A Helping Hand or the Long Arm of the Law? Experimental Evidence on What Governments Can Do to Formalize Firms

Spurred by the work of Hernando de Soto (1989) and the World Bank/IFC's Doing Business project, governments around the world have spent much of the past decade extending a helping hand to informal businesses by trying to make it cheaper and less burdensome to formalize. Since 2004, 75 percent of countries have adopted at least one reform to make it easier to register a business (IFC 2009). However, despite these efforts, the majority of firms in most developing countries remain informal. Studies that have examined the impact of these regulatory reforms find that much of the action comes from increases in the entry of new firms rather than from the formalization of existing firms (e.g., Klapper et al. 2006; Bruhn 2011).¹ Policymakers worry that a large stock of informal firms will result in a loss in tax revenue, unfair competition for formal firms, and a culture of informality (Perry et al. 2007; Levy 2008).

Although policymakers and researchers have devoted attention to reducing the costs of formalizing, much less attention has been given to the issue of increasing the costs of remaining informal. The most obvious way to raise these costs is to use the long arm of the law to increase the enforcement of existing regulations. Yet, to our knowledge, there is very little empirical evidence on whether enforcement attempts can induce firms to register or whether, instead, they cause informal firms to close down and prevent other firms starting up. There is a large body of related literature in developed countries showing that increases in the probability of detection and enforcement lead to an increase in tax compliance and that other factors, such as a household's sense of moral or social obligation, are also important (e.g., Alm et al. 1992; Andreoni et al. 1998). More recent non-experimental studies in developing countries have found evidence that the degree of enforcement matters for labor informality (Ronconi 2007; Almeida and Carneiro 2012), but we are aware of no reliable evidence on the impacts of enforcement on firm informality.

We conducted a field experiment with the state government of Minas Gerais in the city of Belo Horizonte in Brazil to test which government actions work to encourage informal firms to register. Brazil began a process of simplifying firm registration in 1996 with the introduction of the SIMPLES tax system, which consolidated multiple taxes and contributions into a single payment and reduced the tax burden on small firms. Within Minas Gerais, the Minas Fácil service was started in 2005 with the purpose of additionally reducing the number of procedures and time needed to start a business. Minas Fácil is a one-stop-shop system where firms obtain municipal, state, and federal tax registrations simultaneously instead of having to request these from separate offices. However, despite these efforts, survey data from 2009 revealed that 72 percent of firms were still informal. As a result, the state government wanted to test several competing mechanisms for reducing formality.

A listing survey was used to identify potentially informal firms, which were then randomized into four treatment groups and a control group. Survey data revealing a lack of knowledge about how to formalize motivated the first treatment, which provided information about how to register by means of a glossy brochure and a dedicated helpline. A second treatment coupled this information with an exemption in the registration fees and free use of mandatory accounting services for a year to test whether reducing registration costs would induce formalization. The third treatment randomly assigned municipal inspectors to firms to see whether increased enforcement would encourage firms to formalize. The final treatment consisted of having a neighboring firm visited by an inspector to test whether there was a spillover impact of inspection on the formalization behavior of other firms.

We find that efforts to help firms formalize by giving them information and by reducing the initial cost to zero along with offering a free accountant resulted in an increase in knowledge about the role of accountants in the formalization process but did not lead firms to formalize. In fact, this approach resulted in a small reduction in firms registering through a separate formal category – that of individual entrepreneur – which the information campaign did not target and for which the eligibility criteria were relaxed during the course of our study. Moreover, firms that were assigned to either of these two treatments expressed less trust in the government in our follow-up survey.

In contrast, assigning firms to receive a visit from a municipal inspector did result in an increase in municipal registration, although the impact was much less than anticipated by the government, with only an additional 3 percent of those assigned to treatment formalizing. This low rate is due to the inspectors finding some firms closed, not finding others, and from some firms in our sample already being formal to start with. An instrumental variables estimate suggests that the impact of actually receiving an additional inspector visit is much higher – resulting in a 21 to 27 percentage point increase in registration. We find no evidence of spillovers on neighboring firms, perhaps due to the relatively low increase in inspections and to many firms saying they do not communicate very much with neighboring businesses.

The papers that are most closely related to ours are two recent randomized experiments that test the role of “carrots” in inducing informal firms to register. De Mel et al. (2012) found no significant impact of information alone in getting firms to register with the tax authority in urban Sri Lanka, but they found that many firms are willing to register when offered money to do so, although formalizing does not seem to benefit the performance of most of these firms. Alcázar et al. (2010) and Jaramillo (2009) offered firms in Lima, Peru, information and reimbursement of direct costs to encourage municipal registration (which was separate from federal tax registration). They found that approximately one-quarter of those treated registered. This larger impact is consistent with municipal registration imposing fewer costs on firms than tax registration and, potentially, with municipal enforcement being higher.² Our paper builds on these studies by offering information and free-cost “carrots” in a context in which simplification has recently occurred but in which registration costs and complexity still remain much higher than in the Sri Lankan and Peruvian cases, and by also testing simultaneously the role of “sticks” in the form of inspections.³

Other related literature looks at the impact that formalizing has on firms. In addition to the experimental work of de Mel et al. (2012), there are several non-experimental studies that examine this question. Fajnzylber et al. (2011) and Monteiro and Assunção (2012) both analyzed the impact of the SIMPLES program on firms. These authors find that firms created after the reform invested more, were larger, and were more likely to operate in a permanent location than firms created just before the reform. However, it is unclear how much of this is an impact of formalizing versus a difference in the selection of which firms formalize. McKenzie and Sakho (2010) used an instrumental variables strategy in Bolivia based on distance to tax offices and find that some firms in Bolivia that face high costs of formalizing would gain on net from registering for taxes, whereas other firms would lose from doing so and appear to be rationally informal. Taken together, these studies imply that many informal firms would not benefit from becoming formal and are thus consistent with our results that information and reducing the costs of formalizing are not enough to induce formalization.

