metadata: authors: 0: author: Garriga,Pablo
1: author: De Gouvea Scot De Arruda,Thiago
count: Lithuania
docna: 0: docna: Corporate Responses to Size-Based Tax Rates
            in Lithuania
docty: Policy Research Working Paper
theme: Tax policy,Economic Policy,Fiscal Policy
abstracts: cdata!: This paper studies how firms respond to
            differential, size-based tax rates using administrative tax
            data in Lithuania. Exploiting a notch in the tax schedule
            faced by corporations, it documents strong behavioral
            responses to tax incentives&#x2014; revenue elasticity
            is estimated at 0.35 and cost elasticity at &#x2212;1.3,
            implying a large total profit elasticity of 7.4. It then
            leverages the panel structure of the data to provide
            insights on the dynamic effects of these tax incentives.
            Firms located close to but below the notch report
            systematically lower revenue growth in the short term, but
            the effects dissipate over time.
display_title: Corporate Responses to Size-Based
            Tax Rates in Lithuania
listing_relative_url: /research/2023/06/34102106/corporate-responses-size-based-tax-rates-lithuania
topicv3: Private Sector Development m1326060 1921,Public Finance m1326315 713,Taxation m1327615 1121
publishtoextweb_dt: 2023-06-26T00:00:00Z
dois: 10.1596/1813-9450-10500
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
author_keys: 0: author_key: 1471773
1: author_key: 1295861
model_extractions: Policy Research Working Paper 10500 Corporate Responses to Size-Based Tax Rates in Lithuania _Pablo Garriga Thiago Scot_ Development Impact Evaluation Group & Latin America and the Caribbean Region June 2023
Policy Research Working Paper 10500

# **Abstract**

This paper studies how firms respond to differential, sizebased tax rates using administrative tax data in Lithuania. Exploiting a notch in the tax schedule faced by corporations, it documents strong behavioral responses to tax incentives— revenue elasticity is estimated at 0.35 and cost elasticity at −1.3, implying a large total profit elasticity of 7.4. It then leverages the panel structure of the data to provide insights on the dynamic effects of these tax incentives. Firms located close to but below the notch report systematically lower revenue growth in the short term, but the effects dissipate over time.

This paper is a product of the Development Impact Evaluation Group, Development Economics and the Office of the Chief Economist, Latin America and the Caribbean Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at pgarriga@worldbank.org and tscot@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Corporate Responses to Size-Based Tax Rates in Lithuania<sup>∗</sup>

Thiago Scot<sup>†</sup> Pablo Garriga<sup>‡</sup> Keywords: Corporate Taxation, Tax compliance, Firms & Productivity, Lithuania JEL Codes: H25, H32

> ∗The results in this paper were produced in the context of a World Bank project with funding by the European Union in cooperation with the European Commission’s DG REFORM. The views expressed herein can in no way be taken to reflect the official opinion of the European Union. The findings, interpretation and conclusions expressed in this paper do not necessarily reflect the views of the Executive Directors of the World Bank, the European Commission or the Government of Lithuania. We thank Statistics Lithuania, in particular Edita Baltuse and Aleksandra Golubovic, for the collaboration to produce the data used in this study. We thank Alberto Leyton, Cristina Savescu, Munawer Kwahja, Dzelila Kramer, Louise Jensen, Vytautas Adomatis and Vaidas Navickas for continued feedback and guidance during the project. We also thank Pierre Bachas and Camille Semelet for their fundamental role in the initial stages of this project. Javier Feinmann provided excellent research assistance.

> †The World Bank, tscot@worldbank.org

> ‡The World Bank, pgarriga@worldbank.org
# **1 Introduction**

The existence of preferential tax rates based on firm size is usually justified on the grounds of providing support for entrepreneurs and small and medium enterprises (SMEs). However, they may also provide the wrong incentives for some firms that may try to remain small in order to take advantage of the special treatment. On the one hand, there exists broad evidence in the economics literature that sizedependent policies (not only tax policy) can affect the growth of firms: providing strong benefits for small firms might discourage them from becoming larger (Bachas, Fattal Jaef, and Jensen 2019; Asatryan and Peichl 2017). On the other hand, it is an empirical question whether any specific size-dependent policy is enough of a deterrent for firms’ growth.

