WPS7600 Policy Research Working Paper 7600 Taxation, Information, and Withholding Evidence from Costa Rica Anne Brockmeyer Marco Hernandez Macroeconomics and Fiscal Management Global Practice Group March 2016 Policy Research Working Paper 7600 Abstract This paper studies tax withholding on business sales, a documents the anatomy of compliance, providing novel widely used compliance mechanism which is largely measures of compliance gaps on the extensive, intensive ignored by public finance theory. The study introduces a and payment margins. It then shows that interventions withholding scheme, whereby the payer in a transaction leveraging the existing third-party information reduce these collects tax from the payee, in a standard evasion model. If compliance gaps only marginally. Coverage by a withhold- the taxpayer can fully reclaim the tax withheld, withhold- ing scheme, in contrast, is correlated with higher reported ing is irrelevant to her evasion decision. If reclaim is costly, taxable income both across firms and within firms across however, withholding establishes a compliance default. time. Quasi-experimental estimations show that a doubling To show this empirically, the analysis exploits a ten-year of the withholding rate leads to a 40 percent increase in panel of registration, income tax and sales tax records from tax payment among treated firms and a 10 percent increase 400,000 firms in Costa Rica, and over 20 million third- in aggregate revenue. The mechanisms are incomplete party information and withholding reports. The paper first reclaim of the tax withheld and reduced misreporting. This paper is a product of the Macroeconomics and Fiscal Management Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at abrockmeyer@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 Taxation, Information, and Withholding: * Evidence from Costa Rica Anne Brockmeyer, Marco Hernandez The World Bank * Corresponding author: Anne Brockmeyer, abrockmeyer@worldbank.org. Marco Hernandez: marcohernan- dez@worldbank.org. This paper is an udpate of World Bank Policy Research Working Paper 7600 (March 2016). The last version of this paper can be found at https://sites.google.com/site/annebrockmeyerworldbank/home. We are exceedingly grateful to the Ministry of Finance and the General Directory for Taxation of Costa Rica for out- standing collaboration. In particular, we are indebted to Fernando Rodriguez Garro and Carlos Vargas Duran, as well as to Laura Badilla Castro, Lorena Chacon Sanchez, Graciela Garcia Santamaria, Mercedes Padilla Delgado, Manuel Enrique Ramos Campos, Karla Salas Corrales, Ronald Solorzano Vega and Giovanni Tencio Pereira. We thank François Gérard, Henrik Kleven, David McKenzie and Joana Naritomi and seminar participants at LSE STICERD, the National Tax Association conference, Public Economics in the UK conference, and the World Bank for helpful comments. Juliana Londoño Vélez, Spencer Smith and Gabriel Tourek provided excellent research assistance. All errors are our own. 1 Introduction Developing economies are characterized by low tax-to-GDP ratios, and a dierent mix of tax instru- ments than high income countries (Besley & Persson 2013, Best et al. 2015). Withholding on rms' sales is a tax instrument that is extensively used in developing countries, and in low-compliance sec- tors in high income countries (Samanamud 2013, Soos 1990,OECD 2009).1 In a withholding scheme, the payer in a transaction withholds tax from the payee, remitting the tax to the government as an advance tax payment for the payee.2 The payer cum withholding agent can be a state agency, nancial institution, or another rm. The widespread use of withholding stands in contrast to the theoretical prediction that withhold- ing should be irrelevant to evasion. If the taxpayer can claim full credit for tax withheld, withholding is merely a dierent method of tax collection. It shifts the collection task from the tax authorities to the withholding agent, with no direct relevance for evasion decisions. In Costa Rica, the law states that tax withheld is fully creditable against a taxpayer's income or sales tax liability and can give rise to a cash refund if the amount withheld exceeds the liability. In practice, however, it is costly for the taxpayer to reclaim the tax withheld. Taxpayers incur an administrative cost to make a reclaim, they can reclaim only if they are compliant on the extensive margin, and reclaimers may face a higher audit probability. For these reasons, withholding can establish a compliance default, increasing total tax payment. This paper studies the compliance impact of withholding conceptually and empirically. We start by introducing withholding in a simple model of tax evasion following Allingham & Sandmo (1972). We show that, if the withheld tax can be fully reclaimed, withholding is irrelevant to the taxpayer's evasion decision. We then propose a model with costly reclaim, which predicts that only a fraction of taxpayers reclaim the tax withheld and an increase in the withholding rate increases reported taxable income. To test the predictions of our model empirically, we exploit various sources of quasi-experimental variation in the income and sales tax system in Costa Rica, and a nine-year panel of administra- tive tax records. We construct the Costa Rican tax register from the universe of registration and deregistration records since 2006. We match the register with income and sales tax records from the universe of rms, including both self-employed and corporations. We further match these data 1 This is distinct from withholding on wages, a tax compliance mechanism that is applied almost universally and well understood (Kleven et al. 2011). See Figure I for a preliminary analysis of the use of sales withholding by country income levels. 2 In some countries, the payee also withholds from the payer, adding tax to the invoice. 2 with over 20 million third-party and withholding records from rms' transaction partners, nancial institutions and state institutions. We match each rm with the information reports it provided and the information reports received about its activities. Our analysis is divided into two parts. In the rst part, we leverage the data to conduct a detailled anatomy of compliance.3 To our knowledge, this is the rst study to use population-wide third-party and withholding data from a developing country, and to analyze all compliance margins, including the extensive, intensive and payment margin. On the extensive margin, we nd that over 30% of tax-liable rms fail to le a self-assessment declaration for the income tax. The share of non-lers is equally high in the subsample of tax- liable rms covered by third-party information and thus denitely identied as economically active. Overall, 10% of third-party reported sales are not declared by the taxpayer. Unlike survey or macro- based measures of informality, our method uses micro-administrative data to identify compliance gaps at the margin between full informality and formality. Our estimates do not capture fully informal rms, but we argue that they identify the policy relevant segment of tax payers in which compliance can be enhanced at low cost.4 We also nd signicant compliance gaps on the intensive margin, as evidenced by under-reporting of sales compared to third-party information, and large and sharp bunching at the rst income tax kink.5 The share of under-reporters for the income tax constitutes 18% of the self-employed and 9% of corporations. In this sample of under-reporters, over 40% of third-party reported sales remain undeclared. These compliance gaps persist even several years after the relevant ling period, and despite systematic government cross-checks of third-party information with tax records.6 On the payment margin, we nd that compliance is relatively high, although a non-neglegible fraction of small rms pay their liabilities with several years of delay. Together, this evidence of non-ling, misreporting on the intensive margin and signicant payment delays among small taxpayers suggests that there are limits to the extent to which third-party information, reminders and audits can help to enhance tax compliance. This provides a rationale for the use of withholding as an alternative enforcement mechanism. 3 We borrow the term from Kleven et al. (2011) who conduct an anatomy of compliance for wage earners and the self-employed in Denmark. 4 In a companion paper, Brockmeyer et al. (2015) show that credible deterrence messages from the tax authorities signicantly increase tax ling and payment among these rms. 5 Previous studies have shown that bunching is largely driven by misreporting rather than real responses (e.g. Best et al. 2015 for the mininum tax kink in Pakistan, Almunia & Rodriguez 2015 for an enforcement notch in the Spanish corporation tax). 6 These estimates are lower than similar estimates for rms in Ecuador from Carrillo et al. (2014). However, given the incompleteness of third-party records, our estimates are weak lower bounds on evasion, and weaker compared to Carrillo et al. (2014) who also used customs data. 3 We turn to analyze the impact of withholding in the second part. We begin by showing that coverage by a withholding scheme is strongly correlated with higher reported taxable income across rms and within rms across time. Across rms, we nd that bunching is signicantly smaller among rms covered by third-party information reporting and even smaller among rms subject to withholding, either by a state institution or by their credit/debit card provider. Across time, we nd that rms that become subject to withholding exhibit a signicant increase in reported taxable income precisely in the year in which they are subject to withholding for the rst time. We then exploit a sales tax withholding reform in a dierence-in-dierence design, nding that a doubling of the withholding rate leads to an approximately 40% increase in total tax payment among taxpayers subject to withholding. In aggregate, the withholding rate reform increased sales tax payments by about 10%.7 This response is driven by incomplete reclaim of the tax withheld, and an increase in reported taxable income among rms subject to withholding. This conrms the impact mechanisms predicted by our conceptual framework. We also conrm that only a tiny fraction of taxpayers reclaim through other channels, for instance on another tax declaration or by requesting a cash refund.8 We conclude that withholding increases tax payments by establishing a compliance default. Our paper contributes to several strands of literature. First, our work contributes to the literature on taxation and development, as reviewed in Besley & Persson 2013. Theoretical contributions in this literature have discussed why tax systems in developing countries dier from those in high income countries (Keen 2008, Gordon & Li 2009, Best et al. 2015). Our results explain the prevalence of withholding schemes for rms as an enforcement tool in low-compliance environments. They also highlight the important role of rms in enforcing taxes (here as withholding agents), as suggested theoretically by Kopczuk & Slemrod (2006) and Kleven et al. (2015), and demonstrated empirically by Best (2014) in the context of employer reporting on employees' earnings. In addition, our results contribute to the empirical literature on third-party reporting and compliance (Carrillo et al. 2014, Slemrod et al. 2015, Pomeranz 2015, Naritomi 2015). Consistent with Carrillo et al. (2014), we nd under-reporting of sales as well as costs. We also nd that the presence of third-party information is correlated with compliance on the intensive margin, and on the extensive margin among registered rms. Finally, our paper provides novel estimates of extensive margin compliance gaps and payment compliance. Shedding light on substantial payment delays, we highlight the importance of analyzing payment data in addition to tax liability data, which previous studies have focused on. 7 Overall, withholding agents collected 10% of corporate income tax revenue and 20% of sales tax revenue in 2014. 8 Results available upon request. 4 Second, our study extends the literatures on tax withholding and the impact of defaults. A large literature has analyzed withholding for the personal income tax, focusing mostly on the United States (Barr & Dokko 2008, Gandhi & Kuehlwein 2014, White et al. 1993, Highll et al. 1998). Aside from descriptive policy reports (Samanamud 2013, OECD 2009) and legal writing (Soos 1990), the only study analyzing withholding on rms is Carillo et al. (2012). They show that rms bunch at a withholding rate kink, and interpret this as evidence for a (perceived) discontinuity in the audit function. Our paper is the rst to quantify the tax revenue impact of withholding for rms, and identify the impact mechanisms. By showing that witholding establishes a compliance default, we contribute to the behavioral literature on defaults, which shows that defaults increase organ donation (Johnson & Goldstein 2003) and retirement savings (Chetty et al. 2014, Thaler & Benartzi 2004, Madrian & Shea 2001). We show that a default can also be used to induce people into a behavior that even rational agents do not display. To the extent that there might be a behavioral interpretation of some of our ndings, our paper also relates to the study of optimal taxation with behavioral agents in Farhi & Gabaix (2015). Finally, we draw on methodological contributions from two literatures. We follow the lead of Fisman & Wei (2004) in identifying misreporting by comparing two data reports on the same tax base. This approach is also used in Zucman (2013), Kumler et al. (2015), Best (2014) and Rijkers et al. (2015). We also draw on the bunching literature in public nance, initiated by Saez (2010), Chetty et al. (2011) and Kleven & Waseem (2013), and summarized in Kleven (2016). This literature provides the techniques to estimate taxpayers' behavioral responses to discontinuities in the tax schedule, and translate them into income elasticities. The remainder of the paper is organized as follows. We start by describing a simple conceptual framework in Section 2. Sections 3 and 4 present the Costa Rican tax system and data. Sections 5 and 6 present the anatomy of compliance and the impact of withholding, and section 7 concludes. 2 Conceptual Framework This section presents a simple conceptual framework to analyze behavioral responses to withholding. The framework is based on the canonical tax evasion model by Allingham & Sandmo (1972), extended by Kleven et al. (2011) and Carrillo et al. (2014) to include third-party reporting for individuals and rms respectively. We rst present the basic setup of the model, then introduce withholding with full reclaim, and nally consider a model of withholding with costly reclaim. 