TAX EVASION AND SELF-EMPLOYMENT OVER TIME: EVIDENCE FROM SWEDEN

Transcription

1 TAX EVASION AND SELF-EMPLOYMENT OVER TIME: EVIDENCE FROM SWEDEN PER ENGSTRÖM JOHANNES HAGEN Abstract Self-employed individuals have much greater opportunities than wage earners to underreport their incomes. This paper uses recent income and expenditure data ( ) to examine the extent of underreporting of income among self-employed individuals in Sweden. For a given level of observed income, underreporting would be visible in the data as excess food consumption among the self-employed. We look at time trends in tax evasion by estimating and comparing underreporting levels for individual years. In particular, we construct a 5-year moving average estimation method that better captures long-run trends in tax evasion. Our results confirm the underreporting hypothesis, but stress the necessity of distinguishing between incorporated and unincorporated businesses. We find very little or no evidence of underreporting in the former category, whereas households in the latter underreport their total incomes by around 25 percent. Single year estimates suggest that the degree of tax evasion has been quite volatile, but when we increase the number of observations and minimize the effect of extreme years by means of 5- year moving average estimates we find a slight upward trend in underreporting. Authors Johannes Hagen Uppsala University, Department of Economics PhD Student Phone: Fax: johannes.hagen@nek.uu.se Per Engström Uppsala University, Department of Economics Associate Professor, Director of Master Programme Phone: Fax: per.engstrom@nek.uu.se 1

2 Contents 1. Introduction Estimating Tax Evasion from Expenditure Data The Data Estimation Results Food Consumption as Dependent Variable Concatenated Dataset ( ) Single Years Moving Average over 5 Years Income as Dependent Variable Concatenated Dataset ( ) Single Years Moving Average over 5 Years Conclusion Appendix

3 1. Introduction The purpose of this paper is to investigate the extent of income underreporting among self-employed people in Sweden. The major contribution of this paper is to look at whether underreporting has increased or decreased over time and to see in what direction tax evasion among self-employed people seems to head. The paper applies the so-called expenditure-based approach to estimation of tax evasion, which was first pioneered by Pissarides and Weber (1989) and has been applied in a number of other studies. Underreporting is estimated by using information on consumption expenditure and reported income. The method is based on the assumptions that households with similar observed income levels should consume equal amounts of food and that expenditure on food is accurately reported by all people participating in an expenditure survey. If the self-employed underreport their incomes, this would be visible in the data as excess food consumption for a given level of observed income. The excess food consumption can then be used to estimate the true income of the household and thus also the associated amount of unreported income. In these studies, the main purpose has been to estimate the average degree of underreporting among selfemployed people in order to calculate the subsequent tax revenue loss and the size of black economy activities relative GDP. However, what should also be of great interest to the tax authorities is when and by how much tax evasion has increased or decreased and, not least, why this is so. Comparing estimates of tax evasion over time will help realize the political objective of minimizing the size of the black economy by identifying the effect of certain institutional changes on underreporting. Moreover, if a major change in the degree of underreporting cannot be directly linked to a specific reform, comparisons over time may give indications of whether self-employed people are more prone to underreporting today than yesterday or not. Recently, the expenditure-based approach was used by Engström and Holmlund (2006) to estimate the extent of underreporting among self-employed people in Sweden using data from and In large, our study is a replica of Engström and Holmlunds study, but with new data ( ). According to Engström and Holmlund, it is important to take the legal form of self-employment into account, as they find striking differences between incorporated and unincorporated businesses: selfemployed with unincorporated businesses are much more likely to underreport than those with incorporated businesses. Not only will new data help test these observed tax evasion patterns, but also shed light upon how they have evolved over time. The results of our study confirm the underreporting hypothesis, but stress the uncertainty and diversity associated with estimations of tax evasion. Compared to Engström and Holmlund (2006), who estimate that the degree of underreporting hovers around 45 percent and 15 percent of reported disposable income among households with unincorporated and incorporated businesses respectively, our estimates are slightly lower. On average, using data from , underreporting amounts to 25 percent and 15 percent respectively. However, controlling for a number of household characteristics, we find no evidence that self-employed individuals with incorporated businesses earn substantially lower incomes than wage earners. This, in combination with the temporarily extreme fluctuations in the estimates of underreporting among incorporated businesses, suggests that we should be careful when drawing inferences about the degree of tax evasion in this employment category. As for households with unincorporated businesses, the 3