In this paper we study how firms in Lithuania respond to a _notch_ in the corporate income tax (CIT) schedule. The main feature of the CIT in this setting is that firms face two possible tax rates on their profit: a standard 15% rate and a reduced 5% rate for companies with fewer than ten employees and declaring turnover below €300,000. This sudden increase in average tax rates when firms declare slightly higher turnover generates strong incentives to reduce declared turnover. We document the existence of a _static response_ —firms respond to differential tax rates in the short run in order to stay below the threshold—and provide suggestive evidence of a _dynamic response_ —firms bunching in one period are more likely to report lower revenue growth in subsequent periods.

We use novel administrative tax data covering the universe of limited liability corporate taxpayers in Lithuania between 2015 and 2020. The data contain all line items required to file the CIT as well as firm characteristics (e.g., business structure, location, number of employees). Crucially, we are able follow firms across years, allowing us to construct a panel of 600,000 firm-year observations.

In the first part of the paper we document static responses in two dimensions. First, firms respond to the incentives that are present in the tax schedule by bunching below the €300,000 turnover threshold—we see an excess number of firms declaring turnover precisely at that level. However, this is not the only margin that firms have to respond. The tax is designed in such a way that the variable which determines the tax rate (turnover) is not the tax base (profits)—i.e., the amount of _turnover_ (above or below €300,000) determines the fraction of _profits_ that should be paid in taxes. Therefore, firms have more than one option to respond to tax incentives: they can report less turnover to keep a lower tax rate or, if if facing a higher tax rate, over-report costs to reduce profits. We show both responses exist 2
# in the data.

We follow other studies in the literature (e.g. Saez (2010), Kleven (2016), Bachas and Soto (2021), among others) to estimate the behavioral responses of firms and recover estimates of the elasticities. We estimate that firms reduce their turnover by up to €32,000 to locate below the threshold and face the lower tax rate. That is the key quantity that allows us to recover the revenue elasticity: a 1% increase in the tax rate decreases reported turnover by 0.35%. We then show that firms above the threshold, and therefore facing higher average tax rates on their profits, substantially reduce their declared profits: costs change linearly with reported turnover, but they "jump" around the threshold where the tax rate increases, allowing us to estimate the elasticity of costs. We find that costs are much more elastic than turnover: firms change their reported costs by 1.3% when faced with a 1% increase in profit taxes. Putting these two results together, we arrive at the total profit elasticity of 7.4—significantly higher than the range estimated for firms in Costa Rica by Bachas and Soto (2021), for example.

In the second part of the paper we document dynamic responses. We provide evidence that in the short run (from one year to the next) some firms immediately below the threshold will report systematically lower growth than other firms in the economy to avoid paying higher taxes. Specifically, the median reported turnover growth for firms declaring turnover between €100,000 and €500,000 is between 1% and 2%, except for those who declare turnover between €280,000 and €300,000 (right below the threshold), whose median turnover growth is zero. On the mediumrun, we document that these initial differences in growth matter, such that average annualized growth in a five-year period is still lower for those starting below the threshold. Our results do not suggest, however, that firms will be "stuck" below the turnover threshold where rates increase—over time, a large share of these firms will cross the threshold and face higher tax rates on their profits.

This paper builds on several strands of the public finance literature. First, it contributes to the bunching literature.<sup>1</sup> Multiple studies document similar policy designs and convey the same message: taxpayers are keenly aware of large changes in incentives generated by the tax system and will be strategic in their response, altering their behavior to avoid facing higher tax rates. Exploring the same kind of increase in average corporate tax rates as a function of turnover in Costa Rica, Bachas and Soto (2021) document many of the same behavioral responses seen in Lithuania: firms bunch below the threshold for preferential rates and report lower

> 1Bunching has been extensively documented in the economics literature; Kleven (2016) provides an extensive discussion on the economic theory and applications of bunching responses to notches.

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profits when facing higher rates. Kleven and Waseem (2013) also document similar behavior from personal income tax filers in Pakistan: when facing large increases in tax liability in arbitrary thresholds, agents bunch below them. Londoño-Vélez and Ávila-Mahecha (2019) show taxpayers’ bunching behavior in response to a notch on wealth taxes in Colombia. The extent to which these responses are real responses (i.e. changes in economic activity) or misreporting (changes in declared behavior, but not in real activity) is less clear, although all these studies suggest that at least in part misreporting plays an important role (Almunia and Lopez-Rodriguez 2018).

