The Effects of Formalization on Small and - 麻省理工学院人工智能研究专业

The Effects of Formalization on Small and
Medium-Sized Enterprise Tax Payments:
Panel Evidence from Viet Nam
Amadou Boly∗

Do ﬁrms pay more taxes after formalization? The answer to this question is
nontrivial. Tax noncompliance can be a persistent behavior among formerly
informal ﬁrms. Analyzing the relationship between formalization and tax
payments can also be challenging if nonswitching and switching ﬁrms have
different characteristics. I use a panel dataset built from ﬁve small and
medium-sized enterprise surveys conducted in Viet Nam from 2005 到 2013.
By comparing nonswitching informal ﬁrms to switchers, I show that switchers
are more likely to pay taxes and to pay a higher amount, thereby conﬁrming
heterogeneity. By comparing switchers before and after formalization, I ﬁnd
that formalization increases tax payment likelihood by 20% and the tax amount
paid by 93%. A control function approach indicates that my results are
robust to potential endogeneity of formalization. 所以, this paper provides
supportive evidence for a key public policy rationale to promote formalization:
increased tax revenues.

关键词: formalization, 税收, Viet Nam
JEL codes: D22, O12, O17

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我. 介绍

Existing research has mainly focused on the private costs and beneﬁts
of formalization for informal ﬁrms, with available evidence suggesting that
formalization can have a positive effect on ﬁrm performance (McKenzie and Sakho
2010; Fajnzylber, Maloney, and Montes-Rojas 2011; Rand and Torm 2012; Bruhn
and McKenzie 2014; 博利 2018).1 In contrast to most previous studies, 这篇论文

∗Amadou Boly: African Development Bank, Abidjan, Côte d’Ivoire. 电子邮件: a.boly@afdb.org. This article is
published here with due acknowledgement of UNU-WIDER, Helsinki, which commissioned the original research
under the project Structural Transformation and Inclusive Growth in Viet Nam. I am grateful to the Development
Economics Research Group at the University of Copenhagen for granting access to the Viet Nam data, 尤其
Finn Tarp, and to Christina Kinghan for constructing the panel dataset. I would also like to thank Robert Gillanders,
Anthony Mveyange, and Robert D. Osei, the managing editor and the anonymous referees for helpful comments and
suggestions. The views expressed here are those of the author and do not necessarily reﬂect those of the African
Development Bank Group. ADB recognizes “Vietnam” as Viet Nam. The usual ADB disclaimer applies.

1Formalization, which is viewed as a deliberate private decision by the ﬁrm taken after cost–beneﬁt analysis,
occurs when its perceived net beneﬁts are positive (Maloney 2004; De Mel, 麦肯齐, and Woodruff 2013).

Asian Development Review, 卷. 37, 不. 1, PP. 140–158
https://doi.org/10.1162/adev_a_00144

The Effects of Formalization on SME Tax Payments in Viet Nam 141

asks whether a government can also beneﬁt from formalization through additional
tax payments resulting from ﬁrms opting out of the informal sector.

Tax payments are costs to ﬁrms, and these costs will increase as a direct
consequence of formalization only if there is (partial or full) compliance with
formal tax regulations. 然而, noncompliance with formal tax or labor regulations can
persist among formerly informal ﬁrms; noncompliance is a common phenomenon
even among formal ﬁrms, including in member countries of the Organisation
for Economic Co-operation and Development (经合组织 2008).2 In consequence,
the claim that formalization increases government revenues is ultimately an
empirical question, the answer to which can strengthen (或不) a key public policy
rationale for promoting the formalization of small and medium-sized enterprises
(中小企业).3

Analyzing the effects of formalization on informal ﬁrms is challenging due to
potential ﬁrm heterogeneity. Heterogeneity can come from the fact that ﬁrms opting
out of the informal sector have different characteristics (例如, owner capabilities and
ﬁrm preferences) compared with those that remain informal. 而且, unobserved
characteristics that affect ﬁrm outcomes may lead to formalization; 如果, 例如,
more successful ﬁrms become more visible, leading to a higher likelihood to register
formally (McKenzie and Sakho 2010; Fajnzylber, Maloney, and Montes-Rojas
2011).

To study the relationship between formalization and tax payments, I applied
regression analysis to a panel dataset compiled using ﬁve SME surveys from Viet
Nam. I restricted the dataset to informal ﬁrms that remained informal throughout
the survey periods and to informal ﬁrms that became formal at a given point
in time (referred to as switching ﬁrms or formalized ﬁrms). Informality is a
multidimensional concept that is difﬁcult to deﬁne. 然而, for my purpose,
formal ﬁrms are deﬁned as those that registered to pay tax (obtained a tax code),
which is a commonly used indicator of formality in the literature (McKenzie and
Sakho 2010, Rand and Torm 2012).4

McKenzie and Sakho (2010) hypothesize that a proﬁt-maximizing ﬁrm becomes formal if and only if the expected
present discounted value of the net beneﬁts from doing so outweighs the upfront costs:

时间(西德:2)

δt E(πF,t − πI,t ) + θlaw-abiding > CMoney + CTime + CInformation

t=1
where πF,t denotes the ﬁrm’s proﬁts if it is formally registered at time t, and πI,t denotes the ﬁrm’s proﬁts if it is not
formally registered at time t. θlaw-abiding denotes the utility beneﬁt to ﬁrm owners from obeying the law and feeling
they are contributing to national welfare through paying taxes. CMoney, CTime, and CInformation denote the monetary, 时间,
and information costs of registering, 分别.

2See also Basu, Chau, and Kanbur (2010) and Tedds (2010).
3See Bruhn and McKenzie (2014), who consider that the claim that formalization is socially optimal because

it increases government revenues and reinforces a culture of respecting the rule of the law, requires more research.

