OSIPP Discussion Paper : DP-2024-E-004

Inter-municipal cooperation andtax enforcement capabilities
June 21, 2024
Naruki Notsu1
PhD.student, Osaka School of International Public Policy, Osaka University

Haruaki Hirota2
Professor, Faculty of Economics, Musashi University

Nobuo Akai3
Professor, Osaka School of International Public Policy, Osaka University

Abstract: This study examines the effects of enhancing the tax enforcement ofadministration on the tax gap, focusing on inter-municipal cooperation (IMC). IMC
refers to collaborative tax collection efforts among multiple municipalities andpromotes the aggregation of tax collection resources and expertise, improving tax
enforcement. Using the time variation in IMC creation across municipalities, we showthat IMC substantially improves the tax gap measurement by reinforcing tax
enforcement in local governments. The effects also appear to be driven at both theinter-municipal organization and municipal official levels. Our findings suggest thatenhanced administrative capability in tax enforcement can be an effective tool against
noncompliance in ways other than facilitating voluntary compliance.
JEL Classification: H71, H77, H83
Keywords: Inter-municipal cooperation, Tax enforcement, Tax compliancenotsu.naru@gmail.com
hirota@cc.musashi.ac.jp
3 akai@osipp.osaka-u.ac.jp
12

Inter-municipal cooperation andtax enforcement capabilities
Naruki Notsu †Haruaki Hirota ‡Nobuo Akai §June 21, 2024

Abstract
This study examines the eﬀects of enhancing the tax enforcement of administration on
the tax gap, focusing on inter-municipal cooperation (IMC). IMC refers to collaborative
tax collection eﬀorts among multiple municipalities and promotes the aggregation of tax
collection resources and expertise, improving tax enforcement. Using the time variationin IMC creation across municipalities, we show that IMC substantially improves the tax
gap measurement by reinforcing tax enforcement in local governments. The eﬀects also
appear to be driven at both the inter-municipal organization and municipal oﬃcial levels.
Our findings suggest that enhanced administrative capability in tax enforcement can be aneﬀective tool against noncompliance in ways other than facilitating voluntary compliance.
JEL Classification: H71, H77, H83
Keywords: Inter-municipal cooperation, Tax enforcement, Tax compliance

The authors acknowledge the financial support received from the JSPS KAKENHI (20H01504, 20H01450,
22K01542, 22H00856)† Naruki Notsu, Graduate student, Osaka School of International Public Policy, 1-31, Machikaneyama, Toyonaka,
Osaka, 560-0043, Japan. E-mail:notsu.naru@gmail.com, Corresponding author‡ Haruaki Hirota, Faculty of Economics, Musashi University; 1-26-1, Toyotamakami, Nerima-ku, Tokyo, 1768534, Japan. E-mail: hirota@cc.musashi.ac.jp§ Nobuo Akai, Osaka School of International Public Policy, 1-31 Machikaneyama, Toyonaka, Osaka, 560-0043,
Japan. E-mail: akai@osipp.osaka-u.ac.jp

1

Introduction

The tax gap, defined as the diﬀerence between the actual taxes collected by governments fromcompanies and households and the legally mandated taxes, is directly related to government
revenue, fiscal soundness, and the healthy functioning of societies (IRS 2006; IMF 2015;
De Neve, Imbert, Spinnewijn, Tsankova, and Luts 2021). Therefore, closing this gap byincreasing tax collection is a key objective for governments in both developed and developing
countries worldwide (HMRevenue&Customs 2018; De Neve et al. 2021; Basri 2021; Garriga
and Tortarolo 2024). To close the gap, governments can take two main approaches. One
approach is to facilitate taxpayer compliance. (Slemrod 2019; Martinez-Vazquez, Sanz-Arcega,
and Tranchez-Martin 2022).1 The other approach is to enhance the tax enforcement capabilitiesof the administration (IRS 2006; Bethencourt and Perera-Tallo 2024). This latter approachindicates enforcement of tax collection through reforms on the administrative side, which isdistinct from governmental intervention to facilitate taxpayer compliance.
One of the simplest ways to enhance tax enforcement capabilities is by increasing the numberof tax oﬃcials, equipment, and other resources. While this straightforward approach can improvetax collection, it may require additional costs which in turn limits research from the perspectiveof administrative tax enforcement. For instance, deploying police oﬃcers on every street corner
to completely prevent robberies and red light infractions is not optimal; similarly, providing an
excessive number of tax collection oﬃcials to achieve complete tax enforcement is ineﬃcientand impractical (Slemrod 2019).2 Therefore, while improving tax enforcement capabilities may
be eﬀective in closing the tax gap, allocating more oﬃcials and resources is not always a rationaland realistic governmental reform. Therefore, the eﬃcacy of reforms aimed at improving tax
enforcement capabilities remains unclear.
This paper focuses on Inter-municipal Cooperation (IMC) to shed light on the eﬀectivenessof enhancing tax enforcement capabilities. IMC refers to collaborative tax collection among
diﬀerent municipalities, establishing new jurisdictions for collective operations. Its collaborative
approach is expected to improve tax enforcement at both the inter-municipal organization andlocal municipal oﬃcial levels. First, collaborative collection eﬀorts at the IMC organizationlevel can improve tax enforcement through an augmented deployment of tax collection oﬃcials
on a per-case basis. In addition, such increasing collection activities allow for more divisionof labor into more specialized functions within the organization, leading to more eﬀective
tax enforcement. Second, IMC provides local tax oﬃcials with opportunities for training in
professional development and exposure to more sophisticated tax collection practices through
1Many studies examine tax compliance focusing on interventions to the taxpayer side such as digitalization,
third-party reporting, and procedural changes. See Slemrod (2019); De Neve et al. (2021); Bellon, Dabla-Norris,
Khalid, and Lima (2022); Okunogbe and Pouliquen (2022); Garriga and Tortarolo (2024) for the findings on tax
compliance.
2Slemrod (2019) employs this analogy to argue that completely eradicating tax evasion is not optimal.