5 2.1 A Simple Tax Evasion Model The basic setup of our model follows Carrillo et al. (2014). Firms have revenue R = RT + RS , where revenue can be either third-party reported or self-reported, indexed by T and S , and rms declare ˆ Firms have costs C = Cs , which we assume for simplicity to be fully self-reported, and rms R. ˆ The government levies tax at rate τ on declared prots π chose to report C. ˆ . The tax ˆ−C ˆ =R ˆ . With probability p, rms are audited, in which case any evasion is certain to liability is T = τ π be detected, and evaders pay a ne θ which is proportional to the evaded liability. Firms maximize expected utility9 over after-tax income in the audited and non-audited state of the world, YA and YN : EU = (1 − p)U (YN ) + pU (YA ) ˆ ) + pU (π − τ π − θτ (π − π = (1 − p)U (π − τ π ˆ )). To take into account the tax authorities' use of risk scores to target audits, we further follow Carrillo et al. (2014) by assuming that the audit probability is decreasing in the reported prot rate, p = p((ˆ ˆ ) with p < 0, and mis-reporting against third-party information leads to certain π + )/R ˆ < RT .10 With these assumption, rms choose to report R detection: p = 1 if R ˆ ∗ ≥ RT , and choose ˆ ∗ ≷ C to satisfy the rst-order condition. C ˆ > 0 , we assume that θ To ensure that the government always prefers less evasion, i.e. ∂R/∂ π and p are small, which are reasonable assumptions in a middle-income country. As is also standard in the literature, we ensure that the second-order condition is met and avoid non-concavities by imposing p ≥ 0. 2.2 Withholding with Full Reclaim We introduce withholding into the model by assuming that tax is witheld at a rate µ on third-party reported revenue RT . The information reporting agent thus also becomes the withholding agent. As rms are already chosing to report revenue larger than or equal to third-party reported revenue, the introduction of withholding leaves the information environment unchanged. In a rst step, we assume that the tax withheld can be fully reclaimed, as is technically the case in most withholding systems. This means that rms' net tax liability and hence payment is P = T − µRT , where the tax 9 As Carrillo et al. (2014), we consider that modeling rms in a developing country context as risk-averse is reasonable, since more than half of the rms in our sample are unincorporated, and most rms are vulnerable to income volatility. 10 The inclusion of , a small positive number, ensures that rms declaring zero prots on a large revenue base incur a higher audit probability than rms declaring zero prots on a small revenue base, thus dierentiating the two corner cases where πˆ = 0. 6 withheld is deducted from the gross tax liability. There are no restrictions on the sign of P, P ≷ 0, so that rms can request a refund if the reported tax liability is smaller than the tax withheld. In this model, rms' after-tax income in the audited and non-audited state of the world are ¯N = π − µRT − [τ π Y ˆ = YN , ˆ − µRT ] = π − τ π ¯A = π − µRT − [τ π − µRT ] − θ[(τ π − µRT ) − (τ π Y ˆ ) = YA . ˆ − µRT )] = π − τ π − θτ (π − π After-tax income in both states is exactly equal to after-tax income in the model without with- holding. Withholding is thus irrelevant to rms' evasion decisions. This trivial result obviously relies on the assumption of full and costless reclaim, which we relax in the next section.11 2.3 Withholding with Costly Reclaim To bring the model closer to reality, we assume that rms pay a rm-specic xed cost fi , distributed according to the cumulative distribution function H (f ), to reclaim the tax withheld µRT . This xed cost can represent the cost of collecting withholding receipts for each transaction and adding up the amounts when preparing the tax return. It can also capture, albeit in a crude way, the monetary cost of an increase in the monitoring or audit probability that rms may face when reclaiming tax withheld.12 The presence of the xed cost generates a cut-o f ¯ ¯ = µRT such that rms with fi < f ¯ do not reclaim. A rst testable prediction of the reclaim the tax withheld and rms with fi ≥ f ¯) < 1, and that the share of model is thus that reclaim of the tax withheld is incomplete, H (f ¯)/∂µ > 0. reclaimers increases in the withholding rate, ∂H (f Comparative Statics for Firms Absent any behavioral response, reclaimers experience a de- crease in their after-tax income of fi < µRT and non-reclaimers experience a decrease of their after-tax income of µRT . For both types of rms, the absolute decrease is the same in the audited and non-audited state.13 Taxpayers adjust their reporting behavior in response to the decrease in after-tax income. Under decreasing absolute risk aversion, as in Allingham & Sandmo (1972), one ˆ1 and non-reclaimers declare π can show that reclaimers declare π ˆ2 with π ˆ2 >π ˆ ∗ is the ˆ ∗ , where π ˆ1 > π taxpayers' optimum in the baseline model without withholding. Intuitively, the decrease in after-tax income hurts rms more in the audited state, and thus induces them to become more compliant. This simultaneously reduces the likelihood of detection and increases after-tax income in the case 11 Other non-inocuous assumptions of the model are the absence of an extensive margin decision and the full payment of declared net liabilities P . 12 The latter mechanism could also be modeled more explicitely as a discontinuous increase in the audit probability p for reclaimers, e.g. p = 1 for rms reclaiming µRT > τ π ˆ , which would generate bunching at the threshold where the reported tax liability equals the tax withheld, for suciently risk averse rms, as show in Carillo et al. (2012). 13 We assume that non-reclaimers lose the amount of tax withheld also when they are audited. This is true if they did not keep receipts recording the amounts withheld. 7 of detection. As the decrease in after-tax income is larger for non-reclaimers, they respond more strongly to the withholding scheme.14 It is trivial to see that ∂ π ˆ1 /∂f > 0 for reclaimers, with µ ˆ2 /∂µ > 0 for non-reclaimers. The second testable prediction of the model is being irrelevant, and ∂ π ˆ /∂µ > 0.15 thus that an increase in the withholding rate increases reported taxable income, ∂ π Comparative Statics for the Government Government revenue G is equal to total tax payment by all rms. Assume a continuum of rms of measure 1 with xed costs distributed according to H (f ). Then government revenue is the weighted average of revenue across the audited and non- ¯) of rms are reclaimers who pay audited state of the world, where in each state, a fraction H (f ¯)) of rms are non- exactly the declared (or true) tax liability and the remaining fraction (1 − H (f reclaimers from whom the government collects a higher tax liability in addition to the tax withheld: ¯)[τ π G = (1 − p) H (f ¯))[τ π ˆ1 ] + (1 − H (f ˆ2 + µRT ] ¯)[τ π + θτ (π − π +p H (f ¯))[τ π + µRT + θτ (π − π ˆ1 )] + (1 − H (f ˆ2 )] . The introduction of withholding thus increases government revenue both mechanically, through the collection of tax withheld, and through the increase in reported tax liabilities.16 However, the setting of the revenue maximizing withholding rate µ involves a trade-o, so that revenue may increase or decrease in µ, ∂G/∂µ 0. On the one hand, a higher withholding rate allows the government to collect more revenue from non-reclaimers. On the other hand, the higher rate induces more rms to incur the xed cost and become reclaimers, which reduces government revenue as ¯) < 0. The eect of a withholding rate increase on government revenue is thus theoretically ∂G/∂H (f ambiguous. We proceed to estimate this eect empirically using policy variation in Costa Rica. 3 Tax System Costa Rica's tax system relies predominantly on the income tax for rms and the sales tax. Firms in Costa Rica register either as persona física (unincorporated rm, i.e. self-employed individuals) or as persona jurídica (corporation), using the D140 registration form. There are no size thresholds or other requirements obliging rms to chose one rm type or the other, but the governance structure 14 As has been shown in the referenced papers, π ˆ also increases in p, θ and RT . 15 An increase in the withholding rate from µ1 to µ2 > µ1 will also induce some non-reclaimers to become reclaimers. However, these rms will still experience a decrease in their after-tax income by fi − µ1 RT , as µ1 RT < fi < µ2 RT for them, so that they will also chose to increase reported taxable income. 16 This result would be strengthened in a context of extensive compliance gaps or under-payment of liabilities. 8 and income tax schedule for the two rm types dier.17 This section presents rst the income and sales tax system in Costa Rica, and then the compliance mechanisms used to enforce taxes, information reporting by third parties and withholding. 3.1 Income Tax For all rms, income tax is levied on taxable prots, and led annually by December 15, with three quarterly advance payments made in March, June and September.18 The self-employed face a kinked tax schedule on prots, with ve tax brackets. As Table I shows, the location of all the kinks is adjusted annually for expected ination. The new kink locations are announced by decree each year in the early fall, before the begining of the new scal year. The marginal tax rates which apply to incomes in the ve brackets are 0, 10, 15, 20 and 25% respectively. These rates do not change over the period 2006-2014. The rst kink is the largest kink, representing a 10-percentage-point jump in the marginal tax rate, and the most salient one, as crossing the kink generates a payment obligations. Chetty et al. (2011) suggest that larger kinks generate stronger bunching, as the size of the tax incentive allows some taxpayers to overcome optimization frictions that would otherwise prevent them from bunching. Corporations face a notched tax schedule on revenue, with three tax brackets and no exempt amount.19 A rm's revenue determines its average tax rate, which is then applied to prots. The notch locations are again ination-adjusted annually, and the average tax rates of 10, 20 and 30% have not changed during the period we study. Note that the annual adjustment of kink and notch locations generates 54 dierent thresholds over 2006-2014. Out of these, only two are at a round number (kink 1 in 2011, and kink 2 in 2009). This means that persistent bunching at the thresholds cannot be driven by round-number bunching. 3.2 Sales Tax Costa Rica does not have a fully-edged VAT, but levies a sales tax which rms need to declare monthly by the tenth working day of the following month. The base for the sales tax is the sale of goods and certain specied services, which includes for example hotels, tailors, and orists, but excludes most professional services, for instance those provided by lawyers and doctors. The standard 17 Wage earners are taxed according to yet another tax schedule, which features three tax brackets with marginal rates of 0, 10 and 15% respectively. The highest kink for wage earners is below the lowest kink for the self-employed. 18 Fiscal year t in Costa Rica starts on October 1 in year t − 1 and ends on September 30 in year t. Taxpayers can request to pay taxes according to a dierent scal period, which we take into account in our analysis. The quarterly advance payment is a quarter of either the previous year's tax liability, or the average liability over the last three years, whichever is higher. 19 Corporations also claim a dierent set of deductions than unincorproated rms. 9 rate has been constant at 13% for the entire period of our study, and reduced rates of 10% and 5% respectively are levied on wood and residential electricity. Sales tax paid on inputs can be claimed as credit, which makes the sales tax eectively a VAT with a narrow base. Any sales taxpayer is liable for the income tax, but the reverse is not necessarily true. In our sample, approximately 15% of income tax compliant rms also le sales tax. 3.3 Compliance Mechanisms To enhance tax compliance among rms, the tax authorities in Costa Rica make use of third-party information and tax withholding from dierent sources. The relevant informative declarations, sub- mitted by public or private sector agents about the economic activities of tax-liable rms and individuals, are listed in Table III. An informant submits one informative declaration for each cus- tomer/provider, specifying the tax identication number of the informant and the taxpayer, the transaction amount, the tax withheld if applicable, and the income/transaction type. All infor- mation reporting and withholding mechanisms apply in the same way to the self-employed and corporations. Unlike in the United States, taxpayers are not provided with the informative declara- tions at the time they le their declaration, and are not notied about the existence of an informative record. However, given the structure of reporting requirements explained below, the tax authorities expect rms to be aware of any third-party records about them.20 The authorities use all informative declarations, combined with customs declarations D166 and D167 on imports and exports, to automatically cross-check all income tax declarations. Taxpayers with strong discrepancies between the third-party information and the self-assessment declaration are then selected for intensive margin controls or audits. 3.3.1 Information Reporting Declarations D151 and D158 are pure reporting declarations, not involving any withholding. Dec- laration D151 must be led by all rms conducting purchases or sales above a certain threshold. Purchases and sales must be reported if the accumulated annual amount of transactions with a single transaction partner reaches  2.5 mio. The payment of rent, commissions, professional ser- vice fees or interests must be reported if the annual transaction amount with a single transaction partner reaches  50,000. These transactions must be reported by both the seller and the purchaser. Declaration D158 must be led by the organizers of agricultural auctions, and covers all sales and 20 In the rare case that a taxpayer inquires with the tax authorities about the information held about her economic activities, the authorities are legally obliged to provide the information to the taxpayer. 10 purchases at the auction. Each transactions must be reported only once, either by the seller or the buyer. 