4An operational deﬁnition based on business registration would be consistent with the International Labour
Organization’s (2003) deﬁnition of informal sector enterprises, which are basically “unregistered and/or small-scale
private unincorporated enterprises that produce goods or services for sale or barter.” Other criteria of informal
employment include employment contract registration, provision of social security protection, and size of the

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142 Asian Development Review

然而, the absence of registration does not mean that the informal sector
is not taxed, as a nonnegligible fraction of informal ﬁrms pay some sort of taxes
in Viet Nam, albeit mostly local taxes (Cling, Razaﬁndrakoto, and Roubaud 2011,
p. 33).5 It is therefore important to ascertain that formalization leads to additional
tax payments by switching ﬁrms beyond and above what was already paid.

Using the formal status variable (status equals 0 if a ﬁrm is informal and 1
if formal), I constructed a variable called switcher, which equals 1 for all years in
which a switching ﬁrm has been observed in my sample, including the years before
formalization, 和 0 if the ﬁrm remained informal throughout the survey periods.
The switcher variable, as ﬁrm-type ﬁxed effects, allows for capturing heterogeneity
between ﬁrms remaining informal and ﬁrms that switched out of the informal
sector at some point. 因此, when included in my regression, the variable
地位, which takes a value of 1 only for switching ﬁrms after they have formalized,
captures the net effect of formalization on switching ﬁrms.

formalization,

By comparing nonswitching informal ﬁrms to switchers,

I conﬁrm
heterogeneity between switching ﬁrms and nonswitching ﬁrms regarding tax
付款: switchers paid a signiﬁcantly higher amount of taxes than nonswitchers.
然后, by comparing switchers before and after
I ﬁnd that
formalization increases the likelihood of tax payment (经过 20%) and the amount
of taxes (经过 93%) relative to preformalization levels. This signiﬁcant increase
in tax payments persists both in the short and long term. Using a control
function approach, I show that my results are robust to potential endogeneity of
formalization. I also ﬁnd that the increase in tax payments is mainly driven by
a signiﬁcant increase in the payment of taxes such as license fees or import and
export taxes, but not in the payment of revenue taxes that are arguably more difﬁcult
to collect. Firm size, previous performance, and compliance inspection all have a
positive relationship with both the amount and likelihood of tax payments.

The remainder of this paper is organized as follows. Section II brieﬂy
literature on the effects of
presents an overview of the existing empirical
formalization. I describe my dataset in section III and explain the empirical
approach in section IV. Section V presents the main results and section VI
concludes.

二. Literature Review

The literature on the relationship between formalization and ﬁrm
performance has mainly focused on the private beneﬁts for a ﬁrm. Comparing

employer (Henley, Arabsheibani, and Carneiro 2009). 然而, compared to having a tax code, these other deﬁnitions
may not be best ﬁts, given that I am seeking whether formalization leads to additional tax payments.

5See also Olken and Singhal (2011) for a discussion of informal taxation in 10 developing economies,

including Viet Nam.

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The Effects of Formalization on SME Tax Payments in Viet Nam 143

ﬁrms that were created immediately before and after a business tax reduction and
simpliﬁcation scheme in Brazil, Fajnzylber, Maloney, and Montes-Rojas (2011)
ﬁnd that this scheme led to increased levels of registration and to higher revenues,
proﬁts, and employment among registered ﬁrms. 同样地, 夏尔马 (2014) suggests
that registration leads to signiﬁcant gains in both sales and value added per
employee in India. In Bolivia, McKenzie and Sakho (2010) analyze the effects
of formalization on ﬁrm proﬁts, using the physical distance between a ﬁrm and
the tax ofﬁce as an instrument. The assumption is that being closer to a tax ofﬁce
increases the probability of registration. Their ﬁndings suggest that the effect of
tax registration is positive but heterogeneous. Related to the research question in
the current paper, McKenzie and Sakho (2010) also show that registered ﬁrms are
more likely to pay taxes, but not signiﬁcantly more likely to be paying a larger share
of their proﬁts as taxes.

In contrast to most previous cross-section studies, Rand and Torm (2012)
use the same panel data as in this study, but only for 2007 和 2009. 他们的
results indicate that registration leads to an increase in proﬁts and investments for
Vietnamese SMEs. 博利 (2018) shows that becoming formal can further increase
gross proﬁts and the value added of switchers compared with preformalization
级别, both in the short and medium term. The present study is closest to Boly
(2018) as it uses the same dataset and empirical approach, while focusing on
analyzing the relationship between formalization and tax payments. As mentioned
previously, the majority of the existing literature focuses on the private beneﬁts of
formalization for a ﬁrm, leaving an evidence gap on the potential social beneﬁts,
speciﬁcally those accruing to governments.

三、. 数据

The description of the dataset used in this study parallels that in Boly
(2018), restricted to informal and switching ﬁrms. The dataset comes from SME
surveys conducted in Viet Nam in 2005, 2007, 2009, 2011, 和 2013. The surveys,
which were conducted by the Central Institute for Economic Management and the
University of Copenhagen, cover about 2,500 ﬁrms in each year. They were carried
out in 10 locations in the cities of Ha Noi and Hai Phong, in Ho Chi Minh City, 和
in the rural provinces of Ha Tay, Khanh Hoa, Lam Dong, Long An, Nghe An, Phu
Tho, and Quang Nam.