4 results are more clear-cut. Individuals running unincorporated businesses earn, on average, 45 percent less than wage earners with similar life conditions and there is no indication of diminishing income differentials over time. Based on 5-year moving average estimates of excess food consumption, underreporting in this group seems to have increased from 15 percent to just above 25 percent over the time period in question. The next section briefly discusses the Pissarides and Weber methodology. Section 3 presents the data, section 4 gives the results and section 5 concludes. 2. Estimating Tax Evasion from Expenditure Data The Pissarides and Weber approach is the main method applied in this paper to estimate tax evasion trends among self-employed people in Sweden. All estimates of tax evasion are based on comparisons between self-employed people and wage earners, of which the latter makes up the reference group. The idea is straightforward: people with similar incomes should consume equal amounts of food, independent of employment status. In other words, for a given level of observed income, a self-employed individual should consume as much food as a wage earner. If not, there is reason to believe that the self-employed leaves a certain income share unreported. To be able to estimate tax evasion based on relative expenditure patterns, we have to make some crucial assumptions. Firstly, expenditure on food must be accurately reported by all people participating in the expenditure survey. Secondly, reported income corresponds to true income for the wage earners but not for the self-employed. Self-employed people have the possibility of underreporting their income (and actually do so), whereas wage earners have not. Thirdly, the elasticity of consumption with respect to income is assumed to be the same for the two groups, just as food preferences. If, say, self-employed individuals consistently consume less food than wage earners despite similar income levels and other household characteristics (such as age, education length and number of children) we cannot draw inferences about underreporting based on relative food expenditure patterns. The Pissarides and Weber approach can be illustrated graphically as seen in Figure 1. Let c denote log food consumption,, and y log disposable income,. The figure shows two log-linear consumption income-profiles (Engel curves), one for self-employed (SE) and one for wage earners (WE). The slopes, which reflect the elasticity of consumption, are equal and intercepts differ as to capture the possibility of underreporting of income among self-employed people. Imagine two individuals, one selfemployed and one wage earner, who both report consumption level. The wage earner reports income level, whereas the self-employed person reports income. Given our assumptions, two persons that consume the same amount of food should also have similar incomes. Thus, we can infer that the selfemployed person s true income is rather than and that the extent of underreporting is given by. 4

5 Figure 1. Engel curves for wage earners (WE) and self-employed people (SE) Finding the unreported income share,, is done by estimating an equation of the form: (1) where i denotes individual i, X is a vector of variables affecting consumption (in addition to income), SE is a dummy variable for self-employed people and ε is a random error term. The parameter captures the vertical distance between the two Engel curves; 0 implies some underreporting of income among selfemployed people. The degree of underreporting is obtained as / or alternatively as /, which gives the number by which a self-employed person s disposable income has to be multiplied as to get true disposable income. It is easy to extend the model to relate the degree of underreporting to income measures other than disposable income., as defined above, is not an estimate of how much underreporting of selfemployment income there is, but of total household income. Since self-employed households typically also include wage earners with wage income, it would be more interesting to relate underreporting to the income share that is actually manipulable. This is especially true for households with incorporated business, since they are likely to be employed and paid by their company. Therefore, we express unreported income as: Percentage markup on reported disposable income 1 Percentage markup on reported gross income 2 Percentage markup on reported entrepreneurial income 3 Share of true entrepreneurial income 1 Defined as the household s taxable and nontaxable income minus tax payments and other negative transfers 2 Defined as the household s income before tax and transfer payments 3 Two different definitions of entrepreneurial income are applied as explained in table 4 5

6 Logically, relating unreported income to these income measures could be done by replacing disposable income on the left-hand side of equation (1). However, as shown by Engström and Holmlund (2006), the parameter estimates from the original model can be used to derive underreporting expressed in terms of alternative income measures. 3. The Data We have used data from the Swedish Household Budget Survey (Hushållensutgifter, HUT) from The household data is presented annually by Statistics Sweden. Around 4000 households are approached each year, of which slightly more than half participate in the survey. The response rates can be regarded as fairly good, considering the great work effort each household must put into the survey. The participation rate has been quite stable over the years as demonstrated by table 1. The participating households are asked to report their consumption expenditures during randomly selected two-week periods using a detailed expense manager. The expenditures are then multiplied by 26 to represent the annual household consumption level. The households should also note whether the expenditures are associated with a certain household member. Various other questions are asked as to get information on household characteristics, including employment status, age, occupation, type of housing and number of children. Information about different types of income 5 and from which sector each individual retrieves his/her main income share is obtained from official income and tax registers. 6 The income data is then merged with the expenditure data as to complete a detailed data file of the annual income and expenditure levels of the participating households and their individual members. Table 1. Number of households participating in HUT and the survey response rate Year Nr of households Response rate % % % % % % % Total As we are interested in estimating the true income of self-employed people based on estimations of excess food consumption in this group, the two key variables are annual food consumption and annual disposable income. Our measure of food consumption is reported in the data as food purchases and non- 4 The design and main results of the HUT studies are presented in reports from Statistics Sweden( ) 5 This paper is mostly concerned with reported disposable income, but also makes use of gross, entrepreneurial, wage and total factor income 6 LINDA (Longitudinal Individual Data Base) 6