The remainder of the paper is structured as follows. First, we describe the process of becoming formal as a small firm in Belo Horizonte, the information firms have about the process of formalizing, and what firms see as the costs and benefits of becoming formal. We then describe our interventions and subsequently outline the data used to evaluate their impact and the experimental design. Next, we provide the results of the interventions on the rate of formalization among informal firms and conclude with a discussion of implications for policy and further studies in this area.

Context and the Process of Formalizing

Belo Horizonte is the capital city of the state of Minas Gerais in Brazil and has a city population of almost 2.5 million, with 5.5 million in the official metropolitan area (the third largest in Brazil after São Paulo and Rio de Janeiro). A 2009 survey by the Brazilian statistical agency IBGE along with government records was used by SEBRAE, the government agency for supporting micro and small businesses, to estimate that Belo Horizonte had a total of 561,310 businesses, of which 402,744 were informal (72 percent).

Registering a Microenterprise in Belo Horizonte

The Complementary Federal Law 123 defines micro-enterprises as firms with annual revenues up to R$360,000 (US$177,000),⁴ provided they are not a subsidiary of another firm. Microenterprises that meet several other conditions (the key ones being that they do not have a foreign owner or partner and are not in certain sectors such as financial services, consulting, alcohol or tobacco, or transportation) are eligible to register their businesses formally under a national simplified taxation system called SIMPLES. The SIMPLES regime combines several ongoing tax and contribution payments into a single payment (including employee taxes and the state sales tax), but it does not simplify the registration process itself. In addition, at the time our study began, enterprises with one or fewer employees and R$36,000 or less in annual revenues could instead register as individual microentrepreneurs (MEIs). This is an even simpler tax status for proprietorships in which only a fixed amount per month is paid for all taxes.⁵ Eligibility for this category was changed after our intervention had begun; the eligibility threshold was raised to R$60,000 after a law change in September 2011.

The state government created a unit called Minas Fácil in June 2008 to simplify the registration process. Registration under this new system involves registering at the federal, state and municipal levels through a single process (presented in Appendix S1, available at http://wber.oxfordjournals.org/). Many steps in the process are online, and the entire process is estimated to take seven days for an average firm. The key documents obtained are federal tax registration, evidenced by obtaining a Cadastro Nacional de Pessoas Jurídicas (CNPJ) number; state-level registration with the Chamber of Commerce (JUCEMG); and a municipal license (Alvará de Localização e Funcionamento, or ALF). The initial cost of registration is R$236 for a sole proprietorship and R$320 for a limited liability company.

The annual costs of being formal include a sanitary tax (R$53.40–106.76, depending on activity); the TFLF, a municipal inspection tax (R$77.26) that firms need to pay within 30 days of formalizing and again at the beginning of each year; and a revenue tax. The revenue tax is a flat rate of R$51.65 per month for individuals who qualify as a MEI; otherwise, SIMPLES ranges from 4 percent to 8.21 percent depending on the revenue level and industry.⁶ In addition, it is mandatory for formal firms with two or more employees to use an accountant, who must prepare cash flow and accounting statements each month, ensure the firm makes the monthly tax payments, and submit a form each year to the federal tax authority. In Belo Horizonte, accountants charge an average of R$300 per month for this service. Accountants are not required for MEIs with one or fewer workers and revenue under the MEI revenue threshold.

We use our baseline survey data to calculate the estimated costs in the first year from formalizing as a percent of baseline annual profits. Figure 1 shows the distribution of the cost of formalizing. The cost of formalizing is 10.7 percent of baseline profits for a firm at the 25th percentile of firms in our sample, 15.6 percent for a firm at the 50th percentile, and 27 percent for a firm at the 75th percentile. Furthermore, 1.2 percent of firms have a cost of formalizing that exceeds 100 percent of baseline annual profits. Thus, the cost of becoming formal is large for some firms and greatly exceeds what owners would pay in personal income tax if this were taxed as wage income.⁷ These calculations assume that formal firms report their full revenues and all of their workers; in our surveys, firms say that they think firms typically report only 50 percent of revenues for tax purposes. Firms may also underreport workers to escape the requirement of having an accountant. A firm in our sample reporting no more than one worker and reporting only half its revenues for tax purposes would face a median annual cost of being formal of 8 percent of its annual profits.

Are Firm Owners Well Informed about the Process of Formalizing?

Our baseline survey reveals that most of the interviewed informal firms lack key information about the process of formalizing, that there is substantial heterogeneity in their beliefs and that most think formalizing is more time consuming and costly than it is in reality. Only 46 percent of firm owners claim that they know what is needed to register, and only 19 percent know that the Junta Comercial (Chamber of Commerce) is where firms need to go to register. The mean (median) time firm owners think it takes to register after all documents are provided is 51 days (30 days), whereas in practice, the average time is seven to nine days. Almost 30 percent have no idea of the cost of registering, and among those who estimate the cost, the mean estimate is R$1,304, and the 90th percentile of R$2,500 is more than 10 times the 10th percentile of the estimated cost of R$200. As described above, the actual upfront cost of registering is only R$236, or R$366 if one includes the sanitary and municipal taxes due within 30 days of registering. The mean (median) estimated tax rate is 22 (20) percent, compared with the actual tax rate of 4 to 8 percent.