The population of nonstate manufacturing enterprises was based on two data
sources from the General Statistics Ofﬁce of Viet Nam (GSO): the Establishment
Census 2002 (GSO 2004) and the Industrial Survey 2004–2006 (GSO 2008). A
representative sample of registered household and nonhousehold ﬁrms was drawn
from this population, using a stratiﬁed sampling procedure. The aim was to ensure
the inclusion of an adequate number of enterprises in each province with different

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144 Asian Development Review

ownership forms. For reasons of implementation, the survey was conﬁned to
speciﬁc areas in each province or city. 此外, the GSO enterprise census
focused only on “visible” ﬁrms, which are those with ﬁxed professional premises.
Informal household ﬁrms were included in the SME surveys based on
random onsite identiﬁcation within the survey districts observed by the enumerator.
With such an identiﬁcation approach, the informal ﬁrms included in the survey
are those operating alongside ofﬁcially registered enterprises. These informal ﬁrms
may be relatively more competitive (and proﬁtable) compared to informal ﬁrms
clustering in areas with no or very few formal ﬁrms (Rand and Torm 2012). 在这个
看待, the sample of informal ﬁrms in this study may not be fully representative of
the informal sector as a whole in Viet Nam.

Despite the aforementioned weakness, my dataset remains unique by the
number of survey years (5), number of ﬁrms, and focus on the informal sector. 我
restricted my sample to ﬁrms with at least two observations. I also excluded ﬁrms
that were formal when initially entering the sample, given that my interest is in
informal ﬁrms and whether they pay more taxes after formalization. The restricted
sample is dominated by informal nonswitchers, which account for 66% of the total
number of ﬁrms, while switchers account for 34% of the total number of ﬁrms
(Appendix Table A1.1).6

IV. Empirical Approach

To examine the relationship between formalization and tax payments, I use

the following speciﬁcation:

yit = ρDS
我

+ γ Fit + βXit + λt + μi + εit

(1)

is the dependent variable; DS

where yit
i captures ﬁrm-type ﬁxed effects (1 如果
switchers, 0 if nonswitchers); Fit indicates whether a ﬁrm has become formal or
不是 (0 if a ﬁrm is informal, 和 1 if the ﬁrm is formal); Xit represents additional
control variables; λt denotes a full set of time dummy variables; i indexes individual
ﬁrms; and t indexes time. As speciﬁed, my approach is comparable to a difference-
in-difference approach with varying treatment years.
speciﬁcation
difference-in-difference

和
nonswitchers) rests on the parallel trend assumption in tax payments before
switching. A graphical check of this assumption suggests that the parallel trend
assumption holds well between 2005 和 2007 和之间 2007 和 2009, 但

switchers

(之间

这

6I assume that once a ﬁrm becomes formal it stays formal, and I recode its formality status accordingly. 在
也就是说, I do not allow a switcher to move back to the informal sector. This applies to about 4.2% of observations,
a proportion that I consider negligible. The main justiﬁcation is that once a ﬁrm enters tax authorities’ records by
acquiring a tax code, it becomes very difﬁcult for the ﬁrm to move again into informality.

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The Effects of Formalization on SME Tax Payments in Viet Nam 145

not between 2009 和 2011. As a robustness check, I run the above speciﬁcation
for different waves of the survey (see section V.C.3).

A key feature of my approach is the construction of a switcher variable
denoted by DS
我 , using the variable Fit (0 if a ﬁrm is informal, 和 1 if the ﬁrm is
formal). If a ﬁrm has shifted out of the informal sector at any time in my survey
periods, the switcher variable equals 1 for all years in which the ﬁrm has been
observed in my sample (including the years before formalization); the switcher
variable equals 0 if the ﬁrm remained informal throughout the survey periods.
这 (informal) nonswitcher group is used as control group in my regressions. 这
inclusion of ﬁrm-type ﬁxed effects in my main regressions (using dummy variable
DS
我 ) enables me to account for time-invariant heterogeneity between nonswitching
and switching ﬁrms. 因此, the variable Fit, which takes a value of 1 only for
switching ﬁrms after they have formalized, picks up the net effects of formalization.
然而, a known limitation of the ﬁxed-effects approach is that endogeneity due
to time-varying omitted variables is still present, although the bias gets smaller
than with cross-sectional data. I therefore discuss robustness to endogeneity in
section V.C.2.

In addition to the previously mentioned variables, I include several control
variables that could affect ﬁrms’ decisions regarding tax payments. These control
variables are summarized in Appendix Table A1.2 for the pooled sample and by
ﬁrm type.7 The control variables include (我) gender of the owner or manager (1 如果
male, 0 否则); (二) education level of the owner or manager (0 if secondary
school has not been completed, 1 否则) to proxy for the owner’s or manager’s
人力资本; (三、) ﬁrm’s previous performance using previous year’s gross proﬁts;
(四号) number of regular full-time employees (in logarithmic form), as well as the
square, to control for ﬁrm-size effects; (v) whether or not the ﬁrm holds a certiﬁcate
of land use rights to proxy for property rights; (六) government inspections (0 如果
the ﬁrm has not been subject to inspections in a given year, 1 否则); 和
(七) dummy variables to control for location and time factors.

V. 结果

After brieﬂy discussing some summary statistics, I present results on the
relationship between formalization and total tax payments, my main variable of
兴趣, using a Tobit regression that considers both the binary participation
decision and the amount paid.8

7See also Rand and Torm (2012).
8The total tax payments variable is constructed as the sum of various taxes and fees, such as taxes on revenues,

license fees, import and export taxes, luxury good taxes, property taxes, and other taxes and fees.

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146 Asian Development Review

Average Total Tax Payments—Evolution around Formalization Year

笔记: Formalization year is equal to 0.
来源: Author’s calculations.

Summary Statistics

As mentioned earlier, Appendix Table A1.2 describes the dependent
变量 (for the pooled sample) by ﬁrm type, 那是, nonswitchers and switchers
(and for switchers: 全面的, before switching, and after switching). I observe that
nonswitchers paid some form of taxes 57% 当时的, while switchers paid taxes
90% 当时的 (全面的), 83% of the time before switching, 和 97% 当时的
after switching. The differences are signiﬁcant at the 1% level between nonswitchers
and switchers before switching on the one hand, and between switchers before and
after switching on the other hand.