7 alcoholic beverages. 7 Disposable income is based on all types of register-based incomes, including transfers. Taxes are deducted from gross income as to get household disposable income. In order to determine whether self-employed people exhibit excessive food consumption, based on which the degree of income underreporting is estimated, we need to define what constitutes a self-employed household. Different ways of classifying the occupation status of households have been suggested in the literature, of which the most frequently applied is the use of information on income shares attributed to paid employment and self-employment. 8 However, we prefer to make use of self-reported information on employment status of the individual household members, as the former method entails some problems. 9 According to our definition, a household is classified as self-employed if at least one member of the household is self-employed. Since the data contains information about the legal form of the business the self-employed category includes incorporated as well as unincorporated businesses. This distinction is, as we shall see, essential for the results. Some restrictions have been imposed for sample inclusion. Firstly, only households with at least one member self-employed or employed are taken into account. Secondly, farmers are excluded, assuming that their food purchases exhibit a pattern relative to income that differs from other self-employed households. Also, we restrict the analysis to households with cohabiting or married couples. Finally, we impose a minimum annual food consumption threshold of SEK 5000 and a maximum disposable income threshold of SEK two million. Table 2 describes the sample size for each year and for each legal form of the business after imposing these restrictions. The share of self-employed households has been quite stable over the sample period as shown by figure 2. Each legal form accounts for approximately 7-9 percent of the total amount of households. Perhaps one would have expected a more significant rise in the share of self-employed households during the time period in question. However, two major institutional changes that will stimulate the number of incorporated businesses entered into force in 2010, that is, after the sample period of this paper Similar results have been attained for broader measures of food consumption, such as food purchases plus meals out (Engström and Holmlund 2006). 8 Pissarides and Weber (1989) define households as self employed if income from self employment accounts for at least 25 percent of total income. 9 Besides the difficulty of choosing the borderline, this method is likely to be sensitive to the legal form of the business. A person running an incorporated business may nonetheless be formally employed by the company and receive the main part of the compensation in the form of wage income. The household, to which this person belongs, would thus risk not being classified as self employed. 10 Audit obligations for smaller companies were abolished in November 2010 and the minimum capital stock requirement for private companies was halved in April

8 Table 2. Number of observations after imposing sample restrictions Year Nr of households 1 member self-employed No selfemployed members 1 member with incorporated business 1 member with unincoporated business Total Figure 2. Share of self-employed households 18% 16% 14% 12% 10% 8% 6% Self employed 4% 2% 0% Figure 3 and 4 display annual disposable income and average food consumption among wage earners and self-employed, where the latter is divided into incorporated and unincorporated businesses. Average incomes are significantly higher among wage earners than households with unincorporated businesses. However, the income of households with incorporated businesses exceeds, on average, that of wage earners. Unsurprisingly, figure 4 reveals that households with incorporated businesses consume more food than the other two household groups. However, although households with unincorporated business make less money than wage earners they have similar food consumption levels. Figure 5, measuring food consumption as a percentage of disposable income, shows that food consumption relative to income among households with unincorporated businesses is consistently higher than among wage earners. Except for 2009, the difference varies between 2-5 percentage points. This pattern is what we would expect according to the hypothesis that self-employed people are more likely to underreport their true incomes. It is harder to tell from the graph whether the food consumption of 8

9 households with incorporated businesses relative to income is unusually high. As we shall see in the next section when controlling for other variables that may affect consumption, there are significant differences in the likelihood and in the extent of income underreporting among incorporated and unincorporated businesses. Figure 3. Average disposable income kr kr kr kr kr Employees kr kr Figure 4. Average food consumption kr kr kr kr kr kr kr kr kr kr kr Employees 9

10 Figure 5. Food consumption as a percentage of disposable income 19% 17% 15% 13% 11% 9% Employees 7% 5% Estimation Results As explained in section 2, two different methods are applied in this paper to estimate the degree of income underreporting among self-employed people. Of these methods only the first one makes use of expenditure data, treating food consumption as the dependent variable. The second method is merely supplementary, since it puts a certain income measure on the left-hand side of the equation. Since we are interested not only in estimating the average degree of underreporting using the whole data set, but also in identifying possible time trends, regressions are performed on single years and smoothened five-year periods. 4.1 Food Consumption as Dependent Variable Models have been estimated along the lines of equation (1) ln where log food consumption is regressed on log disposable income (β) and a bunch of control variables (X) that are likely to affect food consumption. The control variables include age and age squared, type of housing, number of children under age 20, average years of education among adult household members and a dummy for metropolitan residence. 11 This variable setup has been applied irrespective of time period under investigation. To detect excess food consumption among self-employed households we look at the dummy variable for self-employment with associated parameter. The definition of this dummy variable is changed according to the self-employment status of the household, which takes three forms: self-employed with unincorporated business, self-employed with incorporated business and self-employed with either one of 11 Age is the age of the household head, which is the person with the highest income in the household; type of housing is a dummy for single family house. 10

