outcomes. Motivated by evidence from Hungary, currently the only country in Europe imposing a tax on pre-packaged food products high in sugar and salt, we simulate the short-term impact of the introduction of a differentiated broad-based tax on food products in Latvia. We conclude that to influence consumer behaviour, price increases should be at least 10 percent, which implies introducing tax rates that are at least 1.5 times higher than those in Hungary.

Extremely High Overweight and Obesity Rates in Latvia

Overweight and obesity are serious public health challenges across Europe. Together with an unbalanced diet and low physical activity they contribute to many non-communicable diseases (NCDs), including heart diseases, diabetes and certain cancers (WHO, 2022). For many individuals, being overweight is also linked to psychological problems.

Overweight and obesity rates are extremely high in all EU countries. In 2022, more than half of all adults in the EU (51.3 percent) were overweight (including pre-obese and obese). Latvia has the 2nd highest rate of overweight adults in the EU (60.4 percent). This puts significant pressure on Latvia’s health care system and social resources.

Recognizing that overweight and obesity has multifactorial causes, a comprehensive approach is required to effectively tackle this problem, involving experts from various fields and addressing the issue from multiple angles.

One potential tool in a complex approach is an excise tax on foods and drinks high in sugar and salt since excessive consumption of such foods and drinks represents a major risk factor for NCDs (WHO, 2015a). Such a tax could help to reduce excessive consumption, encourage healthier eating, and improve public health outcomes.

The Intake of Added Sugars

According to data from the EFSA Panel on Nutrition, Novel Foods and Food Alergens (EFSA, 2022), the main source of added sugar intake in almost all European countries is sugar and confectionery. The numbers for adults (18–64 years) range from 20 percent in Austria to 57 percent in Italy (48 percent in Latvia). For children aged 1–18 years, sugar and confectionary contribute to 36 – 44 percent of added sugar intake in Latvia.

In Latvia, other key sources of added sugar are fine bakery wares, processed fruits, and vegetables. The contribution of sweetened soft and fruit drinks to total added sugar intake is only 8 percent for adults (18–64 years) and 3–7 percent for children (1–18 years).

Excise Tax on Soft Drinks

As of 2024, 14 European countries have implemented taxes on sugar-sweetened soft drinks. In Latvia, the tax was introduced in 1999 and was mainly motivated by the financial needs of the state budget.

The evidence from international case studies (WHO, 2023) shows that taxes on sugar-sweetened soft drinks can be effective in reducing consumption in the short term, particularly when the tax leads to significant price increases that reduce affordability. However, the overall evidence on whether these taxes successfully reduce sugar intake is inconclusive. In a review by the New Zealand Institute of Economic Research (NZIER, 2017), the authors conclude that methodologically robust studies  show only small reductions in sugar intake, too small to produce significant health benefits, and easily offset if consumers switch to other high-calorie products. On the other hand, studies reporting a meaningful change in sugar intake often assume no compensatory substitution. At the same time, experience from Hungary suggests that a sugar tax imposed on a wide range of products is effective in reducing the overall consumption of products subject to the tax, and in encouraging healthier consumption habits. The impact assessment conducted 3 years after the introduction of the tax in Hungary showed that consumers of unhealthy food products responded to the tax by choosing a cheaper, often healthier product (7–16 percent of those surveyed), consuming less of the unhealthy product (5–16 percent), switching to another brand of the product (5–11 percent), or substituting it with another food item – often a healthier alternative (WHO, 2015b).

The Short-term Effect of a Broad-Based Excise Tax in Latvia

Approach

Motivated by the evidence from Hungary, we simulate the short-term impact of the introduction of a similar differentiated broad-based tax on food products high in sugar and salt using the approach applied in Pļuta et. al (2020). First, we use AC Nielsen monthly data from 2019 to 2023 on sales volume and prices of pre-packaged food products of selected categories in the modern trade retail market to estimate the price elasticity of demand for these products. The selected product categories included:

  • Pre-packaged sweetened products (e.g., breakfast cereals, cacao, chocolate bars, soft and hard candies, sweet biscuits, etc.)
  • Sweetened dairy products (e.g., ice cream, yoghurt, condensed milk, curd countlines, etc.)
  • Salted snacks (salted nuts, salted biscuits, etc.)
  • Ready-to-eat and instant foods (e.g., pizza cooled and frozen, frozen dumplings, vegetables and canned beans, etc.)
  • Condiments (e.g., dehydrated instant and cooking culinary, dehydrated sauces and seasonings, dressings, ketchup, mayonnaise, etc.)