The total tax payments made by switchers before switching (D1,778) 是
signiﬁcantly higher than that of nonswitchers at the 1% 等级 (D334).9 Switchers
also pay a signiﬁcantly higher amount of total taxes after joining the formal sector
(D3,792). 全面的, the average total tax payments of switchers (D2,883) 是关于 8.6
times higher than the total tax payments of nonswitchers (D334); switching from the
informal to the formal sector resulted in tax payments increasing more than twofold
from D1,778 to D3,792.

The ﬁgure uses an events-study graph to provide an illustration of the
evolution of tax payments for switchers. In this graph, the year of formalization is
set at 0 on the x-axis. Negative numbers refer to years in the preformalization period
and positive numbers to years in the postformalization period. Although there is an

9All monetary values are in real 1,000 Vietnamese dong (D).

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The Effects of Formalization on SME Tax Payments in Viet Nam 147

桌子 1. Effects of Formalization on Total Tax Payments (Tobit)

Variables: Log (1 + 税收), (Real D1,000)

模型 1 模型 2

Switcher (from informal to formal)

Switcher (after formalization)

Time since becoming formal (dummy, 2 years or less)

Time since becoming formal (dummy, 4 + 年)

Gender of owner or manager (female = 0, male = 1)

Owner or manager completed secondary school (no = 0, yes = 1)

Gross proﬁts (previous year, 日志)

Firm size (日志 [1 + 就业])

Firm size squared (日志 [1 + 就业])

Share of female employees

Own land use right certiﬁcate, (no = 0, yes = 1)

Compliance inspections (no = 0, yes = 1)

持续的

观察结果
Number of panels
Time dummies included
Province dummies included

2.44***
(0.19)

2.36***
(0.21)
1.06***
(0.15)

1.39***
(0.14)
0.58***
(0.17)
0.01
(0.13)
0.21**
(0.09)
0.46***
(0.08)
2.10***
(0.43)

0.01
(0.13)
0.19
(0.14)
0.46***
(0.07)
2.10***
(0.51)
−0.38*** −0.38***
(0.12)
0.39
(0.24)
0.22*
(0.12)
0.73***
(0.10)
−3.87*** −3.94***
(0.73)
4,795
1,306
是的
是的

(0.11)
0.39
(0.24)
0.23*
(0.13)
0.68***
(0.14)

(0.93)
4,795
1,306
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是的

D = dong.
Notes: Bootstrapped standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations. increasing trend in tax payments in the preformalization period (−8; −2), I observe a signiﬁcant jump in the short term, postformalization period (0; +2); this increase in tax payments persists in the long term (+4; +6) compared to the preformalization period (−8; −2). The preliminary analysis above therefore suggests that tax payments increase after formalization. B. Panel Regression I also study the relationship between formalization and tax payments using a random effects Tobit regression (left-censored at 0). The results in Table 1 (Model 1) show that switchers’ total tax payments are signiﬁcantly higher than nonswitchers. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 148 Asian Development Review I therefore ﬁnd heterogeneity between switching and nonswitching ﬁrms; that is, switchers tend to pay higher taxes while in the informal sector than nonswitchers do. This heterogeneity has been typically assumed or differenced out in most of the previous studies on formalization. I ﬁnd that the coefﬁcient of is analyzed by looking at The amount of switchers’ tax payments, both before and after they (after formalized, formalization). tax amounts signiﬁcantly compared to preformalization levels (Table 1, Model 1). For switchers, the mean marginal effects of formalization on the expected value of the censored outcome is about 93%, and the mean marginal effects of formalization on the expected value of the truncated outcome is about 73%, controlling for province and year ﬁxed effects. formalization increases switchers’ switcher To study the effects of formalization over the short and long term, I use two dummy variables that reﬂect the length of time since formalization. The ﬁrst dummy (short term) is 1 for ﬁrms that have been formal for 2 years or less, while the second dummy (long term) is for ﬁrms that have been formal for 4 years or more.10 As can be seen in Table 1 (Model 2), the increase in total tax payments is observed both in the short and long term. However, the coefﬁcient for total tax payments in the short term (2 years or less after formalization) is signiﬁcantly higher than the coefﬁcient for tax payments in the long term (4 or more years after formalization), suggesting a decrease in total tax payments over time. Alternatively, the higher coefﬁcients in the short term for total tax payments may be capturing initial entry costs into the formal sector. Several other control variables are noteworthy in Table 1. First, lagged gross proﬁts have a positive and signiﬁcant relationship with tax payments at the 1% conﬁdence level, indicating that more successful ﬁrms pay more taxes. Second, ﬁrm size also has a positive and signiﬁcant relationship with tax payments, likely explained by the fact that it is more difﬁcult for larger ﬁrms to hide their activities. Finally, undergoing at least one compliance inspection is positively related to the amount of total taxes. C. Robustness Check In this section, I test the robustness of my results to measurement errors or possible endogeneity. 10The time since switching to the formal sector is computed as follows. In the ﬁrst survey year (2005), all ﬁrms were informal. The ﬁrst switchers are recorded in 2007, with formalization having taken place between 2005 and 2007. For all switching ﬁrms, I assume that formalization took place in the year of the survey. As a result, for ﬁrms that were informal in 2005 but formal in 2007, the number of years since switching is 0 in 2007. For these ﬁrms that switched in 2007, the number of years since switching becomes 2 in 2009, 4 in 2011, and 6 in 2013. The same procedure is applied to ﬁrms that switched in 2009, 2011, or 2013. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 The Effects of Formalization on SME Tax Payments in Viet Nam 149 1. Likelihood of Tax Payments An advantage of the dataset used in this paper is the provision of hard evidence on tax payments made by informal sector ﬁrms. However, asking about tax payments through traditional survey techniques can be problematic as ﬁrms may decide to misreport.11 Given these possible reporting errors, I conduct a robustness check by using a dummy variable that equals 1 when tax payments are strictly positive (see summary statistics in Appendix Table A1.2). This dummy dependent variable reﬂects the binary participation decision to pay or not to pay taxes; it is estimated using a random effects logit regression. Table 2 shows that switchers’ likelihood of paying taxes is signiﬁcantly higher than nonswitchers (Model 1). The results also suggest that becoming formal is positively and signiﬁcantly associated with an increased likelihood to pay taxes when looking at the coefﬁcient of switcher (after formalization). Table 2 also shows that an increased likelihood of paying taxes is observed both in the short and long term (Model 2). 2. Endogeneity12 This section analyzes the robustness of my results to potential endogeneity of formalization, using a control function approach (Wooldridge 2015). As a ﬁrst step, I estimate a model of the endogenous explanatory variable: Fit = 1 [βXit + ωIit + νit] = 1 [δZit + νit] (2) where 1[.] is the binary indicator function; Fit, the dependent variable, is a dummy variable that takes a value of 1 if a ﬁrm is formal and 0 otherwise; Xit are control variables described earlier in section IV; Iit corresponds to a set of exogenous variables that are omitted from equation (1) and that are partially correlated with formalization; Zit = (Xit, Iit ); and νit is an error term. As a second step, I compute generalized residuals, ˆrit, based on results obtained from equation (2) as follows: ˆrit = Fitλ (cid:4) (cid:3) ˆδZit − (1 − Fit )λ (cid:4) (cid:3) − ˆδZit (3) where λ(.) = ϕ(.)/(cid:13)(.) is the inverse Mills ratio. As a third and ﬁnal step, I reestimate equation (1) by adding ˆrit as an additional regressor to control for endogeneity. To construct Iit, I take the annual provincial-level averages for the following two binary variables: access to powered equipment (1 if with access, 0 otherwise), 11For example, the World Bank Enterprise Surveys ask about “compliance of similar ﬁrms to yourself” to limit the threat of getting wrong responses. 12See also Boly (2018). l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 150 Asian Development Review Table 2. Effects of Formalization on Total Tax Payments (Logit) Variables: Dummy Variable (1 if Taxes > 0)