11 them. For example, the variable SE (inc.) takes the value of one when at least one household member runs an incorporated business. The extent of underreporting can then be measured as, where j is the self-employment status and β the parameter for disposable income Concatenated Dataset ( ) Firstly, regressions are made after concatenating all data, obtaining a data set comprising 7 years and almost observations. All coefficients, including those pertaining to self-employment, are statistically significant at conventional levels. The interpretation of the results in table 3 is that households with unincorporated businesses are characterized by excess food consumption of approximately 5 percent, about 2 percentage points above that of households with incorporated businesses. That is, they spend 5 percent more on food than wage earners with the same reported income. Interestingly, the lower confidence limit of the parameter estimate associated with self-employed with incorporated business does not exceed zero, which emphasizes the uncertainty of excessive food consumption in this category. Table 3. Excess consumption among self-employed at given income level Data: Dependent variable: ln(food) SE - uninc. SE - inc. SE - all Estimation 5,5% 3,3% 4,5% St. error 1,7% 1,7% 1,3% T-value 3,2 1,9 3,6 P-value 0,002 0,057 0,000 L95CL 2,0% 0,0% 2,1% U95CL 8,8% 6,7% 7,1% Note: Control variables include the age of the household head (and age squared), a dummy for single family house, number of children, a dummy for metropolitan residence and average years of schooling in the household. Table 4 displays the estimates of unreported income among the different self-employment groups. According to the results, with an excess food consumption of five percentage points in relation to wage earners with similar income, households with unincorporated business underreport around 25 percent of their income. This corresponds to percent of their gross income and some percent of their entrepreneurial income. To illustrate, if a self-employed household reports an annual gross income of SEK , this number must be multiplied by 1.35 as to get the true gross income, that is, SEK A self-employed household with unincorporated business hide, on average, as much as 35 percent of its true entrepreneurial income. The unreported income share of households with incorporated business is substantially lower, amounting to 15 percent of reported disposable income. These results are consistent with the hypothesis that incorporated businesses face higher costs of tax evasion as a result of more detailed regulations. However, despite the great number of observations ( ) the parameter estimate for households with incorporated businesses is only marginally significant, which motivates some caution when interpreting the results. These estimates of unreported income are about one-third lower than suggested by Engström and Holmlund (2006), partially explained by the use of different sample periods and sample sizes. 11

12 Table 4. Estimation of unreported income among self-employed households Data: Reference group: Households without self-employed members Self-employed households with unincorporated business Self-employed households with incorporated business All selfemployed households Excess food consumption at given income level 5,5% 3,3% 4,5% Households unreported income expressed as: - markup on reported disposable income 25% 15% 20% - markup on reported gross income 30-35% 20% 25-30% - markup on reported entrepreneurial income* 55% (50%)** 30-35% 45-50% - share of true entrepreneurial income 35% (33%)** 25% 30-35% * Entrepreneurial income refers to business income for self-employed households with unincorporated business. For self-employed households with incorporated business this measure also includes possible wage income. ** Extended measure of entrepreneurial refers to business income and possible wage income for both incorporated and unincorporated businesses Single Years Similar models have been estimated based on individual years. A graphical representation of the parameter estimate for excess food consumption for each year enables us to identify possible trends in tax evasion among the different self-employment categories. Figure A.1 and A.2 and Table A.1 in the appendix show that very few of these estimates, for both categories, are significantly different from zero. This stresses the uncertainty associated with year-to-year estimates and encourages the use of bigger data sets. The uncertainty is most clearly reflected in the volatility of the estimates. For instance, it seems unlikely that households with incorporated businesses would underreport more than half of their income in 2005 and then actually over report (i.e. consume less than wage earners with similar income) their income three years later. Although the small sample size (about 100 households with incorporated businesses per year) constitutes the major problem, we are still uncertain about the degree of underreporting in this group, if any underreporting at all. As for households with unincorporated businesses, the degree of underreporting varies between zero and 60 percent. There is no discernable trend, but there are two breakpoints in 2006 and Whether underreporting will continue at very low levels, as indicated by the 2009 estimate, is too early to tell, especially since the parameter is highly insignificant. Interestingly, when households with unincorporated businesses seem to increase underreporting, households with incorporated businesses decrease underreporting. 12

13 Figure 6. Excess consumption among self-employed households relative wage earners with similar income 20% 15% 10% 5% 0% 5% Self employed 10% Figure 7. True disposable income as a percentage of reported disposable income 240% 220% 200% 180% 160% 140% 120% 100% 80% 60% Self employed Moving Average over 5 Years Performing regressions on smoothened 5-year periods increases the sample size, neutralizes extreme years and allows us to identify trends in the medium and long run. Since we only have access to 7 years of data, regressions are run on three different time periods ( , , ), but as new data will be available, this series will provide good indications of where the degree of underreporting is heading. 13

