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Higher Taxes, More Evasion? Evidence from Border Differentials in TV License Fees. (2015). Traxler, Christian ; Sausgruber, Rupert ; Fellner-Röhling, Gerlinde ; Berger, Melissa.
In: CESifo Working Paper Series.
RePEc:ces:ceswps:_5195.

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  1. Earthquake Hazard and Civic Capital. (2021). Puca, Marcello ; Plevani, Giacomo ; Buonanno, Paolo.
    In: CSEF Working Papers.
    RePEc:sef:csefwp:612.

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  2. The incidence of VAT evasion. (2020). Gomtsyan, David ; Asatryan, Zareh.
    In: ZEW Discussion Papers.
    RePEc:zbw:zewdip:20027.

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  3. The Incidence of VAT Evasion. (2020). Gomtsyan, David ; Asatryan, Zareh.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_8666.

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  4. A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years. (2020). Villamizar-Villegas, mauricio ; Ruiz-Sanchez, Maria Alejandra ; Pinzon-Puerto, Freddy A.
    In: Borradores de Economia.
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  5. What Motivates Tax Compliance. (2019). Alm, James.
    In: Working Papers.
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  6. Observing Economic Growth in Unrecognized States with Nighttime Light. (2019). Kudamatsu, Masayuki.
    In: OSIPP Discussion Paper.
    RePEc:osp:wpaper:19e002.

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  7. Will destination-based taxes be fully exploited when available? An application to the U.S. commodity tax system. (2019). Mardan, Mohammed ; Agrawal, David R.
    In: Journal of Public Economics.
    RePEc:eee:pubeco:v:169:y:2019:i:c:p:128-143.

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  8. Tax evasion and religiosity in the Muslim world: the significance of Shariah regulation. (2018). Nurunnabi, Mohammad.
    In: Quality & Quantity: International Journal of Methodology.
    RePEc:spr:qualqt:v:52:y:2018:i:1:d:10.1007_s11135-017-0471-1.

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  9. Will Destination-Based Taxes be Fully Exploited when Available? An Application to the U.S. Commodity Tax System. (2018). Mardan, Mohammed ; Agrawal, David.
    In: CESifo Working Paper Series.
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  10. Follow-the-leader? Measuring the internalisation of law. (2017). Swanson, Timothy ; Panzone, Luca ; Larcom, Shaun.
    In: CIES Research Paper series.
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  11. Higher taxes, more evasion? Evidence from border differentials in TV license fees. (2016). Traxler, Christian ; Sausgruber, Rupert ; Fellner-Röhling, Gerlinde ; Fellner-Rohling, Gerlinde ; Berger, Melissa.
    In: Journal of Public Economics.
    RePEc:eee:pubeco:v:135:y:2016:i:c:p:74-86.

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  12. Compliance Behavior in Networks: Evidence from a Field Experiment. (2015). Traxler, Christian ; Mengel, Friederike ; Drago, Francesco.
    In: CSEF Working Papers.
    RePEc:sef:csefwp:419.

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  13. Compliance Behavior in Networks: Evidence from a Field Experiment. (2015). Traxler, Christian ; Mengel, Friederike ; Drago, Francesco.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp9443.

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  14. State Tax Differentials, Cross-Border Commuting, and Commuting Times in Multi-State Metropolitan Areas. (2014). Hoyt, William ; Agrawal, David.
    In: CESifo Working Paper Series.
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References

References cited by this document

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  9. Appendix Appendix A. Data (A1) Data sources and summary statistics We compiled municipality data and regional characteristics from various data sources. Fee Information Service (FIS) provided us with data on TV license fees and state taxes, the number of registered households and enforcement activities during 2005. As described in the main text, the evasion rate is given by the ratio of non-registered households to the total number of households (see Section 2).
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  22. Hi, the number of households in 2005 is calculated by inflating the 2001 census data on households by the 2001-2005 population growth in each municipality. The annual fees are the total fees due in 2005 in nominal Euro values. The variable includes federal and state taxes. The enforcement rate is computed as the ratio of enforced registrations generated by door-to-door controls of FIS’ enforcement division relative to the total number of households in each municipality.
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  38. Yitzhaki, S. (1974). A note on ‘Income Tax Evasion: A Theoretical Analysis’. Journal of Public Economics 3(2), 201–202. Tables and Figures Table 1: Basic Summary Statistics Variable Mean S.D. Evasion Rate 0.045 0.077 Enforcement Rate 0.012 0.025 Annual Fees 238.122 19.916 Households (Hi) 1,521 5,802 Labor Income 30,496 3,274 Distance (minutes) 40.980 24.408 Notes: The table reports descriptive statistics for the evasion rate, annual license fees (nominal Euro values), the enforcement rate, and selected municipality characteristics (see Appendix A1). Number of observations: 2,380. Table 2: Cross-Sectional Estimation Coefficients Clustered SEs Robust SEs log Fees 0.129 [0.087] [0.022] Enforcement −0.273 [0.169] [0.072] log Income −0.017 [0.034] [0.028] Selfemployed 0.215 [0.084] [0.046] Observations 2,378 R2 0.298 Notes: Results from OLS regressions of equation (5). Additional control variables are included.
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