模型 1 模型 2

Switcher (from informal to formal)

Switcher (after formalization)

Time since becoming formal (dummy, 2 年)

Time since becoming formal (dummy, 4 + 年)

Gender of owner or manager (female = 0, male = 1)

Owner or manager completed secondary school (no = 0, yes = 1)

Gross proﬁts (previous year, 日志)

Firm size (日志 [1 + 就业])

Firm size squared (日志 [1 + 就业])

Share of female employees

Own land use right certiﬁcate (no = 0, yes = 1)

Compliance inspections (no = 0, yes = 1)

持续的

观察结果
Number of panels
Time dummies included
Province dummies included

笔记: ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations. 1.77*** (0.21) 1.72*** (0.21) 1.95*** (0.26) 3.32*** (0.50) 1.23*** (0.30) 0.02 (0.13) 0.12 (0.12) 0.33*** (0.08) 1.36*** (0.41) 0.03 (0.13) 0.10 (0.12) 0.33*** (0.08) 1.39*** (0.41) −0.29*** −0.29*** (0.11) 0.37 (0.24) 0.23* (0.12) 0.66*** (0.15) −4.07*** −4.13*** (0.82) 4,795 1,306 Yes Yes (0.11) 0.37 (0.24) 0.22* (0.13) 0.64*** (0.15) (0.82) 4,795 1,306 Yes Yes and bribe payments (1 if the ﬁrm has made any bribe payments in a given year, 0 otherwise). Here, I restrict my sample to only always-formal ﬁrms and formalized ﬁrms (i.e., switchers once they have switched), with the latter included in the year following formalization. As noted in section III, informal ﬁrms in the sample were selected based on random onsite identiﬁcation in the neighborhoods of formal ﬁrms. In Viet Nam, over 80% of formal ﬁrms consider that registration is beneﬁcial, while nearly 50% of informal ﬁrms do not see any value to it (Cling, Razaﬁndrakoto, and Roubaud 2012). My exclusive restriction assumption is that informal ﬁrms are more likely to formalize when they can observe formal ﬁrms’ characteristics and potentially attribute those characteristics to formalization. Yet, these formal ﬁrms’ observable characteristics will not affect informal ﬁrms’ tax payment behavior. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 The Effects of Formalization on SME Tax Payments in Viet Nam 151 Table 3. Effects of Formality on Total Tax Payments and Likelihood to Pay Taxes—Control Function Approach Variables Switcher (from informal to formal) Switcher (after formalization) Time since becoming formal (dummy, 2 years) Time since becoming formal (dummy, 4 + years) Generalized residuals Gender of owner or manager (female = 0, male = 1) Owner or manager completed secondary school (no = 0, yes = 1) Gross proﬁts (previous year, log) Firm size (log [1 + employment]) Firm size squared (log [1 + employment]) Share of female employees Own land use right certiﬁcate (no = 0, yes = 1) Compliance inspections (no = 0, yes = 1) Access to machinery by formal ﬁrms (province-level average of dummy: 0 = no, 1 = yes) Bribe paid by formal ﬁrms (province-level average of dummy: 0 = no, 1 = yes) Constant Observations Time dummies included Province dummies included Number of panels Log Tax (Real D1,000), Tobit Logit (1 if Taxes > 0)

(1)

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(0.19)
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(0.14)

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(0.17)
0.01
(0.14)
0.19*
(0.10)

0.46***
(0.09)
2.10***
(0.43)
−0.38***
(0.11)
0.39
(0.27)
0.22*
(0.12)
0.73***
(0.16)

(2)

2.45***
(0.19)

1.44***
(0.18)
0.62***
(0.22)
−0.07
(0.17)
0.01
(0.11)
0.21*
(0.12)