The baseline survey asked firm owners open-ended questions about what they saw as the main benefits and costs of formalizing. The main benefits mentioned were the ability to open a bank account in the business name (51 percent), a better reputation for the business (47 percent), reduced risk of being fined (44 percent), ability to get business loans (43 percent), and the ability to sell to other firms that require registration (39 percent). Only 13 percent said that they saw no advantages. The main disadvantages mentioned were the initial costs of registration (62 percent), having to pay taxes (58 percent), having to pay for an accountant (34 percent), and the process of registering taking too much time (32 percent).⁸

The baseline survey also asked firms if they had received an inspection visit from various types of inspectors in the past year. Thirty-two percent of firms responding to the baseline survey had received a visit from the municipal inspector (typically to check whether they had paid for a sign outside), 5.5 percent from a state tax inspector, and 3.1 percent from a federal tax inspector. The other main form of inspection was sanitary inspections, which 20.1 percent had received. Only two percent reported having paid a fine for being informal; the mean (median) fine was R$2,340 (R$600), with the majority of these fines paid to the municipality. Note that these data come from surviving firms and may understate the rate of inspection and fine receipt among all informal firms if many firms that are inspected or fined close as a result.

Interventions

The context is thus one of pervasive informality, despite the introduction of the simplified taxation program SIMPLES and the efforts by the Minas Facil unit to streamline the registration process. Given this context, Descomplicar, a unit within the state government of Minas Gerais that has the mandate to simplify relations between citizens, firms and the state, worked with the World Bank to test various mechanisms that could be used to induce more firms to formalize under the existing system in place. The focus was on trying to target firms that fell under the eligibility criteria for SIMPLES, which, at the time of design, was for revenues in the range of R$36,000 to R$240,000 or having two or more workers if revenues were below this level.⁹

The following three interventions were designed, along with a fourth, indirect treatment and a process to test them experimentally (described in the next section).

Communication Treatment

Given the lack of information many firm owners have about the process, time, and costs of formalizing, the first intervention considered was an information treatment. An attractive and colorful brochure titled “formalization of enterprises” (see Appendix S2 for example pages) was designed by professional marketing staff. This 18-page brochure included (i) information on the advantages and importance of formalizing, explaining benefits such as the availability of lines of credit, the ability to participate in tenders and public bids, increased credibility, and compliance with social obligations; (ii) the disadvantages of being informal, including the risk of seizure of goods and application of fines, difficulty dealing with medium and large suppliers and customers, limited business growth prospects, the inability to practice judicial recovery, and the inability to obtain financing due to a lack of accounting records and formal status; (iii) explaining how firms can tell if they qualify as a microenterprise; (iv) discussion of opportunities in business procurement and the simplicity of selling to the Government of Minas Gerais; (v) opportunities for lines of credit for small formal businesses through the state development bank; (vi) the importance of working with an accountant; (vii) how to calculate taxes; and (viii) the 10 steps needed to register for SIMPLES (see appendix S1) and a telephone number firms could call for help.

Firms selected for this intervention were given this brochure in person by a trained interviewer from the survey company Sensus Pesquisa e Consultoria. Descomplicar staff trained these interviewers on the content of the brochures and on an accompanying short speech explaining the content. Firms that stated they were formal and that could produce a federal taxpayer number (CNPJ) were not given the brochures. Those that stated they were formal but could not document this assertion were also given the brochure.

Free-Cost Treatment

The second intervention combined the information brochure given in the communication treatment with an effort to eliminate as many of the costs of registering as possible. As part of this intervention, Descomplicar made an arrangement with its counterparts in the other agencies involved in registration for all registration fees to be waived for the firms selected for this pilot intervention. This arrangement included waiving the JUCEMG registration fee and municipal license fees as well as paying the first year's sanitary tax and municipal inspection fee, which are due within 30 days of registering. The fees waived amounted to between R$366 and R$504 (US$183–250) depending on the type of firm. In addition, an arrangement was made with the local accountants' association whereby 50 accountants would be available to provide one year of free accounting services to these firms. This service has an effective value of R$3,600 given the prevailing cost of accounting services and the mandate for certain types of firms to use an accountant. Thus, firms participating in this treatment and being formalized through this offer would pay no initial registration fees, and the only cost of formalizing in the first year would be their SIMPLES taxes. This offer was again delivered in person to firm owners by trained enumerators, with a phone number of a government office firm owners could call for further information or help. Firm owners were given 90 days to take advantage of the offer.

Inspector Treatment

In addition to informing firm owners about how to register and making it cheaper for them to do so, the other main instrument governments can use to influence the behavior of informal firms is enforcement. As evidenced by our baseline data, the most common source of enforcement comes from municipal inspectors, which is also the typical pattern in other countries. In countries where municipal registration is separate from tax registration, the result is that many firms tend to be registered with the municipality but not with other levels of government. In Minas Gerais, because registration is a streamlined process requiring registration at all three levels, it is possible that municipal inspection may also result in full formalization. Note that before Minas Fácil was introduced in 2005, municipal, state, and federal registration processes were not linked in Minas Gerais, so it was possible for firms that registered pre-reform to have one type of registration but not the others.

The Prefeitura de Belo Horizonte (PBH) is the authority in charge of municipal inspections within the city of Belo Horizonte. The PBH has approximately 100 inspectors divided across nine semi-autonomous subregions, each with their own decision-making processes about which firms to inspect. These inspectors perform two types of inspections. The first is to check whether firms have a permit to display a sign outside the firm (placa). Second, the inspectors can conduct visits that request proof that a firm has a current municipal license (ALF), which expires every five years, and can check whether a firm has a CNPJ (tax registration). Firms that are lacking the ALF receive and notification and are given 30 to 45 days to formalize, at which time the inspector returns. If the firm is still lacking municipal registration, the inspector fines the firm owner (the fine amount varies depending on the area of the premises)¹⁰ and closes the firm.¹¹ If firms can prove they are in the process of registering, they can receive more time. The inspectors do not have the power to fine firms for not being registered with the state or federal authorities, but they can threaten to report un-registered firms to these authorities. In practice, this usually does not occur. When a firm applies for a municipal license following the inspection, it should technically also receive the state and federal licenses because all three registration processes are now integrated.