Second, we contribute to burgeoning empirical research on the effects of tax policy on firms’ growth. There exists ample evidence that firms’ real investment and growth respond to changes in the tax base (Ohrn 2019; Ohrn et al. 2022; Cummins, Hassett, and Hubbard 1994; Ohrn 2018; Zwick and Mahon 2017; Bilicka 2020). The dynamic effects we observe, nonetheless, might be driven not by decrease in real activity but by misreporting. Aghion et al. (2023) document how revenue thresholds that affect tax payments and simplicity generate bunching over time for self-entrepreneurs in France, and argue that evasion plays an important role.

The paper is organized as follows. Section 2 provides details about the tax system in Lithuania and discusses our data sources. Section 3 documents the shortrun response on turnover and profits and derives the elasticity parameters. Section 4 studies the long-run effect on firm growth. Section 5 concludes.

# **2 Context and data**

**Context** . The Lithuanian tax system is characterized by its high degree of schedularity, whereby different legal entities file taxes under various regimes based on their business characteristics. Private companies, which comprise the largest group,<sup>2</sup> are subject to the Corporate Income Tax (CIT), which features two possible tax rates: a standard 15% rate and a reduced 5% rate for companies with fewer than ten employees and declaring turnover below €300,000.<sup>3</sup> To file their taxes, companies

> 2There are about 83,000 private companies followed by about 20,000 small partnerships. Other categories include agricultural companies, cooperative partnerships or companies, public companies, professional partnerships of lawyers, municipal enterprises and state-owned companies, and public institutions.

> 3The preferential tax rate for SMEs dates back to 2000 and its thresholds have shifted over time. For the periods 2000-2001 and 2012-2014 the income threshold was set at LTL 1,000,000 and the employee requirement was set at 10. Conditions were momentarily relaxed during the period 2002-2011 with an income threshold of LTL 500,000 and employee requirement of 50. The €300,000 income cutoff was introduced in 2015 when Lithuania switched its currency to the Euro— given the exchange rate set at LTL 3.4528, this amount was roughly equivalent to LTL 1,000,000. Notably, there are no other policies utilizing the income or employee thresholds as a reference that could potentially impact firm behavior.

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submit their tax returns electronically through a self-reported system, with the tax authority conducting compliance assessments to ensure corporations fulfill their tax obligations.<sup>4</sup>

**Data** . We use microdata on the universe of limited liability corporate taxpayers between 2015 and 2020 to characterize firms’ responses to the existence of different CIT rates.<sup>5</sup> In Table 1 we present key descriptive statistics for the data. The entire panel is composed of almost 600,000 firm-year observations, with between 90,000 and 105,000 filers per year in the more recent periods. We highlight a key change in the composition of limited liability firms in the period.<sup>6</sup> In 2015 over 90% of them were joint stock companies (UAB) and 7% were small partnerships—the remaining entities are a mix of agricultural companies, cooperatives and a range of public institutions. Between 2015 and 2020, the share of small partnerships increased by 12 p.p., with an equivalent decrease in the share of private companies. Geographically, 80% of firms are from the three main regions of the country—Vilnius, Kaunas and Klaipeda. As in most countries, the distribution of firms is characterized by a long right-tail of large firms and a majority of small ones. While the average turnover (gross revenue) in 2020 was close to €1 million, the median was below €50,000 and over 15% of firms reported zero turnover. Approximately 20,000 firms (or 20% of those filing corporate income taxes) report turnover above the €300,000 threshold that defines larger firms (those not receiving the preferential 5% income tax rate). Across years, the average tax liability is quite stable at approximately €13,000 (median below €1,000). The same dispersion is observed for number of employees: the average number is 62 but the median is only 2 employees.<sup>7</sup>

> 4The tax authorities focus their enforcement activities on taxpayers with a higher likelihood of non-compliance, utilizing a risk-based approach that encompasses a variety of methods, including general risk reviews, questionnaires, reviews of specific issues, and tax audits (see https://taxsummaries.pwc.com/lithuania/corporate/tax-administration).