0.46***
(0.08)
2.11***
(0.45)
−0.38***
(0.12)
0.39*
(0.24)
0.23*
(0.14)
0.68***
(0.13)

(1)

0.22***
(0.02)
0.06***
(0.02)

0.03
(0.02)
0.01
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0.01
(0.01)

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0.19***
(0.05)
−0.04***
(0.01)
0.05*
(0.03)
0.03*
(0.01)
0.08***
(0.02)

(2)

0.23***
(0.02)

0.10***
(0.02)
0.02
(0.02)
0.02
(0.02)
0.01
(0.01)
0.01
(0.01)

0.04***
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0.20***
(0.05)
−0.04***
(0.01)
0.05*
(0.03)
0.03
(0.02)
0.08***
(0.02)

正式的
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Yes = 1),
Probit

−0.12*
(0.07)
0.38***
(0.06)

0.35***
(0.06)
1.01***
(0.22)
−0.16***
(0.05)
−0.28**
(0.12)
0.01
(0.06)
−0.04
(0.06)
8.70***
(0.91)

−0.70***
(0.12)

−13.38***
(0.93)
4,795
是的
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−3.87***
(0.92)
4,795
是的
是的
1,306

−3.94***
(0.82)
4,795
是的
是的
1,306

−0.28***
(0.10)
4,795
是的
是的
1,306

−0.28***
(0.09)
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Notes: Bootstrapped standard errors in parentheses; ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations The results of the ﬁrst-step regression in the ﬁrst columns of Table 3 (Formal, Probit) indicate that bribes paid by a formal ﬁrm have a negative and signiﬁcant effect on the likelihood of formalization, while access to powered equipment has 152 Asian Development Review a positive and signiﬁcant effect. As a result, Iit fulﬁlls a requirement of the control function approach that at least one exogenous variable that is omitted from equation (1) be partially correlated with the dependent variable in equation (2). The results of the third step (in the control function approach described above) are also presented in Table 3, both for the total tax amount and the likelihood to pay tax. They suggest that endogeneity is not an issue. This provides supportive evidence that formalization can have a positive effect on switchers’ total tax payments and that this effect can persist over time for the amount paid but not the likelihood to pay tax. 3. Unbalanced Panel This paper uses an unbalanced panel, which includes only ﬁrms with at least two observations. However, if ﬁrms that remain informal are more likely to drop out of the panel (as formalized ﬁrms are more visible and easier to locate in subsequent rounds), then this would bias the estimates derived from ﬁrms that remain in the panel. As a ﬁrst robustness check to the unbalanced panel issue, I run regressions using the full sample, or the sample of ﬁrms with at least three, four, or ﬁve observations. In the second check, I keep ﬁrms with at least two observations but vary the number of survey waves, starting with the ﬁrst two waves in 2005 and 2007. In all cases, the full model (including controls) is estimated. However, in Appendix Table A2.1 (varying sample size) and Appendix Table A2.2 (varying number of waves), I present the coefﬁcients for only the variables switcher (from informal to formal) and switcher (after formalization) to save space. My results show that switching ﬁrms are different from informal nonswitchers and that the effect of formalization is positive and signiﬁcant at conventional levels for all samples. D. Discussion To explore where the increase in tax payments after formalization comes from, I make a distinction between revenue taxes and other taxes, with the latter obtained by excluding revenue taxes from total tax payments. Such a distinction is motivated by the difﬁculty to monitor and collect income taxes compared with other types of taxes such as license fees or import and export taxes. This difﬁculty partly explains the use of presumptive taxes for taxing informal sector activities (Joshi, Prichard, and Heady 2014; Dube and Casale 2016). Regression analysis indicates that both the likelihood of payments and the amount paid in revenue-related taxes and other taxes by switchers are signiﬁcantly higher after formalization (Appendix Table A2.3). However, a large share of additional taxes after formalization appears to come from other types of taxes, l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 The Effects of Formalization on SME Tax Payments in Viet Nam 153 not revenue-related taxes. Indeed, switchers report only a small increase in revenue taxes paid before and after switching, based on the sample overall average (D1,152 before switching and D1,175 after switching); while other tax payments appear to increase signiﬁcantly at more than double the amount paid in revenue-related taxes (D625 before switching and D2,616 after switching). Such a result could suggest that some ﬁrms formalize when they realize that in order to start importing or exporting, they need a tax identiﬁcation number to make subsequent trade- related tax payments. To some extent, these results also conﬁrm that revenue-related taxes can be challenging to collect, even after formalization, compared with other types of taxes such as license fees or import and export taxes. Arguably, collecting trade taxes mainly requires being able to control trade ﬂows at major entry points (e.g., ports, airports, or land borders), while collecting income or sales taxes requires major investments in enforcement and compliance structures throughout the entire economy. Overall compliance with tax obligations is another interesting aspect that can be considered when analyzing tax payments. To obtain an estimate of the degree of overall compliance, I compared reported total taxes paid to revenue levels by switchers, before and after formalization. However, a precise computation of the level of compliance would require a tax calculator, which is beyond the scope of this paper. The results on compliance should therefore be treated with caution. I ﬁnd that, using an overall average, the total tax-to-revenue ratio of switchers slightly increased from 1.26% before formalization to 1.44% after formalization.13 Using fractional regression, given that the ratio of total tax to revenue is between 0 and 1, I ﬁnd that the increase in the compliance level is signiﬁcant at the 1% level.14 Notably, the compliance rate of switchers, even after formalization, remains below that of always-formal ﬁrms, which stands at 3.47% in my sample, suggesting that switchers may still not be fully compliant with their tax obligations even after joining the formal sector. VI. Concluding Remarks Using a panel dataset consisting of ﬁve waves of SME surveys in Viet Nam, this paper analyzes the relationship between formalization and tax payments. Such an analysis can be challenging because of potential ﬁrm heterogeneity, due to the fact that ﬁrms choosing to formalize can have different underlying characteristics compared with the ones that remained informal. 