1interactions between oﬃcials from participating municipalities. This training and interaction
within IMC can lead to more eﬀective tax enforcement of each oﬃcial.3 Therefore, IMC has
the potential to enhance tax enforcement at both the inter-municipal organization and local
municipal oﬃcial levels.4
To investigate evidence, we take advantage of the setting of implementing IMC in Japanand data on tax enforcement. First, we exploit the timing variation of implementing IMC in
Japan. This IMC refers to collaborative tax collection eﬀorts among multiple municipalities
without establishing an independent fiscal authority, such as creating new tax rights. Thus, we
can examine the eﬀects of IMC on tax enforcement without confounding the existence of otherinstitutional tax changes that can influence tax enforcement.5
Second, we can use the unpaid tax collection rate to examine the eﬀects of IMC on the tax
gap. The unpaid tax collection rate is the percentage of unpaid taxes that have been successfullycollected. That is, this rate denotes the gap in which local governments can collect actual unpaid
taxes from companies and households relative to the total unpaid taxes that should be collected.
In particular, IMC covers tax collection on unpaid taxes only. Therefore, IMC may increase
unpaid tax collection rates by improving tax enforcement.
To examine the eﬀects of IMC on unpaid tax collection rates, we use a diﬀerence-indiﬀerences (DID) approach and an event study specification, exploiting the timing of IMC
implementation across municipalities. For the unpaid tax collection rate, our analysis focuseson two tax categories—inhabitant tax and property tax. We find that IMC increases unpaid tax
collection rates for inhabitants and property taxes by approximately 17 percent and 28 percent,respectively. However, the pre-implementation financial condition of the municipalities may
pose a potential confounding factor, given the anticipation of increased tax revenue throughIMC participation. To consider this concern, we perform placebo tests, which reveal that themain results are robust. Furthermore, in the event study analysis, we confirm that there are nodiﬀerences in the pre-trends of the outcomes before IMC implementation.
In addition, we perform a triple-diﬀerence analysis by stacking the present tax collection
rates with unpaid tax collection rates as an additional variation in the outcome. The present
tax collection rate is a measure of the tax collection rate that is unrelated to unpaid taxes andnoncompliance and is not subject to IMC operations. For the triple diﬀerence, it is not necessary
to assume two parallel trends for the present and unpaid tax collection rates under specificassumptions. Using this stacked dataset, we find that IMC increases unpaid tax collection rates,
3Some literature points out the importance of the relationship between learning and experience and humancapital interaction (Acemoglu and Angrist (2000); Henderson (2007); la Roca and Puga (2017)). In particular,
there is evidence that the existence of highly productive or skilled workers leads to more productivity gains throughworker interaction and training (Mas and Moretti (2009); Grip and Sauermann (2012); Bentsen, Munch, and Schaur(2019))
4See Section 2.1 for more information on the relationship between IMC and tax enforcement.
5For example, IMC in France involves the transfer of competencies and tax powers, enabling the setting of tax
rates.

2

which is consistent with the baseline results.
We also show the heterogeneous eﬀects of IMC. First, to focus on channels, we demonstrate
the heterogeneous eﬀects of the composition of IMC. IMC is expected to increase unpaid tax
collection rates through inter-municipal organizations and municipal oﬃcial levels. At themunicipal oﬃcial level, training and interaction within the IMC lead to more eﬀective tax
enforcement by municipal oﬃcials, and this eﬀect occurs only when municipal oﬃcials are partof the IMC. Therefore, we analyze the heterogeneous eﬀects of IMC based on the presence ofmunicipal oﬃcials. We find that IMC composed of municipal oﬃcials increases unpaid tax
collection rates relative to that composed of nonmunicipal oﬃcials in terms of inhabitant taxes.
These findings suggest that training and interaction within the IMC lead to the specialization of
tax oﬃcials in the municipality, thus improving tax enforcement.
Second, we show the heterogeneous eﬀects of IMC on tax administrative costs by population
share. Tax administrative costs are the comprehensive costs associated with tax collection.
In the context of IMC, both positive and negative aspects of cost are often pointed and theirheterogeneity depending on the population size of the municipality is also emphasized (Beland Warner 2015; Allers and de Greef 2018; Ferraresi, Migali, and Rizzo 2018; Notsu 2024).
This paper investigates the heterogeneity of eﬀects by population size across municipalities andpopulation share within IMC to determine whether IMC aﬀects cost aspects. The results showthat IMC decreases in tax administrative costs only in municipalities with larger populations andotherwise has null eﬀects. These results suggest that collaborative tax collection via IMC is nota costly measure and may even reduce the costs of tax collection.
Finally, we examine the eﬀects of IMC advertisements. Some IMCs advertise the sale ofassets seized from taxpayers with unpaid dues as a warning, aiming to facilitate compliance. By
using variations in whether IMCs engage in such advertising, we investigate the heterogeneouseﬀects of IMCs. We find no significant diﬀerences in the impact of IMC on unpaid tax
collection rates based on these warnings. The findings suggest that IMC can close the tax gap byenhancing tax enforcement on the administrative side, rather than by encouraging complianceon the taxpayer side.
This study is most related to the work of Jia, Ding, and Liu (2020), which examines theeﬀects of administrative reform on local tax revenue. However, our research diverges in termsof its focus. While the above study focused on the amount of tax revenue, we focus on the tax
gap. Furthermore, the biggest distinction between our study and the work of Jia et al. (2020) is
their interest in the eﬀects of fiscal decentralization, whereas we are interested in enhancing tax
enforcement through municipal cooperation
More generally, this paper contributes to the broad literature on policy responses to tax
compliance. A growing body of research focuses on initiatives designed to encourage tax compliance, including the introduction of third-party reporting, tax audits, and digital technologies
3

(Slemrod 2019; Alm 2019; Bellon et al. 2022; Okunogbe and Pouliquen 2022). De Neve et al.
(2021) investigate the simplification of communications, focusing on the probability of payment
to letters sent.6 While most of these studies examine services and policy interventions that facilitate behavioral change on the taxpayer side, our study focuses on enhancing tax enforcement
capabilities on the administrative side.
This paper also contributes to the extensive body of research on IMC. Existing empiricalstudies have examined the impact of IMC on local government costs (Bel and Warner 2015;
Allers and de Greef 2018; Ferraresi et al. 2018). Almost all studies on IMC have focused on
the cost aspect of local governments, targeting capital-intensive services such as sewage andwaste disposal (Bel, Fageda, and Mur 2012). Meanwhile, only a limited number of studies have
explored aspects other than local government costs. For instance, Tricaud (2024) demonstrates
that in France, IMC leads to more construction and fewer public services, while Banaszewska,
Bischoﬀ, Bode, and Chodakowska (2022) finds that IMC in Poland reduces local unemployment
rates. This paper complements this stream of literature by investigating the impact of IMC on
revenue.
Also, Breuillé, Duran-Vigneron, and Samson (2018) examines the eﬀects of establishmentsof IMC (EIMC) in France on local tax rates. This paper substantially diﬀers from their work on
tax rates in focusing on local tax enforcement. Furthermore, the framework of IMC in Japan,
which has no independent fiscal authority, diﬀers in its purpose and nature from that of EIMC,
as EIMC involves transferred competencies and tax powers from participating municipalities.
Therefore, Japan’s IMC setting allows us to estimate the eﬀect of improving the tax enforcement
capacity of the administrative side without confounding the influence of complex institutional
tax change that can aﬀect tax enforcement.
The remainder of the paper is organized as follows. In Section 2, we present an overview of
IMC and local taxation. Section 3 describes the data used in the analysis. Section 4 outlines theempirical strategy, while Section 5 presents the heterogeneity results. Section 6 concludes thepaper.