Second, we simulate different scenarios to assess the increase in price, reduction in sales and budgetary effect using the estimated elasticities and assuming different degrees of tax pass-through rate to retail prices (100 and 50 percent, respectively). Our results represent a short-term or direct fiscal effect, meaning we do not account for any second-round effects that may arise due to changes in domestic production and employment, which could in turn generate additional tax revenues.

The Tax Object and Rates

In defining the scenarios to be considered when modelling the potential broadening of the tax base, we use the Hungarian Public Health Product Tax (PHPT) as a practice example. As a basis, we use the list of product categories under taxation by the PHPT, the two-tier tax system and the PHPT rates as of 2024. In addition, we are also looking at other product categories (such as sugar sweetened dairy products, sweetened cereals and vegetables and beans containered), expanding the tax base even more. In total, we simulated four scenarios for taxing the food products high in sugar and salt. The scenarios consider a two-tier tax system, meaning products with lower sugar or salt content are taxed at a lower rate, while those with higher content face a higher tax. For condiments, only a high rate is applied due to the, usually high, salt content. A differentiated tax rate is expected to stimulate the industry to drive down sugar and salt content in their products, i.e., offering sugar and salt-reduced options. The scenarios differ from each other in the applicable rates.

  • Scenario 1: Uses the same tax rates as Latvia’s excise tax on non-alcoholic beverages (as of March 2024) – EUR 7.40 per 100 kg (low rate) and EUR 17.50 per 100 kg (high rate).
  • Scenario 2: Uses Hungary’s PHPT rates – in the general case, the low rate is EUR 17 per 100 kg, and the high rate is EUR 54 per 100 kg.
  • Scenario 3: Sets rates 1.5 times higher than Hungary’s rates.
  • Scenario 4: Doubles Hungary’s rates.

Assumptions

Unfortunately, the retail price and sales time series used in the analysis are not disaggregated into groups according to the sugar and salt content in the product. As a result, we apply assumptions to estimate the potential range of tax impacts.

To calculate the lower bound of the expected impact, we assume that 100 percent of sales in each product category are subject to the new sugar and salt tax, but all products have low sugar and salt content and therefore qualify for the lower tax rate.

To calculate the upper bound, we assume that 25 percent of the sales volume is taxed at the lower rate (due to low sugar and salt content), while the remaining 75 percent of sales are taxed at the higher rate, reflecting higher sugar and salt levels in those products.

Results

According to our estimations, the application of an excise tax on food products high in sugar and salt could lead to a price increase and sales decrease of taxed food products. The magnitude would depend on the type of food product (i.e., average retail price in the country) and scenario assumed (i.e., tax rates). Within each single scenario, the largest impact is expected for condiments. This is because we simulate only the high tax rate applied to them (not a two-tier system), as is the case in Hungary. The tax makes up a larger share of their price, and due to high price sensitivity, the decrease in sales is also greater.

Based on previous research, we conclude that price increases need to reach at least 10 percent to meaningfully influence consumer behaviour. This level of change is achieved in Scenario 3, which assumes tax rates 1.5 times higher than those used in Hungary.

Below we present the obtained estimations under Scenario 3.  The estimates for Scenarios 1 and 2 are not included here because the price increase caused by the tax does not reach 10 percent for several product categories. Under Scenario 4 the price changes could exceed 10 percent but this scenario may also provide stronger incentives for manufacturers to reformulate their products (and in this case, the average price increase within a given product category will be lower). The results for Scenario 4 are available in a recent BICEPS report (Pļuta et al., 2024).

Under Scenario 3, with full tax pass-through (100 percent), the estimated reduction in sales volume is:

  • 3.0–8.1 percent for pre-packaged sweetened products;
  • 3.6–17.1 percent for sweetened dairy products;
  • 0.9–4.7 percent for salted snacks;
  • 10.4–54.1 percent for ready-to-eat and instant foods;
  • 11.0–11.8 percent for condiments.

If only 50 percent of the tax is passed through to retail prices, the sales reductions would be approximately half as big.

The estimated revenue from the excise tax in this scenario would range between EUR 15.0 million and EUR 54.9 million. The resulting change in VAT revenue would range from a loss of EUR 0.7 million to a gain of EUR 1.1 million.