13These levels are in line with the lower bound of estimates (1.3%–5% of annual income) provided by Demenet (2016, p. 40). 14The results of these calculations are available from the author upon request. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 154 Asian Development Review To control for unobserved heterogeneity, I created dummy variables that distinguish between two groups of ﬁrms in my sample: those that remain informal and those that switch to the formal sector at some point. As a result, when the variable status, which takes a value of 1 only for switching ﬁrms after they have formalized, is included in my regression, it picks up only the net effects of formalization on tax payments. My results show that switching ﬁrms are different from informal nonswitching ﬁrms regarding total tax payments. Such heterogeneity is typically assumed in most previous studies on formalization but not explicitly assessed. After formalization, I observe a signiﬁcant increase in the amount and likelihood of tax payments, both in the short and long term. These results are mainly driven by a signiﬁcant increase in the payment of other types of taxes—such as license fees, import and export taxes, and property taxes—not in the payment of revenue taxes. Overall, my results are supportive of government efforts to reduce the size of the informal sector by promoting formalization. Such efforts are likely to result in additional revenues for governments, which is an important assumption underpinning the public policy rationale for promoting formalization. References Basu, Arnab K., Nancy H. Chau, and Ravi Kanbur. 2010. “Turning a Blind Eye: Costly Enforcement, Credible Commitment, and Minimum Wage Laws.” Economic Journal 120 (543): 244–69. Boly, Amadou. 2018. “On the Short- and Medium-Term Effects of Formalisation: Panel Evidence from Vietnam.” Journal of Development Studies 54 (4): 641–56. Bruhn, Miriam, and David McKenzie. 2014. “Entry Regulation and the Formalization of Microenterprises in Developing Countries.” World Bank Research Observer 29 (2):186– 201. Cling, Jean-Pierre, Mireille Razaﬁndrakoto, and François Roubaud. 2011. “The Informal Economy in Viet Nam.” Ha Noi: International Labour Organization. _____. 2012. “To Be or Not to Be Registered? Explanatory Factors behind Formalizing Non- Farm Household Businesses in Vietnam.” Journal of the Asia Paciﬁc Economy 17 (4): 632– 52. De Mel, Suresh, David McKenzie, and Christopher Woodruff. 2013. “The Demand for, and Consequences of, Formalization among Informal Firms in Sri Lanka.” American Economic Journal: Applied Economics 5 (2): 122–50. Demenet, Axel. 2016. “Insights into a Predominant and Dynamic Informal Sector: The Case of Vietnam.” Economies and Finances, PSL Research University. English. https://tel.archives- ouvertes.fr/tel-1587795. Dube, Godwin, and Daniela Casale. 2016. “The Implementation of Informal Sector Taxation: Evidence from Selected African Countries.” eJournal of Tax Research 14 (3): 601–23. Fajnzylber, Pablo, William F. Maloney, and Gabriel V. Montes-Rojas. 2011. “Does Formality Improve Micro-Firm Performance? Evidence from the Brazilian SIMPLES Program.” Journal of Development Economics 94 (2): 262–76. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 The Effects of Formalization on SME Tax Payments in Viet Nam 155 General Statistics Ofﬁce of Viet Nam (GSO). 2004. Results of Establishment Census of Vietnam 2002: Vol. 2. Business Establishments. Ha Noi: Statistical Publishing House. _____. 2008. The Real Situation of Enterprises through the Results of Surveys Conducted in 2005, 2006, 2007. Ha Noi: Statistical Publishing House. Henley, Andrew, G. Reza Arabsheibani, and Francisco G. Carneiro. 2009. “On Deﬁning and Measuring the Informal Sector: Evidence from Brazil.” World Development 37 (5): 992– 1003. International Labour Organization. 2003. “Guidelines Concerning a Statistical Deﬁnition of Informal Employment.” 17th International Conference of Labour Statisticians, Geneva. Joshi, Anuradha, Wilson Prichard, and Christopher Heady. 2014. “Taxing the Informal Economy: The Current State of Knowledge and Agendas for Future Research.” Journal of Development Studies 50 (10): 1325–47. Maloney, William F. 2004. “Informality Revisited.” World Development 32 (7): 1159–78. McKenzie, David, and Seynabou Sakho. 2010. “Does It Pay Firms to Register for Taxes? The Impact of Formality on Firm Proﬁtability.” Journal of Development Economics 91 (1): 15– 24. Olken, Benjamin A., and Monica Singhal. 2011. “Informal Taxation.” American Economic Journal: Applied Economics 3 (4): 1–28. Organisation for Economic Co-operation and Development (OECD). 2008. “Declaring Work or Staying Underground: Informal Employment in Seven OECD Countries.” In OECD Employment Outlook 2008. Paris. Rand, John, and Nina Torm. 2012. “The Beneﬁts of Formalization: Evidence from Vietnamese Manufacturing SMEs.” World Development 40 (5): 983–98. Sharma, Smriti. 2014. “Beneﬁts of a Registration Policy for Microenterprise Performance in India.” Small Business Economics 42 (1): 153–64. Tedds, Lindsay M. 2010. “Keeping It Off the Books: An Empirical Investigation of Firms that Engage in Tax Evasion.” Applied Economics 42 (19): 2459–73. Wooldridge, Jeffrey M. 2015. “Control Function Methods in Applied Econometrics.” Journal of Human Resources 50 (2): 420–45. Appendix 1 Table A1.1. Frequency of Sample Firm Types Overall Between Firm Type Frequency Percentage Frequency Percentage Informal nonswitchers Switchers (informal to formal) Total 3,170 1,859 5,029 63 37 100 896 458 1,354 66 34 100 Source: Author’s calculations. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 156 Asian Development Review r e t f A g n i h c t i w S e r o f e B g n i h c t i w S ) l a m r o F o t l a m r o f n I ( s r e h c t i w S l l a r e v O s r e h c t i w s n o N D S n a e M N D S n a e M N D S n a e M N D S n a e M N e p y T m r i F y b s e l b a i r a V t n e d n e p e d n I d n a t n e d n e p e D f o s c i t s i t a t S y r a m m u S . 2 . 1 A e l b a T s e l b a i r a V t n e d n e p e D 3 1 1 1 1 , 6 2 1 0 . 2 9 7 3 , 9 6 9 0 . 2 3 4 2 3 4 2 7 6 , 5 3 3 3 . 0 8 7 7 , 1 4 3 8 . 0 2 3 4 2 3 4 3 5 4 , 7 2 9 1 . 0 3 8 8 , 2 2 0 9 . 0 2 3 4 2 3 4 0 3 0 , 1 5 7 3 . 0 9 6 5 . 0 9 . 3 3 3 4 7 8 4 7 8 , 0 >

