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Survey on the Shadow Economy and Undeclared Work in OECD Countries. (2011). Schneider, Friedrich ; Feld, Lars P..
In: Chapters.
RePEc:elg:eechap:13432_2.

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  1. On Estimating the Size of the Shadow Economy. (2017). Kirchgassner, Gebhard.
    In: German Economic Review.
    RePEc:bla:germec:v:18:y:2017:i:1:p:99-111.

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  2. On Estimating the Size of the Shadow Economy. (2016). Kirchgässner, Gebhard ; Kirchgassner, Gebhard.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2016:03.

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  3. On Estimating the Size of the Shadow Economy. (2016). Kirchgässner, Gebhard ; Kirchgassner, Gebhard.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_5753.

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  1. 2. The assumption on independence between structural disturbance zt, and measurement errors the measurement errors et could be considered as too restrictive, when mainly using economic dataset and, consequently, espoused to question the validity of this approach. Hayduk (1987, p. 193) explains it ‘is purely a matter of arbitrary convention ’ for SEM analysis. Dell’Anno (2003) in the context MIMIC model presents a reparameterization of the MIMIC able to test the assumption on independence between structural disturbance zt, and measurement errors et.
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  2. 3. A further criticism is pointed out by Dell’Anno (2003). When using the MIMIC approach he finds that there is a frequent possibility that an indefinite covariance matrix is encountered in the estimation procedure.
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  3. 3. In the standard MIMIC model the measurement errors are assumed to be independent of each other, but this restriction could be relaxed (Stapleton, 1978, p. 53).
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  4. 4. Another criticism of the reliability of the MIMIC estimates of shadow economy is related to the benchmark method (Breusch 2005a, b). This criticism has its origin in the complications researchers face, when he or she wants to convert the index of shadow economy (estimated by the MIMIC model) into cardinal values. This is not an easy task, as the latent variable and its unit measure are not observed. The model just provides a set of estimated coefficients from which one can calculate an index which shows the dynamics of the unobserved factor.
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  5. 4. There are several rules of thumb about the sample size in the literature (Garson, 2005): the sample size should be at least 50 observations or have more than eight times the observations than the number of independent variables in the model. Another one, based on Stevens (1996), is to have at least 15 observations per measured variable or indicator.
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  6. 5. Compare, for example, the criticism by Helberger and Knepel (1988) with respect to the pioneering work of Frey and Weck-Hannemann (1984).
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  7. 6. Compare the studies cited in Section 2.4. 7. In Dell’Anno and Schneider (2009, pp. 110–130), four different benchmarking strategies are discussed.
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  8. A further advantage of the MIMIC approach has been stressed by Schneider and Enste (2000a, b), who emphasize that the MIMIC approach leads to some progress in the estimation techniques of underground economy, because this methodology allows a wide flexibility in its application, therefore it is potentially superior over all other estimation methods.
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  9. According to Bollen and Long (1993), this problem arises when the data contain too little information, like small sample size, too few indicator variables, small factor loadings, missing values and so forth.
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  38. Disadvantages Besides advantages there are, of course, disadvantages, and the following six ones are shown: 1. When estimating the shadow economy using the MIMIC model approach the most common objection concerns the meaning of the latent variable (Helberger and Knepel, 1988; Giles and Tedds, 2002; Smith, 2002; Dell’Anno, 2003), because the MIMIC approach is largely a confirmatory rather than exploratory technique. This means a researcher is more likely to determine whether a certain model is valid, rather than to ‘find’ a suitable model. Therefore, it is possible that the theoretical construct ‘shadow economy’ could include other potential definitions (traditional crime activities, DIY and so forth). This criticism, which is probably the most common in literature, remains difficult to overcome as it goes back to the theoretical assumptions behind the choice of variables and empirical limitation on the availability of data.
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  105. M2678 - SCHNEIDER TEXT.indd 123 M2678 - SCHNEIDER TEXT.indd 123 27/07/2011 16:16 27/07/2011 16:16 Friedrich Schneider - 9781848443358 Downloaded from Elgar Online at 10/06/2016 03:06:09PM via CitEc (NOT FOR DISTRIBUTION, SHARING or POSTING) Handbook on the shadow economy Schneider, F. (1997), The shadow economies of Western Europe, Economic Affairs, 17, 42–48.
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  106. M2678 - SCHNEIDER TEXT.indd 128 M2678 - SCHNEIDER TEXT.indd 128 27/07/2011 16:16 27/07/2011 16:16 Friedrich Schneider - 9781848443358 Downloaded from Elgar Online at 10/06/2016 03:06:09PM via CitEc (NOT FOR DISTRIBUTION, SHARING or POSTING) Survey on the shadow economy in OECD countries 129 2. Another objection is expressed by Helberger and Knepel (1988). They argue that the MIMIC estimations lead to unstable estimated coefficients with respect to changes in the sample size and with respect to alternative model specifications. As Dell’Anno (2003) shows, instability disappears asymptotically as the sample size grows large and if data are stationary and normally distributed.

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  113. Moreover, it is quite flexible, allowing one to vary the choice of causal and indicator variables according to the particular features of the economy under study, the period in question, and the availability of data. Again, following Giles and Tedds (2002), the MIMIC model leads to a formal estimation and to testing procedures, such as those based on the method of MLE. These procedures are well known and are generally ‘optimal’, if the sample is sufficiently large.
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  114. Mummert, A. and F. Schneider (2001), The German shadow economy: parted in a United Germany? Finanzarchiv, 58, 260–285.

  115. NOTES 1. This appendix closely follows Dell’Anno and Schneider (2009, pp. 110–130).
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  124. Schneider, F. (1986), Estimating the size of the Danish shadow economy using the currency demand approach: an attempt. Scandinavian Journal of Economics, 88, 643–668.

  125. Schneider, F. (1994a), Can the shadow economy be reduced through major tax reforms? An empirical investigation for Austria. Supplement to Public Finance/ Finances Publiques, 49, 137–152.

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  131. Schneider, F. (2004), Einige Volkswirtschaftliche Überlegungen über die Interaktionen zwischen der Schattenwirtschaft und der offiziellen Wirtschaft. In K. Bizer, A. Falk and J. Lange (eds), Am Staat vorbei: Transparenz, Fairness und Partizipation kontra Steuerhinterziehung. Berlin: Duncker & Humblot, pp.29–45.

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  133. Schneider, F. (2006), Shadow economies and corruption all over the world: what do we really know? Discussion paper. Universität Linz: Institut für Volkswirtschaftslehre.

  134. Schneider, F. (2009), Size and development of the shadow economy in Germany, Austria and other OECD countries: some preliminary findings. Revue Economique, 60, 1079–1116.

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  44. The Learning Path of the Hidden Economy: The Tax Burden and Tax Evasion in New Zealand. (1999). Giles, David ; Caragata, Patrick J..
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  45. Understanding Tax Evasion Dynamics. (1999). Hines, James ; Engel, Eduardo ; Jr., .
    In: NBER Working Papers.
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  46. Decomposing Revenue Effects of Tax Evasion, Base Broadening and Tax Rate Reduction. (1998). Gang, Ira.
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  47. A General Model of the Behavioral Response to Taxation. (1998). Slemrod, Joel.
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  48. Tax Arbitrage and Labor Supply. (1998). Persson, Mats ; Agell, Jonas.
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  49. Understanding Tax Evasion Dynamics. (1998). Hines, James ; Engel, Eduardo.
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  50. Tax evasion in a semi-decentralised tax administration. (). Alejandro Estelle-Moré, .
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