3.3.2 Withholding System Declarations D150 and D153 are led by withholding agents, and are accompanied by remittance of the tax withheld to the tax authorities. The taxpayer whose tax payment has been (partially) withheld can deduct the corresponding amount on the relevant tax declaration (income or sales tax) for the same scal period, or in future scal periods. Declaration D150 is led by state institutions making purchases from rms, and by rms pur- chasing certain specied services (e.g. transport, communications) from non-resident rms. State institutions withhold tax at a rate of 2% on all purchases, and rms withhold at a rate of 3% on the specied purchases. This withholding applies to the income tax only. Declaration D153 is led for the purpose of sales tax withholding by companies processing credit/debit card payments. The companies report all sales that their sales-tax-liable customers conduct through card transactions. On this base, they withhold sales tax at a rm-specic rate varying between 0 and 6% of the transaction value. The sales tax withholding rate schedule is displayed in Table II. Prior to August 2011, the withholding rate was determined by a notched schedule on value-added. Value-added is dened as the ratio of taxed sales over taxed purchases and imports reported on the sales tax declaration. The notches are located at 5, 20, 30, 40, 55, and 75% of value-added. All notches are associated with a one percentage point increase in the withholding rate. Prior to August 2011, 40.3% of rms subject to D153 reporting beneted from the zero-withholding rate, and only 21.8% were subject to the 6% rate. To increase the extent of withholding, a reform announced by decree in July 2011 and eective since August 2011 consolidated the withholding rate schedule to three rates of 0, 3 and 6% and changed the rate determination. The rates are now based on the share of local sales in total sales, with notches at 0 and 50%. Since the reform, 68.7% of D153-covered rms are subject to a withholding rate of 6%. For the entire period of our study, withholding rates are determined each semester t with ref- erence to the value-added/share of local sales in semester t − 2. The tax authorities determine the withholding rate based on rms' tax returns, using sector averages for rms with no tax history, and communicate the withholding rate to the withholding agent. In special circumstances, rms can request the tax authorities to change the withholding rate before the end of the semester. In this 11 case, or in case the rm colludes with the withholding agent to apply a lower withholding rate, the actual withholding rate may dier from the rate predicted by value-added or share of local sales in semester t − 2. 4 Data Our analysis combines anonymized tax return data and third-party and withholding declarations from the General Directory for Taxation in Costa Rica. The tax return data contains the universe of income tax declarations (D101) for 2006-2014 and sales tax declarations (D104) for 2008-2014, as well as the corresponding payment returns (D110) for the income and sales tax. Since 2006, all tax returns have been digitzed, and electronic ling has gradually been introduced for the dierent declarations, ensuring that the data have nearly complete coverage and a high degree of acurracy. The ling software EDDI-7 conducts automatic validation checks to ensure the internal consistency of led returns. The data contain all line items of the tax return, including rm type and sector, income sources, cost items, deductions, gross and net liability and payment.The nal data set contains 112,000 to 250,000 self-employed per year, 90,000 to 150,000 corporations and 58,000 to 70,000 sales tax lers per month.21 We merge the tax records with the informative declarations D150, D151, D153 and D158, also for the period 2006-2014. These data have been led eletronically through the DECLAR@7 system, which conducts similar validation checks as EDDI-7. Table III provides an overview of the number of records and their coverage for each of the informative declarations. Declaration D151 registers both the largest number of observations, and the widest coverage, being available for approximately half of all rms. The coverage is similar for the self-employed and corporations. The ling of informative declarations is more concentrated than the coverage, meaning that an even small share of rms act as informants (results available upon request). Note that information reporters are slightly more likely to report their own costs rather than their own sales, as evidence by the fact that 54.3% of the D151 records represent sales records. Declaration D158 is similar to D151 in that sense, but has much lower coverage, given the specic nature of the transactions it covers (agricultural auctions). In our analysis, we thus use the sum of third-party information on sales/costs from D151 and D158. Withholding by state institutions and nancial institutions, as reported in D150 and D153, has a 21 Only the tax records for 2012-2014, and a small share of records for 2010 and 2011 have rm type indicators (self- employed or corporation). During this period, we observe only a handful of rms switching rm type. We therefore use the 2010-2014 tax return data and the tax register to assign a rm type to the tax returns for 2006-2011. We drop returns for which we cannot determine the rm type with this strategy. 12 much lower coverage among rms than pure information reporting, especially for the self-employed. D150 and D153 records are available for only 5.0% and 5.8% of the self-employed and 8.4% and 11.% of corporations respectively.22 98.5% of D150 records are submitted by state institutions, meaning that withholding by private non-nancial rms is minimal. A signicant share of informative declarations cannot be matched with income tax records, suggesting that a large number of rms covered by third-party information or withholding are incompliant on the extensive margin. The picture is currently incomplete, as we still work on incorporating the simplied regime declarations D105 into this analysis.23 However, given the small number of rms in this regime (20,000-30,000 returns led per quarter) their absence from our analysis cannot fully explain the discrepancies between the presence of third-party reports and tax declarations. In addition to the tax returns and informative declarations, we use the D140 and D141 regis- tration and deregistration records for 2006-2014 to construct snapshots of the tax register for each scal period. Firms use the D140 form both for registration purposes, as well as for modication and deregistration. If the government deregisters a rm de ocio, which happens if a rm has not led taxes for at least three years, a D141 form is used. 5 Anatomy of Compliance This section presents the anatomy of tax compliance in Costa Rica, identifying mis-reporting through discrepancies between two data reports on the same tax base, as applied by Fisman & Wei (2004). We start with the extensive margin, matching tax declarations led and the set of tax liable rms as constructed from the tax register and available third-party reports. We then consider the intensive margin, comparing third-party reported and self-reported sales and analyzing bunching around tax bracket thresholds. Finally, we estimate compliance with the payment obligation, comparing tax returns with payment returns. To the extent possible, we compare compliance by the self-employed and by corporations. 22 As indicated by the percentages in squared brackets in Table III, the coverage of D153 declarations among sales- tax-liable rms is higher, since they constitute only a small subsample of income taxpayers. 23 Retailers in certain sectors and below certain size thresholds (annual purchases less than 150 base salaries, xed assets less than 350 base salaries, less than six employees) can opt into a simplied regime. In this regime, tax is levied on input at sector-specic rates that vary from 3% to 9.8%. Firms in this regime declare and present quarterly, and can claim credit for withholding by state institutions for the income tax, but not for withholding by credit card institutions for the sales tax. Firms can opt out of the regime by submitting a D140 modication form. For details, see United Nations (2014). 13 5.1 Extensive Margin Compliance To examine compliance on the extensive margin, we construct the set of tax liable rms and compare it to the self-assessment declarations led for the income tax and the sales tax. A rm is considered income tax liable for scal year t if it fullls at least one of the following conditions: (i) the rm is in the tax register in year t, (ii) has led income tax in year t, (iii) is covered by a at least one third-party informative declaration in year t,24 (iv) has led income tax at least once in the previous three scal years and has not deregistered since, or (v) has registered within the previous three scal years and has not deregistered since.25 The three-year window reects the tax authorities' practice of deregistering a rm de ocio if it has not led for three years.26 For the sales tax, we consider only rms that are registered as liable for the sales tax and have not changed their registration status since, or are covered by information reporting by credit/debit card providers for the purpose of sales tax compliance. The algorithm allows us to estimate the share of non-lers, i.e. tax-liable rms that failed to submit their self-assessment declaration, for dierent taxes, subsamples and rm types. For demonstration purposes, we consider ling in scal year 2014 and December 2014 for the income tax and the sales tax respectively. However, the results are similar for years 2009-2012 (gures available upon request). We are currently studying late ling behavior, and updating the results to take into account the tax returns led under the simplied regime. The rst panel of Figure II shows that the share of non-lers is substantial, ranging from 34% for the income tax to 45% for the sales tax. The share is equally high (and even higher for the sales tax) among rms covered by third-party information. This suggests that, though third-party information helps to identify taxable activities, it does not necessarily induce the reportees to comply with their tax ling obligations. The high share of non-lers among third-party reported sales-tax-liable rms could be due to the fact that credit/debit card companies report transactions even for rms that are not liable for the sales tax, an explanation we are currently investigating. For the income tax, an average of 10% of total third-party reported sales remain unreported for 2009-2013, and 30% are still unreported for 2014. To analyze ling behavior across rm types, we focus on the subsample of registered rms, 24 We exclude information on D151 cost reports, which could pertain to wage-earning individuals who purchased goods from a rm. 25 This algorithm will be described in more detail in a forthcoming data appendix. 26 According to the codigo de normas y procedimientos tributarios, the period until a taxpayer gets deregistered de ocio is three years until September 2012 (when the relevant article was amended), and four years from then on. A resolution in September 2014 emphasized that non-lers should be deregistered after four years, so the tax authorities' implementation of the rule may have strengthened thereafter. 14 which are identied as either self-employed or corporation. The second panel in Figure II shows that compliance is generally higher among registered rms. Besides, we now observe a positive correlation between information-coverage and ling, as theory would predict. The fact that third- party information is correlated with ling only for registered rms could be due to the fact that the authorities have contact information for registered rms, and can thus follow up on non-lers. This is more dicult for rms that are identied by third-party information but not registered, for whom the authorities have only incomplete contact information. Consistent with the self-enforcing nature of the VAT, compliance is higher for the sales tax than for the income tax. However, whether rm type is correlated with ling is unclear and warrents further analysis. Corporations exhibit higher compliance for the income tax, while the self-employed exhibit higher comliance for the sales tax. Given the incomplete nature of the third-party information trail, these estimates are a weak lower bound of extensive margin compliance gaps. The estimates do not capture rms that are fully informal and do not trade with institutions or rms that are withholding or information reporting agents. However, we consider that our estimates capture the policy-relevant subsample of extensive margin non-compliers. Indeed, while several studies nd that formalizing fully informal rms is dicult and costly (de Mel et al. 2013, Bruhn & McKenzie 2014), a companion paper by Brockmeyer et al. (2015) shows that ling rates in the sample captured in Figure II can be increased signicantly through low-cost deterrence emails. 5.2 Intensive Margin Compliance 5.2.1 Self-Reports vs. Third-Party Reports To examine compliance on the intensive margin, we rst compare self-reports and third-party reports, for sales and costs respectively. More specically, we follow Carrillo et al. (2014) by plotting the distribution of the log dierence of self-reports and third-party reports, and extend the analysis to the sales tax. The tax authorities in Costa Rica systematically cross-check all tax returns against third- party information and notify rms with substantial discrepancies, or invite them for an interview with a tax ocial. To take into account that rms may revise their return to correct discrepancies, we consider the tax year 2012 rather than more recent years. However, the results for other years are similar and are available upon request. The rst panel in Figure III compares sales reports for the income tax to third-party reports. Third-party reported sales is either the sum of sales reported under D150, D151 and D158, or sales reported under D153, whichever is larger.27 The gure shows that the marjority of rms report 27 While the D150, D151 and D158 declarations are mutually exclusive and the sales amounts can be summed, as 15 sales higher than third-party reports and few rms bunch at the point where the self-report equals the third-party report. Yet, 18% of the self-employed and 9% of corporations report sales lower than third-party reports. Overall, among the under-reporters, the self-employed declare only 52% and corporations declare 54% of third-party reported sales. Of course, these estimates are again lower bounds to the true compliance gaps, given the incompleteness of the information trail. It is striking that these substantial discrepancies persist even three years after the ling period, after revisions were requested by the authorities, and in an environment with a relatively high capacity tax administration. This conrms that there are limits to the extent to which third-party information can help to enhance tax compliance, especially among the self-employed. The second panel repeats the exercise of the rst panel, focusing on cost reports. Third-party reported costs for the income tax is the sum of costs reported under D151 and D158. Surprisingly, a large share of rms declares costs lower than third-party reported costs, and this behavior is much more pronounced among the self-employed. 