Conclusion

Although overweight and obesity rates are extremely high in all EU countries, Latvia, in 2022, had the second highest rate in the EU. In this brief, we explore the use of the excise tax as one of the tools in a complex approach to discourage excessive consumption of foods and beverages high in sugar and salt and encourage a balanced diet and promote positive health outcomes. Based on findings from previous studies, a price increase of at least 10 percent is needed to influence consumer behaviour. In Latvia, this would require tax rates approximately 1.5 times higher than those applied in Hungary, i.e. in the general case equal to EUR 25.5 (low rate) and EUR 81 (high rate) per 100 kg of product. Under such a scenario, the estimated revenue from the tax could range from EUR 15.0 to 54.9 million. For comparison, in 2024, Latvia’s excise tax on soft drinks generated EUR 15.6 million. To remain effective, tax rates should be adjusted over time in line with growth in disposable income.

Acknowledgement

This brief is based on a study Taxation of the non-alcoholic beverages with excise tax in the Baltic countries. Potential broadening of the tax base to food products high in sugar and salt completed by BICEPS researchers in 2024 (Pļuta et al., 2024). The study was commissioned by VA Government. It was developed independently and reflects only the views of the authors.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Increasing Resources for Families with Children Through the Tax System: Recent Reform Proposals from Poland

Posted on December 2, 2013 | Policy Brief

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This brief discusses the consequences of a recent reform proposal that aims to redistribute resources to low-income families with children through the income tax system in Poland. The proposed reform replaces the current child tax credit with additional amounts of the universal tax credit, and by changing the sequence in which tax deductions are accounted for, it increases resources of low-income families with children by about 1.7 billion PLN per year (0.4 billion EUR). The brief examines four possible ways of additional tax system modifications that would make the reform package neutral for the public finances, and presents distributional implications of the reforms.

The level and structure of financial support for families with children has become an important policy focus in Poland; a country that faces high levels of child poverty and one of the lowest fertility rates in Europe (Immervoll et al., 2001; Haan and Wrohlich, 2011; Eurostat, 2013). In this brief, we outline recent tax reform proposals that aim to increase financial support for low-income families with children through the tax system. A range of such potential reforms has been examined in Myck et al. (2013b); a report prepared for the Chancellery of the President of the Republic of Poland. One of the options became the key element of the President’s family support program Better climate for families proposed in May 2013. Below we discuss its main features and various options for financing the proposals.

The proposed modification of financial support for families would replace the current child tax credit with additional amounts of the universal tax credit conditional on the number of children, and increase tax advantages for families by changing the sequence in which tax credits are accounted for in a way that is favorable for families with children (Chancellery of the President of Poland, 2013). The main beneficiaries of this reform would be low-income families with children whose income is too low to take full advantage of the current child-related advantages. The overall cost of the reform would amount to about 1.7 billion PLN (0.4 billion EUR). In the final section of the brief we discuss potential ways of making the reform budget neutral.

The analysis has been conducted using CenEA’s micro-simulation model SIMPL on reweighted and indexed data from the 2010 Household Budget Survey (HBS) collected annually by the Polish Central Statistical Office (see Morawski and Myck, 2010, 2011; Myck, 2009; Domitrz et al., 2013; Creedy, 2004).

Financial Support for Polish Families in 2013

In Poland, financial support for families with children depends on the level of family income and the demographic structure of the household. The system consists of two main elements – family benefits on the one hand, and tax preferences for families with children on the other. Following Myck et al. (2013a), we define financial support for a family j (FSFj) as the sum of family benefits received by the family (FBj), and tax preferences that families with children collect in the PIT system is defined as the difference in the level of tax liabilities and health insurance contributions paid by the family (PITHIjD0 – PITHIjDn) supposing they have no children (D0) and on condition them having n number of dependent children (Dn):

FSFj = FBj + (PITHIjD0 – PITHIjDn)             [1]

Figure 1a presents the current level of the financial support for single-earner married couples and Figure 1b presents the same for single parents with one and three children in relation to the level of gross earnings.

Family benefits

Family benefits, which include family allowance with supplements, childbirth allowance and nursing benefits, are means-tested and related to the number and age of dependent children in the family and specific family circumstances. Family benefits are granted only to low-income families and are subject to point withdrawal once the family crosses the income eligibility threshold (539 PLN of net income per person). For example, the stylized married couples in Figure 1 lose family benefits when their monthly gross income exceeds 2,060 PLN if they have one child and 3,435 PLN if they have three children (for single parents these thresholds equal 785 PLN and 1,825 PLN respectively).