The third intervention consisted of giving these inspectors a list of selected firms to receive this second type of inspection, which involves requesting proof of the municipal license (ALF) and checking whether the firm has a CNPJ.

Indirect Inspector Treatment

The cost effectiveness of inspection as a means of getting firms to formalize depends in part on whether there are spillover impacts from inspected to non-inspected firms. Our final treatment is therefore an indirect one, whereby a firm does not receive an inspection but firms very closely located to it do receive an inspection. The next section explains our experimental design to measure these spillovers.

Data and Experimental Design

To experimentally test these interventions, we needed a sample of informal firms. However, since no recent sample frame of informal firms was available, we had to construct one through a listing exercise. The presence of the inspector treatment added a complication to this listing process for ethical and survey-response reasons. In particular, if a firm owner voluntarily provided information about the firm's formality status in an interview, it may not be considered ethical to then use this information to potentially assign an inspector to visit them.¹² Even if it were considered ethical (because the government has a right to ask firm owners about their formality status and a right to conduct inspections), we were still concerned that individuals who were interviewed in a baseline survey and then received an inspection may be unwilling to respond to a follow-up. Therefore, a listing stage was performed that did not involve talking to the firm owner.

Listing Survey

The survey firm Gauss Estatística & Mercado was hired by the Minas Gerais government through a public procurement process to undertake a listing survey in 600 census blocks in Belo Horizonte. Appendix S4 describes how these census blocks were selected. Listing consisted of enumerators visiting every firm operating out of a fixed building in the census block. It excluded individuals operating informally on the street because our interest was in larger informal firms, and it excluded transportation firms because the rules for formalizing are different for them. Enumerators recorded basic information about the firm that could be observed without talking to the firm owner, including the full street address, the business sector, the “fantasy name” of the firm (the name on a sign outside the firm if they had one), whether the business had a sign, the approximate area in square meters of the premises, and the approximate number of employees in the business. A photo was also taken of the firm to aid in subsequent identification.

Through this process, more than 10,000 firms were listed during January and February of 2011 (appendix S3 provides a timeline). The firms were then matched by Gauss against two databases of formal firms – a database from PBH of 140,628 firms with municipal registration and a database from JUCEMG (the Chamber of Commerce) of 117,350 firms with state registration. This approach was used to eliminate the “definitely formal” firms (i.e., firms who appeared on both of these lists), resulting in a sample of 7,852 listed potentially informal firms in 574 census blocks. In terms of the listed sector, 48 percent were in commerce, 45 percent were in services, only 1 percent were in manufacturing, and 6 percent were undefined. The large number of firms to be matched in a short timeframe, the requirement for firms to be on both formal lists, and possibly the inexperience of the survey firm in performing this matching exercise meant that, as we will see, a number of formally registered firms remained in this listed sample.

Because part of our design involves examining spillovers within blocks, we wanted to minimize the risk of spillovers across treatment blocks. To do this, we used the address of each listed firm and obtained from this the GPS latitude and longitude. We then calculated the number of firms in other census blocks that lay within 100 meters of the listed firm in a straight line. We examined in detail the 239 census blocks in which at least 10 percent of the firms were close to at least one firm in another census block. We were most concerned with adjacent census blocks, where firms on one side of the street that was a block boundary were in one block and those on the other side of the street were in a different block. We then used an algorithm to reclassify these into new blocks,¹³ resulting in a total of 662 geographic blocks. Of these blocks, 57 contained only one potentially informal firm each, so we dropped these blocks for a final sample of 605 geographic blocks containing 7,795 firms.

Randomization into Treatments at the Geographic Block Level

We randomized these 605 geographic blocks into three groups: control blocks, communication blocks, and inspector blocks. Randomization was stratified by the 9 sub-districts in Belo Horizonte and by whether the block had firm density above or below the median (measured by the number of listed informal firms divided by the area of the block).¹⁴ This method resulted in 201 blocks being chosen as control blocks, 202 inspector blocks, and 202 communication blocks (figure 2).

Baseline Survey of Control and Communication Blocks

All of the firms listed in the communication and control blocks were targeted for a baseline survey that took place between May and August 2011 and was conducted by the same firm (Gauss) that performed the listing.¹⁵ Of these 5,419 firms, 1,455 were found to be formal (through the presentation of documents). In 832 cases, the firm had closed, and neighbors said this was a permanent closure. In 871 cases, the owner was unable to be contacted on three visits at different times and days. In 699 cases, the owners said that they were too busy and/or refused outright to be interviewed. There were errors in records for 209 firms (such as being listed twice), and 1,353 firms were interviewed. Thus, the interview rate was 25 percent of all listed firms and 48 percent of non-formal, non-closed firms without listing data errors.

Firms that appeared in the baseline survey were almost evenly split between commerce and services, with less than 5 percent in manufacturing. The most common types of firms were hairdressers/salons (20 percent), bars (14 percent), automobile mechanics (8 percent), clothing (4 percent), and grocery stores (4 percent), with a wide range of other types of firms, such as restaurants, bookstores, photocopying, flower shops, laundromats, and dance and language schools. The average owner was 44 years old and had run the business for eight years; 37 percent of the owners were female, and 42 percent had completed a high school education or higher. The average firm had 1.3 employees (not including the owner) and reported annual revenues of R$52,000 (US$26,000) and monthly profits of R$2,000 (US$1,000).