2

Institutional Background

2.1

Inter-municipal cooperation

2.1.1

Inter-municipal cooperation in Japan

IMC is formed beyond municipal boundaries to enhance the eﬃciency of public service delivery
by leveraging economies of scale. The structure of local governments in Japan comprises
6These authors use the number of tax collections as a measure of the tax gap, while our study uses the amountof revenue from tax collections.

4

two levels—47 prefectures and 1.78 municipalities. While IMC is not embedded in these twolayers of government, it establishes an additional level of jurisdiction for specific tasks andhas the responsibility of performing the work instead of each municipality itself. In Japan,
these collaborations are utilized across various services, including joint waste management,
firefighting, and healthcare, in addition to tax collection, to leverage economies of scale.
In Japan IMC, municipal collaboration on tax collection exists.7 This IMC involves collaborative tax collection specializing in unpaid taxes by residents and property taxes and does not
involve independent fiscal authority, such as the creation of taxation rights. Notably, IMC does
not jointly collect all unpaid taxes among participating municipalities, and individual municipalities also continue to collect unpaid taxes themselves. The operation of unpaid tax collection
involves several complicated tasks, such as notification, property investigation, seizure, public
auction, and deficiency disposition. Notification is a notice of demand to the taxpayer who has
failed to pay the tax. When there is no response to such a notification, property investigations,seizures, and public auctions are executed. In particular, the task of property investigation includes inquiries to the national tax oﬃce, legal aﬀairs bureau, other public oﬃces, and relevant
financial institutions to ascertain the actual status of income and real estate ownership and toobtain a list of bank accounts and the number of deposits. In addition, knowledge of tax laws
is necessary for seizure and public auctions. Therefore, property investigations, seizures, andpublic auctions are considered more sophisticated techniques (Tezuka 2012).
The cost burden within IMC is determined by the population share, the amount of unpaid
taxes, and the percentage of tax revenues within IMC. For example, the Kyoto Regional Tax
Organization has a uniform 5 percent share of the total operating burden for IMC, and theremaining share is determined by population percentage, tax revenue percentage, and the amountof unpaid tax for each municipality.
2.1.2

Inter-municipal cooperation on tax collection

IMC is expected to enhance tax enforcement through two potential channels, as shown in Figure
1. First, tax enforcement can be enhanced by collecting taxes at the IMC organization level.
Collaborative tax collection in IMC increases the deployment of tax collection oﬃcials on a
per-case basis. In particular, the recent trend in Japan of a declining number of oﬃcials in thelocal governments has led to a shortage of human capital for tax collection services (Murakami2012). Consolidating local tax oﬃcials through IMC can substantially increase the numberof available tax oﬃcials, thereby compensating for these gaps. Furthermore, these increasing
activities may allow for more division of labor into more specialized functions (Blom-Hansen,
7This type of IMC can be organized in the form of a “multitask extended association,” “single-task extended
association,” or “voluntary organization.” Multitask and single-task extended associations are types of IMC that
constitute legal entities. In contrast, voluntary organizations have no legal authority. However, any type oforganization is still a form of municipal cooperation on tax collection.

5

Houlberg, and Serritzlew 2014). Establishing specialized departments, based on the unpaid tax
collection process, can result in more eﬃcient collection operations (Tezuka 2012). However,such a division of labor requires a larger workforce and scale. Therefore, the scale increase
by IMC enables more division of labor into more specialized and may lead to enhanced tax
enforcement.
Additionally, the tax administration could conduct tax collection at lower costs by leveraging
economies of scale through IMC. Therefore, within a limited budget, IMC leads to the provisionof more services and may compensate for the lack of services for tax collection.
Second, training and interaction within IMC may improve the tax enforcement of eachmunicipal oﬃcial. IMC not only takes over the work of the municipality but also provides local
tax oﬃcials with opportunities for training and exposure to more sophisticated tax collection
practices. For example, the Mie Local Tax Management and Collection Organization, one of the
IMCs, provides training and conferences to improve the tax enforcement skills of staﬀ members.
Furthermore, IMC establishes teams of knowledgeable and novice tax oﬃcials, to provide thelatter an opportunity for them to be exposed to more sophisticated tax collection practices(Murakami 2012). Such training and worker interactions can lead to increased productivity(Grip and Sauermann 2012). In particular, it is diﬃcult to accumulate expertise on the unpaid
tax collection process at the municipal level where oﬃcials are transferred every few years
and do not specialize in tax collection compared to the national level in Japan (Hayashi 2009).
Therefore, local tax oﬃcials may become more eﬀective in tax collection through training andinteraction within IMC, thus enhancing tax enforcement.
Figure 1: Relationship between IMC and local tax enforcement

Note: This figure shows the workflow of IMC intervention.

6

2.2

Local Taxation

In Japan, both central and local governments collect taxes. While local government revenue isapproximately half that of the central government, the total exceeds 40 trillion yen (approximately
300 billion U.S. dollars). The tax base of the central government consists primarily of income
taxes, corporate income taxes, and consumption taxes. Local governments also have corporate
income tax and consumption tax. In local governments, the tax base diﬀers between prefecturesand municipalities. In particular, at the municipal level, inhabitant and property taxes account for
70 percent of total revenue. Property tax accounts for 41 percent, and inhabitant tax accounts for
37 percent of total municipal tax revenues in 2021.8 However, Figure A.1 shows the inhabitantand property tax revenue per taxpayer, indicating that property tax revenue per taxpayer is morethan double the inhabitant tax per taxpayer. The collection of inhabitant tax is distributed among
municipalities and prefectures, leading to comparatively modest amounts per case.9
IMC prioritizes high-value tax cases.10 Therefore, IMC is more likely to focus on property
tax, the most expensive tax category per taxpayer among municipal tax revenues, than on
inhabitant tax.
Tax collection can be divided into present and unpaid tax collection. The present tax
revenue is the tax amount to be collected within the fiscal year and serves as a measure offlow. In contrast, unpaid tax revenue is the total tax due that has not been collected in thecurrent period, representing a stock measure. Figure 2 presents the unpaid tax amount from2000 to 2018, where the blue and red lines represent the unpaid inhabitant and property taxes,
respectively, and the green lines represent the total amount of unpaid taxes. In all tax categories,
unpaid taxes are approximately 400 billion yen or higher (approximately 26 billion U.S. dollars).
Furthermore, as with local tax revenues, the sum of the inhabitant tax and property unpaid tax
accounts for 70 percent of the total unpaid tax.
8The third largest share, corporate income tax, accounts for approximately 9 percent.
9The inhabitant tax in municipalities is generally set at 6 percent of an individual’s income.
10More than 70 percent of instances of IMC set the conditions for collaborative tax collection as amounts of
unpaid taxes and diﬃcult-to-process cases.