60% of the self-employed and 28% of corporations under-utilize costs. For the self-employed, prots below the rst kink are tax exempt, so a rm has an incentive to under-report only until its prot is below the rst kink. For corporations, there is no exemption, so the under-utilization of costs is all the more surprising. Among the under-reporters, the self-employed declare 59% and corporations declare 76% of third-party reported costs. These ndings are in line with Carrillo et al. (2014), who show evidence for cost under-reporting among rms in Ecuador, arguing that rms have an incentive to appear small by under-reporting both costs and sales. The third panel compares self-reported and third-party reported sales for the sales tax, using the credit/debit card reports as third-party information. Compared to the rst panel, we nd a similar share of under-reporters among corporations (10%), but a smaller share among the self-employed (12%).28 However, interpreting the discrepancy as a compliance gap is more complicated for the sales tax than for the income tax. The D153 reports cover all transactions that a sales taxpayer conducts, including transactions not liable for the sales tax. Firms also report both taxed and non-taxed sales on their tax return, but they might under-report the non-taxed sales as those are irrelevant to their tax liability. Interpreting under-reporting as a compliance gap thus requires assuming that rms do not selectively under-report non-taxed sales. they refer to transactions conducted with three dierent types of agents, a transaction could potentially be reported both in a D153 and a D150/D151/D158 form. 28 Note that both sales reported on the D153 informative declaration and on the D104 sales tax return should be inclusive of sales tax. However, the spike in the histogram at −.122 ≈ log(X ) − log(1.13 ∗ X ) for a large X suggests that some rms erroneously report their sales net of sales tax. 16 This seems to be a strong assumption, as the nal panel suggests. The gure shows that rms which le both sales tax and income tax exhibit a high degree of internal consistency. The share of bunchers, reporting the same amount of sales for the income tax as for the sales tax is 67% and 60% among the self-employed and corporations respectively. However, the non-bunchers are more likely to report higher sales on the income tax declaration compared to the sales tax declaration than vice-versa. 5.2.2 Bunching While the comparison of self-reports to third-party reports has uncovered signicant compliance gaps, at least for the income tax, this approach can identify misreporting only for rms which are covered by third-party information. Besides, it constitutes only a weak lower bound of misreporting, given the incomplete nature of the information trail. To identify misreporting in the full sample, including rms not covered by information reports, we analyze bunching of taxpayers around the rst threshold in the income tax schedule. In theory, bunching can be driven by a real response or by evasion or avoidance. In practice, however, most studies have found that bunching is largely driven by misreporting rather than real response (e.g. Almunia & Rodriguez 2015, Seim 2015). This section desmonstrates that the nature of bunching in Costa Rica is consistent with bunching through misreporting, but dicult to reconcile with a real response. Instead of comparing the bunching behavior for self-employed and corporations, which is com- plicated by the fact that the relevant thresholds are kinks in one case and notches in the other and also located at dierent points in the income distribution, we focus in this section on bunching among the self-employed at the rst income tax kink. Bunching among corporations at the rst revenue notch behaves in qualitatively similar ways and will be used in Section 6.1 to examine the correlation between misporting and withholding.29 We focus on the rst kink in the self-employed tax schedule, which is the largest and most salient, featuring a marginal tax rate jump from 0% to 10%. Bunching at the second kink is qualitatively similar but smaller, consistent with the fact that the tax incentive is smaller and the second kink is less salient as a reference point. Bunching at the third and fourth kinks is dicult to estimate as the density distribution around these kinks is lower and more noisy, making it more dicult to distinguish bunching behavior from noise.30 Figure V plots the frequency distribution of taxable income for the self-employed around the rst kink, in income bins of  20,000, for each year from 2006 to 2014. The solid vertical line marks the 29 See also Bachas (2015) who uses the notches in the corporate income tax to estimate the elasticity of corporate revenue, costs and prots. 30 Results available upon request. 17 kink location in year t, corresponding to the gure title, and the dotted vertical line marks the kink location in year t − 1. The income distribution is characterized by a large and sharp excess mass at the kink in every single year. The movement of bunching with the kink location over time supports the interpretation of bunching as a behavioral response to the kink rather than a feature of the income distribution which coincides with the kink location. Except in two years (2010 and 2014), there is no excess mass at the previous year's kink, suggesting that rms adjust almost immediately and fully to the new kink location. The consistent and speedy adjustment corroborates our interpretation of bunching as a reporting response rather than a real production change. If bunchers moved to the kink by adjusting their production level, this adjustment would likely take longer to materialize and would yield less precise bunching. Strikingly, the excess mass is always concentrated to the left of the kink. For the years 2010 to 2014, the distribution also displays a clear missing mass to the right of the kink, which is at odds with the prediction of standard utility theory. This theory predicts that kinks generate symmetric bunching around the threshold, and notches generate asymmetric bunching below the threshold and a missing mass in a dominated range above the threshold Kleven & Waseem (2013).31 However, as discussed in Kleven (2016), several studies have found asymmetric bunching also at kink points,32 suggesting that taxpayers may perceive a kink as a notch. One possible explation is that crossing the kink may be associated with a xed cost, such as having to make a payment, as is the case for the rst kink in the self-employed tax schedule in Costa Rica. However, tax payments can be done online and should generate little transaction cost in Costa Rica. Another explanation is that the threshold creates a reference point, which constitutes a notch in the rm's utility function, so that bunching is driven by reference point dependence rather than the traditionally assumed response to the nancial incentive change at the kink.This warrents caution when using bunching to estimate the elasticity of taxable income, but does not prevent us from interpreting bunching as a measure of misreporting which generates a revenue loss for the government. 31 Kink are thresholds at which the marginal tax rate jumps discontinuously. Notches are thresholds at which the average tax rate jumps discontinuously. Kinks imply a marginal change in tax liablity, and hence generate bunching which is symmetric around the threshold. Taxpayers are equally well-o just below and just above the kink. Notches, on the contrary, imply an increase in the tax rate on all units of income, and hence a discrete jump in the tax liability. Notches therefore create a strictly dominated area above the threshold, where rms would not locate unless optimization frictions prevent them from responding to the tax incentive. This generates bunching below the threshold and a missing mass (hole) above the threshold. 32 See for instance Devereux et al. 2014 and Brockmeyer 2014 for evidence on this from the United Kingdom. 18 5.3 Payment Compliance To examine taxpayers' compliance with the obligation to pay their net tax liability, we match the income and sales tax returns with payment records from the D110 payment returns. To our knowledge, this is the rst attempt at estimating payment compliance for the income and sales tax33 , testing the previously implicit assumption that declared tax liabilities automatically translate into payments. The relevant liability is the taxpayer's nal tax liability to be paid as per the nal (revised) tax returns, after deductions, advance payments and tax withheld have been subtracted.34 We compare this liability to the tax payment that the taxpayer makes herself, excluding payments made by withholding agents and advance payments made by the taxpayer.35 We take the share of payment over liability and average this share across all taxpayers in each scal period. The results are displayed in Figure VI for the income tax (top panel) and for the sales tax (bottom panel). In both gures, the average payment share is below 100% in all scal periods, and decreases as we consider more recent years, dropping to 70% for the income tax and 85% for the sales tax in 2014. This is despite the fact that we consider payments made until June 2015 for the income tax and until October 2015 for the sales tax. Thus, although the payment rate reaches an average of approximately 95% within four years of the ling period, a non-negligible share of payments are made with several years of delay. This is consistant with anedotal evidence that cash-constrained rms make tax payments when they are liquid rather than when the payment is due, as nes and interest fees are small and legally enforcing outstanding payments is costly for the tax authorities. However, the total payment share, meaning the sum of payments as a share of the sum of net liabilities for all rms, is higher than the average payment share for the self-employed and reaches almost 100% even in recent years, suggesting that the late payments are predominantly small amounts. This is again consistent with the fact that smaller rms are more likely to be cash constrained. For corporations, however, the total payment share is substantially below 100%, driven by a small number of taxpayers with large liabilities and zero payment. This is likely due to missing payment records and may also explain why the average payment rates are lower for corporations than for the self-employed, at least for the sales tax. We show this result in appendix Figure XIII. To ensure that our main results on the causal impact of withholding are not driven by gaps in 33 Del Carpio (2014) provides estimates of property tax compliance in Peru. 34 Note that we use the net liability as derived on the rm's tax return, and taking into account only the amount of advance tax payments and tax withheld that the taxpayer chose to reclaim on her tax declaration. As the advance payments for the income tax constitute three quarters of the total tax liability, the remaining tax to be paid at the end of the scal year is relatively small. 35 Including payments that are enforced retroactively by the tax authorities through administrative or judicial procedures makes little dierence to the results. 19 the payment data, we conduct a series of robustness checks explained below and displayed in the appendix. To summarize, the anatomy of compliance allows the following preliminary conclusions. First, a substantial share of rms fail to le their taxes, and there are limits to the extent to which third- party information induces compliance on the extensive margin. The share of non-lers is similarly large in the full sample of tax liable rms and in the subsample of rms covered by third-party infor- mation. Second, a substantial share of rms under-report sales compared to third-party reports, and misreport taxable income to bunch below kink points, despite the fact that the authorities systemat- ically cross-check tax returns and informative declarations and request corrections of discrepancies. Finally, a non-negligible share of small rms pay their outstanding liabilities with several years of delay. The fact that these compliance gaps are present despite the use of third-party information, and are particularly prevalent among small rms which are costly to follow up on for the authorities, provide a rationale for the use of withholding as an additional compliance mechanism, which comes at a low implementation cost for the authorities. 6 Impact of Withholding This section analyzes the compliance impact of withholding. We start by examining the correlation between coverage by withholding and tax compliance, across rms and across time. Heterogeneity in bunching across subsamples of rms provides for cross-sectional correlations. An event study around the timing of the receipt of the rst withholding declaration provides for correlations within rm across time. We then exploit the 2011 reform of sales tax withholding to estimate the causal impact of the withholding rate increase in a dierence-in-dierence design, and investigate the mechansims driving the impact. 