Randomization to Treatment Status at the Individual Level

Given that only one-quarter of the listed firms answered the baseline survey, it was decided to focus the communication treatments on this subgroup because there was little point in trying to provide information on the process of formalization to firms that were already formal, closed, or for which the owner could not be found. Therefore, we randomly chose half of the firms that had responded to the baseline survey in each communication block to receive the communication treatment and the other half to receive the free-cost treatment. These firms would then be directly comparable to the firms in the control block that had answered the baseline survey. This method produced a sample of 1,348 firms, which were divided into 689 control firms, 331 communication firms and 328 free-cost firms for use in evaluating the effectiveness of the communication and free-cost treatments (indicated by the solid black box in figure 2).¹⁶

where the d_s are dummies for the 27 sub-district*firm density strata used in the block-level randomization, and the standard errors are clustered at the block level. The first five rows show variables obtained from the listing survey, and the remainder show variables from the baseline survey. Of the 48 coefficients shown, five are significantly different from zero at the 10 percent level, and only one is significantly different from zero at the 5 percent level, which is in line with what would be expected by pure chance.

In contrast, because the inspector block firms were not interviewed at baseline, randomization for this group required randomizing among all firms originally listed (indicated by the dashed line box in figure 2). Our original plan called for assigning half the firms listed in these blocks to receive the inspection treatment and half to be indirect inspector firms. However, this was not feasible with the existing number of inspectors, so we had to randomly choose only one-quarter to be inspector firms. This method resulted in 577 firms being assigned to the inspector treatment. The remaining firms in this block were all indirectly inspected. Budget constraints required us to randomly choose 593 of the indirectly inspected firms as the sample we would target for the follow-up survey. The correct control group for these firms consists of listed firms in the control blocks. Recall that we already have a sample of 689 firms in the control blocks that had answered the baseline survey. We therefore randomly chose an additional sample of 709 control block firms that had not answered the baseline survey and assigned them for follow-up. We then reweighted the control group sample to take account of the fact that we had all firms that answered the baseline and only a sample of those that did not in this group.

Although this comparison offers far fewer variables for checking balance than is possible for the communication and free-cost treatments, the results are still reassuring, with only one of the 10 coefficients being significant at the 10 percent level.

Follow-up Surveys

A very short phone survey of firms selected for the communication and free-cost treatments was conducted between April 10 and 18, 2012, by Sensus. The purpose of this survey was to follow up with the firms that had received the communication or free-cost content to assess whether they had started the process of formalization, their intent to formalize, and whether the information in the brochure had been useful. It was also intended to serve as a last prompt to use the information and free-cost offer. This survey was not given to firms to which Sensus had not made the treatment offers; thus, it was given to 464 firms, of which 367 responded (79 percent). In this survey, 86 percent of the firms said they remembered receiving the information, and 48 percent had read the brochure after having had it explained in person. Of those who read the brochure, 48 percent said they had learned that there were more potential benefits of formalizing than they had realized, but 42 percent also said they had learned that formalization involved more costs than they had known. Fifty-seven percent said that they had learned the process of formalizing was simpler than they had thought, whereas 18 percent said that they learned the process was more complicated than they had thought.

The full follow-up survey consisted of an in-person survey administered by Sensus between July and September 2012. The target sample size was 3,227 firms consisting of 328 free-cost firms, 331 communication firms, 577 firms assigned to inspectors, 593 indirectly inspected firms, 689 firms in the control blocks that had completed the baseline, and 709 firms in the control blocks that had not completed the baseline. Three attempts on different days at different times were made to contact these firms. A total of 1802 (56 percent) of the targeted firms were interviewed, with a further 14 percent closed, 20 percent absent and 10 percent refusing to be interviewed (see the last row of figure 2).

This attrition rate is relatively high. Appendix S5 examines whether attrition differed systematically between the treatment and control groups and does not find any evidence for such a difference. Nevertheless, in this appendix, we also calculate bounds to show the robustness of our main survey outcome variables to attrition. Importantly, this attrition is only an issue for survey-based outcomes. For our most important outcomes regarding formalization, we are able to use administrative data that are free of attrition.

Administrative Data

We received a list from JUCEMG of all firms that registered with the chamber of commerce in Belo Horizonte between October 25, 2011 (the day the communication treatment started) and September 19, 2012. This list contained the official business name, fantasy name, street address, phone number, and CNPJ of the business as well as registrations for MEI status and SIMPLES. In addition, we obtained a list from PBH of all firms that registered for an ALF license during this same period. We used a matching algorithm and manual checking to match this to the listing survey data described in Appendix S6. For each formalization measure, we define “definite” matches as cases where there are sufficient data in both data sources to make it almost certain we are matching the same firm and “definite or probable matches” to include cases where it seems very likely to be the same firm but less data are available to confirm the match. We also construct an overall measure of whether a firm has formalized that measures whether the firm is a definite or probable match for at least one of these three forms of formalization (MEI, SIMPLES, or ALF).

Estimating Treatment Effects

where ITT is the intention to treat effect. Because the group that did not answer the baseline survey consists of firms that were either closed, already formal, or could not be found, it seems reasonable to assume that any intervention in this group would have smaller impacts than it would on the group that agreed to answer the baseline survey. Therefore, we view our ITT estimates for the communication and free-cost treatments as an upper bound of what they would be in the full sample listed, whereas a lower bound can be obtained by multiplying these estimates by 0.25, the probability of being in the baseline. This approach allows direct comparison of the inspector treatment effects to the communication and free-cost treatment effects.

A further issue to address is that we are examining a number of different outcomes. The tests of significance provided for these outcomes are appropriate if we are interested in a particular outcome, such as whether the communication treatment increases the likelihood of a firm having obtained a municipal license (ALF). However, when looking at the range of outcomes, we need to make adjustments for multiple hypothesis testing. Two approaches are commonly used in the literature. The first is to aggregate outcomes into indices and test whether the overall impact of the treatment on a family of outcomes is different from zero (e.g., Kling and Liebman 2004). We use this approach when considering formalization as an outcome because it is natural to aggregate different types of permits into a single measure of whether a firm has obtained any permit. This approach is less useful when we are interested in the individual outcomes themselves, so the alternative is to adjust the p-values used to test each individual null hypothesis. We use the Benjamini and Hochberg (1995) correction, which controls the false discovery rate within families of outcomes. Fink et al. (2012) provide more detail on this method and the need for its use in the analysis of development experiments.