Figure 1. Monthly level of financial support received by families with one and three children dependent on their age and family gross income in 2013 (PLN/month)
(a) Married couple with one spouse working
b) Single parent working
figure1_vertical
Note: FB – family benefits; CTC – child tax credit; joint taxation preferences: UTC – additional amount of universal tax credit; IB – shift of tax income bracket. In case of the single parent alimonies from the absent parent are assumed at the median value from 2010 data, which is 410.50 PLN for 1 child and 724.67 PLN for 3 children. Gross income of the single parent includes income from work only. Alimonies are taken into account for FB income means testing. Source: Myck et al. (2013a).

Tax preferences

Taxpayers with children can deduct a non-refundable child tax credit (CTC) from the accrued tax, with the maximum values of the CTC related to the level of universal tax credit available to all tax payers (UTC is 46.37 PLN per month). For each of the first two children in the family, taxpayers can deduct up to two values of the UTC (92.67 PLN per month), for the third child up to three values (139.00 PLN per month) and for the fourth and following children up to four values of the UTC (185.34 PLN per month). The CTC is not available for high-income parents with one child (whose annual taxable income exceeds 112,000 PLN per year).

Further tax advantages are available for single parents through joint taxation, which translates into substantial gains in particular for high-income parents. As Figure 1 shows, single parents whose gross income exceeds the second tax income bracket (15,745 PLN per month) gain up to 1,044.19 PLN per month if they have one child and 1,368.54 PLN if they have three children. With the same income levels, the system grants nothing to married couples if they have one child and 324.34 PLN if they have three.

In the current system, the CTC can be deducted from the accrued tax only after the full amount of UTC and the tax-deductible part of health insurance (HI) contributions have been exhausted. As a consequence, there is a large group of low-income families whose income is too low to take full advantage of the CTC. As Figure 2 illustrates, the higher the number of children is in a family, the lower is the proportion of families who take full advantage of the credit. Although the percentage of those using the full CTC is 76.1% for families with one child, it decreases to 67.6% for those with two children and is as little as 30.8% for families with three or more kids. Over 40% of the latter use only half of the CTC they are entitled to.

Figure 2. Use of maximum amount of CTC by number of children

figure2

Note: Proportions of families with taxable income satisfying other conditions for CTC. Source: Myck et al. (2013a).

Recent Reform Proposals

In a recent report for the Chancellery of the President of Poland, we have analyzed several options for the reform of the family-related elements of the tax system (Myck et al., 2013b). One of these has become the key element of the presidential reform proposal (Chancellery of the President of Poland, 2013). The reform assumes that the CTC is replaced with the amounts of the Universal Tax Credit conditional on the number of children in the family in such a way as to maintain the current maximum advantages offered to families through the CTC system. The main purpose of the reform is to reverse the tax deduction sequence so that tax advantages related to having children are deducted from the accrued tax before considering credits related to health insurance contributions. Such construction would enable low-income families to make greater use of child-related tax advantages, while leaving the situation of higher-income families unchanged.

Figure 3. Monthly tax advantages from the reform among families with 1-4 children (PLN/month)

 figure3

Source: CenEA – own calculation based on SIMPL model and 2010 HBS data.

Figure 3 presents monthly levels of tax advantages resulting from the proposed reform conditional on the number of children in the family and the level of gross income. We note that families with children gain from the reform if their income exceeds 735 PLN per month. Tax advantages resulting from the proposed modifications are exhausted at different levels of gross income depending on the number of children (from 2,630 PLN for families with one child to 8,010 PLN for those with four children). The higher the number of children is, the greater is also the potential maximum gain – for example, families with four children and income of 4,010 PLN per month would gain up to 311.35 PLN per month.

The results of the analysis show that, overall, 2 million households with children would benefit from this reform (below referred to as System 1). The total annual change in households’ disposable income (equivalent to the total cost for public finances) would amount to 1.69 billion PLN (see Table 1 below).

Table 1. Average annual change in households’ disposable income by number of children in Systems 1-5 (billion PLN)

No children

1 child

2 children

3+ children

Total
System 1

0,00

0,39

0,60

0,70

1,69
System 2

-0,45

-0,20

0,04

0,55

-0,08
System 3

-0,65

-0,09

0,17

0,59

0,02
System 4

-0,66

-0,15

0,23

0,59

0,01
System 5

-0,86

-0,04

0,31

0,63

0,04
 
Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).
 

Table 1 shows that most of the resources would be beneficial for families with three or more children (0.7 billion PLN per year), while families with one or two children would benefit about 0.39 billion PLN and 0.6 billion PLN per year, respectively.