6.1 Correlations across Firms: Heterogeneity in Bunching To examine the heterogeneity of bunching across subsamples of rms, we pool the data for all years and display the distribution as percentage dierence from the year-specic threshold location in 1% bins. To estimate the size of bunching, we t a exible polynomial to the observed distribution, excluding a range around the thresholds, as is standard in the bunching literature (Chetty et al. 2011, Kleven & Waseem 2013). Given the asymmetric nature of bunching, we estimate bunching to the left of the kink and the missing mass to the right of the kink. As the missing mass does not seem to be the same size as the excess mass, at least for the self-employed, we apply the estimation 20 strategy suggested by Best & Kleven (2015) rather than the covergence method. We choose the lower bound of the excluded range as the point where bunching starts and the upper bound as the point where the derivative of the observed distribution shifts from positive to negative.36 The convergence method would require the missing mass and the excess mass to be of the same size and assumes that there are no extensive margin responses, which is unlikely in a context with high shares of non-lers even among registered rms. Figure VII displays the observed distribution (dotted blue line), the estimated counterfactual (solid red line) and excess/missing mass estimates for three dierent subsamples. The top row shows the distribution of taxable income for the self-employed around the rst kink, the bottom row shows the distribution of revenue for corporations around the rst notch. The gures on the far left reect the sample of rms not covered by any information reporting or withholding declaration. The gures in the middle reect the sample of rms covered only by information reporting through the D151 or D158 declarations. Whereas several papers have analyzed the heterogeneity in bunching by proxies of evasion propensity (Best 2014, Almunia & Rodriguez 2015), this is to our knowledge the rst exercise of estimating the heterogeneity of bunching by actual third-party information coverage. The subsample of information-covered rms still exhibits a large excess mass around both the kink and the notch, but in both cases, the excess mass estimate is signicantly smaller than the estimate for rms not covered by information reporting. The excess mass drops from 4.5 to 2.08 for the self-employed and from 4.49 to 3.17 for corporations.37 The fact that bunching is smaller but still highly signicant among information-covered rms is consistent with the fact that bunching can be partly driven by legal avoidance, and that the information trail is incomplete, covering only large transactions. Firms can still manipulate their taxable income by misreporting small and cash transactions, inating costs, and using deductions and exemptions.38 Comparing the gures in the center to the far right gures, which reect the sample of rms covered by withholding by either state instituions (D150) or credit/debit cards (D153), it becomes clear that withholding further reduces rms' ability to misreport. The excess mass drops to 1.19 for the self-employed and to 1.33 for corporations, estimates which are statistically signicantly dierent from the estimates in the corresponding middle panels, and the missing mass also decreases in both 36 The location of the upper bound is less clear from visual inspection. In a forthcoming appendix table, we provide robustness checks varying the degree of the polynomial and the size of the excluded range below and above the kink. 37 Note that the change in the missing mass estimate is driven by a change in the counterfactual density which scales the excess mass, rather than by a change in the absolute size of the excess mass. The missing mass drops for corporations, but increases for the self-employed. In fact, the missing mass for the self-employed is clearly visible only in the middle and far right gures. This suggests that the threshold may still be perceived as a kink by some rms in the subsample not covered by information reporting. 38 Bunching is also present in all economic sectors and relatively homogenous across sectors. 21 samples.39 Although the heterogeneity of bunching across subsamples is consistent with a compliance im- pact of information reporting and withholding, these results are based on correlations. Subsamples of rms covered by information reporting are dierent from non-covered subsamples in many as- pects. It is possible that characteristics other than coverage by informative declarations explain the weaker bunching in covered subsamples. Similarly, the results are consistent with the notion that withholding may be a more eective compliance instrument than mere information reporting, but do not constitute causal evidence for this.40 The D151/D158, D150 and D153 declarations ap- ply to dierent types of transactions, rm-to-rm, rm-to-state transactions and card transactions respectively, so that the declarations and the rms covered by them are not strictly comparable.41 6.2 Correlations across Time: Event Study To hold at least rm characteristics constant, we exploit the panel dimension of the data set and es- timate within rm correlations across time between information reporting/withholding coverage and reported taxable income. Each year, over a thousand rms switch into being covered by information reporting and/or withholding. This can happen for several reasons. A rm becomes covered by D151 information reporting from other rms once the transaction volume with a tranaction partner passes the annual threshold for D151 reporting, if an agreement with a transaction partner to not report the transaction breaks down, or if the rm gains a new (reporting compliant) transaction partern. A rm becomes covered by D150 withholding by state institutions once it sells to a state institution, and a rm becomes covered by D153 withholding by credit/debt card companies when it starts conducting sales through card transactions.42 To assess whether becoming covered by information reporting or withholding increases rms' re- ported taxable income, we conduct an event study around the time of switching into coverage by one of these compliance mechanisms. As in in Hilger (2014) and Naritomi (2015), we construct an event control group, that is the propensity-score weighted average of the control rms, the propensity-score 39 The results are similar when considering separately rms subject to withholding by state institutions and by credit/debit card companies. 40 Our results are also consistent with estimates from the United States, where the Internal Revenue Service reports tax evasion rates of 56%, 8% and 1% respectively on income covered by little information reporting, income covered by substantial information reporting and income subject to withholding (IRS 2012). 41 For example, managers of rms deciding to sell their output to a state institution may have higher tax morale, or be more committed to public goods provision, than managers transacting only with other private sector rms. Similarly, transactions conducted by credit card have dierent characteristics than transactions conducted in cash. 42 Given the structure of reporting requirements, each rm should be aware of the informative declarations held by the tax authorities about its business activities. When subject to withholding, rms also receive a receipt from the withholding agent stating the amount of tax withheld. 22 capturing each control rm's likelihood of becoming covered by the relevant compliance mechanism (receiving the relevant informative declaration for the rst time).43 However, as rms have con- trol over the conditions which lead to information reporting and withholding (e.g. sales volume, transaction partners, accepted payment methods), the event study cannot be interpreted as a causal estimation. Firms that become information/withholding covered might be rms that experienced an increase in their true prots, or were already planning to become more tax compliant. With these caveats in mind, we consider the event group E of rms that switch into informa- tion/withholding coverage for the rst time in event year k = 0, and the event control group C of rms which have not switched into coverage by k = 0. For each event year, we estimate the rms' propensity score of switching into information/withholding coverage.44 Following DiNardo et al. (1996), we re-weight the control group by percentile bins of the propensity score to match the distribution of the event group. To examine pre-event trends, we restrict the estimation to rms in the balanced sample for 2006-2014 and events happening in 2010 and 2011. The estimation thus covers event years k ∈ [−4, 3].45 Each panel in Figure VIII displays the change in reported taxable income for the event group (orange dots) and the control group (blue crosses), compared to the pre-event average, along with the DD coecient obtained from estimating ygk = αg + γk + β · I {k ≥ 0, g = E } + ugk , (1) where ygk is log taxable income reported by event group g in event year k , αg and γk are group and year xed eects, and ugk is the error term. Panels on the left side of the gure correspond to the self-employed, and panels on the right side correspond to corporations. The rst panel shows that becoming covered by information reporting is associated with an 18% increase in reported taxable income for the self-employed. For corporations, the control group dis- plays a dierent trend, so that it is dicult to draw a conclusion from the evidence. The middle and bottom panels on the left side show that becoming covered by withholding, either by a state institution or by a credit/debit card company, is associated with a larger 42-44% increase in re- ported taxable income for the self-employed. For corporations, becoming covered by withholding is associated with a 21-25% increase in taxable income. 43 See also the appendix in Yagan (2015). 44 The propensity score of a rm receiving its rst informative declaration is estimated separately for each declaration type, using xed eects for year, rm type, sector, tax administration, and the two lags of a third-order polynomial of total income and taxable income. 45 Results are robust to considering a shorter balanced sample, or fewer or more event years. 23 These correlations across time are consistent with the correlations across rms, suggesting that withholding is more strongly associated with increases in reported taxable income than pure informa- tion reporting, at least for the self-employed. However, it remains unclear whether the association is causal. The income increase associated with receiving a D150 or D153 declaration could be stronger than the increase associated with receiving a D151 reporting declaration, either because because the former are submitted by state and nancial institutions rather than other rms, or because they are accompanied by withholding, or both. The next section therefore attempts to isolate the impact of withholding on compliance causally. 6.3 Causal Impact of Withholding: Dierence-in-Dierence Study To examine the causal impact of withholding on tax compliance, we exploit the August 2011 re- form which increased the withholding rate for a large share of sales taxpayers under reporting by credit/debit card companies. The rst panel in Figure IX shows that the reform lead to a doubling of the average withholding rate but was not accompanied by a discontinuous change in the tax base, or in the number of sales tax or withholding declarations led.46 This is consistent with the reform design, which aected only the withholding rate but not the reporting requirements. It also conforms with the notion that credit/debit card providers are highly compliant with their report- ing and withholding obligations, and that most rms do not have the market power to refuse card transactions, thus preventing an extensive margin response to the rate increase.47 This conrms that the reform changed only the rate of withholding, but not rms' coverage by information reporting, allowing us to isolate the eect of withholding. Our estimation focuses on the balanced panel of rms which submitted sales tax declarations within a 30-months window around the reform, and compares a treatment group to a control group in a dierence-in-dierence design. Treated rms experience an increase in the predicted withholding rate between July and August 2011. Firms in the control group experience no rate increase or are not subject to withholding.48 Note that we condition on the predicted rather than the realized increase in the withholding rate (although the two closely track each other), as the latter may be aected by collusion between rms and withholding agents, or a rm-specic connection to the tax authority which allowed the rm to obtain a lower withholding rate. As the predicted rate change depends on value added and the share 46 There is a reduction in credit/debit card reporting on small transactions, but these transactions are too marginal in size to aect the overall average withholding base. 47 There is only a weak behavioral response to the withholding rate notches, suggesting that few rms, if any, can manipulate the withholding rates they are subject to. 48 Results are robust to excluding the latter subsamples of rms. 24 of local sales in the second semester of 2010, long before the reform decree was designed, it is not possible that rms could have gamed the system to avoid an increase in the predicted withholding rate. We estimate the eect of the rate increase using the model yit = αi + γt + µi · t + β · T reati · P ostt + it , (2) where yit is the outcome reported by rm i in month t; αi and γt are rm and month xed eects and µi is a rm-specic linear time trend; and T reati and P ostt are dummies indicating the treatment group and post-reform period. it is the error term. We consider as outcomes all main line items on the tax return, as shown in table IV. The table reports the pre-reform mean in the treatment group, and the coecient β for dierent specications, either using the raw data, or winsorizing by the 99.9th, 99th and 95th percentile. As several outcome variables take value zero for a larger share of observations, we use levels rather than logs, and report the treatment eect as marginal eect on the pre-reform average. However, the results are qualitively similar when using log(outcome+1) or a dummy variable indicating if the outcome is non-zero. To visualize the identifying assumption and treatment eect on total tax payment, the top panel in Figure X plots the month-on-month change in total tax payment for the treatment and control group, together with the DiD coecient estimates from Equation 2.49 Despite seasonal uctuations, the two groups exhibit parallel pre-reform trends, which conrms the suitability of the control group. At the time of the reform, tax payments in the treatment group increase sharply by about 40% and remain at this higher level for the next 15 months.50 A possible interpretation for this large eect is that the reform sends treated rms a signal about increased tax enforcement. However, the bottom panel shows that the treatment eect varies signicantly by treatment strength, suggesting that it is not just the enactment of the reform, but the amount of tax withheld that generates the eect. The gure shows the treatment eect for three treatment groups, distinguishing rms experiencing a 1-2, 3-4 and 5-6 percentage point increase in the withholding rate respectively. The reform generates a 29% increase in tax payment among rms experiencing the smallest rate increase, a 38% increase among rms experiencing a rate increase of 3-4 percentage points (and this point estimate is statistically signicantly dierent from 49 For the purpose of this gure, the data is winsorized by the 99th percentile. 