Results

We begin by discussing the implementation of the different interventions and use our survey data to examine whether this implementation resulted in changes in knowledge or in inspection frequencies. We then examine whether these interventions changed the rate of business closure and, ultimately, the impact on different aspects of formalization.

Implementation of Interventions

The communication treatment began on October 26, 2011, with up to four attempts made to deliver the brochure to the owner. This method resulted in 208 of the 331 firm owners assigned to this treatment receiving the brochure (63 percent). A further 100 firm owners declared themselves to be formal and were not given the brochure. Only two owners outright refused the brochure, and the remainder were either unable to be found or absent.

The free-cost treatment took place in February 2012 once arrangements had been finalized with both the government agencies that would waive the costs and with the accountants' association. We realized that many of the firms that claimed to be formal in the communication treatment may have possessed one document (a federal, state, or municipal registration) but may not have SIMPLES (i.e., all types of required registrations). Therefore, the instructions were to give the offer to all firms without SIMPLES and to explain that it was also valid to take the firms from partially formal to fully formal. As a result, this offer was delivered to 255 of the 328 firms assigned to this treatment (78 percent). Take-up of the offer was incredibly low: one month after the offer, our partner government agency and hotline had received only five calls and two visits; three months after the offer, only 10 to 15 people had called, and one had started the formalization process. Ultimately, only one firm in this treatment group took the offer to formalize and use one of the free accountants.

The inspector treatment began in December 2011 and lasted through April 2012. Of the 577 firms identified for inspection, the inspectors said they were able to locate 530, of which 387 firms were open. Among these 387 firms, 170 were found to have a municipal license, although some of these had expired and others were using more space than licensed or had other infractions. The inspectors notified 269 firms that they were operating without the proper licenses. The inspectors reported that in their follow-up visits, 143 firms were closed and 88 firms were in the process of formalizing.¹⁷ Their final report showed that 17 of the notified firms had produced a valid municipal license, four had produced a license as a microentrepreneur, and the rest were still classified as in process.

Impacts on Knowledge and Inspection Likelihood

The first part of table 2 examines whether the treatments changed individuals' knowledge about the process of formalization. We obtain these treatment impacts through estimating equations (1) and (2) with different knowledge measures as the outcome of interest. We see first that approximately 60 percent of the control group firms claim to know the steps required to fully register a business and that none of the treatments has a statistically significant impact on this outcome. This high rate of self-assessed knowledge contrasts dramatically with objective measures of knowledge; firm owners were asked the cost of registering and the tax rate faced by firms that register. As in the baseline survey, knowledge of this information is very low, with only 3 percent of the control group giving an answer in the right range for the cost and only 4 percent in the right range for knowing the tax rate. The communication and free-cost treatments have no significant impact on this outcome, whereas the marginally significant impacts of the inspector treatment on knowledge of the tax rate and of the indirect inspector treatment on knowledge of the cost of registration are not significant once a correction is made for multiple hypothesis testing.

We find stronger impacts on whether individuals claim to use an accountant (a requirement of being formal for most firms) and whether they know the cost of an accountant. The free-cost treatment raises the likelihood of claiming to use an accountant by 11.6 percentage points (p = 0.014) and the likelihood of knowing the cost of an accountant by 11.8 percentage points (p = 0.0002). The communication treatment has a similar magnitude impact on claiming to use an accountant (p = 0.022). However, applying the Benjamini-Hochberg (1995) false discovery correction procedure to the 10 information and knowledge estimates results in only a significant impact of the free-cost treatment on knowing how much an accountant costs. Firms assigned to the inspector treatment are also significantly more likely to know the cost of the accountant, even after controlling for false discoveries. Taken together, these results suggest little impact of the treatments on precise details of the formalization process, such as costs and tax rates. However, firm owners did gain information about the role and cost of accountants in this process.

The second part of table 2 examines a second family of outcomes relating to inspector visits. Approximately 47 percent of firms in the control blocks report having been visited by a municipal inspector in the past year. This result increases by 13.5 percentage points for the firms assigned to the inspector treatment (p = 0.0002), which is consistent with the inspector treatment increasing the likelihood of receiving an inspection. Note, however, that the combination of firms that were closed or unable to be located by the inspectors coupled with the fact that some firms would have received an inspection anyway means that this difference between the treatment and control groups is much less than 100 percentage points. However, note also that we do not know how many of these reported visits were only to check on the signage of the firm versus how many also checked the municipal license. The inspector treatment firms are marginally more likely to say that they obtained information on how to formalize from an inspector (not significant after adjustment for multiple testing) and are no more likely to be notified or fined than control firms.

The indirectly inspected firms are no more likely to report having seen or heard that a neighboring firm had received an inspection in the past 12 months. This may result from the fact that inspections occur to some extent anyway, and that firm owners do not always communicate amongst each other – 35 percent of firm owners say they do not talk at all to other firm owners about business matters. Additional support for the view that many firms do not notice inspections in neighboring firms comes from the fact that twice as many firms report having been inspected themselves than those that report having seen a neighboring firm inspected. These findings imply that we should expect the spillover impact from inspecting the inspector group firms on the indirectly inspected firms to be minimal in terms of formalization.

Impacts on Firm Survival

La Porta and Shleifer (2008) noted that a competing view to the De Soto/Doing Business view of the informal economy as home to potentially productive entrepreneurs held back by regulatory barriers is the dual economy view associated with Tokman (1992) and Rauch (1991). In this view, the informal sector is a source of subsistence livelihoods for individuals with relatively low levels of human capital, and any increase in firm value that these owners would be able to generate by formalizing would not be large enough to offset the additional costs of taxes and other regulatory requirements. The result is that enforcing formalization may cause these firms to shut down because they cannot afford to operate formally. In both cases, the entrepreneur is making a cost/benefit calculation of whether to formalize, but the competing views differ in terms of what they see as the main costs and benefits entering this calculation.

