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Non-compliance notifications and taxpayer strategic behavior: evidence from Ecuador

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This paper examines the effect of enforcement on taxpayer behavior using administrative data from Ecuador. To overcome confounding factors, a regression discontinuity design that exploits a discrete increase in the probability of receiving a non-compliance notification is used. Results indicate that the notification significantly increases reported taxes but does not affect tax revenues. The evidence suggests that refiling explains this situation. Additional findings indicate that this intervention also increases taxes reported in the year following it and that some taxpayers strategically attempt to evade taxes while trying to avoid being notified. Collectively, these findings suggest that continuous monitoring and limiting refiling might reduce tax evasion, especially in developing countries.

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Data availability

This research was implemented using proprietary data provided by the Ecuadorian Internal Revenue Service (Servicio de Rentas Internas—SRI). Independent researchers can obtain the data by writing a formal request directed to the General Director of the SRI.

Code availability

Replication Stata Do-files are fully available for researchers.


  1. Papers that study the persistence of interventions include Advani et al. (2017), Boning et al. (2018), DeBacker et al. (2018), and Kleven et al. (2011)

  2. Omer and Yetman (2007) and Neuman et al. (2015) use internal inconsistencies to estimate tax misreporting in nonprofit organizations.

  3. Individuals are obligated to keep accounting records if they have businesses with yearly revenues greater than $100,000, or yearly costs and expenses greater than $80,000, or begin economic activities with a capital of at least $60,000.

  4. There are some exemptions to this formula for financial institutions, agricultural businesses, leasing companies, and new businesses, among others.

  5. Income is withheld when a taxpayer sells a product or service to a special taxpayer, who are public institutions or companies assigned this status by SRI. The percentage of income withheld depends on the economic activity.

  6. All the calculations of compliance were produced by the SRI.

  7. These estimations are available upon request.

  8. Since 2000, the American dollar is the official currency in Ecuador.

  9. SRI provided summary statistics for the population of firms and individually owned businesses obligated to keep accounting records separately. I use that information to estimate t-tests for the differences in means and confidence intervals of quantile regressions with no independent variables for the difference in medians.

  10. Estimations in which the bandwidths selected minimize the coverage error (CE) instead of the MSE bring about very similar results that are available upon request. See Calonico et al. (2019) for details.

  11. The statistic found is equal to 0.16, and it is not significant (t-stat of 1.16).

  12. Special taxpayers are those required to withhold taxes from other taxpayers.

  13. Very comprehensive literature reviews on the determinants of tax compliance can be found in Alm (2019), Slemrod (2019), and Torgler (2007).

  14. The width of the bin used to calculate the local averages is 0.05 standard deviations. Similar plots were obtained when using different widths and degrees of the polynomial.

  15. The main reason for attrition is that taxpayers stopped economic activities.

  16. Following Lindo et al. (2010), in any bootstrap replication in which the estimated change in the probability of attrition is negative, taxpayers with the highest (lowest) reported taxes from the group to the right of the cut-off are dropped when estimating the lower (upper) bound.

  17. The variables used for the predictions are those in the summary statistics of Table 3 and province fixed effects.

  18. I follow Ahrens et al. (2020) and use the lassopack in Stata to implement the rlassologit command and estimate a regularized logistic regression with rigorous penalization.

  19. Similar results are obtained if the indicators take the value of one if the prediction is greater than 0.5.

  20. I use the Stata package rddsga developed in Carril et al. (2017). The variables used for the predictions are those in the summary statistics of Table 3.

  21. According to the Ecuadorian Law, the SRI can review tax declarations several years after they are filed, so likely many of the taxpayers that refiled more than once to evade taxes were eventually notified again. That additional process is endogenous and it is not analyzed in this paper, since its main goal is to study effect of the exogenous variation created by the notification on taxpayer’s behavior.

  22. The authors derived this term from the First World War: troops under enemy fire hid in craters of recent explosions because they believed it to be very unlikely that two bombs will fall exactly in the same spot in a short period of time.


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I would like to thank the Ecuadorian Internal Revenue Service (Servicio de Rentas Internas-SRI) and the Center of Fiscal Studies of Ecuador (Centro de Estudios Fiscales del Ecuador) for their support and assistance. In particular, the access granted by the SRI to its anonymous databases and statistics was key in the realization of this project. I am especially indebted to César Cueva, Diana Arias, and Rolando Mantilla. I would also like to thank Mark Hoekstra, Andrew Rettenmaier, Jonathan Meer, Jason Lindo, Lauren Rhodes, and Paul Carrillo for their advice and suggestions. Thanks also go to workshop participants at the Center of Fiscal Studies of Ecuador and the Department of Economics at Texas A&M University, and anonymous referees for helpful comments and suggestions. The results presented in this paper do not reflect the opinions of the aforementioned organizations. Any errors are my own.


No funding was received to assist with the preparation of this manuscript.

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Correspondence to Gonzalo E. Sánchez.

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An earlier version of this paper was circulating under the name: The Impact of Low-Cost Intervention on Tax Compliance: Regression Discontinuity Evidence.



See Fig. 14 and Tables 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24.

Fig. 14
figure 14

ITA timeline (2010–2011)

Table 9 Comparison of sample and population means and medians (US$ in thousands)—2009
Table 10 Identification test: discontinuities in covariates
Table 11 RDD estimates of the discontinuity in the probability of receiving the tax notification (first stage)
Table 12 RDD estimates of the effect (LATE) of the tax notification on the probability of perceived compliance
Table 13 RDD estimates of the effect (LATE) of the tax notification on reported ITA 2010—US$
Table 14 RDD estimates of the effect (LATE) of the tax notification on prepaid ITA (2010)—US$
Table 15 RDD estimates of the effect (LATE) of the tax notification on collected taxes—US$ (2010 RIT)
Table 16 RDD estimates of the effect (LATE) of the tax notification on reported IT 2010—US$
Table 17 RDD estimates of the effect (LATE) of the tax notification on reported ITA 2010—US$ (ITA is RIT)
Table 18 RDD estimates of the effect (LATE) of the tax notification on reported ITA 2010—US$ (IT is RIT)
Table 19 RDD estimates of the effect (LATE) of the tax notification on the probability of refiling more than once
Table 20 RDD estimates of the effect (LATE) of the tax notification on the probability of refiling more than once (ITA is RIT)
Table 21 RDD estimates of the effect (LATE) of the tax notification on the probability of refiling more than once (IT is RIT)
Table 22 RDD estimates of the persistence of the effect (LATE) of the tax notification
Table 23 RDD estimates of the effect (LATE) of the tax notification on the probability of attrition and on reported taxes with bounds analysis
Table 24 RDD estimates of the effect (LATE) of the tax notification conditional on which tax is the RIT: reported ITA 2010 and refiling more than once

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Sánchez, G.E. Non-compliance notifications and taxpayer strategic behavior: evidence from Ecuador. Int Tax Public Finance 29, 627–666 (2022).

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