14 In figure 9, there is a strong downward trend in the underreporting of self-employed with incorporated businesses. Although largely influenced by the extreme year of 2005, excess consumption does seem to go down during the time period in question. The parameter estimate for , however, is insignificant 12, which raises even more concern about the applicability of the expenditure based approach to estimation of tax evasion on this group of self-employed. The estimated excess consumption would imply that underreporting has decreased from slightly above 35 percent to just below 10 percent over the period. Relating underreporting to gross income, true gross income as a percentage of reported gross income has decreased from 150 to 110 percent. 13 The results are clearer when it comes to self-employed with unincorporated businesses. Excess consumption varies between 3 and 6 percent, whereas true disposable income makes up percent of reported disposable income. True entrepreneurial income increases from 140 percent to 160 percent of reported entrepreneurial income, implying that some percent of the true entrepreneurial income is unreported. 14 Updating this series of 5-year periods when new data is available will reveal whether the high degree of tax evasion detected during the last few years will persist or revert back to lower levels. Figure 8. Excess consumption among self-employed households relative wage earners with similar income 5-year periods 7% 6% 5% 4% 3% 2% Self employed 1% 0% Note: 2005 stands for the data set including year , 2006 for and 2007 for Appendix Table A.2 13 Appendix Figure A.3 14 Appendix Figure A.4 A.5 14

15 Figure 9. True disposable income as a percentage of reported disposable income 5-year periods 140% 135% 130% 125% 120% 115% 110% Self employed 105% 100% Note: 2005 stands for the data set including year , 2006 for and 2007 for Income as Dependent Variable Since the expenditure based approach has produced quite various and inconsistent results, among all caused by oversensitivity to outliers, small sample sizes and incorrect budget survey responses, an arguably straightforward supplementary method would be to look at differences in reported income between wage earners and self-employed individuals with similar measurable human capital and other characteristics. Models have been estimated along the lines of equation (2) ln where log income is regressed on a number of variables (Z) likely to determine income, including a dummy for self-employment status (SE). We perform regressions on individual data instead of aggregated household data, nonetheless imposing the same restrictions as in the previous case. For example, individuals must be married or co-habitant in order to be included in the sample. The control variables include age and age squared, type of housing, number of children under age 20, years of education, six regional dummies and industry dummies. A negative sign of σ would be consistent with underreporting of income among self-employed. As before, we can change the definition of the self-employment dummy according to the legal form of the business (incorporated business, unincorporated business or either one of them). Two different income measures are used: wages plus entrepreneurial income and total factor income Concatenated Dataset ( ) The results are interesting, as there is great divergence between people with incorporated and unincorporated businesses. For given characteristics, the level of reported income is around percent lower among individuals with unincorporated businesses than among wage earners, depending on what income measure is used. As for individuals with incorporated businesses, the negative effect is very small (about 6 percent) when relating underreporting to wages plus entrepreneurial income. However, as 15

16 table 5 suggests, reported total factor income is actually higher than that of wage earners with similar characteristics. This emphasizes the notion that individuals with incorporated are less likely, perhaps not likely at all, to underreport their income. Table 5. Comparison of reported income levels between self-employed households and employed households controlling for household characteristics Data: Dependent variable: ln Y Y: Wages plus entreprene rial income Y: Total factor income* SE - uninc. SE - inc. SE SE - uninc. SE - inc. SE Estimation (σ) -0,454-0,065-0,212-0,4910 0,074-0,138 P-value 0,000 0,029 0,000 0,0390 0,029 0,024 St. error 0,040 0,030 0,025 0,0000 0,012 0,000 U95CL ,123-0,264-0,5670 0,016-0,186 L95CL -0,376-0,007-0,168-0,4150 0,131-0,091 * Total factor income include in addition to wages and entrepreneurial income dividends, interest payments and capital gains. Note: Control variables include age of the household head (and age squared), a dummy for single family house, number of children, six dummies for H-region, average years of schooling in the household and a full set of (feasible) industry dummies (maximum 100) Single Years Comparing annual income levels for wage earners and self-employed people with similar characteristics yields some interesting results. As seen in figure 10, Individuals with unincorporated businesses report between 35 and 70 percent less income (wage and entrepreneurial income) than wage earners with similar characteristics. All coefficients are highly significant 15 and the degree of underreporting seems to be increasing over time. This supports the results from the expenditure based approach, indicating an increase in underreporting from 2006 onwards. Comparing total factor income levels, as shown by figure 11, reveals the same pattern; individuals with unincorporated businesses persistently earn substantially lower incomes than wage earners. The year-to-year analysis also shows that individuals with incorporated businesses do not earn lower wages than wage earners with similar characteristics. Only a few estimates are negatively significant and some of them are actually positively significant 16. Figure 11 shows that most estimates are positive when total factor income levels are compared. Thus, the patterns are consistent with what we found in the analysis of consumption behavior, i.e., weak or even no evidence of underreporting among self-employed with incorporated businesses, but strong evidence for households with unincorporated businesses. 15 See appendix 16 See appendix 16