Table 3 examines this possibility by looking at the impact of the different treatments on firm closure. Firm closure is measured by whether the firm is observed to be closed at the time of the follow-up survey coupled with information obtained from neighboring businesses. Between 14 and 16 percent of the control group was verified as closed at follow-up, with none of the treatments having any sizeable or significant impact on this closure rate. In particular, it is not the case that firms that received enforcement through the inspector treatment are more likely to have closed.

Impact on Formalization

Table 4 turns to the main outcome of interest, whether the treatments succeeded in getting firms to formalize. We use the administrative data to measure formalization because these data offer impacts without attrition and substantially larger samples to measure impacts, providing the most power.¹⁸ The first few columns compare the control firms to the free-cost and communication firms. We see that assigning firms to the free-cost treatment has a strongly significant negative impact on the likelihood of MEI registration (p = 0.008 for definite matches, p = 0.010 for probable matches). One possible explanation for this is that the free-cost and communication interventions explained how to register for SIMPLES but not how to register as a MEI. The free-cost treatment also emphasized the need to have an accountant if the firm formalized, which is not required for MEIs. The unexpected policy change immediately after we launched this intervention increased the revenue thresholds under which firms could register as MEIs. It is plausible that firms that received the communication and free-cost intervention were less aware of this policy change given the information about the need to register for SIMPLES and to obtain an accountant that they were given in person, causing them to decide not to register. The point estimates are also negative for the communication treatment. Testing for equality of treatment effects, we cannot reject that the communication-only treatment has the same negative impact as the free-cost treatment – but neither can we reject a zero treatment effect for communication only.

We see no significant impacts of the free-cost or communication treatments on registering for SIMPLES or obtaining an ALF license. Pooling together all three measures,¹⁹ we see that 8–10 percent of the control group that was interviewed at baseline obtained some form of formal status after our interventions began and that this was approximately 3 percentage points lower for the free-cost group. Given the size of the free-cost group, this equates to approximately 10 firms not formalizing that would have in the absence of this intervention.

Turning to the last three columns, which consider the inspector versus control block comparisons, we see that assignment to the inspector treatment group leads to a strongly significant 2 to 3 percentage point increase in the likelihood of obtaining an ALF. Recall that the ALF license is the only one the municipal inspectors are legally able to enforce. Under the one-stop shop for registration, we expected that firms would register and obtain SIMPLES and an ALF all at once. However, if firms had already obtained a CNPJ or if they had previously had an ALF that had expired (they are valid for five years), firms could just register and obtain an ALF only. It therefore appears that this extra formalization was by firms that were already partially formal. There are small and insignificant impacts of inspections on the other forms of formalization; thus, the overall impact of formalizing comes from the ALF registrations. We find a significant overall impact of between 2 and 4 percentage points, which is equivalent to between 11 and 22 extra firms formalizing of the 577 assigned to the inspector group.

In contrast, we find a rather precise zero effect of the indirect inspector treatment on the likelihood of formalizing. The 95 percent confidence for the treatment effect on “definitely or most likely obtained any type of formal status” is [−0.020, +0.013]. This result is consistent with the evidence in table 2 that the firms in this treatment group did not notice any increase in inspections of neighboring firms.

Estimates of the Impact of Being Inspected

where we instrument the follow-up survey report of whether the firm had received a municipal inspection in the past year with assignment to the inspector treatment group.²⁰ We estimate this equation using the follow-up survey data for the control group and inspector group only. We consider both ALF registration, which is the registration form most closely tied to municipal inspection, and our overall measure of formalizing.

Table 5 displays the results. We see that the point estimates range from 0.214 to 0.265, so receiving an inspection results in a 21 to 27 percentage point increase in the likelihood of formalizing. The statistical significance is greatest for ALF registration, where the p-value is 0.108 for definite registration and 0.051 for definite or probable registration. This is the impact on the group of firms that answered the follow-up survey. It therefore removes firms that had closed or that could not be found easily but still includes some firms that were already formally registered.

The estimated cost of an inspection is R$64.34, which is based on an estimated inspection taking 56 minutes per visit plus 17 minutes of travel time (estimates provided by PBH). The inspectors visited 387 firms (the rest were closed or not found), so the total cost of inspections is estimated at R$24,900. Taking our estimated impact of 11 to 22 more firms formalizing, the cost per firm formalized is R$1132–2264. Under the more questionable assumption that our inspections did not differ from the inspections these firms would have received anyway, the IV estimates suggest that approximately four additional inspections are required to get one firm to register for an ALF license, so the estimated cost of formalizing one firm is approximately R$256.

Annual tax revenue is R$620 for a MEI; based on 4 percent revenue tax on the average revenue of R$57,000 for newly formalized firms with an ALF, the annual tax revenue is R$2280. Firms report that firms like theirs typically only report only half their revenues, which would take the SIMPLES annual tax down to R$1140. Therefore, it appears that the cost of formalizing a firm in our experiment via inspections would be gained back within the first year of tax payments (or more than gained back if we consider only the marginal visits under the IV estimation), with subsequent years of tax payments then a net gain for the government.

However, because our estimates above suggest that the main effects are for firms that were already partly formal, it is unclear whether all of these tax gains would be realized in practice. The municipality would gain the fixed renewal fees, but it is less clear whether these firms would now pay SIMPLES taxes. Even if they did, the municipality (which pays for the municipal inspectors) only receives a share of this additional revenue, with the remainder going to the state and federal governments. Apart from the annual inspection tax, under SIMPLES, municipalities only directly obtain tax revenue from service firms.²¹ One component of the SIMPLES tax, called the ISS, is 2 percent of revenues on the first R$180,000 of revenues and 2.79 percent after that. Therefore, the municipality could gain approximately R$570 per year from formalizing a typical service firm in our sample. This result suggests that the municipality could benefit from well-targeted attempts to formalize service firms, but our results also suggest that this can be difficult in practice.