7Figure 2: Reform of unpaid tax collection

Note: Trends in the total amount of unpaid tax collection in Japan from 2000 to 2018. The green line shows
the total amount of unpaid tax for all tax categories, the red line shows the unpaid tax collection amount for the
inhabitant tax, and the blue line shows the unpaid tax collection amount for the property tax. The monetary unit isa billion yen.

3

Data

Our analysis uses an exhaustive administrative panel of Japanese municipalities and covers the
fiscal period from 2000 to 2018. In Japan, a devastating earthquake called the Great East Japan
Earthquake occurred in 2011, causing extensive damage to the administration and residents inthe aﬀected areas, particularly in the Iwate, Miyagi, and Fukushima Prefectures. Therefore, we
exclude these three prefectures from our panel.11 In addition, excluding the 23 wards of Tokyoand amalgamated municipalities, we create a balanced panel dataset.12

3.1

Outcome Variables

We use the unpaid tax collection rate as a measure of the tax gap. This measure indicates thedegree to which the local government could have collected unpaid tax. The unpaid tax collection
11For example, residents in the areas aﬀected by the earthquake took special measures, such as extended deadlines
and exemptions from local tax payments, during the crisis.
12The 23 wards of Tokyo have a fiscal base in which revenues exceed expenditures and property taxes arecollected at the prefectural level, which is very diﬀerent from the financial status of other municipalities.

8

rate in municipality 8 in year H is as follows:
Unpaid tax collection rateH =Unpaid tax collectionH
Total unpaid tax

where Unpaid tax collectionH is the unpaid tax collected by municipality 8 in year H.
Total unpaid taxH is the stock of the unpaid tax. In other words, the denominator captures
the total tax with which has not been complied, while the numerator reflects the actual amountcollected within the denominator. Therefore, enhanced tax enforcement on unpaid taxpayers
leads to a narrower gap between these two figures (i.e., an increase in the unpaid tax collectionrate).

3.2

Treatment Variables

Our analysis uses treatment variables that exploit the timing of implementation of IMC acrossmunicipalities. To establish these treatment variables, we obtain data from the Ministry ofInternal Aﬀairs and Communications in Japan. Figure A.2 shows the distribution of municipalities participating in IMC. Because IMC is implemented within neighboring municipalities, its
distribution is concentrated in certain regions. A potential concern regarding treatment timingis the possibility of the municipality’s decision to participate in IMC being confounded by otherspecific features. Nevertheless, prior to IMC implementation, there were no disparities in unpaid
tax collection rates. In Figure 3, the red and blue lines compare the average rates of unpaid
tax collection between the not-yet-treated group and the never-treated group for inhabitant taxes(left panel) and property taxes (right panel), respectively. This comparison reveals minimal
diﬀerences in unpaid tax collection rates between the two groups over time. In addition, ouranalysis incorporates municipal fixed eﬀects and prefecture-by-time fixed eﬀects, which ensure
appropriate comparisons between the treatment and control groups within the prefecture. In
the event study specification, the findings suggest that the treatment eﬀects are not driven by
the pretreatment periods. Moreover, when including observable covariates in our analysis, themagnitudes of the estimated coeﬃcients remain largely unchanged, implying that confounders
in terms of IMC implementation are unlikely to be a concern.

9Figure 3: Comparison of not-yet-treated and never-treated groups

Note: Trends in the average unpaid tax collection rate from 2000 to 2015. The red line shows the average
unpaid tax collection rate in the not-yet-treated group within the treatment group (i.e., the treatment group before
IMC implementation), and the blue line shows the average unpaid tax collection rate in the control group, which isnever treated.

4

Empirical Strategy and Results

4.1

DID Specification

Collaborative tax collection enhances tax enforcement capabilities at both the inter-municipal
and local municipal levels, which in turn is expected to improve the tax gap. To examine this,
we present a strategy for estimating the eﬀect of IMC on the tax collection rate. By exploiting
diﬀerent timings of IMC introduction, we estimate the following:
Y8,?,H = VIMC8,?,H + `8 + d ?,H + Y8,?,H(1)

where .8,?,H is the unpaid collection rate for each tax type, indicating tax enforcement inmunicipality 8 of prefecture ? in year H. This unpaid tax collection rate is converted into its
10logarithmic form. IMC8,?,H is a binary dummy variable that equals 1 if IMC is adopted inmunicipality 8 within prefecture ? during year H and 0 otherwise. The parameter of interest is
V. `8 and d ?H are municipality- and prefecture-by-time fixed eﬀects, respectively, and Y8 ?H isthe error term. By including these fixed eﬀects, we control for the characteristics specific to themunicipalities but that remain constant over time, as well as macro shocks at the national level,
and address the issue of omitted variable bias. In addition, by including prefecture-by-time
fixed eﬀects, the comparison between the treatment and control groups becomes a comparison
within a prefecture over time. Therefore, regional diﬀerences in the introduction of IMCs acrossprefectures, as shown in Figure A.2, can be controlled.
In the main specification, we do not include any covariates, as the DID estimator with fixedeﬀects and time-varying covariates requires an additional identification assumption of DID on
the covariates (Sant’Anna and Zhao 2020). Therefore, in Section 4.3.2 on the robustness check,we present the estimation results with additional covariates.

4.2

Event Study Specification

We demonstrate the dynamic eﬀects of IMC on tax enforcement using event study analysis,
which oﬀers two advantages. First, such analysis enables us to indirectly test the parallel trend
assumption, which is the identifying assumption for the DID specification. The parallel trend
assumption requires that the outcome variables of the treatment and control groups follow similar
trends in the absence of treatment. By examining the trends in outcome variables between thetreatment and control groups during the pretreatment period through event study analysis, we
can check the validity of the parallel trend assumption. In addition, this analysis allows us
to examine the eﬀect of IMC appearance and how the eﬀect of IMC persists following IMC
implementation.
In the analysis, we use normalized time C, which represents the diﬀerence between thecalendar year H and the year when the municipality 8 first participated in IMC.

Y8,?,C =8’8,g< 1

g
Vg IMC8,?,C+ `8 + d ?,H + Y8,?,H(2)"⇠8g?C denotes the lead and lag indicators that take a value of 1 if C is equal to g, greater thanor equal to 8, or less than or equal to 8.13 Vg represents the dynamic treatment eﬀects for the 8
periods before and the 9 periods after the introduction of the IMC. To satisfy the parallel trend
assumption, the treatment eﬀect should not be observed in the periods before the treatment.
13g = -1 is excluded from the equation as the reference period.