> 5To streamline our analysis, we have chosen to exclude other corporate structures, such as sole proprietorships, general partnerships, and limited partnerships that file a different tax form. Furthermore, we have limited our time frame to years when the threshold remained constant, omitting observations between 2011 and 2014.

> 6That change in the nature of corporate entities is likely a result of incentives in the personal income tax system, which provides benefits for owners of small partnerships. This illustrates the important links between Personal Income Taxes (PIT) and the choice of corporate form.

7While the median number of employees is stable over time, the average increases steeply from about 11 in 2015 to over 60 in 2020. That is driven by an increase in the number of very large firms: the largest firm by number of employees in 2015 has approximately 45,000 employees and only 5 firms have more than 10,000 employees. In contrast, the largest firm in 2020 has almost 100,000 employees and almost 100 firms declare 10,000 employees or more.

5
# **3 to the in** **_Bunching_ responses change average tax rate**

We start this section documenting that, consistent with the incentives discussed above, firms behave strategically and systematically report turnover below the €300,000 threshold in order to avoid facing a higher tax rate. These bunching responses can be easily detected through visual inspection in Figure 1, where we present the distribution of declared turnover for all firms with revenue between €280,000 and €300,000 in the period 2015-2020.<sup>8</sup> Similar to most countries, we observe a large number of very small firms and a limited number of firms with large turnover—reflected in the downward slope of the density presented. Precisely around the €300,000 threshold, nonetheless, we see an unusual spike: many firms declare turnover exactly below that level. We can also see a "missing" mass of firms immediately above the threshold: this response is precisely what we should expect given the incentive involved. Firms which would have reported turnover slightly above the threshold instead declare below it in order to benefit from the reduced rate.

Bunching could be driven by two different underlying behaviors: real production decisions and/or misreporting. First, given the large increase in tax liability when crossing the threshold, firms have a real incentive not to increase their turnover. To illustrate the incentives involved, consider a firm with turnover of €299,900 and profit of €15,000. That firm faces a 5% tax rate and will pay €750 in taxes. If the same firm increases its sales by €101 and declares a turnover slightly above €300,000, it now faces a 15% tax rate on all of its profit and, keeping profits constant, would face a tax liability of €2,250. In other words, a very small increase in turnover leads to a very large (€1,500) increase in tax liability. In that sense, any profits gained from an extra €101 sales will be negligible next to the tax liability increase of €1,500 from facing the higher rate. So a store might decide not to sell another product to a customer or a provider might decide not to work an extra day to avoid generating revenue that will push them above the threshold. Second, firms might decide to still realize extra revenue that push their _true turnover_ above €300,000, but not report that to the tax authority. Under this model, firms declaring turnover slightly below the threshold are likely misreporting part of their revenue. In reality, bunching is likely driven by a mix of the two behaviors and it is not always simple to

> 8In Figure A1, we present the same distribution but zoomed out to show revenues between €50,000 and €1,000,000. This alternate figure conveys the idea of exactly how skewed the firm-size distribution actually is.

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disentangle and quantify the contribution of each.<sup>9</sup> In the next section we quantify firms’ bunching responses and show how we can use them to learn about underlying firm behavior.

# **3.1 Turnover response**

In order to estimate how many firms were strategically locating below the threshold to avoid the increase in average tax rate, we follow other studies in the literature of _bunching_ responses (e.g. Saez (2010), Kleven (2016), Bachas and Soto (2021)). We provide more details about the methodology in Appendix A, but the intuition behind the exercise is that we consider what a "usual" distribution would look like in the absence of the incentive provided by differentiated tax rates. We do that by first excluding the region affected by the bunching behavior and "fitting" a curve to the observed distribution. We then extrapolate that prediction to the excluded region and obtain our estimates of bunching as the difference between the observed distribution of firms and the predicted values.