Comparing Actual Impacts with Expectations of Treatment Impacts

A standard question regarding impact evaluations is whether they deliver new knowledge or merely formally confirm the beliefs that policymakers already have (Groh et al. 2012; Hirshleifer et al. forthcoming). To measure whether the results differ from what was anticipated, in January 2012 (before any results were known), we elicited the expectations of the Descomplicar team regarding what they thought the impacts of the different treatments would be. Their team expected that 4 percent of the control group would register for SIMPLES between the baseline and follow-up surveys. We see from table 4 that this is an overestimate of the SIMPLES registration rate, but given the change in MEI requirements, it is in line with the combined SIMPLES and MEI registration level.

The communication-only group was expected to double this rate so that 8 percent would register, the free-cost treatment would lead to 15 percent registering, and the inspector treatment would lead to 25 percent registering. The team did not expect there to be any indirect inspector effect and so expected that only 4 percent of the untreated firms in the inspector blocks would register. The zero or negative impacts of the communication and free-cost treatments are therefore surprising. The overall impact of the inspector treatment is much lower than expected but is in line with the IV estimates, suggesting that the Descomplicar team has a reasonable sense of what to expect when an inspection actually occurs but may have overestimated the amount of new inspections that would take place. Their expectation of a lack of impact for the indirect inspector treatment was also accurate.

Impacts on Trust and Attitudes towards Government

De Mel et al. (2012) offer Sri Lankan firms monetary payments to get them to formalize and find that one outcome of formalization is that firms have more trust in local government. In their case, formalization is much cheaper and quicker than firms had believed. They note that one possible reason for this increase in trust was that firms experienced better services from the government than they had expected, whereas an alternative could be that they were less afraid of being shut down after registering.

Our follow-up survey asked firms about their trust and views of government. Individuals were asked on scale of 1 to 10 how much they trusted different actors, where 10 denoted the most trust and 1 denoted the least trust. They were also asked whether they believed that government acts in the interests of the people or in its own interest. Table 6 reports the results of estimating the impacts of our treatment assignments on these outcomes. We see a strong contrast to the results in Sri Lanka: the attempts at formalization in Belo Horizonte appear to have generally worsened trust in government. The results for the communication and free-cost treatments all remain significant after controlling the false discovery rate at α = 0.10, whereas the impact of the free-cost treatment on believing the government acts in its own interests also remains significant when controlling the false discovery rate at α = 0.05.

The impacts are not that large: a reduction of 0.3 to 0.5 points on a 10-point trust scale, which represents a 0.1 to 0.15 change, and an increase of 4 to 10 percentage points in the likelihood that firm owners think the government acts in its own interest rather than in the interests of the people. Nevertheless, in an environment of widespread informality, efforts to reach out to particular firms and bring them into the formal system using either carrots or sticks may run the risk of increasing distrust in government if firm owners do not see any benefits from being brought into this formal system. The distrust effect is more significant for information and free-cost efforts than for the inspection treatment, possibly because a government initiative that invited individual firms to register is different from usual activities and appears to have aroused suspicion.

Conclusion

Despite reforms that make it faster and simpler for informal firms in Brazil to register, the majority of firms remain informal. Although simply paying firms to formalize has been found to have large impacts on formalization rates in Sri Lanka, this approach is unlikely to be on the policy menu for most governments. Instead, governments can use a range of carrots and sticks to attempt to bring firms into the formal sector. Our experiment tests some of the most common ones: informing firms, making it cheaper for them to register, and increasing the enforcement of rules. Our findings suggest that sticks rather than carrots seem more effective at getting firms to formalize, but we also find limits to this approach.

The process of registering in Belo Horizonte still requires more steps and complications than in a number of other countries that have pursued entry reforms. In addition to facing taxes, firms that do register face a relatively large cost in terms of the need to hire an accountant. Faced with these costs of being formal, it appears that few informal firms want to formalize unless they are forced to do so by enforcement. We are unable to measure whether firms benefit from being forced to formalize because the number of firms induced to formalize is too small, and our follow-up survey suffered from high item non-response on sales and profits questions. However, evidence from other countries (McKenzie and Sakho 2010; de Mel et al. 2012) suggests that although some informal firms benefit from formalizing, the majority appear not to. Being informal is thus likely to be privately optimal for many firms.

This finding suggests three directions for government policy. The first is to reconsider where it is desirable to even attempt to bring these firms into the formal sector. It may not make much sense for the smallest firms, but given the limited tax base and the fact that firm owners with revenues in the range that qualifies for SIMPLES are likely to be at least in the middle of the income distribution, there may be a public benefit to formalizing these firms even if there is no private benefit. Formalization may also bring other wider benefits, such as reducing a “culture of informality” and allowing more efficient reallocation by protecting formal firms from “unfair competition” from less efficient informal firms. The second avenue for policy is to further simplify the ease of formalizing and, more importantly, to revisit the need for an accountant, which dramatically increases the cost of being formal. Efforts to link formality with access to government programs and bank financing might help to induce some firms to register, but many firms will not benefit from such approaches. Improved enforcement is thus the third part of policy efforts. Our research shows that enforcement can induce formalization, but there are limits. Rather than having separate inspectors for different forms of registration, having municipal inspectors who are able to enforce municipal, state, and federal registration should have stronger impacts. Furthermore, given that many of the firms the inspectors said they had closed were open again at the time of our follow-up survey, there appears to be scope for improving the degree of enforcement that inspection actually entails. Combining enforcement with carrots may offer the greatest impact because firms may be far more receptive to information and lower costs of registering when they have an enforcement incentive to register.

References