50 To ascertain that this result is not driven by the missing payment data for corporations, discussed in Section 5.3, we replicate the estimation in Appendix Figure XIV for the following subsamples: the self-employed (for whom the payment data is complete), rms with zero net liability or non-zero (own) tax payment, and rms making a non- zero (own) tax payment. The results are qualitatively similar and statistically signicant in all subsamples. Only the very small subsample of rms making a non-zero payment in each month exhibits a relatively smaller treatment eect of 35%. 25 the previous one), and a 90% increase in tax payment among rms experiencing the largest increase in withholding. Although the three treatment groups may also dier along other dimension, the results are consistent with the interpretation that it is the amount of tax withheld that aects total tax payment. 6.4 Mechanisms of Withholding Impact Figure XI analyzes the mechanisms through which the withholding rate reform aects tax payment. The rst prediction of our conceptual framework is that reclaim of the tax withheld is incomplete, but increases as the withholding rate increases. The rst panels of Figure XI support this predic- tion. The share of withholdees making a reclaim on their sales tax declaration is only around 60% before the reform, and drops close to 50% at the time of the reform. This drop occurs because the reform increases the number of taxpayers subject to withholding, and many of the new withholdees might not be familiar with the reclaim procedure, or might not even realize that they are suject to withholding. As these new withholdees start to reclaim the tax gradually, the share of withholdees making a reclaim increases, and eventually surpases the pre-reform share of reclaimers by approxi- mately 7 percentage points. The average share of withheld tax reclaimed, as displayed in the second panel, follows a similar pattern. The share uctuates between 65% and 80% before the reform, then drops sharply at the time of the reform, and recovers gradually. This provides evidence that incomplete reclaim is indeed a mechanism through which withholding increases total tax payment. However, while the increase in total tax payment arises sharply at the time of the reform and then remains constant over time, the share of reclaimers rises over time. This suggests that a second mechanism is at play. The second prediction of our conceptual framework is that the withholding rate increase leads to an increase in reported taxable income. The bottom panels of Figure XI support this prediction. The gures display results from estimating Equation X, as in Figure X, with dierent outcome variables, as indicated in the panel titles. The gures show that the reform led to a 2% reduction in reported input tax credits in the treatment group, but to no change in sales tax collected. Combining these two results means that the reported gross tax liability in the treatment group increased by about 12%. The gure also suggests that the impact on input tax credits emerges gradually over time. The reduction input tax credits and accompanying increase in gross tax liabilty thus compensates for the increase in reclaims, so that net liability changes little. The nding suggests that rms generally evade tax by over-reporting input tax credits, but report more accurately after the withholding rate is increased. In the conceptual framework, the increase in reported tax liability is driven by the non-reclaimers. Given the small eect size and noisy data, 26 it is dicult to test whether this is the case in Costa Rica. The results do not rule out the possibility that the tax liability increase could be driven by reclaimers, who reduce evasion in anticipation of possible audits. 7 Conclusion Although withholding schemes for rms are widespread in developing countries and collect a sig- nicant share of tax revenue, they have been largely ignored by the public nance literature. This paper proposes an explanation for the attractiveness of withholding schemes. In a simple Allingham- Sandmo model, withholding creates a compliance default if reclaiming the tax withheld is costly. Exploiting a unique nine-year panel of tax declarations and third-party information and with- holding reports for the universe of rms in Costa Rica, we identify signicant compliance gaps on the extensive and intensive margins, and to a lesser extent on the payment margin, providing a rationale for the use of withholding. We then show that coverage by withholding is associated with higher reported taxable income across rms and across time, and more strongly so than coverage by pure information reporting. Finally, we demonstrate that a doubling in the withholding rate increases tax payments among rms subject to withholding by about 40%. This eect is driven by incomplete reclaim of the tax withheld, and reduced misreporting. Overall, the results show that withholding indeed establishes a compliance default, providing the government with a larger and more foreseeable stream of revenue. However, even if withholding increases tax revenue, its welfare impact remains ambiguous. With- holding shifts administrative costs from the tax authorities to the withholding agent, and generates administrative costs for the withholdee who needs to track the tax withheld. In addition, withhold- ing transfers liquidity from the taxpayer to the government by advancing the timing of payment. Analyzing the welfare implications of withholding is thus an important next step in this research project. 27 Table I: Income Tax Schedule 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Panel A: Self-Employed Kink 1 1,858 2,074 2,252 2,599 2,747 2,890 3,042 3,171 3,339 3,522 Kink 2 2,775 3,097 3,362 3,880 4,102 4,316 4,543 4,735 4,986 5,259 Kink 3 4,629 5,167 5,609 6,473 6,843 7,199 7,577 7,898 8,317 8,773 Kink 4 9,276 10,354 11,241 12,972 13,713 14,427 15,185 15,827 16,667 17,581 Panel B: Corporations Notch 1 27,811 31,043 33,701 38,891 41,112 43,253 45,525 47,451 49,969 52,710 Notch 2 55,943 62,444 67,791 78,231 82,698 87,004 91,573 95,447 100,513 106,026 Notes: The table shows the income tax schedule for the years 2006 to 2015. Amounts are in tousands of Costa Rican colones (CRC, ). Panel A shows the location of the kinks on taxable income that separate the ve tax brackets for the self-employed. The tax is applied to taxable income at marginales rates of 0, 10, 15, 20 and 25% respectively for the rst to fth tax bracket. Panel B shows the location of the notches on revenue that separate the three tax brackets for corporations. The tax is applied to taxable income at average rates of 10, 20 and 30% respectively for the rst to third tax bracket. For more information on the tax base, tax schedule and the ling procedure, see http://www.hacienda.go.cr/contenido/12994-regimen-tradicional. Table II: Withholding Rate Schedule for Sales Tax Withholding Rate 0 1 2 3 4 5 6 Base before 08/2011: Value-Added Rate ≤ 5 20 30 40 55 75 ∞ Base since 08/2011: Share of Local Sales ≤ 0 - - 50 - - 100 Notes: The table shows the withholding rate which credit/debit card companies apply to the sales of their sales-tax-liable clients. Prior to August 2011, the average withholding rate was determined by a notched schedule on value-added, with notches at value-added rates of 5, 20, 30, 40, 55 and 75%, and resulting withholding rates between 0 and 6%. Since August 2011, the schedule has been consolidated to three withholding rates of 0, 3 and 6%. The rates are determined by a notched schedule on the share of local sales, with a notch at 50%. 28 Table III: Informative Declarations to Tax Authorities (1) (2) (3) (4) (5) (6) Form Purpose Record Type Coverage of Coverage of % Matched With Corporations Self-Employed Income Tax Records D151 Reporting of rm-rm transactions Sales 46.5 38.9 37.0 N=17,125,017 (54.3% sales) Purchases 49.3 54.1 65.5 D158 Reporting of transactions at auctions Sales 0.5 1.7 16.4 N=369,002 (71.0% sales) Purchases 0.3 0.9 23.5 D150 Withholding on purchases State purchases 8.4 5.0 78.7 N=759,391 (98.5% state purchase) Private purchases 0.22 0.08 39.9 D153 Withholding on card transactions for GST Sales 11.5 [26.7] 5.8 [18.4] 67.8 [48.7] N=4,198,384 Notes: This table provides information about the nature and coverage of third-party informative declarations used by the tax authorities in Costa Rica, 29 for 2006 to 2014. Columns 1-3 provide the form number, its purpose, the number of observations and the record type. Columns 4 and 5 display the share of income tax lers covered by the dierent third-party declarations, distinguishing corporations and the self-employed. Column 6 displays the share of informative declarations which are matched with an income tax declaration. In the last row, the shares in brackets refer to the match rate with the monthly sales tax declarations for 2008-2014. The shares are calculated on the pooled data for all years/months. All declarations identify the reporter and taxpayer by their administration-internal anonymous tax ID, and provide information on the transaction amount, and (where applicable) the amount of the tax withheld. Amounts are accrued. Since January 2012, all declarations must be prepared using the DECLAR@7 software. Sanctions for non-compliance with the obligation to submit informative declarations are specied in the Codigo de Normas y Procedimientos Tributarios. All declarations are annual, except D153, which is monthly. D151 requires reporting of transactions >2.5 mio  annually with a transaction partner, and transactions of >50,000  annually for rent, commissions, professional services or interests. For D150, the withholding rate is 2% and 3% respectively for state and private purchases. For D153, the withholding rate is rm specic, following the schedule in Table II. For more information on the ling of informative declarations, see http://www.hacienda.go.cr/contenido/12997-declaraciones-informativas. Table IV: Intensive Margin Misreporting Sales Reports Cost Reports Self-Employed Corporations Self-Employed Corporations Panel A: Underreporting IT 1) % Underreporters IT vs TPI 16.9 14.2 50.6 29.8 2) Unreported Amount 270.6 2799.7 271.1 1021.1 3) Underreporters' TPI 652.9 7010.6 953.2 3603.3 4) Total TPI 1859.8 20664.1 1507.5 16421.4 5) Unreported Amount(% UR TPI) 41.4 39.9 28.4 28.3 6) Unreported Amount(% TPI) 14.5 13.5 18 6.2 Panel B: Underreported Liability 7) Unreported Tax IT 12.7 71.1 8) Underreporters' Reported Tax 3.3 51.8 9) Total Reported Tax 26.6 800.1 10) Unreported Tax (% UR Tax) 385.6 137.4 11) Unreported Tax (% Tax) 47.7 8.9 Panel C: Internal Consistency 12) % Underreporters IT vs OTPI 3.6 5.3 17 8.3 13) % Overreporters IT vs OTPI 43.5 62.9 81.1 90.2 14) % Underreporters IT vs ST 9.4 9.6 14 5.9 15) % Overreporters IT vs ST 53.8 61.6 83.5 93.6 Notes: This table displays estimates of compliance gaps between third-party reports and self-reports for the income tax. Third-party reported sales for the income tax is the sum of sales reported under D150, D151, D158, D153, and exports. Third-party reported costs for the income tax is the sum of costs reported under D151 and D158. Third-party reported sales for the sales tax is the sum of sales reported on D153 declarations. Columns 1-2 are for sales reports, and columns 3-4 for cost reports. In both analyses, we consider separately the self-employed (columns 1 and 3) and corporations (columns 2 and 4). All gures in this table are either in percent (as indicated), or in billions of constant 2015 colones. Underreporters (overreporters) are rms reporting an amount at least 0.25% smaller (larger) than the relevant comparison amount. Rows 1-6 examine underreporting of third-party reported sales/costs. They show the share of under-reporters among rms subject to third-party reporting for the income tax (1), the amount unreported (as compared to third- party reports) (2), the total third-party reports for under-reporters (3), the total third-party reports for the full sample (4), and the unreported amount as a share of the underreporters third-party reports (5), and as a share of total third-party reports (6). Rows 7-11 convert unreported sales into tax liabilities. They show an estimate of the unreported tax liability (7), the underreporters' reported tax liability (8), and the total reported tax liability (9), and the unreported tax as share of the underreporters' reported tax (10), and as a share of the total reported tax (11). The estimation of the unreported (gross) tax liability assumes that the prot rate on unreported sales is the same as the prot rate on reported sales (capped at 100%), and applies the tax schedule as displayed in Table I. Rows 12-15 analyze internal constency in ling. Rows 12 and 13 compare self-reports for the income tax to a rm's own third-party reports (third-party reports submitted by the rm itsself about transactions with other rms), and rows 14 and 15 compare income tax reports to sales tax reports. All calculations are based on 2010 data. Results are similar for other years, and when focusing only on rms that le according to the regular scal period. 30 Table V: Impact of Withholding Rate Increase (1) (2) (3) (4) (5) (6) Pre-Reform Mean Pre-Reform Mean Basline Winsorized Winsorized Winsorized Treated, Raw Data Treated, 99.9th pctile Raw Data 99.9th pctile 99th pctile 95th pctile Sales Tax Collected 3079.697 3077.173 0.031 -0.000 -0.002 0.015∗ (36.814) (21.050) (0.041) (0.020) (0.009) (0.006) Input Tax Credits 2657.075 2657.075 -0.038 -0.043 -0.032∗∗ -0.034∗∗∗ (20.749) (17.332) (0.033) (0.023) (0.011) (0.007) Import Credits 680.918 680.918 -0.092 -0.085 -0.015 -0.076∗∗∗ (12.184) (9.884) (0.062) (0.045) (0.027) (0.019) Local Purchase Credits 1976.060 1975.925 -1.015 -0.023 -0.030∗∗ -0.029∗∗∗ (200.210) (11.026) (0.978) (0.022) (0.010) (0.007) Pre-Gross Tax Liability 580.168 580.055 0.154∗∗∗ 0.163∗∗∗ 0.180∗∗∗ 0.193∗∗∗ (8.387) (7.662) (0.033) (0.029) (0.021) (0.013) Pre-Gross Tax Balance 155.477 148.291 -0.144 0.118 0.090∗ -0.050∗ (7.824) (2.464) (0.182) (0.078) (0.044) (0.025) Previous Gross Tax Balance 19631.301 223.293 -3.965 0.063 0.117∗∗ 0.232∗∗∗ (9468.210) (2.723) (3.678) (0.072) (0.043) (0.027) Gross Tax Liability 464.368 460.498 0.184∗∗∗ 0.182∗∗∗ 0.196∗∗∗ 0.227∗∗∗ (7.593) (7.021) (0.037) (0.035) (0.024) (0.016) Withholding Base 7541.377 7502.520 -0.024 0.005 0.009 -0.009 (67.197) (61.485) (0.031) (0.017) (0.012) (0.009) Withheld Tax 90.552 90.302 2.159∗∗∗ 2.180∗∗∗ 2.633∗∗∗ 2.927∗∗∗ (2.391) (2.148) (0.132) (0.127) (0.101) (0.071) Withheld Tax Reclaims 79.953 79.665 1.607∗∗∗ 1.676∗∗∗ 2.099∗∗∗ 2.367∗∗∗ (2.834) (2.145) (0.140) (0.133) (0.109) (0.078) Net Tax Liability 378.400 378.186 -0.041 -0.037 -0.029 -0.048∗∗ (6.348) (5.827) (0.037) (0.036) (0.026) (0.016) Compensation Requests 22.580 16.018 0.729∗∗ 0.531∗ 0.154 0.000 (2.151) (0.509) (0.280) (0.207) (0.163) (.) Final Tax To Pay 418.517 366.641 -0.046 -0.092∗ -0.093∗∗∗ -0.107∗∗∗ (14.260) (5.551) (0.133) (0.036) (0.025) (0.016) Final Tax To Pay (Constructed) 361.288 361.177 -0.088∗ -0.085∗ -0.068∗∗ -0.079∗∗∗ (5.991) (5.477) (0.035) (0.034) (0.025) (0.016) Taxpayer Payment 290.444 280.948 -0.070 -0.048 -0.068∗∗ -0.079∗∗∗ (4.455) (2.911) (0.037) (0.027) (0.021) (0.015) Total Payment 380.996 378.150 0.471∗∗∗ 0.476∗∗∗ 0.571∗∗∗ 0.680∗∗∗ (5.516) (4.376) (0.038) (0.036) (0.029) (0.021) Total Payment (Constructed) 509.068 458.060 0.351∗∗∗ 0.368∗∗∗ 0.412∗∗∗ 0.568∗∗∗ (14.743) (6.712) (0.113) (0.036) (0.025) (0.020) Observations 1061280 1061280 1061280 1061280 1061280 1061280 R2 0.001 0.004 0.265 0.645 0.770 0.816 OLS estimation. Point estimates are marginal eects compared to pre-reform average. Columns 3-6 allow for year and rm FE and a rm-specic linear time trend. Standard errors in parentheses, clustered at the taxpayer level in parantheses. All amounts are in '000 CRC, deated with base in 06/2015 (1USD=530CRC). (W) indicates that outcome variables are winsorized at the 99th percentile. 