Firms reduce their reported turnover by more than €30,000 to avoid facing the higher statutory tax rate. In Figure 2 we present our estimates for the sample consisting of all firms filing between 2015 and 2020. The grey, smooth line in the figure is the fitted curve to the observed distribution of firms. Below the €300,000 threshold, we estimate an excess of approximately 1,150 firms—the shaded area in green. This mass is equivalent to almost five times the predicted number of firms we "should" be seeing immediately below the threshold, about 250 firms. If we observe this excess number of firms locating below the threshold, we should also observe a similar missing number of firms above, which we illustrate in the graph using the grey shaded area. The green and grey shades have the same area, since by our assumptions the firms that bunch below the threshold are coming from immediately above. In the graph we present our estimate of the _marginal buncher_ : the firm with highest turnover that still decides to locate below the threshold. We estimate that number to be _yu_ = €332,000: firms decrease their declared turnover by up to €32,000 to avoid the increase in tax liabilities.

We estimate that between 150 and 270 firms are _bunching_ below the threshold each year. In Figure 3 we reproduce the same exercise separately by year. We highlight two features of that exercise. First, we note that the bunching behavior is increasing over time. For 2015, for example, we estimate an excess number of 140

> 9Almunia and Lopez-Rodriguez (2018) and Lobel, Scot, and Zúniga (2023) use third-party reporting to show that, in Spain and Honduras, respectively, bunching behavior is partially driven by misreporting.

7
firms below the threshold or four times the predicted mass of firms. That number increases to approximately 250 in 2018-2020 (six to seven times the predicted mass). This pattern is consistent with firms learning about the new incentives after the change in the notch location with the introduction of the euro in 2015 and gradually adjusting their behavior over time. Second, bunching estimates are quite stable in the last two years of the period: we observe an excess mass between five and six times what is predicted and firms are decreasing their reported turnover by approximately €25,000-30,000 each year.

The bunchers are high-profit firms that gain more from the lower tax rate. Not all firms face the same incentives to locate below the turnover threshold where the statutory tax rate increases. Consider for example firms facing losses. For them, paying 5% or 15% of zero taxable income is the same, so we should not expect them to respond by declaring lower revenue. Now consider two firms with the same turnover of slightly more than €300,000, one with a 1% profit margin and another with 10% margin. The low-profit firm would owe 15%*€3,000 = €450 in taxes staying above the threshold and 5%*€3,000 = €150 if they report below, therefore saving €300. The high-profit firm would owe €4,500 above and €1,500 below, saving €3,000 by bunching. The incentives to bunch are much larger for high-profit firms, so we should expect to see more of them bunching. This is precisely what we document on Figure 4: firms slightly below the threshold report a much higher profit margin, of up to 15% on average, when compared to firms with lower or higher revenue. This is a purely composition effect: bunchers are high-profit firms, so we observe a much higher average profit margin where they locate.

# **3.2 Profit-reporting response**

An additional margin of response to higher tax rates is the reporting of profits. In the previous section we documented one dimension of taxpayers’ response to the tax incentives generated by the 5% and 15% tax rate regimes: firms that would have reported turnover above the €300,000 threshold instead bunch below that level to avoid the increase in tax liability. In this section we document a second behavioral response to the higher tax rate regime: firms changing their reported taxable income.

Higher tax rates on profits encourage firms to overreport their true costs. Firms whose turnover is significantly above the €300,000 threshold will most likely not bunch below that level: either by decreasing their sales or misreporting their turnover, it is probably too costly for them to declare much lower turnover. Nonetheless, the higher tax rate on their income creates another incentive. Under a 5% 8
income tax rate, increasing the reported costs (deductions) by €1 leads to a €0.05 decrease in tax liability. Under the 15% tax rate regime, by contrast, the same increase in reported costs will reduce tax liability by €0.15. Since the incentive of firms to report taxable income changes so starkly, it is a natural question to investigate whether firms also change their reported profit margins.

In Figure 5, we document that seems to be the case: firms located slightly above the €300,000 threshold (liable for a 15% tax rate) declare substantially lower profit margins when compared to those facing the 5% tax regime. On the left-hand side of the figure, we see that firms declaring turnover below €280,000 (those below the region where we observe bunching) declare pre-tax profit margins on the range of 5% to 7%. Absent the change in tax policy, there is no reason to believe that firms that are slightly larger, with turnover around €350,000 for example, should have systematically different _pre-tax profit margins_ . But that seems to be the case in the data: firms with turnover above €320,000 declare on average profit margins close to 2%-3%—three to four percentage points lower than those facing the reduced tax rate regime. This behavior is consistent with what has been seen in other contexts such as Costa Rica (Bachas and Soto 2021) where firms face similar incentives. That stark change in declared pre-tax profit margins around the threshold is consistent with a model where firms can over-report part of their costs to reduce their tax liability: when the incentives to do so become stronger due to an increase in tax rates, firms respond accordingly by increasing over-reporting.