The distribution of total income gains by income deciles is presented in Figure 4. The gains are clearly focused in the lower part of the income distribution. For example, families with children in the second income decile would receive a total of 0.4 billion PLN, while those in the bottom and third decile would recieve approximately 0.25 billion PLN. Only 0.04 billion PLN of the total cost would be distributed to families in the top income decile.

Figure 4. Distribution of total annual gains in households’ disposable income by deciles: Systems 1-5 (billion PLN)

 figure4

Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).

Potential Ways of Financing the Reform

Concerns about the state of public finances naturally imply questions related to the potential ways of financing any additional tax giveaways. Myck et al. (2013b) presents four alternative modifications of the tax system that make the entire package of reforms neutral for the public finances. These are:

  • System 2 – CTC reform + limitations on joint-taxation preferences for married couples (both with or without children) and single parents;
  • System 3 – CTC reform + reduction of tax income threshold from 85,528 to 68,000 PLN per year;
  • System 4 – CTC reform + reduction of tax revenue costs from 1,335 to 475 PLN per year;
  • System 5 – CTC reform + reduction of tax-deductible part of health insurance from 7.75% to 7.45%.

The overall total outcomes of these proposals for household disposable income are illustrated in Table 1 and Figure 4. The implications in terms of the redistribution of the packages – with losses among childless households and gains among those with children – are clear under all of the proposed packages, although all of the reform combinations imply small losses also for families with one child.  Total disposable income of childless households falls by 0.45 PLN per year under System 2 and by as much as 0.86 billion PLN under System 5. By shifting the majority of the costs to households without children, the latter is simultaneously the most generous for families with children since income of those with two children grows on average by 0.31 billion per year, while of those with more children see a growth of 0.63 billion PLN per year.

Figure 4 illustrates that in all of the revenue neutral reform packages, the households from the highest two deciles are the biggest losers. That the financing of the shift of resources to low-income families falls on households from the top income decile is particularly evident in the case of Systems 2 and 3 where total disposal income for these households fall by 1.64 billion PLN and 1.52 billion PLN, respectively. Since changes to revenue costs and deduction of HI contributions apply to almost all taxpayers, Systems 4 and 5 are less favorable for households from the lower deciles and generate losses for the upper part of the income distribution. However, a large part of cost is also born by households from the tenth decile (0.26 and 0.39 billion PLN, respectively).

While the combinations of tax changes presented above would be neutral with respect to the current system of taxes in Poland, it is worth noting that the policy of tax increases through the tax-parameter freezing implemented in 2009 has increased taxes by far more than the cost of the Presidential reform proposal. As we showed in Myck et al. (2013c), this policy increased taxes by 3.71 billions PLN per year, of which 2.21 billions was paid by families with children. The recent proposal could thus be thought of as a way of redistributing these resources back to families with children.

Conclusions

Financial support for families with children is an important element of government policy with implications for child poverty, labor-market participation among parents, as well as fertility (Immervoll et al., 2001; Haan and Wrohlich, 2011). In this brief, we outlined the results of a recent analysis of direct financial consequences of modifications in the Polish system of support for families through the tax system with the focus on a reform proposal presented by the Polish President in the program Better climate for families. The reform would benefit lower-income families with children at the cost of about 1.7 billion PLN. As a result, annual income of the families from the three bottom deciles would grow by 0.93 billion PLN. A high proportion of the gains (0.7 billion PLN) would go to families with three or more children.

We also presented four additional modifications of the tax system that would make the CTC reform revenue neutral. Reform packages that withdraw joint-taxation preferences and decrease the threshold of the income tax to a higher rate would be most effective in ensuring redistribution of support for low-income households. It is worth noting though, that the recent approach of the Polish government to the tax system has implied substantial increases in the level of income taxes through the freezing of income tax parameters, and these alone would be more than sufficient to finance the proposed tax changes.