31 Figure I: Withholding Systems and GDP per capita 50 10 40 30 Bars 1-4 Bars 5-6 5 20 10 0 0 N=175 N=47 N=27 N=20 N=5 N=4 s H H H H H rie W W W W W nt ith d ed : no AT ou oa w et : D lC AT Br rg s TA rie Al Ta D nt TA ou C Mean GDP pc Median GDP pc 95% CI Notes: This gure displays the mean and median GDP per capita, and the 95% condence interval on the mean, for dierent subsamples of countries. GDP per capita is measured in thousands of current international dollars (purchasing-power parity) from the World Development Indicators for 2012. The year 2012 is chosen as it provides GDP data for the largest number of countries. The number below each bar provides the sample size. The rst bar refers to all countries captured in the dataset. The second bar refers to the subsample of countries that use withholding on business sales, as per the above-mentioned secondary sources (some of which are outdated and are currently being updated) and the condential TADAT (Tax Administration Diagnostic Assessment Tool) reports. The third and fourth bar further divide this subsample into countries that use a broad withholding regime (in which withholding may be limited to certain types of rms or transactions, but not to specic sectors), and those that use a specialized withholding regime, applicable only to certain sectors (e.g. construction, shing). The fth and sixth bar focus on the sample of countries covered by the rst TADAT round (excluding one OECD country), comparing countries that do not use withholding on business sales to countries that use withholding (combining both broad and specialized schemes). 32 Figure II: Filing Behavior Share of Non-Filers (All Tax-Liable Firms) 60 56.3 50 44.7 40 37.0 Percent 34.1 30 20 10 0 Income Tax Income Tax (TPI) Sales Tax Sales Tax (TPI) Income Tax: 2014, Sales Tax: 12/2014. Share of Non-Filers (Registered Firms) 25.2 25 18.8 18.9 20 14.4 Percent 15 11.8 11.7 10 5 1.9 1.3 0 Income Tax Income Tax (TPI) Sales Tax Sales Tax (TPI) Self-Employed Corporations Notes: The gure shows the share of non-lers, i.e. tax-liable rms which have not submitted their own tax declaration for the relevant scal period. The rst panel focuses on all tax liable rms, identied from the tax register, previous tax declarations and informative declarations, as per the algorithm explained in Section 5.1. The bottom panel focuses on the subset of registered rms, for which we can identify the rm type (self-employed or corporation). In the top panel, the orange bars pertain to the income tax and the green bars pertain to the sales tax. The dark bars are for the full sample, and the light bars are for the subsample of rms covered by third-party information. In the lower panel, the red bars are for all tax liable rms, the blue bars are for the subsample of tax liable rms which are covered by third-party information. The dark bars are for the self-employed, the light bars for corporations. In both gures, the income tax data is for scal year 2014, the sales tax data is for December 2014. 33 Figure III: Self-Reports vs Third-Party Reports Sales Report For Income Tax Costs Report For Income Tax 3 2 % Under-Reporters [Bunchers]: Self-Employed: 18% [1%] 1.5 2 Corporations: 9% [2%] % Under-Reporters [Bunchers]: Percent Percent Self-Employed: 60% [2%] Corporations: 28% [3%] 1 1 .5 0 0 -1 -.5 0 .5 1 -1 -.5 0 .5 1 log(self-report+1)-log(third-party-report+1) log(self-report+1)-log(third-party-report+1) Self-Employed Corporations Self-Employed Corporations Sales Report For Sales Tax Sales Report For Income Tax vs Sales Tax 150 1.5 % Under-Reporters [Bunchers]: % Under-Reporters [Bunchers]: 100 Self-Employed: 12% [1.3%] Self-Employed: 8% [66.9%] 1 Percent Percent Corporations: 10% [.8%] Corporations: 6.5% [60.0%] 50 .5 0 0 -1 -.5 -.122 0 .5 1 -.1 -.05 0 .05 .1 log(self-report+1)-log(third-party-report+1) log(income-tax-report+1)-log(sales-tax-report+1) Self-Employed Corporations Self-Employed Corporations Notes: The gure shows the distribution of the log dierence between rms' self-reported and third-party reported sals and costs, for rms with non-zero amounts of third-party reports and ling taxes for scal year 2012. As the third-party reported data is always reported for the regular scal year (October to September), we focus on rms that le their tax declaration according to the same period, dropping the 32% of rms that le outside of a 10-day interval around the ling deadline for the regular scal period, December 15. Third-party reported sales for the income tax is either the sum of sales reported under D150, D151 and D158, or D153, whichever is larger. Third-party reported costs for the income tax is the sum of costs reported under D151 and D158. Third-party reported sales for the sales tax is the sum of sales reported on D153 declarations. Bunchers are rms that exactly match third-party reports (within a 1% error margin). Under-reporters are rms with a dierence between log self-reports and log third-party reports of more than -0.05. The bin size is 0.01 for all gures, except the bottom right one, for which the bin size is 0.005. 34 Figure IV: Impact of Desk Audits Income Tax 2013 & 2014 Income Tax Zero-Declarers 2014 500 500 Share of revisers: 1% Share of revisers: 1% Initial tax declared: 759 mio CRC Initial tax declared: 0 mio CRC Increase post revision: 1335 mio CRC (+.12% of total revenue) Increase post revision: 122 mio CRC 400 400 Cost change (mio CRC) Cost change (mio CRC) Cost: 5138*36,700 = 188 mio CRC Cost: ~0 CRC 300 300 200 200 100 100 0 0 0 100 200 300 400 500 0 100 200 300 400 500 Revenue change (mio CRC) Revenue change (mio CRC) Taxpayer-Year 45 degree line Linear fit Taxpayer-Year 45 degree line Linear fit Sales Tax 2013 Share of revisers: 1% 5 Change in Input Tax Credit (mio CRC) Initial tax declared: 165 mio CRC Increase post revision: 224 mio CRC (+.02% of total revenue) Cost: 2000*36,700 = 73 mio CRC 1 2 0 3 4 0 1 2 3 4 5 Change in Tax Collected(mio CRC) Taxpayer-Month 45 degree line Linear fit Notes: The gure shows the revenue and cost adjustments made by rms contacted via phone calls by tax ocers after a desk audit uncovered a discrepancy between self-reported and third-party reported sales. 35 Figure V: Bunching At First Income Tax Kink for Self-Employed 2006 2007 2008 1500 2000 1500 1500 Number of Taxpayers Number of Taxpayers Number of Taxpayers 1000 1000 1000 500 500 500 0 0 0 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 Taxable Income (in '000 colones) Taxable Income (in '000 colones) Taxable Income (in '000 colones) 2009 2010 2011 1500 2000 2000 1500 1500 Number of Taxpayers Number of Taxpayers Number of Taxpayers 1000 1000 1000 500 500 36 500 0 0 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 Taxable Income (in '000 colones) Taxable Income (in '000 colones) Taxable Income (in '000 colones) 2012 2013 2014 2000 1200 2500 1000 2000 1500 Number of Taxpayers Number of Taxpayers Number of Taxpayers 1500 800 1000 1000 600 500 500 400 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 Taxable Income (in '000 colones) Taxable Income (in '000 colones) Taxable Income (in '000 colones) Notes: The gures show the frequency distribution of taxable income of the self-employed (personas sicas con actividad lucrativa) around the rst kink in the income tax schedule, for the years 2006-2014. The data is aggregated in bins of  20,000. The black solid line marks the kink in year t (as per the gure title), the black dashed line marks the kink in year t − 1. Figure VI: Payment of Tax Liabilities Average Payment Share of Net Liability, Income Tax 1 Average Payment Share .85 .9 .8 .95 2006 2008 2010 2012 2014 Year Self-Employed, cut 04-2015 Corporations, cut 04-2015 Self-Employed, cut 04-2013 Corporations, cut 04-2013 Self-Employed, cut 04-2011 Corporations, cut 04-2011 Average Payment Share of Net Liability, Sales Tax 1 .95 Average Payment Share .8 .85 .75 .9 2009m1 2010m7 2012m1 2013m7 2015m1 Month Self-Employed, cut 04-2015 Corporations, cut 04-2015 Self-Employed, cut 04-2013 Corporations, cut 04-2013 Self-Employed, cut 04-2011 Corporations, cut 04-2011 Notes: This gure shows the average of the payment share, dened as the total payment made by the taxpayer for a specic tax period, divided by the nal tax liability to be paid for that period. The average is an unweighted average across all taxpayers with an positive nal liability for each scal period. The nal tax liability is net of any deduction made for tax withheld, and the payment data does not include tax withheld. The income tax data includes all declarations led and payments made by June 2015. The sales tax data includes all declarations led and payments made by October 2015. The blue series correspond to the self-employed and the red series corresponds to corporations. We show the series for three dierent cuts in the paymen data, taking into account all payments made before the cut date. 37 Figure VII: Bunching, Information Reporting and Withholding Self-Employed Not Subject to Information Reporting/Withholding Self-Employed Subject to Information Reporting Self-Employed Subject to Withholding .0035 .008 .006 Excess mass b=2.08(.17) Excess mass b=1.19(.19) Excess mass b=4.5(.3) .005 .003 .006 Missing mass m=-.14(.06) Missing mass m=.75(.08) .004 Missing mass m=.23(.07) .0025 Density Density Density .004 .003 .002 .002 .002 .0015 .001 0 50 100 150 50 100 150 50 100 150 Taxable Income/Kink (%) Taxable Income/Kink (%) Taxable Income/Kink (%) Observed distribution Counterfactual Observed distribution Counterfactual Observed distribution Counterfactual Corporations Not Subject to Information Reporting/Withholding Corporations Subject to Information Reporting Corporations Subject to Withholding .0008 Excess mass b=4.49(.47) .002 .002 Excess mass b=3.17(.21) Excess mass b=1.33(.27) .0006 Missing mass m=3.65(1.01) .0015 Missing mass m=1.07(.2) .0015 38 Missing mass m=.72(.25) Density Density Density .0004 .001 .001 .0002 .0005 .0005 0 50 100 150 50 100 150 50 100 150 Total Revenue/Notch (%) Total Revenue/Notch (%) Total Revenue/Notch (%) Observed distribution Counterfactual Observed distribution Counterfactual Observed distribution Counterfactual Notes: The gure shows the density distribution of taxable income for the self-employed around the rst kink in the income tax schedule (top row), and the density distribution of total revenue for corporations around the rst notch in the corporation tax schedule (bottom row). The data is pooled for years 2006-2014, represented as percentage distance from the kink, and aggregated in taxable income bins of 1%. The panels show the distribution for dierent subsamples, as indicated by the panel titles. The blue dotted line marks the empirical distribution, the red solid line marks the counterfactual, tted as a exible polynomial to the observed distribution outside the excluded range. We use an eighth-degree polynomial for self-employed and a sixth-degree polynomial for corporations. The excluded range above the threshold covers four and seven bins respectively in the two groups of rms. The excess mass b and missing mass m are estimated as the dierence between the observed and estimated density, weighted by the height of the counterfactual density. The standard errors are bootstrapped. Figure VIII: Event Study of Reporting Behavior Reporting by Other Firms (D151 Sales) Reporting by Other Firms (D151 Sales) Self-Employed Corporations 2.5 2.5 Change in Taxable Income Change in Taxable Income 2 2 1.5 1.5 DD=.182 (.027) DD=.058 (.114) 1 1 .5 .5 -4 -3 -2 -1 0 1 2 3 -4 -3 -2 -1 0 1 2 3 Event Year Event Year Control Group Event Group Control Group Event Group Withholding by State (D150) Withholding by State (D150) Self-Employed Corporations 2.5 2.5 Change in Taxable Income Change in Taxable Income 2 2 1.5 1.5 DD=.425 (.069) DD=.253 (.045) 1 1 .5 .5 -4 -3 -2 -1 0 1 2 3 -4 -3 -2 -1 0 1 2 3 Event Year Event Year Control Group Event Group Control Group Event Group Reporting by Credit/Debit Card Company (D153) Reporting by Credit/Debit Card Company (D153) Self-Employed Corporations 2.5 2.5 Change in Taxable Income Change in Taxable Income 2 2 1.5 1.5 DD=.442 (.133) DD=.211 (.048) 1 1 .5 .5 -4 -3 -2 -1 0 1 2 3 -4 -3 -2 -1 0 1 2 3 Event Year Event Year Control Group Event Group Control Group Event Group Notes: The gures display the change in tax liability, compared to the pre-event average of the event and control group, for event years -4 to 3. The event group includes rms that receive a rst informative declaration in event year 0. Event years considered in this estimation are 2010 and 2011, and control rms are all rms that have not received a rst informative declaration by the event year. The left column is for the self-employed, the right column is for corporations. Panel A considers the receipt of a rst informative declaration from another rm (information reporting only), panel B considers the receipt of a rst informative declaration from a state institution (information reporting and withholding), and panel C considers the receipt of a rst informative declaration from a credid/debit card company (information reporting and withholding). The text displays the dierence-in-dierence estimate from equation 1. 