In Table 2, we estimate a regression model that allows us to quantify exactly how much firms reduce their reported profit margins when facing a higher tax rate. Specifically, our regression has profit margin as dependent variable and evaluates whether, controlling for firm and year fixed-effects, as well as a linear trend of turnover, firms facing the 15% tax rate regime report lower margins. The answer is a compelling yes: we estimate that, compared to firms facing the 5% regime, they declare 5 percentage points lower profit margins—a similar result to what we observe in Figure 5.

# **3.3 Recovering elasticities using behavioral responses**

When considering how firms change their behavior in response to tax policy, one key parameter to be considered is elasticities. The elasticity of (reported) turnover, for example, is by how much (in percentage terms) firms change their reported turnover when facing a 1% increase in the tax rate. An extensive literature has shown how one can recover the reported profit elasticity of firms by using their responses to tax notches such as the one we study in Lithuania. We provide detailed explanation of 9
the methodology in Appendix A. The intuition for these exercises follows directly from the previous analysis: when firms face an increase in their turnover beyond the €300,000 threshold, they face a higher tax rate and respond, as we have shown, by changing _both_ their reported revenue (bunching) and their reported costs (driving a change in profit margins). We explore these behavioral responses and obtain their implied elasticities.

When facing a 1% increase in the profit tax rate, firms around the notch reduce their reported profits by 7% to 10%. We summarize our findings in Table 3, separately for each year and for all years (2015-2020) pooled together. This is our preferred specification since it allows us to have a larger sample. For that period, as presented above, we estimate that firms reduce their turnover by up to €32,000 to locate below the threshold and enjoy lower tax rates. That is the key quantity that allows us to recover the elasticity of turnover, which we estimate to be 0.35—a 1% increase in turnover taxes decrease reported turnover by 0.35%.<sup>10</sup> To estimate the elasticity of costs, we exploit the fact that firms below and above the €300,000 threshold report systematically different costs, which explains the changes in levels of profit margins we documented in the previous section. In Figure 6, we show that costs change linearly with reported revenue—but they "jump" around the threshold where the tax rate increases from 5% to 15%, allowing us to estimate the elasticity of costs. Consistent with findings from other settings (Bachas and Soto 2021), we find that costs are more elastic than revenues: firms change their reported costs by 1.3% when faced with a 1% increase in profit taxes. Putting these two results together, we can arrive at the total profit elasticity of 7.4 for the pooled years. We note that across years there is quite a substantial variation in our estimated elasticities, particularly for 2017 and 2018, when we estimate extremely high elasticities. For the last two years in our sample and the pooled period our estimates are more stable at 7% to 10%.

# **3.4 Robustness exercises**

We perform a series of robustness exercises meant to reinforce the findings discussed so far.

**Extended time frame.** The preferential 5% tax rate for SMEs already existed before the introduction of the euro in 2015: firms declaring revenue below 500,000 litas in 2011 and 1,000,000 litas in 2012-2014 also benefited from the reduced rate.

> 10While there are no explicit turnover taxes for corporations in Lithuania, the increase in average profit taxes above the threshold is equivalent to a turnover tax: by increasing their turnover, firms face a larger tax liability.

10
In Figure A2, we show that the same bunching behavior observed in 2015-2020 was also present to some extent in the previous period. In 2011, when the threshold was 500,000 litas, we observe some amount of bunching at that level, and the bunching moves to 1,000,000 litas when the policy changes in 2012-2014. Immediately after the introduction of the Euro, the bunching again moves from the equivalent 1,000,000 litas to the new €300,000 threshold—reinforcing the message that the bunching behavior is indeed a response to the change in tax rates.

**Balanced panel of firms.** In our main analyses, we use an unbalanced panel of firms - not all firms file every year, so our sample is changing every year. While there is no reason to believe that firms are exiting or entering precisely around the €300,000 threshold, we replicate our main finding of the bunching behavior for a balanced panel of firms that file every year in Figure A3. The result is qualitatively similar: we observe the same behavior of an excess number of firms declaring turnover precisely below the level that separates the 5% and 15% tax rate regimes.