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The Effects of Formalization on SME Tax Payments in Viet Nam 157

附录 2

Table A2.1. Effects of Formalization on Total Tax Payments (Tobit)—Varying Sample Sizes

Variables: Log (1 + Taxes), (Real D1,000)

Minimum Observations in Panel

Switcher (from informal to formal)

Switcher (after formalization)

持续的

观察结果
Number of panels
Other controls
Time dummies included
Province dummies included

2.57***
(0.21)
1.12***
(0.17)

2.75***
(0.21)
0.90***
(0.19)

2.72***
(0.31)
0.75***
(0.23)

2.60***
2.31***
(0.21)
(0.18)
1.09***
1.14***
(0.20)
(0.15)
−3.29*** −3.07*** −3.63*** −4.25*** −3.48***
(0.99)
(0.94)
4,240
5,155
1,020
1,666
是的
是的
是的
是的
是的
是的

(1.31)
2,773
570
是的
是的
是的

(1.20)
3,393
731
是的
是的
是的

(0.83)
4,795
1,306
是的
是的
是的

D = dong.
Notes: Bootstrapped standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations. Table A2.2. Effects of Formalization on Total Tax Payments (Tobit)—Varying Survey Waves Variables: Log (1 + Taxes), (Real D1,000) Switcher (from informal to formal) Switcher (after formalization) Constant Observations Number of panels Other controls Time dummies included Province 2005– 2007 2005– 2009 2005– 2011 2005– 2013 2007– 2009 2007– 2011 2007– 2013 2009– 2011 2009– 2013 2011– 2013 2.71*** (0.26) 2.82*** (0.23) 2.61*** (0.20) 2.57*** (0.21) 2.45*** (0.23) 2.27*** (0.21) 2.32*** (0.21) 1.67*** (0.36) 1.77*** (0.35) 0.79 (0.59) 1.12*** (0.17) 1.54*** (0.14) 1.31*** (0.18) 1.07*** 2.40*** (0.57) (0.20) −4.23*** −3.67*** −3.81*** −3.07*** −6.67*** −6.04*** −4.41*** −6.40*** −4.43*** −2.35 (1.45) (1.33) 1,778 1,962 970 1,075 (1.17) 2,128 1,203 (0.83) 4,795 1,306 (1.01) 3,979 1,306 (0.95) 3,017 1,204 (1.06) 3,906 1,305 (0.87) 3,090 1,305 (1.18) 2,833 1,157 (1.12) 2,017 1,157 1.58*** (0.17) 1.90*** (0.23) 1.34*** (0.17) 1.99*** (0.30) 2.32*** (0.33) Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes dummies included D = dong. Notes: Bootstrapped standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 158 Asian Development Review Table A2.3. Effects of Formalization on Revenue and Other Tax Payments Revenue-Related Taxes Other Taxes Variables Switcher (after formalization) Gender of owner or manager (female = 0, male = 1) Owner or manager completed secondary school (1 if completed, 0 otherwise) Gross proﬁts (previous year) Firm size (log [1 + employment]) Firm size squared (log [1 + employment]) Share of female employees Own land use right certiﬁcate (no = 0, yes = 1) Compliance inspections (no = 0, yes = 1) Constant Observations Number of panels Time dummies included Province dummies included Tobit 4.52*** (0.76) −0.64 (0.79) 0.30 (0.62) 1.26*** (0.40) 8.78*** (2.65) −1.50*** (0.57) −0.40 (1.18) −0.53 (0.57) 0.65 (0.76) −20.96*** (4.66) 1,744 432 Yes Yes Logit (1 if Taxes > 0)

1.01***
(0.23)
−0.15
(0.17)
0.05
(0.15)
0.28**
(0.11)
1.88***
(0.58)
−0.32***
(0.12)
−0.11
(0.28)
−0.09
(0.17)
0.15
(0.17)
−4.53***
(1.20)
1,744
432
是的
是的

Tobit

1.60***
(0.19)
0.03
(0.13)
0.23
(0.14)
0.35***
(0.09)
2.76***
(0.61)
−0.55***
(0.14)
−0.08
(0.28)
−0.20
(0.12)
0.36***
(0.13)
−1.93**
(0.93)
1,744
432
是的
是的

Logit (1 如果
Taxes > 0)

3.19***
(0.45)
0.36
(0.27)
−0.07
(0.28)
0.31**
(0.13)
3.46***
(0.86)
−0.75***
(0.19)
−0.01
(0.57)
−0.26
(0.27)
0.67**
(0.30)
−4.19***
(1.54)
1,744
432
是的
是的

Notes: Bootstrapped standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1. Source: Author’s calculations. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / 3 7 1 1 4 0 1 8 4 6 7 6 3 a d e v _ a _ 0 0 1 4 4 p d / . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 The Effects of Formalization on Small and image

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