11

4.3

Main Results

4.3.1

DID and Event Study Results
Table 1: DID estimate: Impact of IMC on the unpaid tax collection rate
(1)
(2)
(3)
Inhabitant tax Property tax Corporation tax
TaxIMC
0.168***
0.279***
0.021[0.048][0.076][0.092]
Observations
R-squared
Municipality FE
Pref*Year Yes

22135
0.567
Yes
Yes

22264
0.550
Yes
Yes

17038
0.439
Yes
Yes

Note: The table shows the results in Equation (1). Columns (1), (2) and (3) represent the eﬀects of IMC on
the unpaid collection rate on inhabitant tax, property tax, and corporation tax. Clustered standard errors at themunicipality level are given in brackets. ***, **, * represent that the estimates are significantly diﬀerent from zeroat the levels of 1%, 5%, and 10%, respectively.

Columns (1) and (2) of Table 1 show the eﬀects of IMC on the unpaid tax collection rate forinhabitant and property taxes. We estimate approximately 17 percent and 28 percent increases
in the probability of the unpaid tax collection rate for inhabitant and property taxes, respectively,by IMC implementation. In all the estimation results, we observe positive eﬀects of IMC thatare significant at the 1 percent level. Column (3) of Table 1 illustrates the eﬀects of IMC on theunpaid tax collection rate of corporation taxes and we cannot observe the eﬀects of IMC. This
result is consistent with the fact that IMC covers resident and property taxes but does not covercorporation taxes.
Figure 4 presents the event study results in Equation (2) with 95 percent confidence intervals,
in which the top and bottom panels indicate the results for inhabitant and property taxes,
respectively. In all the panels of Figure 4, the coeﬃcients spike positive and significant after
the introduction of IMC, which is consistent with the DID results. Moreover, prior to theintroduction of IMC, the estimated coeﬃcients are close to zero and almost nonsignificant.
These results suggest the absence of pretreatment diﬀerences in IMC in terms of trends between
the treated and control groups and indicate that the introduction of IMC continually improves
tax enforcement.
These findings indicate that improved tax collection by IMC results in more eﬀective tax
enforcement. Additionally, IMC enhances unpaid tax collection measures on property taxes
more substantially than those on inhabitant taxes. This may be attributed to property taxes being
more likely to be subject to collaborative collection at the inter-municipal, owing to their higher
unpaid tax amount per taxpayer.
12Figure 4: Event study plots: The unpaid tax collection rate

Note: This figure plots the estimation results of the event study analysis and 95% confidence intervals (dottedlines). The horizontal axis indicates years relative to the introduction of IMC. The model controls for municipality
fixed eﬀects and prefecture-by-year fixed eﬀects. Standard errors are clustered at the municipality level.

4.3.2

Robustness

Control variables When the timing of the introduction of IMC is confounded by the geographic
and financial features of the municipality, the estimation results may be biased. For example,
if IMC adoption is biased toward municipalities with certain geographic factors, then this bias
can lead to the timing of IMC implementation, which would aﬀect the outcome variables. In
particular, the financial factor of the municipality may be a confounder in terms of tax collection
via IMC. Therefore, we use i) the population size, the share of the population younger than 15
13

Table 2: DID estimate: Impact of IMC on the unpaid tax collection rate
Inhabitant tax
Property tax
(1)
(2)
(3)
(4)
TaxIMC0.175*** 0.174*** 0.283*** 0.282***[0.048][0.048][0.075][0.075]Observations
R-squared
Municipality FE
Pref*Year FE
Basic characteristic
covariates
Local public finance andadministration covariates

22135
0.568
Yes
Yes

22135
0.568
Yes
Yes

22264
0.551
Yes
Yes

22264
0.551
Yes
Yes

Yes

Yes

Yes

Yes

Yes

Yes

Note: The table shows the results in Equation (1). Basic geographic covariates include the population size, shareof the population size under the age of 15 years, share of the population size over the age of 65 years, share ofsecondary industrial workers among total workers, and share of tertiary industrial workers among total workers.
Local public finance covariates include the financial capability indicator, local government debts, taxable income,number of municipal oﬃcials, and number of workers. Column (1) represents the eﬀect of IMC on the unpaid
tax collection rate on inhabitant tax, controlling for covariates on basic geographic characteristics, and Column (2)additionally controls for covariates on local public finance. Column (3) represents the eﬀect of IMC on the unpaid
tax collection rate on property tax, controlling for covariates on basic geographic characteristics, and Column (4)additionally controls for covariates on local public finance.

years old, the share of the population older than 65 years old, the share of secondary industrial
workers among total workers, and the share of tertiary industrial workers among total workers
as covariates of basic geographic characteristics and ii) the financial capability indicator, local
government debts, taxable income, the number of municipal oﬃcials and the number of workers
as covariates of local public finance and administration. Columns (1) and (3) of Table 2 show
the results of the specification in Equation (1), controlling for basic geographic characteristic
covariates. Columns (2) and (4) of Table 2 show the results of the specification in Equation(1), controlling for both basic geographic characteristics and local public finance covariates.
The estimated coeﬃcients are almost consistent with the results of the baseline analysis without
covariates in Table 1. Furthermore, Figure A.3 in the Online Appendix similarly shows results
consistent with those in Figure 4, thus suggesting that the timing of the introduction of IMC is
not confounded by any covariates.14
Expense item The financial status of municipalities can also be a potential confounding
factor in IMC implementation. For instance, a municipality facing increasing expenditures may
adopt IMC to enhance its tax revenue generation. To rule out this possibility of confounders,
we examine the impact of IMC on expenditures by character. Expenditure by character is local
14In addition, Figure A.4 in the Online Appendix presents a test of covariate balances.

14

government expenditure categorized into personnel, supplies and services, maintenance, andsocial assistance expenditures. Figure 5 shows the impact of IMC on expenditure by character
using Equation (2), where all point estimates are indistinguishable from zero. Moreover, theresults do not show any specific trend prior to IMC adoption, reinforcing the conclusion that
implementing IMC is not influenced by the fiscal conditions of municipalities.
Figure 5: Event study plots: Expenditure item

Note: This figure plots the estimation results of the event study analysis and 95% confidence intervals (dottedlines). The horizontal axis indicates years relative to the introduction of IMC. The model controls for municipality
fixed eﬀects and prefecture-by-year fixed eﬀects. Standard errors are clustered at the municipality level. The top left
panel shows the dynamics of the eﬀect of IMC on personnel expenditure. The top right panel shows the dynamics
of the eﬀect of IMC on supply and service expenditures. The bottom left panel shows the dynamics of the eﬀect
of IMC on maintenance expenditure. The bottom right panel shows the dynamics of the eﬀect of IMC on social
assistance expenditure.