**Number of employees and bunching behavior.** While our focus throughout this report is on the turnover threshold that separates the two regimes, the number of employees is also a determinant of the tax rate faced by firms: the preferential 5% tax rate is only applied to firms that declare less than €300,000 in turnover and also declare fewer than 10 employees on average throughout the year. In Figure A4, we show that the level of employment matters for the bunching behavior. The figure presents a heatmap, where lighter colors indicate bins (intervals of employment and turnover) where there are more taxpayers. First, note the clear bunching pattern around the €300,000 level: the bright colors to the left of the threshold immediately disappear to the right of it. But note also that this behavior only exists for firms with fewer than 10 employees: for those above, there seems to be no bunching in turnover, consistent with the fact that larger firms do not benefit from the 5% tax rate, regardless of their turnover level. There is also some evidence that firms bunch below the 10 employee level, with a slight concentration of firms below that level. Since the vast majority of firms are much smaller than that, however, it is harder to precisely estimate the importance of that behavior.

**Economic sectors.** In Figure A5 we document that bunching behavior is widespread but not equal across economic sectors. We observe particularly large responses in construction, wholesale, real estate and other services. Potentially surprising, we actually see no bunching in retail, and restaurant and hotels—sectors that are often seen as at-risk for misreporting taxes.

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# **4 incentives: does the notch re- Dynamic affect ported firm growth?**

A firms’ response to the tax notch can be static or dynamic. The previous sections provided evidence that firms respond strategically to the threshold where tax rates change and locate below the notch. However, that is a _static response_ : firms that, in any given year, would have located above the threshold in the absence of tax policy, decide to locate below. A different question is whether the existence of the notch affects the growth path of smaller firms.

It is not easy to answer whether the notch generated by tax policy in Lithuania hampers firm growth. To start, it is not obvious to determine which firms are affected by the existence of the threshold. It is expected that firms with revenue slightly below €300,000 are aware of the change in incentives if they grow past that limit. But it is possible that all firms with turnover below €300,000 take those incentives into consideration and therefore adjust their behavior considering the future possibility of growing "too much" and starting to pay taxes. In this section we provide evidence that in the short run—that is, from one year to the next—some firms report lower growth when facing the immediate possibility of crossing the threshold. For longer periods the evidence is less compelling and, therefore, we avoid making any claims about the effects of this specific notch on the long-term growth pattern of SMEs.

For the short run response, we find that firms immediately below the threshold in one year will report systematically lower growth than other firms in the economy to avoid paying higher taxes. In Figure 7 we present how the growth pattern of firms differ across different levels of turnover for the period 2016-2020. Notice that the pattern of growth is very similar at most turnover levels: when we observe a firm in year _t-1_ declaring turnover between €100,000 and €500,000, the median turnover growth expected in the following year is between 1% - 2%. There is one very stark exception in that figure: if we observe a firm declaring turnover between €280,000 and €300,000, immediately below the notch, the median turnover growth observed in the following year is zero - more than half of firms in that turnover bin will declare zero or negative growth the following year. An alternative way to visualize that change in behavior is looking at the distribution of firm growth in each bin, presented in Figure A7. While the density of growth is very similar for bins farther from the threshold, those immediately below (€280,000 - 300,000) have disproportionate growth below or at zero - compared to other firms, there is a clear lack of firms with positive but small growth. Given the incentives for firms not to 12
grow above the threshold, this is compelling evidence that, at least in the short run, firms avoid growing (at least on their declared turnover to the tax authority) when approaching the threshold.

Evaluating the medium- to long-term growth effects of the tax notch is a more challenging task, precisely because it is not clear which firms will eventually be affected. We provide evidence on the medium-term growth pattern for two specific groups of firms: those that in 2015 declared turnover slightly below the €300,000 and those that in the same year declared turnover slightly above. The idea is that those below are likely to consider the incentives provided by the threshold and grow less, while those above will not be affected by it.