17 Figure 10. Reported income of self-employed individuals in relation to wage earners controlling for household characteristics Dependent variable: Y = wage plus entrepreneurial income 20% 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% Self employed Figure 11. Reported income of self-employed individuals in relation to wage earners controlling for household characteristics Dependent variable: Y = total factor income 30% 20% 10% 0% 10% 20% 30% 40% 50% 60% 70% Self employed 17

18 4.2.3 Moving Average over 5 Years Using 5-year periods supports the patterns proposed in the previous sections. Irrespective of which income measure is applied, there is no significant negative effect on income for self-employed individuals with incorporated businesses. 17 Individuals with unincorporated businesses, on the other hand, report percent lower income than wage earners with similar characteristics, all estimates being highly significant. 5. Conclusion Our study of food expenditure and income among wage earners and self-employed has produced a rather complex picture of the degree and the development of tax evasion. Firstly, the results pertaining to unincorporated and incorporated businesses must be separated, as the degree of tax evasion between those two legal forms varies considerably. Secondly, by what means potential time trends in tax evasion should be captured is not completely straightforward, although we recommend the use of 5-year moving average estimates for future analysis. It is of no use to pay attention to the estimates of underreporting among the collective group of selfemployed people, as the results vary in almost all cases with the legal form of the business, i.e. unincorporated or incorporated. Moreover, looking at individual years (figure 6), the food consumption patterns of these two groups seem to go in opposite directions, that is, when people with unincorporated businesses increase underreporting, people with incorporated businesses reduce the unreported income share and vice versa. Combining annual data from to a large data set reveals that excess consumption relative wage earners differ by more than two percent between the two categories, which implies that the income share left unreported among incorporated businesses accrues to only 60 percent of that of unincorporated businesses. Note that this average measure of underreporting among incorporated businesses is largely influenced by the extreme year of 2004, when true disposable income soared to 220 percent of reported disposable income. These extreme levels of underreporting are unlikely to be true, considering the estimates of 2003 and the years following 2004, which encourages great concern when interpreting the degree of tax evasion among households with incorporated businesses. People with unincorporated businesses underreport their incomes at the average rate of 25 percent, which corresponds to 35 percent of their true entrepreneurial income left unreported. The average rate of underreporting among incorporated businesses is estimated to 15 percent, but there is, as said, good reason to believe that this estimate is too high. Looking at income differentials between wage earners and self-employed emphasizes the need to distinguish between the two legal forms of self-employment. Reported incomes among self-employed with unincorporated businesses are substantially lower (45-50 percent) than incomes among wage earners after controlling for human capital characteristics and industry affiliation. Income differentials are quite stable at this level with a slight negative inclination, which goes in line with the findings of the expenditure-based approach. As for households with incorporated businesses, there is no evidence of significant income differentials. Quite the opposite, relating income differentials to total factor income actually yields a positive effect on income of being self-employed with incorporated business. 17 Appendix Table A.4 18

19 Not only are estimates of average tax evasion among self-employed of interest to the tax authorities, but also how tax morale has developed during recent years and also how it will develop in the future. Our results show that measures of underreporting, based on single year estimates of excess food consumption, could be misleading. Few of the estimates pertaining to self-employment are significant, even for households with unincorporated businesses. Moreover, the confidence intervals for excess food consumption are large (Figure A.1-A.2) and the fluctuations sometimes unreasonably big. To minimize the effect of outliers, extreme years and small sample sizes, which probably cause the instability of single year estimates, we have applied moving average estimates over 5 years. The results confirm previous findings that people with unincorporated businesses seem to have increased underreporting over time to up above 25 percent of disposable income, whereas underreporting of people with incorporated businesses has fallen below 10 percent. This method will provide the best indications of where tax evasion among self-employed people is heading in the long run. Quite recently, two bills were passed by the Swedish Parliament that most likely will have significant effects on the rate of growth of small companies and on tax evasion. Audit obligations for smaller companies were abolished in November 2010 and the minimum capital stock requirement for private companies was halved in April The former bill might spur income underreporting in two ways: some owners may consciously increase underreporting as a response to the reduced number of control bodies, whereas some may unconsciously misreport their income to the authorities just because there is no auditor there to control them. Halving the minimum capital stock requirement will undoubtedly have a positive effect on the number of private companies, thereby increasing the absolute value of unreported income. Whether this will leave the average degree of underreporting among private company owners unaffected is not as easy to tell. Applying the expenditure-based approach, using single year estimates and 5-year period estimates, will be valuable tools in analyzing the effects of these reforms once new data is available. 19

20 6. Appendix Figure A.1. Excess consumption of households with incorporated business at given level of income 30% 25% 20% 15% 10% 5% 0% 5% 10% 15% 20% Excess consumption Lower confidence limit Upper confidence limit Figure A.2 Excess consumption of households with unincorporated business at given level of income 25% 20% 15% 10% 5% 0% 5% 10% 15% Excess consumption Lower confidence limit Upper confidence limit 20