39 Figure IX: Withholding Rate Reform Withholding Rate Withholding Base 12000 3 10000 11000 2.5 Average Withholding Base Average Rate 2 9000 1.5 8000 7000 1 2008m7 2010m1 2011m7 2013m1 2014m7 2008m7 2010m1 2011m7 2013m1 2014m7 Month Month Number of Sales Tax and Withholding Declarations 40000 Matching of Sales Tax and Withholding Declarations 70000 .27 .53 .26 .52 Share Withholding 35000 Share Sales Tax 65000 N Withholding .25 N Sales Tax .51 .24 30000 60000 .5 .23 .49 .22 55000 25000 2009m1 2010m1 2011m1 2012m1 2013m1 2009m1 2010m1 2011m1 2012m1 2013m1 Month Month Share Sales Tax Declarations Matched With Withholding N Sales Tax Declarations N Withholding Declarations Share Withholding Declarations Matched With Tax Declaration Notes: The gure displays the average withholding rate among rms subject to withholding (panel A), the average withholding base (credit/debit card sales) among those rms (panel B), the total number of sales tax and withholding declarations per month (panel C), and the share of sales tax declarations matched with at least one withholding declaration, and vice versa (panel D). The black solid line marks 08/2011, when the increase in withholding rates entered into eect. The gures show that the withholding rate increase was not accompanied by a discontinuous change in the average withholding base, the number of sales tax or withholding declarations, and only a modest increase in the likelihood that a taxpayer covered by withholding les her sales tax declaration. 40 Figure X: Impact of Withholding Rate Increase Total Payment 2.5 2 DD=.412 (.025) Change 1.5 1 .5 2010m1 2011m1 2012m1 2013m1 Date Treatment Group (Rate Increase) Control Group Total Payment: Impact by Treatment Strength 3 DD=.940 (.058) DD=.384 (.034) Change 2 DD=.294 (.031) 1.5 1 .7 2010m1 2011m1 2012m1 2013m1 Date T: 1-2 pp Increase T: 3-4 pp Increase T: 5-6 pp Increase Control Group Notes: The gure displays the results of the dierence-in-dierence estimation of Equation 2, with total tax payment as outcome variable. The rst panel considers the overall impact of the reform, pooling all rms with a predicted rate increase in the treatment group. The second panel considers the impact of the reform by treatment strength, distinguishing rms with a predicted rate increase of 1-2, 3-4 and 5-6 percentage points. The control group includes rms experiencing no increase in the predicted withholding rate and rms not subject to withholding. The black solid line marks 08/2011, when the increase in withholding rates entered into eect. The data is winsorized by the 99th percentile, and scaled by the pre-reform average. The text displays the coecient β (marginal eect compared to pre-reform average) from estimating Equation 2. 41 Figure XI: Mechanisms of Withholding Rate Impact Mechanism 1: Incomplete Reclaim Reclaimers over Withholdees Share of Withheld Tax Reclaimed 1.2 .7 .65 1.1 .6 1 Share Share .55 .9 .5 .45 .8 .4 2010m1 2011m1 2012m1 2013m1 2010m1 2011m1 2012m1 2013m1 Date Date Mechanism 2: Reduced Mis-Reporting Input Tax Credits Sales Tax Collected 1.2 1.3 DD=-.02 (.009) DD=.007 (.007) 1.2 1.1 1.1 Change Change 1 1 .9 .9 .8 .8 .7 2010m1 2011m1 2012m1 2013m1 2010m1 2011m1 2012m1 2013m1 Date Date Treatment Group (Rate Increase) Control Group Treatment Group (Rate Increase) Control Group Gross Tax Liability 2 DD=.116 (.017) 1.5 Change 1 .7 2010m1 2011m1 2012m1 2013m1 Date Treatment Group (Rate Increase) Control Group Notes: The gure displays evidence on the mechanisms for the withholding rate impact. In all panels, the black solid line marks 08/2011, when the increase in withholding rates entered into eect. Panels A and B display, for all rms subject to withholding in a given month, the share of rms making a reclaim, and the average share of withheld tax reclaimed. The shares are winsorized by the 99.9th percentile. Panels C, D and E show results of the dierence-in-dierence estimation of Equation 2, with dierent outcome variables, as indicated by the gure titles. The treatment group includes rms experiencing an increase in the predicted withholding rate in 08/2011, the control group includes rms experiencing no increase in the predicted withholding rate and rms not subject to withholding. The data is winsorized by the 99th percentile, and scaled by the pre-09/2011 average. The text displays the coecient β (marginal eect compared to pre-reform average) from estimating Equation 2. 42 Figure XII: Aggregate Impact Total Sales Tax Revenue (Official Statistics) 15 Pre-Reform Mean: RD: 4.73 (1.13) Revenue Demeaned (Bio. Col) 49.5 bio. CRC 0 5 -5 10 2008m1 2010m1 2012m1 2014m1 2016m1 Month Tax Revenue Linear Fit Notes: This gure shows the impact of the withholding rate reform in August 2011 on aggregate sales tax revenue. The dots represent monthly sales tax revenue in billions of Costa Rican colones, as per the ocial statistics. The red line is a linear t, allowing for a discontinuity at the time of the reform. The text displays the coecient and standard error on the post-reform dummy. The results are robust to omitting or controlling for the outlier months of December and January. 43 Appendix Figure XIII: Payment of Tax Liabilities Share of Net Tax Liability Paid, Income Tax 1 .8 Share Paid .6 .4 .2 2006 2008 2010 2012 Year Total Share, Self-Employed Total Share, Corporations Mean Share, Self-Employed Mean Share, Corporations Share of Net Tax Liability Paid, Sales Tax 1 .8 Share Paid .4 .2 0 .6 2009m7 2010m7 2011m7 2012m7 2013m7 2014m7 Month Total Share, Self-Employed Total Share, Corporations Mean Share, Self-Employed Mean Share, Corporations Notes: This gure extends Figure VI, displaying additionally the share of total tax payments made by the taxpayers over the total nal tax liablity. All variable denitions are as in the notes to Figure VI. See Section 5.3 for a discussion of these results. 44 Figure XIV: Robustness of Withholding Impact Panel A: Self-Employed Panel B: Payers and Zero-Liability Firms 2.2 DD=.857 (.045) DD=.465 (.025) 2 2 2.2 Change Change 1.5 1.5 1 1 .7 .7 2010m1 2011m1 2012m1 2013m1 2010m1 2011m1 2012m1 2013m1 Date Date Treatment Group (Rate Increase) Control Group Treatment Group (Rate Increase) Control Group Panel C: Payers Only Total Payment 2.2 2 DD=.353 (.039) Change 11.5 .7 2010m1 2011m1 2012m1 2013m1 Date Treatment Group (Rate Increase) Control Group Notes: This gure replicates Figure X, limiting the sample to the self-employed (panel A), rms with zero net liability or non-zero (own) tax payment (panel B), and rms making a non-zero (own) tax payment (panel C). 45 Figure XV: Impact if Income Tax Withholding for Firms Gross Tax Liability 1.4 DD=.237 (.018) Year-on-Year Change 1 1.2 Introduction of CIT WH .8 2008 2010 2012 2014 2015 Year Treatment Group (Withholdees) Control Group Notes: This gure shows the impact of the introduction on withholding for the income tax in 2015 (corporation and self-employed) on reported gross tax liability, using a dierence-in-dierence estimation. 46 Figure XVI: Audit Rates 1000 .3 900 .25 Number of Audits Audit Rate (%) 800 .2 700 .15 600 500 .1 2009 2010 2011 2012 2013 2014 Year N planned audits N planned (non-LTU firms) Realized audit rate (%) Notes: This gure shows the evolution over time of the number of planned audits, planned audits for rms that are not part of the large taxpayer unit, and the audit rate (total number of executed audits over number of tax-ling rms). 47 References Allingham, Michael G., & Sandmo, Agnar. 1972. Income Tax Evasion: A Theoretical Anal- ysis. Journal of Public Economics, 1, 323338. Almunia, Miguel, & Rodriguez, David Lopez. 2015. Under the Radar: The Eects of Moni- toring Firms on Tax Compliance. Social Science Research Network, August. Bachas, Pierre. 2015. Not(ch) Your Average Tax System: Corporate Taxation Under Weak En- forcement. Mimeo. Barr, Michael S., & Dokko, Jane K. 2008. Paying to save: tax withholding and asset allocation among low- and moderate-income taxpayers. Finance and Economics Discussion Series 2008-11. Board of Governors of the Federal Reserve System (U.S.). Besley, Timothy J., & Persson, Torsten. 2013 (Jan.). Taxation and Development. CEPR Discussion Papers 9307. C.E.P.R. Discussion Papers. Best, Michael, Brockmeyer, Anne, Kleven, Henrik, Spinnewijn, Johannes, & Waseem, Mazhar. 2015. Production vs Revenue Eciency with Low Tax Compliance: Theory and Evi- dence from Pakistan. Journal of Political Economy, 123(6), 13111355. Best, Michael Carlos. 2014. Salary Misreporting and the Role of Firms in Workers' Responses to Taxes: Evidence from Pakistan. Mimeo. Best, Michael Carlos, & Kleven, Henrik Jacobsen. 2015. Housing Market Responses to Transaction Taxes: Evidence from Notches and Stimulus in the UK. Mimeo. Brockmeyer, Anne. 2014. The Investment Eect of Taxation: Evidence from a Corporate Tax Kink. Fiscal Studies, 35(4), 477509. Brockmeyer, Anne, Hernandez, Marco, Smith, Spencer, & Kettle, Stewart. 2015. Casting the Tax Net Wider: Experimental Evidence from Costa Rica. Mimeo. Bruhn, Miriam, & McKenzie, David. 2014. Entry Regulation and the Formalization of Mi- croenterprises in Developing Countries. World Bank Research Observer, 29(2), 186201. Carillo, Paul, Emran, Shahe, & Rivadeneira, Anita. 2012. Do cheaters bunch together? Prot taxes, withholding rates and tax evasion. Mimeo. 48 Carrillo, Paul, Pomeranz, Dina, & Singhal, Monica. 2014. Tax Me if You Can: Evidence on Firm Misreporting Behavior and Evasion Substitution. Working Paper, Harvard University. Chetty, Raj, Friedman, John, Olsen, Tore, & Pistaferri, Luigi. 2011. Adjustment Costs, Firm Responses, and Micro vs. Macro Labor Supply Elasticities: Evidence from Danish Tax Records. Quarterly Journal of Economics, 126, 749804. Chetty, Raj, Friedman, John N., Leth-Petersen, Súren, Nielsen, Torben Heien, & Olsen, Tore. 2014. Active vs. Passive Decisions and Crowd-Out in Retirement Savings Accounts: Evidence from Denmark. The Quarterly Journal of Economics, 129(3), 11411219. de Mel, Suresh, McKenzie, David, & Woodruff, Christopher. 2013. The Demand for, and Consequences of, Formalization among Informal Firms in Sri Lanka. American Economic Journal: Applied Economics, 5(2), 12250. Del Carpio, Lucia. 2014. Are the Neighbors Cheating? Evidence from Social Norm Experiment on Property Taxes in Peru. Mimeo. Devereux, Michael P., Liu, Li, & Loretz, Simon. 2014. The Elasticity of Corporate Taxable Income: New Evidence from UK Tax Records. American Economic Journal: Economic Policy, 6(2), 1953. DiNardo, John, Fortin, Nicole M., & Lemieux, Thomas. 1996. Labor Market Institutions and the Distributoin of Wages, 1973-1992: A Semiparametric Approach. Econometrica, 64(5), 10011044. Farhi, Emmanuel, & Gabaix, Xavier. 2015 (Sept.). Optimal Taxation with Behavioral Agents. NBER Working Papers 21524. National Bureau of Economic Research, Inc. Fisman, Raymond, & Wei, Shang-Jin. 2004. Tax Rates and Tax Evasion: Evidence from "Missing Imports" in China. Journal of Political Economy, 112(2), 471500. Gandhi, Ashvin, & Kuehlwein, Michael. 2014. Reexamining Income Tax Overwithholding as a Response to Uncertainty. Public Finance Review. Gordon, Roger, & Li, Wei. 2009. Tax structures in developing countries: Many puzzles and a possible explanation. Journal of Public Economics, 93(7-8), 855866. 49 Highfill, Jannett, Thorson, Douglas, & Weber, William V. 1998. Tax Overwithholding as a Response To Uncertainty. Public Finance Review, 26(4), 376391. Hilger, Nathaniel G. 2014. Parental Job Loss and Children's Long-Term Outcomes: Evidence from 7 Million Fathers' Layos. Mimeo. IRS. 2012. Tax Year 2006 Tax Gap Estimates. Tech. rept. Internal Revenue Service. FS-2012-6. Johnson, Eric J., & Goldstein, Daniel. 2003. Do Defaults Save Lives? Science, 302(5649), 13381339. Keen, Michael. 2008. VAT, taris, and withholding: Border taxes and informality in developing countries. Journal of Public Economics, 92(10-11), 18921906. Kleven, Henrik. 2016. Bunching. Annual Review of Economics, forthcoming, 8. Kleven, Henrik J., & Waseem, Mazhar. 2013. Using Notches to Uncover Optimization Fric- tions and Structural Elasticities: Theory and Evidence from Pakistan. Quarterly Journal of Economics, 128, 669723. Kleven, Henrik Jacobsen, Knudsen, Martin B., Kreiner, Claus Thustrup, Pedersen, Søren, & Saez, Emmanuel. 2011. Unwilling or Unable to Cheat? Evidence From a Tax Audit Experiment in Denmark. Econometrica, 79(3), 651692. Kleven, Henrik Jacobsen, Kreiner, Claus Thustrup, & Saez, Emmanuel. 2015. Why Can Modern Governments Tax So Much? An Agency Model of Firms as Fiscal Intermediaries. Mimeo. Kopczuk, Wojciech, & Slemrod, Joel. 2006. Putting Firms into Optimal Tax Theory. Amer- ican Economic Review Papers and Proceedings, 96(2), 130134. Kumler, Todd, Verhoogen, Eric, & Frías, Judith A. 2015. Enlisting Workers in Improving Payroll-Tax Compliance: Evidence from Mexico. NBER Working Paper 19385. Madrian, Brigitte C., & Shea, Dennis F. 2001. The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior. The Quarterly Journal of Economics, 116(4), 11491187. Naritomi, Joana. 2015. Consumers as Tax Auditors. Mimeo. 50 OECD. 2009. Withholding and information reporting regimes for small or medium-sized businesses and self-employed taxpayers, Information Note. Tech. rept. OECD. Pomeranz, Dina. 2015. No Taxation without Information: Deterrence and Self-Enforcement in the Value Added Tax. American Economic Review, 105(8), 25392569. Rijkers, Bob, Baghdadi, Leila, & Raballand, Gael J. R. F. 2015 (June). Political connec- tions and tari evasion : evidence from Tunisia. Policy Research Working Paper Series 7336. The World Bank. Saez, Emmanuel. 2010. Do Taxpayers Bunch at Kink Points? American Economic Journal: Economic Policy, 2(3), 180212. Samanamud, Enrique. 2013. Estudio comparado de los regimenes de retenciones y percepciones del IVA e impuesto a la renta en America Latina y el Caribe. Tech. rept. Inter-American Centre of Tax Administrations. Seim, David. 2015. Behavioral Responses to an Annual Wealth Tax: Evidence from Sweden. Mimeo. Slemrod, Joel B., Collins, Brett, Hoopes, Jeffrey L., Reck, Daniel H., & Sebas- tiani, Michael. 2015. Does Credit-Card Information Reporting Improve Small-Business Tax Compliance? Mimeo. Soos, Pirosko. 1990. Self-employed evasion and tax withholding: a comparative study and analysis of the issues. UC Davis Law Review, 24(107), 107193. Thaler, Richard, & Benartzi, Shlomo. 2004. Save more tomorrow: Using behavioral eco- nomics to increase employee saving. The Journal of Political Economy, 112(1), 164187. United Nations. 2014. Measuring Tax Transactions Costs in Small and Median Enterprises. Tech. rept. United Nations and Inter-American Centre of Tax Administrations. White, Richard A., Harrison, Paul D., & Harrell, Adrian. 1993. The Impact of Income Tax Withholding on Taxpayer Compliance: Further Empirical Evidence. Journal of the American Taxation Associationl, May, 6378. Yagan, Danny. 2015. Capital Tax Reform and the Real Economy: The Eects of the 2003 Dividend Tax Cut. American Economic Review, forthcoming. 51 Zucman, Gabriel. 2013. The Missing Wealth of Nations: Are Europe and the U.S. net Debtors or net Creditors?*. The Quarterly Journal of Economics, 128(3), 13211364. 52