Other DID estimators While two-way fixed eﬀects DID with staggered treatment adoption,such as in Equations (1) and (2), has been widely accepted across numerous studies, recent
15

studies have highlighted the need for strict assumptions, which include homogeneous treatmenteﬀects (de Chaisemartin and D’Haultfoeuille 2020; Callaway and Sant’Anna 2021; GoodmanBacon 2021; Sun and Abraham 2021; Borusyak, Jaravel, and Spiess 2024). For staggered
DID settings, Sun and Abraham (2021) proposes a methodology that combines relative period
indicators with cohort indicators and estimates the full set of cohort-time-specific treatmenteﬀects. Following their technique, we examine the robustness of the event study results. Figure
A.5 shows the event study results obtained using the Sun and Abraham (2021) estimator, whichis consistent with the results in Figure 4, suggesting the robustness of the main analysis.

4.4

Triple-Diﬀerence Results

Our findings thus far suggest that the unpaid tax collection rate in municipalities substantially increases after the introduction of IMC. In this section, we estimate triple-diﬀerence specifications
to demonstrate that the results are robust even under weaker assumptions.
In this specification, we stack the unpaid tax collection rate with the present tax collection
rate, which is not aﬀected by IMC, and use the diﬀerence between these outcome variables as
an additional variation. Therefore, this specification includes dummy variables capturing thetiming of the introduction of IMC, which interact with indicators of two tax collection rates.
The specification is as follows:

Y8,?,C,D =8’

8,g< 1

g
Vg IMC8,?,C,D+

8’

8,g< 1g[g IMC8,?,C,D⇥+ `D,H + UD,8 + d ?,H + Y8,?,H,DD(3).8,?,H,D is the tax collection rate of tax type D (either the unpaid or present tax collectionrate) in municipality 8 of prefecture ? in year H.

D is an indicator variable that equals 1 if .D8 ?His the unpaid tax collection rate and 0 if .28 ?H is the present tax collection rate. `DH and UD8
are tax-type-by-municipality and tax-type-by-time fixed eﬀects, respectively. The parameters ofinterest are [, which captures the eﬀects of IMC on the unpaid tax collection rate relative to thepresent tax collection rate.
In this specification, we can capture the eﬀect of IMC under the assumption that in theabsence of treatment, the relative outcomes of the two tax collection rates follow the same
trend between the treatment and control groups. In other words, it is not necessary to assume
two parallel trends for the two tax collection rates (Olden and Møen 2022). Therefore, thisspecification allows for the introduction of IMC to be correlated with unobserved factors, thus
requiring only the assumption of this relative comparison.

16

Figure 6: Event study plots by the Triple-Diﬀerence: The tax collection rate

Note: This figure plots the estimation results of the event study analysis counterpart of the triple-diﬀerence
specification and 95% confidence intervals (dotted lines). The horizontal axis indicates years relative to theintroduction of the IMC. The model controls for tax-type-by-municipality and tax-type-by-time fixed eﬀects.
Standard errors are clustered at the municipality level.

Figure 6 presents the triple-diﬀerence estimator in Equation (3) with 95 percent confidence
intervals, in which the top and bottom panels indicate the results for the inhabitant and property
taxes, respectively. In all the panels of Figure 6, we observe that the coeﬃcients spike to positiveand significant in the post-treatment periods and that the estimated coeﬃcients are close to zeroprior to the introduction of IMC. These results are consistent with the DID results.

17

5

Heterogeneity

5.1

Inter-municipal organization and municipal oﬃcial levels

In this section, we explore two potential channels, focusing on IMC composition.15 First, IMC
establishes a new jurisdiction, that takes over a part of the tax collection for unpaid taxes withineach municipality. Collaborative tax collection at the IMC organization level increases the
deployment of tax collection oﬃcials on a per-case basis, leading to eﬀective tax enforcement.
Second, training and interaction within IMC may improve the tax enforcement capabilities ofoﬃcials at each municipal level. Therefore, implementing IMC may improve tax enforcement
through the channels at the inter-municipal organization and municipal oﬃcial levels.
To investigate two levels, we focus on IMC composition, particularly the inclusion of municipal oﬃcials. The lack of municipal oﬃcials within IMC implies the absence of interaction
between each local tax oﬃcial within IMC, suggesting that the impact of IMC on tax enforcement is derived solely from collaborative collection at the IMC organization level. Thus, weestimate the heterogeneous eﬀects of IMC on tax enforcement based on its composition with thefollowing specification:

Y8,?,H+1,2 = V1 IMC8,?,H,2 + V2 IMC8,?,H ⇥ Municipal oﬃcial2 + `8 + fH + Y8,?,H,2(4)

where .8,?,H+1,2 is the tax collection rate with a one-period lead. This specification incorporates a lead period of outcome variables, considering that municipal oﬃcials who benefit from
IMC may require some time to enhance their tax enforcement capabilities. Municipal oﬃcial2 is
an indicator variable that equals 1 if municipality 8’s oﬃcial participates in IMC and 0 otherwise.
`8 and f?H are municipality and time fixed eﬀects, respectively.16 The parameter of interest
V2 is the diﬀerential impact of IMC on tax enforcement redbetween the group composed ofmunicipality oﬃcials and the group composed of other than municipality oﬃcials. If there areexternalities through training and interaction within IMC, then the sign of V2 should be positive.
The estimates of Equation (4) for IMC composition are shown in Table 3.17 The coeﬃcients of
the interaction term in Table 3 are positive and statistically significant exclusively in Column (1),which pertains to the inhabitant tax. This result suggests that the tax collection of inhabitant taxes
benefits from the learning and interaction within IMC, resulting in improved tax enforcement.
15See Section 2.1 for more information on the IMC channels.
16While 46 municipalities participate in the IMC without sending any oﬃcials, the majority of municipalities
participated in these collaborations. Therefore, due to the small degree of variation between the treatment groupand the control group within prefectures, we use time fixed eﬀects instead of prefecture-by-time fixed eﬀects in theestimation of Equation (4).
17Table A.2 shows the estimates of Equation (4) for a variable representing IMC composition, which equals 1 forall municipalities participating in the IMC if one or more municipal oﬃcials from those municipalities participate
in the IMC.

18

Table 3: DID estimate: Heterogeneous eﬀects by IMC composition(1)(2)
Inhabitant tax Property tax
TaxIMC ⇥ Municipal oﬃcial
0.184***
0.141[0.062][0.102]TaxIMC-0.0910.244***[0.058][0.098]R-squared
Observations
Municipality FE
Year FE

0.559
20313
Yes
Yes

0.541
20455
Yes
Yes

Note: The table shows the results in Equation (4). The outcome variables in Columns (1) and (2) are the unpaid
collection rate on inhabitant and property taxes, respectively. Clustered standard errors at the municipality levelare given in brackets. ***, **, * represent that the estimates are significantly diﬀerent from zero at levels of 1%,
5%, and 10%, respectively.