21 Table A.1 Excess food consumption of self-employed households at given level of income parameter information Data: Single years Dependent variable: ln(c) Variable Year Estimation St. error T-value P-value L95CL U95CL SE - uninc ,3% 0,045 2,075 0,038 0,5% 18,2% SE - uninc ,7% 0,040 1,176 0,240-3,1% 12,5% SE - uninc ,2% 0,043 0,281 0,779-7,3% 9,7% SE - uninc ,4% 0,047-0,076 0,939-9,4% 8,7% SE - uninc ,7% 0,048 1,418 0,157-2,6% 16,1% SE - uninc ,0% 0,045 2,914 0,004 4,3% 21,8% SE - uninc ,0% 0,052 0,008 0,994-10,1% 10,2% SE - inc ,4% 0,045 0,323 0,747-7,3% 10,2% SE - inc ,8% 0,044-0,174 0,862-9,4% 7,9% SE - inc ,8% 0,045 3,268 0,001 5,9% 23,7% SE - inc ,5% 0,046 2,269 0,023 1,4% 19,6% SE - inc ,4% 0,044 0,317 0,751-7,2% 10,0% SE - inc ,8% 0,045-1,304 0,193-14,6% 2,9% SE - inc ,0% 0,047 0,633 0,527-6,2% 12,2% SE ,4% 0,033 1,943 0,052 0,000 0,123 SE ,0% 0,031 0,619 0,536-0,042 0,080 SE ,8% 0,033 2,369 0,018-0,013 0,143 SE ,1% 0,034 1,775 0,076-0,006 0,129 SE ,1% 0,034 1,213 0,225-0,025 0,107 SE ,5% 0,033 1,052 0,293-0,030 0,100 SE ,4% 0,037 0,386 0,700-0,058 0,086 Note: Control variables include age of the household head (and age squared), a dummy for single family house, number of children, a dummy for metropolitan areas and average years of schooling in the household 21

22 Table A.2 Excess food consumption of self-employed households at given level of income parameter information Data: 5-year periods Dependent variable: ln(c) Variable Year Estimation St. error T-value P- value L95CL U95CL SE - uninc ,029 0,022 1,358 0,175-0,013 0,073 SE - uninc ,056 0,022 2,474 0,013 0,012 0,101 SE - uninc ,054 0,024 2,286 0,022 0,008 0,101 SE - inc ,058 0,022 2,617 0,009 0,015 0,102 SE - inc ,046 0,023 2,055 0,040 0,002 0,091 SE - inc ,017 0,023 0,774 0,439-0,028 0,062 SE ,046 0,017 2,809 0,005 0,014 0,079 SE ,054 0,017 3,254 0,001 0,022 0,088 SE ,038 0,018 2,186 0,029 0,004 0,071 Note: Control variables include age of the household head (and age squared), a dummy for single family house, number of children, a dummy for metropolitan areas and average years of schooling in the household Figure A.3. True gross income as percentage of reported gross income 5-year periods 160% 150% 140% 130% 120% 110% Self employed 100% 90% 80% Note: 2005 stands for the data set including year , 2006 for and 2007 for

23 Figure A.4 True entrepreneurial income as percentage of reported entrepreneurial income 5-year periods 200% 180% 160% 140% 120% Self employed SE inc** 100% 80% Note: 2005 stands for the data set including year , 2006 for and 2007 for Figure A.5. Unreported income expressed as share of true entrepreneurial income 5-year periods 50% 45% 40% 35% 30% 25% 20% 15% Self employed SE inc** 10% 5% 0% Note: 2005 stands for the data set including year , 2006 for and 2007 for

24 Table A.3. Reported income of self-employed individuals in relation to wage earners controlling for household characteristics parameter information Data: Single years Dependent variable: ln(y) Y: Wages plus entrepreneurial income Variable Year Estimation St. error T-value P-value L95CL U95CL SE - uninc ,350 0,129-2,651 0,008-0,593-0,088 SE - uninc ,457 0,102-4,307 <,0001-0,641-0,239 SE - uninc ,481 0,1-4,494 <,0001-0,647-0,254 SE - uninc ,371 0,104-3, ,574-0,168 SE - uninc ,719 0,099-7,245 <,0001-0,915-0,525 SE - uninc ,344 0,096-3, ,551-0,174 SE - uninc ,651 0,129-5,069 <,0001-0,904-0,399 SE - inc ,141 0,078-1,795 0,073-0,294 0,013 SE - inc ,118 0,078-1,51 0,131-0,271 0,035 SE - inc ,163 0,085-1,908 0,057-0,329 0,004 SE - inc ,001 0,082-0,009 0,993-0,162 0,160 SE - inc ,08 0,073 1,094 0,274-0,063 0,224 SE - inc ,015 0,074 0,2 0,841-0,129 0,159 SE - inc ,146 0,077-1,909 0,057-0,296 0,004 SE ,207 0,069-2,989 0,003-0,339-0,070 SE ,262 0,064-3,946 <,0001-0,379-0,127 SE ,290 0,067-4,513 <,0001-0,433-0,171 SE ,149 0,066-2,298 0,022-0,283-0,022 SE ,206 0,061-3,437 0,001-0,327-0,089 SE ,119 0,06-2,194 0,028-0,250-0,014 SE ,284 0,067-4,296 <,0001-0,417-0,155 24