Over a five year period, firms starting slightly below the threshold grow less than those above, but the effect is concentrated in the initial years. In Figure 8 we present the median growth rate for these groups of firms, for each year between 2016 and 2020. For the 2016, we observe the same pattern as documented for short-term growth above: while firms with turnover above €300,000 declare a medium growth rate of 2%, those below declare virtually zero growth. The difference in growth rates is also observed in the second year, when larger firms register growth rate of 5% vs. 2% for those below the threshold. Nonetheless, after the second year the picture becomes less clear: firms below the threshold grow slightly more in 2018, then less in 2019 and negative but smaller in magnitude growth rates in 2020 (where most firms declare negative growth rates, likely due to the shock of Covid-19 pandemic).

These differences in the yearly growth in the first two periods are sufficient to generate some medium-term effects. When we observe the median growth in the full period 2015-2020, the median growth of those starting below the threshold is almost zero while those above the threshold grow by about 1%. The picture is similar if we exclude 2020, when firms were severely affected by the Covid-19 crisis. While the median growth is much higher for the two groups, the gap between them is similar: firms starting above €300,000 grew by 3% while those below grew less than 2%.

An alternative way to assess the dynamic effects of the tax notch is to ask whether firms below the threshold are likely to get "stuck" in the €300,000 level. In Figure A8 we compute the share of firms declaring turnover below the threshold in one year that end up above the threshold in the following year. For firms with revenue between €260,000-300,000 in one year, almost 40% will declare turnover above that level in the next year. This tells us that several firms will not be deterred by the increase in tax rate and will grow into the higher tax-rate bracket. But this cannot tell us what we _should expect_ growth to be, in the absence of the tax notch.

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To provide evidence on that question, in Figure A9 we show, for different horizons, what is the share of firms declaring growth of €20,000 or more. The orange line shows that, on a one-year period, those declaring revenue in the interval €280,000300,000 are much less likely to declare growth above that level than other firms with lower or higher revenues—meaning that they are more likely to stay below the threshold. On a five-year period (2015-2020), however, that effect disappears: firms starting below the threshold are no less likely to have grown enough to surpass the threshold providing beneficial tax rate. This is additional evidence that, while the notch seems to have very meaningful effects in the short run, in the medium-run it seems to be less of a stark deterrent to the growth of all small firms.

# **5 Conclusion**

This report studies how legal entities in Lithuania respond to the existence of differential tax rates based on firm size by leveraging administrative microdata on the universe of limited liability corporate taxpayers. Corporations in Lithuania face an increase in the average tax rate when they declare turnover above €300,000—this notch in the tax schedule creates a sudden increase in average tax rates from 5% to 15%. The use of preferential tax treatment targeted towards entrepreneurs and small and medium enterprises as the one described above is usually justified on the grounds of providing support to firms in their early stages<sup>11</sup> . However, this type of policy may also provide the wrong incentives for firms that may take advantage of the special treatment by remaining small in order to pay lower taxes. We document a clear response of firms to this policy in the short run, while this effect weakens as we extend the time horizon.

In the short run, firms respond to the incentives that are present in the tax schedule by reporting turnover such that they remain below the threshold and by overreporting costs. Firms reduce their reported turnover by up to €32,000 to avoid facing the higher statutory tax rate. This bunching response could be driven by two different underlying behaviors: real production decisions and/or misreporting. However, an additional finding suggests it is mostly misreporting. We document that higher tax rates on profits encourage firms to overreport their true costs and therefore small firms declare higher pre-tax profit margins than large firms. Absent the change in tax policy, there is no reason to believe that firms that are slightly larger should have systematically different profit margins. Therefore, this discontinuity in firms’ costs at the revenue threshold is more compatible with misreporting

> 11See for example Piza (2018).

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than real reduction in economic activity. Finally, by quantifying the response on both reported turnover (bunching) and reported costs (change in profit margins) we are able recover the reported profit elasticity of firms: when facing a 1% increase in the profit tax rate, firms close to the notch reduce their reported profits by 7-10%.

The evidence of firms responding in the medium- to long-run is less clear. The main difficulty faced when trying to determine how the differential tax rates affect the long term growth of firms is that it is not obvious which firms are affected by the existence of the threshold (even firms far from it may adjust their behavior in response) which complicates the definition of a group that can serve as a benchmark. We provide insights that firms facing the immediate possibility of crossing the threshold react by reporting lower growth in turnover. This effect is clear for year-on-year growth calculations, but dissipates as we consider longer time spans.

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