In contrast, the coeﬃcients of the interaction on property tax in Column (2) are null. In addition,
the coeﬃcients that do not involve an interaction term are positive and statistically significant,while it is diﬃcult to obtain the exact suggestion from this result because of unrelated taking thelead of the outcome and collaborative tax collection at the IMC level. However, assuming thatthe eﬀect of collaborative collection at the IMC level is constant, this positive eﬀect may imply
that only property taxes benefit from collaborative tax collection at the IMC level.
These findings are consistent with the fact that IMC prioritizes property taxes, which are
more expensive per case, over inhabitant taxes. Property tax is subject to collaborative collection
by IMC, which may increase the unpaid collection rate. In contrast, collecting inhabitant tax isprimarily done at the municipal level, and improving the capability of oﬃcials at each municipal
level may lead to more eﬀective tax collection. Therefore, the eﬀects of training and interaction
at the municipal level are more eﬀective for tax categories where there is room for individualmunicipalities to intervene.
These findings suggest that human resource development is crucial, not just to augmenthuman capital, but for enhancing local tax enforcement. Furthermore, in municipal cooperation,
it may be necessary to consider the eﬀects of interactions within the IMC rather than merely
focusing on scaling operations.

5.2

Impact on tax collection costs

In this section, we examine whether IMC aﬀects the costs of tax collection. While the purposeof this study is to show the eﬀects of enhanced tax enforcement by IMC, it is also true that
additional tax collections may be costly. In the context of IMC, two conflicting mechanisms of19

cost eﬃciency are considered: cost savings from economies of scale and operational eﬃciencies
of administration, and increasing cost due to coordination issues (Bel and Warner 2015; Allers
and de Greef 2018). Additionally, some studies emphasize the importance of population sizein a municipality for cost reduction (Bel and Warner 2015; Ferraresi et al. 2018; Notsu 2024).
In the setting of IMC and tax enforcement, collaborative collection at the inter-municipal level
can impact the costs of tax collection.18 Specifically, this collaboration is likely to target tasks
involving substantial amounts per case, such as property taxes. In Japan, where the population is
declining, the issue of unpaid property tax on vacant houses has become increasingly problematic, and particularly, municipalities with larger populations tend to have more vacant houses.
Therefore, IMC may be more cost saving in these larger municipalities through collaborativecollection eﬀorts at the inter-municipal level.
From a cost perspective, we examine the heterogeneous eﬀects of IMC on tax administrative
costs based on population share. Tax administrative costs include comprehensive costs associated with tax collection, such as personnel expenditures, travel expenditures, demand-related
expenditures, and consignment expenses for creating program systems. We estimate as follows:

Y8,?,H = V1 IMC8,?,H + V2 IMC8,?,H ⇥ pop500008 + V3 IMC8,?,H ⇥ (1pop500008 )+ `8 + d ?,H + Y8,?,H(5)

where .8,?,H is the tax administration costs in municipality 8 of prefecture ? in year H, which
are converted into their logarithmic forms. Tax administrative costs refer to the comprehensive
costs associated with tax collection (Notsu 2024). Pop50000 is a binary dummy variable that
equals 1 if municipality 8 has more than 50,000 inhabitants and 0 otherwise.19 The parametersof interest V2 and V3 are the eﬀects of IMC in municipality 8 on more than 50,000 inhabitants
and the eﬀects of IMC in municipality 8 on fewer than 50,000 inhabitants.
In addition, we consider the population shares relative to the total population within IMC
and estimate as follows.
Y8,?,H = V1 IMC8,?,H + V2 IMC8,?,H ⇥ Share8 + `8 + d ?,H + Y8,?,H(6)

where Share8 is the population share of municipality 8 relative to the total population of
all municipalities engaged in IMC. V2 indicates diﬀerences in the impact of IMC by higher
population share within IMC.
18Tax collection involves personnel, travel, demand-related expenditures, and system expenditures. In particular,
joint collection by IMC is expected to spread out the fixed costs of these expenses and reduce personnel expendituresby improving operational eﬃciency (Notsu 2024). Meanwhile, additional costs may be incurred in coordinating
among municipalities for joint collection.
19We use this binary variable because a population of 50,000 or more is one of the general requirements for a
Japanese city20

Table 4: DID estimate: Tax administrative costs
(1)
(2)
(3)
TaxIMC
0.001
0.029[0.021][0.024]pop50000
0.010[0.026]TaxIMC ⇥ pop50000-0.078***[0.030]TaxIMC ⇥ (1 - pop50000)
0.008[0.021]TaxIMC ⇥ Share-0.222***[0.060]R-squared
Observations
Municipality FE
Year FE

0.880
22523
Yes
Yes

0.880
22523
Yes
Yes

0.880
22523
Yes
Yes

Note: The table shows the eﬀects of IMC on tax administrative costs, where columns 1, 2, and 3 correspond to
Equations (1), (5), and (6), respectively. Clustered standard errors at the municipality level are given in brackets.
***, **, * represent that the estimates are significantly diﬀerent from zero at levels of 1%, 5%, and 10%, respectively.

Table 4 presents the estimation results of heterogeneous eﬀects by population size, wherecolumns (2) and (3) correspond to the estimated Equations (5) and (6), respectively. Column (1)of Table 4 provides the baseline estimate without any interaction with the population, and wecannot observe the eﬀects of IMC on tax administrative costs. In Column (2), only the coeﬃcientsof the interaction term between IMC and a population of more than 50,000 inhabitants indicate
a decrease in tax administrative costs by IMC implementation. Furthermore, in Column (3), thecoeﬃcients of the interaction term between IMC and population share demonstrate the negativeeﬀects of IMC on tax administrative costs, consistent with the results of Column (2) in Table 4.
These results suggest that IMC decreases tax administrative costs in municipalities with larger
populations.
These results indicate that collaborative tax collection at the inter-municipal level does notlead to increased costs of tax collection. Rather, costs are reduced in larger municipalities
with numerous projects subject to inter-municipal collaborative tax collection. Furthermore, asdetailed in subsection 4.3.2, there is no observed increase in costs for other expense items due
to IMC. Those results suggest that IMC could be a rational governmental reform for enhancing
tax enforcement.