▪

References

  • Creedy J. (2004). Reweighting Household Surveys for Tax Microsimulation Modelling: An Application to the New Zealand Household Economic Survey. Australian Journal of Labour Economics 7 (1): 71-88. Centre for Labour Market Research.
  • Domitrz A., Morawski L., Myck M., Semeniuk A. (2013). Dystrybucyjny wpływ reform podatkowo-świadczeniowych wprowadzonych w latach 2006-2011 (Distributional effect of tax and benefit reforms introduced from 2006-2011). CenEA MR01/12; Bank i Kredyt 03/2013.
  • Chancellery of the President of Poland (2013). Dobry klimat dla rodziny. Program polityki rodzinnej Prezydenta RP. (Better climate for families. Family support program of the Polish President.)
  • Eurostat online database 2013 – epp.eurostat.ec.europa.eu. Date of access: 28.11.2013.
  • Haan P., Wrohlich K. (2011) Can Child Care Encourage Employment and Fertility? Evidence from a Structural Model. Labour Economics 18 (4), pp. 498-512.
  • Immervoll H., Sutherland H., de Vos K. (2001). Reducing child poverty in the European Union: the role of child benefits. In: Vleminckx K. and Smeeding T.M. (eds.) Child well-being, Child poverty and Child Policy in Modern Nations. What do we know? The Policy Press: Bristol.
  • Morawski L., Myck M. (2010).‘Klin’-ing up: Effects of Polish Tax Reforms on Those In and on Those Out. Labour Economics 17(3): 556-566.
  • Morawski L., Myck M. (2011). Distributional Effects of the Child Tax Credits in Poland and Its Potential Reform. Ekonomista 6: 815-830.
  • Myck M. (2009). Analizy polskiego systemu podatkowo-zasiłkowego z wykorzystaniem modelu mikrosymulacyjnego SIMPL (Analysis of the Polish tax-benefit system using microsimulation model SIMPL). Problemy Polityki Społecznej 11: 86-107.
  • Myck M., Kundera M., Oczkowska M. (2013a). Finansowe wsparcie rodzin z dziećmi w Polsce w 2013 roku (Financial support for families with children in Poland in 2013). CenEA MR01/13.
  • Myck M., Kundera M., Oczkowska M. (2013b). Finansowe wsparcie rodzin z dziećmi w Polsce: przykłady modyfikacji w systemie podatkowym (Financial support for families with children in Poland: examples of modifications in the tax system). CenEA MR02/13.
  • Myck M., Kundera M., Najsztub. M, Oczkowska M. (2013c). Ponowne „mrożenie” PIT w kontekście zmian podatkowych od 2009 roku (PIT freezing in the context of tax reforms since 2009). Komentarze CenEA: 06.11.2013.

________________________________________________________________________________________________

* This brief draws on recent research at the Centre for Economic Analysis in the projects financed by the Chancellery of the President of the Republic of Poland and the Batory Foundation (project no: 22078). The analysis has been conducted using CenEA’s micro-simulation model SIMPL based on the 2010 Household Budget Survey data collected annually by the Polish Central Statistical Office (CSO). The CSO takes no responsibility for the conclusions resulting from the analysis. Any views presented in this brief are of the authors’ and not of the Centre for Economic Analysis, which has no official policy stance.

Baltic Shadow Economies

Posted on September 26, 2011 | Policy Brief

Policy Brief Image of Two Shadows from Walking Men Representing Shadow Economies

This policy brief summarises the results and implications of a recent study of the size and determinants of the shadow economies in Estonia, Latvia, and Lithuania. The results suggest that the shadow economy in Latvia in 2010 is considerably larger than in neighboring Estonia and Lithuania. While the shadow economy as a percentage of GDP in Estonia contracted from 2009 to 2010, it expanded in Latvia and Lithuania. An important driver of shadow activity in the Baltic countries is the entrepreneurs’ dissatisfaction and distrust in the government and the tax system. Involvement in the shadow economy is more pervasive among younger firms and firms in the construction sector. These findings have a number of policy implications, which are discussed at the end of this brief.

Background and Aims

Anecdotal evidence suggests that the shadow economies in the Baltic countries and other emerging Central and Eastern European countries are substantial in size relative to GDP. This is an important issue for these countries because informal production has a number of negative consequences.

First, countries can spiral into a ‘bad equilibrium’: individuals go underground to escape taxes and social welfare contributions, eroding the tax and social security bases, causing increases in tax rates and/or budget deficits, pushing more production underground and ultimately weakening the economic and social basis for collective arrangements. Second, tax evasion can also hamper economic growth by diverting resources from productive uses (producing useful goods and services) to unproductive ones (mechanisms and schemes to conceal income, monitoring of tax compliance, issuance and collection of penalties for non-compliance). Third, informal production can constrain entrepreneurs’ ability to obtain debt or equity financing for productive investment because potential creditors/investors cannot verify the true (concealed) cash flows of the entrepreneur. This can further impede growth. Finally, shadow activities distort official statistics such as GDP, which are important signals to policy makers.