25 Variable SE - uninc. SE - uninc. SE - uninc. SE - uninc. SE - uninc. SE - uninc. SE - uninc. Year Y: Total factor income Estimation St. error T-value P-value L95CL U95CL ,264 0,127-2,077 0,038-0,513-0, ,622 0,099-6,272 <,0001-0,816-0, ,627 0,097-6,438 <,0001-0,818-0, ,362 0,106-3,392 0,001-0,571-0, ,606 0,094-6,393 <,0001-0,791-0, ,453 0,091-4,935 <,0001-0,633-0, ,495 0,125-3,935 <,0001-0,741-0,248 SE - inc ,044 0,077-0,567 0,571-0,196 0,108 SE - inc ,041 0,077-0,533 0,594-0,193 0,111 SE - inc ,017 0,084-0,196 0,845-0,181 0,148 SE - inc ,126 0,084 1,481 0,139-0,040 0,291 SE - inc ,246 0,069 3, ,110 0,382 SE - inc ,185 0,072 2,569 0,01 0,043 0,327 SE - inc ,043 0,074 0,573 0,567-0,103 0,189 SE ,109 0,067-1,604 0,109-0,242 0,024 SE ,28 0,063-4,413 <,0001-0,404-0,155 SE ,295 0,065-4,468 <,0001-0,424-0,165 SE ,066 0,068-0,967 0,334-0,200 0,068 SE ,052 0,057-0,905 0,366-0,165 0,061 SE ,061 0,058-1,034 0,301-0,176 0,054 SE ,1 0,065-1,532 0,126-0,228 0,028 Note: Control variables include age of the household head (and age squared), a dummy for single family house, number of children, six dummies for H-region, average years of schooling in the household and a full set of (feasible) industry dummies (maximum 100) 25

26 Table A.4. Reported income of self-employed individuals in relation wage earners controlling for household characteristics parameter information Data: 5-year periods Depedent variable: ln Y Y: Wages plus entrepreneurial income Estimation Variable Year St. error T-value P-value L95CL U95CL SE - uninc ,461 0,046-9,996 <,0001-0,551-0,370 SE - uninc ,468 0,044-10,558 <,0001-0,555-0,381 SE - uninc ,491 0,045-10,721 <,0001-0,580-0,401 SE - inc ,061 0,035-1,729 0,084-0,130 0,008 SE - inc ,032 0,035-0,909 0,363-0,100 0,036 SE - inc ,040 0,034-1,142 0,254-0,108 0,028 SE ,222 0,028-7,673 <,0001-0,279-0,165 SE ,212 0,028-7,463 <,0001-0,267-0,156 SE ,217 0,028-7,600 <,0001-0,273-0,161 Y: Total factor income Variable Year Estimation St. error T-value P-value L95CL U95CL SE - uninc ,510 0,045-11,285 <,0001-0,599-0,422 SE - uninc ,538 0,043-12,420 <,0001-0,623-0,453 SE - uninc ,512 0,044-11,479 <,0001-0,600-0,425 SE - inc ,061 0,035 1,757 0,0789-0,007 0,130 SE - inc ,105 0,034 3,029 0,0025 0,037 0,173 SE - inc ,121 0,034 3,520 0,0004 0,053 0,188 SE ,161 0,028-5,640 <,0001-0,217-0,105 SE ,154 0,028-5,494 <,0001-0,209-0,099 SE ,120 0,028-4,272 <,0001-0,175-0,065 Note: Control variables include age of the household head (and age squared), a dummy for single family house, number of children, six dummies for H-region, average years of schooling in the household and a full set of (feasible) industry dummies (maximum 100) 26

27 Figure A.5. Reported income of self-employed individuals in relation to wage earners controlling for household characteristics Dependent variable: Y = wage plus entrepreneurial income 0,0% 10,0% ,0% 30,0% 40,0% Self employed 50,0% 60,0% Note: 2005 stands for the data set including year , 2006 for and 2007 for Figure A.6. Reported income of self-employed individuals in relation to wage earners controlling for household characteristics Dependent variable: Y = total factor income 20,0% 10,0% 0,0% 10,0% 20,0% 30,0% 40,0% 50,0% 60,0% Self employed Note: 2005 stands for the data set including year , 2006 for and 2007 for

28 28