21

5.3

Taxpayer complianceIn this section, we examine whether IMC influences taxpayer behavior. Some IMCs advertisethe sale of seized assets as a warning to those with unpaid taxes. These IMC warnings may
increase unpaid tax collection rates by promoting taxpayer compliance rather than by enhancing
administrative tax enforcement capabilities. To explore this, we demonstrate the heterogeneouseﬀects of IMC based on its engagement in advertising, a specification similar to that in Equation(6).
Table A.3 presents the estimation results of the heterogeneous eﬀects based on advertisements. The coeﬃcients of no interaction are almost consistent with the baseline eﬀects in Table
1, and the coeﬃcients of the interaction term between IMC and the presence of advertisements
are null. These results suggest that advertising by IMCs does not significantly aﬀect unpaid tax
collection rates. Furthermore, the findings imply that IMC can close the tax gap by enhancing tax
enforcement on the administrative side, rather than by encouraging compliance on the taxpayer
side.

6

Conclusions

This study examines the eﬀects of enhancing administrative tax enforcement on the tax gap, using
the timing variation in IMC creation across municipalities and unpaid tax collection rates. The
results of the DID analysis reveal that IMC increases unpaid tax collection rates for inhabitantand property taxes by approximately 17 and 28 percent, respectively. Furthermore, we examine
the heterogeneity eﬀects of IMC. First, to examine potential channels, we use data on whether
the IMC is composed of municipal oﬃcials. The results show that the unpaid tax collection
rate for inhabitant taxes increases when the IMC is composed of municipal oﬃcials, while
there is no observed relationship between the composition of IMC and property taxes. Thisfinding suggests that, in the case of inhabitant taxes, training and interaction within IMC leadto more eﬀective tax collection for each municipal oﬃcial, which is consistent with the fact thatproperty taxes are prioritized in collaborative eﬀorts at the inter-municipal organization level.
Second, we estimate the heterogeneous eﬀect of IMC on tax administrative costs by population
size. The analysis does not show any increase in tax administrative costs due to IMC, rather,in municipalities with larger populations, IMC reduces tax administrative costs. These results
suggest that IMC reform to enable enhanced tax enforcement could be a rational governmental
reform compared to a simple reform such as an increase in tax collection resources.
This study has policy implications aimed at increasing revenue. Given limited resources,
improving the tax enforcement capacity of the administration remains challenging. Meanwhile,
we demonstrate that IMC, which integrates and scales tax collection among local governments,
can substantially close the tax gap through enhanced tax enforcement. Moreover, we found no22

disadvantages of IMC, even from a cost perspective. Therefore, these results suggest that it is
crucial to consider the restructuring of the local government framework not only from a cost
perspective but also in terms of revenue.

23

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27

A

Appendix
Figure A.1: Reform of tax collection amount per taxpayer

Note: Trends in the total tax collection amount per taxpayer in Japan from 2013 to 2018. The red line shows thetax collection amount for the inhabitant tax per taxpayer, and the blue line shows the tax collection amount for theproperty tax per taxpayer.

28

Figure A.2: Introduction of IMC in Japan

Note: This map shows the distribution of the introduction of IMC in municipalities. The blue regions represent
the regions implementing IMC as of 2018.

29

Table A.1: Summary statistics for 2007
Variables
MeanSD
Outcome variables
Unpaid tax collection rate
Inhabitant tax
0.22
0.096
Property tax
0.18
0.096
Expenditures by character
Personnel (thousand JPY)
92
47
Supplies and services (thousand JPY)
60
42
Maintenance (thousand JPY)
4.9
6.3
Social assistance (thousand JPY)
41
19
Covariates
Population
73680
218126
Pop. 65 (%)
0.24
0.064
Pop. 15 (%)
0.13
0.023
Primary ind. (%)
0.10
0.11
Secondary ind. (%)
0.27
0.08
Financial indicator
0.64
0.35
Local debt
2037570 8795084
Taxable income
113689 380836
Number of municipal oﬃcials
538
1656
Number of workers
35215
103954
Note: The monetary unit is 1,000 yen (approximately 6.7 dollars at an exchange rate of 150 yen to 1 U.S. dollar).
Tax administrative, personnel, supplies and services, maintenance, and social assistance expenditures are measured
on a per capita basis. Overtime payment is measured per municipal oﬃcial. This summary uses samples as of2007. The first column shows the average of the outcome variables, treatment variables, and covariates. The second
column shows the standard deviation of the outcome variables, treatment variables, and covariates.

30

Figure A.3: Event study plots: Adding Covariates

Note: This figure plots the estimation results of the event study analysis and 95% confidence intervals (dottedlines). The horizontal axis indicates years relative to the introduction of IMC. The model controls for basic
geographic characteristic and local public finance covariates, municipality fixed eﬀects, and prefecture-by-year
fixed eﬀects. Standard errors are clustered at the municipality level.

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Figure A.4: Covariate balance in 2007

Note: This figure provides a test of covariate balance in 2007. I regress the treatment indicators (which equal
1 for municipalities with the introduction of IMC) on all covariates.

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Figure A.5: Event study plots: Sun and Abraham (2021)

Note: This figure plots the estimation results of the event study analysis and 95% confidence intervals (dottedlines), corrected following Sun and Abraham (2021). The horizontal axis indicates years relative to the introductionof IMC. In Sun and Abraham (2021), the full set of cohort-time-specific treatment eﬀects estimated is aggregatedusing weight considering the sample shares of each cohort in the relevant period.

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Table A.2: DID estimate: The case of municipal oﬃcials from all municipalities participatingin IMC(1)(2)
Inhabitant tax Property tax
TaxIMC ⇥ Municipal oﬃcial
0.121**
0.080[0.047][0.059]TaxIMC-0.0180.178***[0.042][0.050]R-squared
Observations
Municipality FE
Year FE

0.559
20313
Yes
Yes

0.541
20455
Yes
Yes

Note: The table shows the results in Equation (4). The outcome variables in Columns (1) and (2) are the unpaid
collection rate on inhabitant and property taxes, respectively. Clustered standard errors at the municipality levelare given in brackets. ***, **, * represent that the estimates are significantly diﬀerent from zero at the levels of
1%, 5%, and 10%, respectively.

Table A.3: DID estimate: Heterogeneous eﬀects by IMC advertising(1)(2)
Inhabitant tax Property tax
TaxIMC ⇥ Warning
0.049-0.038[0.084][0.133]TaxIMC
0.162***
0.283***[0.052][0.082]R-squared
Observations
Municipality FE
Year FE

0.559
20313
Yes
Yes

0.541
20455
Yes
Yes

Note: The table shows the results in Equation (4). The outcome variables in Columns (1) and (2) are the unpaid
collection rate on inhabitant and property taxes, respectively. Clustered standard errors at the municipality levelare given in brackets. ***, **, * represent that the estimates are significantly diﬀerent from zero at the levels of
1%, 5%, and 10%, respectively.

34