The aim of our study is to measure the size of the shadow economies in Estonia, Latvia, and Lithuania, and to analyse the factors that influence participation in the shadow sector. We use the term ‘shadow economy’ to refer to all legal production of goods and services that is deliberately concealed from public authorities. The study also makes a methodological contribution by developing an index of the size of the shadow economies as a percentage of GDP. It is foreseen that the index will be published regularly.

Although an index invites comparisons, and maybe even ‘competitions’ between countries, the purpose here is not to create a ‘Baltic championship’ on shadow economies. The index should primarily be seen as a tool to promote discussion on the size and role of the shadow economy and to provide a metric which can be used to measure the degree of success in fighting the shadow economy.

Method of Measuring the Shadow Economies

Estimates the size of the shadow economies are derived from surveys of a stratified random sample of entrepreneurs in the three countries (591 in Latvia, 536 in Lithuania and 500 in Estonia). The rationale for this approach is that those most likely to know how much production or income goes unreported, are the entrepreneurs who themselves engage in the misreporting and shadow production.

Survey-based approaches face the risk of underestimating the total size of the shadow economy due to non-response and untruthful response given the sensitive nature of the topic. We minimise this risk by employing a number of surveying and data collection techniques shown in previous studies to be effective in eliciting more truthful responses (e.g., Gerxhani, 2007; Kazemier and van Eck, 1992; Hanousek and Palda, 2004).

These approaches include framing the survey as a study of satisfaction with government policy, gradually introducing the most sensitive questions after less sensitive questions, phrasing misreporting questions indirectly, e.g., asking entrepreneurs about the shadow activity among ‘firms in their industry’ rather than ‘their firm’, and, in the analysis, controlling for factors that correlate with potential untruthful response, such as tolerance towards misreporting. We aggregate entrepreneurs’ responses about misreported business income, unregistered or hidden employees, as well as unreported ‘envelope’ wages to obtain estimates of the shadow economies as a proportion of GDP.

There are three common methods of measuring GDP: the output, expenditure and income approaches. Our index is based on the income approach, which calculates GDP as the sum of gross remuneration of employees (gross personal income) and gross operating income of firms (gross corporate income). Computation of the index proceeds in three steps: (i) estimate the extent of underreporting of employee remuneration and underreporting of firms’ operating income using the survey responses; (ii) estimate each firm’s shadow production proportion as a weighted average of the two underreporting estimates with the weights reflecting the proportions of employee remuneration and firms’ operating income in the composition of GDP; and (iii) calculate a production-weighted average of shadow production across firms. Taking weighted averages of the underreporting measures rather than a simple average is important for the shadow economy index to reflect a proportion of GDP.

Size of the Shadow Economies

Table 1 indicates that the shadow economy as a proportion of GDP is considerably larger in Latvia (38.1%) compared to Estonia (19.4%) and Lithuania (18.8%) in 2010. Only Estonia has managed to marginally decrease the proportional size of its shadow economy from 2009 to 2010 – a statistically significant decrease of 0.8 percentage points. In contrast, the proportional size of the shadow economies in Lithuania and Latvia has increased by an estimated 0.8 and 1.5 percentage points, respectively.

Table 1. Shadow economy index for the Baltic countries

 

Note: This table reports point estimates and 95% confidence intervals for the size of the shadow economies as a proportion of GDP. The third column reports the change in the relative size of the shadow economies from 2009 to 2010.

Form of Shadow Activity

Figure 1 illustrates the average levels of underreporting (business profits, number of employees and salaries) in each of the countries in 2009 and 2010. The average levels of underreporting in all three areas are in the order of two to three times higher in Latvia compared to Lithuania and Estonia. In Latvia and Lithuania, the degree of underreporting of business profits and salaries (‘envelope’ wages) is approximately twice as large as the underreporting of employees. The exception to this trend is the relatively low amount of underreported business profits in Estonia, likely to be a result of low corporate tax rates. Bribery in Latvia and Lithuania constitutes a similar fraction of firms’ revenue, approximately 10%, whereas in Estonia bribery is less pervasive and constitutes around 6% of firms’ revenue.

Figure 1. Simple averages of underreporting and bribery among Estonian (EE), Lithuanian (LT) and Latvian (LV) firms in 2009 and 2010.

 

Determinants of Involvement in the Shadow Economy

The literature on tax evasion identifies two main groups of factors that affect the decision to evade taxes and thus participate in the shadow economy. The first set emerges from rational choice models of the decision to evade taxes. In such models individuals or firms weigh up the benefits of evasion in the form of tax savings against the probability of being caught and the penalties that they expect to receive if caught. Therefore the decision to underreport income and participate in the shadow economy is affected by the detection rates, the size and type of penalties, firms’ attitudes towards risk-taking and so on. These factors are likely to differ across countries, regions, sectors of the economy, size and age of firm, and entrepreneurial orientation (innovativeness, risk-taking tendencies, and pro-activeness).

Empirical studies find that the actual amount of tax evasion is considerably lower than predicted by rational choice models based on pure economic self-interest. The difference is often attributed to the second, broader, set of tax evasion determinants – attitudes and social norms. These factors include perceived justice of the tax system, i.e., attitudes about whether the tax burden and administration of the tax system are fair. They also include attitudes about how appropriately taxes are spent and how much firms trust the government. Finally, tax evasion is also influenced by social norms such as ethical values and moral convictions, as well as fear of feelings of guilt and social stigmatisation if caught.

Our study uses regression analysis to identify the factors that are statistically related to firms’ involvement in the shadow economy. The results indicate that the size of the shadow economy is smaller in Estonia and Lithuania relative to Latvia, after controlling for a range of factors.

Tolerance towards tax evasion is positively associated with the firm’s stated level of income/wage underreporting. Satisfaction with the tax system and the government is negatively associated with the firm’s involvement in the shadow economy, i.e. dissatisfied firms engage in more shadow activity, satisfied firms engage in less.

This result is consistent with previous research on tax evasion, and offers an explanation of why the size of the shadow economy is larger in Latvia than in Estonia and Lithuania; namely that Latvian firms engage in more shadow activity because they are more dissatisfied with the tax system and the government as illustrated in Figure 2. Analysing each of the four measures of satisfaction separately we find that shadow activity is most strongly related to dissatisfaction with business legislation, followed by the State Revenue Service, the government’s tax policy, and finally the government’s support for entrepreneurs.

Figure 2. Average satisfaction of firms with the tax system and government in 2010.

Note: These questions use a 5-point scale: 1=“very unsatisfied”; 2=“unsatisfied”; 3=“neither satisfied nor unsatisfied”; 4=“satisfied”; and 5=“very satisfied”. SRS is State Revenue Service.

Another strong determinant of involvement in the shadow economy is firm age, with younger firms engaging in more shadow activity than older firms. This effect dominates relations between firm size and shadow activity. A possible explanation for the relation is that young firms entering a market made up of established competitors use tax evasion as a means of being competitive in their early stages. The regression results also provide some evidence that after controlling for other factors, firms in the construction sector and firms that have a pro-active entrepreneurial orientation tend to engage in more shadow activity.

Policy Implications

First, the relatively large size of the shadow economies in the Baltic countries, and their different expansion/contraction trends, cause significant error in official estimates of GDP and its rates of change, because although statistics bureaus in each of the countries attempt to include some of the shadow production in GDP estimates they do not capture the full extent. Not only is GDP used in key policy ratios such as government deficit to GDP, debt to GDP, but also the rate of change is used as a key indicator of economic performance and therefore guides policy decisions. When the shadow economy is expanding (as in Latvia and Lithuania) official GDP growth rates underestimate true economic growth and when the shadow economy is contracting (as in Estonia) official GDP growth rates overstate true economic growth. At a minimum, policy makers need to be aware of these biases in official statistics, but ideally, statistical bureaus would implement more rigorous methods to estimate and incorporate shadow production in official statistics.

Second, our results suggest that to reduce the size of the shadow economies in the Baltic countries by encouraging voluntary compliance, a key factor that needs to be addressed is the high level of dissatisfaction with the tax system and with the government. Addressing this issue could involve actions such as making tax policy more stable (less frequent changes in procedures and tax rates), and increasing the transparency with which taxes are spent.

Finally, our estimates of the size of the shadow economies suggest that there is significant scope for all three governments to increase their revenues by bringing production ‘out of the shadows’. Investment in programs aimed at reducing the size of the shadow economies could be rather profitable for the Baltic governments, because even a small influence on entrepreneurial behaviour could result in significant revenue increases.

References

  • Gerxhani, K. (2007) “‘Did you pay your taxes?’ How (not) to conduct tax evasion surveys in transition countries”, Social Indicators Research 80, pp. 555-581.
  • Hanousek, J., and F. Palda (2004) “Quality of government services and the civic duty to pay taxes in the Czech and Slovak Republics, and other transition countries”, Kyklos 57(2), pp.237-252.
  • Kazemier, B., and R. van Eck (1992) “Survey investigations of the hidden economy”, Journal of Economic Psychology 13, pp. 569-587.

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