The Shadow Economy in Colombia: Size and Effects on Economic Growth

Friedrich Schneider; Bettina Hametner

doi:10.1515/peps-2013-0059

Article

The Shadow Economy in Colombia: Size and Effects on Economic Growth

Published/Copyright: March 18, 2014

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From the journal Peace Economics, Peace Science and Public Policy Volume 20 Issue 2

Abstract

Using the currency demand approach, size and development of Colombia’s shadow economy are estimated over the period from 1980 to 2012. The results show a great extent of shadow economic activity varying over time between 27 and 56% of GDP. The most important factors driving the shadow economy are indirect taxation and unemployment. Analyzing the interaction between shadow and official economy, the shadow economy has a negative effect on the official one. Average growth of real per capita GDP is 1.86% between 1980 and 2012, without shadow economy it would have been higher around 0.12 percentage points on average.

Keywords: Colombian shadow economy; currency demand method; taxation; unemployment; interaction between the shadow and official economy

JEL Code: 017; 05; D78; H2; H11; H26

Corresponding author: Friedrich Schneider, Department of Economics, Johannes Kepler University Linz, Altenberger Straße 69, A-4040 Linz/Austria, Phone: 0043-732-2468-8210, Fax: 0043-732-2468-8209, E-mail: friedrich.schneider@jku.at, http://www.econ.jku.at/Schneider

¹
For further studies about Colombia, see the recently published special issue “Conflict, Crime and Violence in Colombia” of the journal “Peace Economics, Peace Science and Public Policy” (Caruso and Vargas (eds.) 2014).
²
This definition is used, for example, by Feige (1989, 1994), Schneider (1994a, 2003, 2005), and Frey and Pommerehne (1984). Do-it-yourself activities are not included.
³
This definition is taken from Dell’Anno (2003), Dell’Anno and Schneider (2004) and Feige (1989). See also Thomas (1999) and Fleming, Roman, and Farrell (2000).
⁴
The United Nations together with the European Commission elaborated a framework classifying economic activity non-covered by national accounts systems in 7 types that can be summarized in 4 main groups namely not registered, not surveyed, misreporting and others. For a detailed description of the framework consult United Nations (2008), page 4, Box 1.
⁵
Compare also the excellent discussion of the definition of the shadow economy in Pedersen (2003, 13–19), who uses a similar definition.
⁶
It has to be mentioned at this point that especially for the case of Colombia it would of course be interesting to include illegal economic activities in the calculations of the size of the shadow economy. Unfortunately, due to a lack of reliable data in this respect the authors needed to refrain from basing their estimations of the size of the shadow economy on this broader definition.
⁷
See Enste in Bajada and Schneider (2005), Schneider (2005, 2006), Alm (1996).
⁸
However, even major tax reforms with major tax rate deductions may not lead to a substancial decrease of the shadow economy (see results for Austria in Schneider (1994b, 1998b)) Such reforms may stabilize the size of the shadow economy and avoid a further increase. Social networks and personal relationships, high profits form irregular activities, and associated investments in real and human capital prevent people from going back to the official economy (for Canada, see Spiro 1993).
⁹
The great importance of tax and social security contribution burdens on the size and development of the shadow economy has also been shown in numerous empirical studies, among others by Schneider (1994b, 2001, 2005) and Johnson, Kaufmann, and Zoido-Lobatón (1998a, b).
¹⁰
Compare Besozzi (2001), Naylor (1996) cited in Besozzi (2001, 12), Lubell (1991) and Schneider (2005).
¹¹
A number of papers dealing with the economic and social situation in Colombia have recently been published in the special issue “Conflict, Crime and Violence in Colombia” of the journal “Peace Economics, Peace Science and Public Policy” edited by Raul Caruso and Juan F. Vargas (Caruso and Vargas (eds.) 2014).
¹²
For a more detailed study about insecurity and crime in Colombia see Romero (2014).
¹³
For more details about gold mining and the problems involved with it see Idrobo, Mejia, and Tribin (2014).
¹⁴
Data source: Departamento Administrativo Nacional de Estadística DANE (July 2013).
¹⁵
Data source: Departamento Administrativo Nacional de Estadística DANE (July 2013).
¹⁶
Ministerio de Hacienda y Crédito Público.
¹⁷
Oficina de Investigaciones Socio Económicas y Legales Ltda., Bogotá.
¹⁸
Arango, Misas, and Lopez (2005). The surveys only deal with “traditional” informal activities, illegal economic activities like drug trafficking are excluded.
¹⁹
Additionally these measures can also make a contribution to the reduction of violence, see Cotte Poveda (2011).
²⁰
Steiner (1998).
²¹
Echeverry (2013).
²²
United Nations (2008).
²³
For a detailed description and criticism on the currency-demand method see Appendix A.
²⁴
Due to the lack of available results from personal interviews and the impossibility of doing surveys ourselves, micro approaches for estimating the size of the shadow economy could not be used. We could not apply discrepancy methods either as we had no access to the necessary data. Physical input approaches have not been considered as they did not seem a good approach to describe the Colombian shadow economy where a large part of the informal activity is trade in simple goods whose production and distribution only need marginal input of electricity.
²⁵
Another tax which certainly distorts the amount of cash is the financial transaction tax which exists in Colombia since the deep crisis of the end of the century. Botero (2013) shows, that the presence of this tax has created distortions in the demand for cash.
²⁶
For a detailed description of the variables used see Appendix B, Table 7.
²⁷
For test results detecting autocorrelations see Table 3.
²⁸
A first attempt to show that the currency demand function may be biased has been undertaken in a study by Ardizzi et al. (2014) for Italy.
²⁹
For a detailed discussion on possible corrections with respect to the restrictions mentioned see Ahumada, Alvaredo, and Canavese (2007)
³⁰
Without this correction the simulations would overestimate the size of the shadow economy: The average size of the shadow economy between 1980 and 2012 is 43% for the models where the adjustment has been done whereas the average without correction would be 47%.
³¹
We do not include the estimation results based on model variant 1 including drug business as the outcomes do not differ a lot from the ones resulting from the original model 1 (cash demand per capita).
³²
Arango, Misas and López who carried out the cited study for the Colombian Central Bank estimated a MIMIC model. As simulations of the size of the shadow economy based on MIMIC models only give index numbers a second, absolute estimation for the size of the shadow economy for at least one point in time is needed to convert the indices in absolute numbers. In this case, the figures fall back on an estimate based on the currency demand method by Schneider (2002) giving a size of the Colombian shadow economy of 39% of GDP for 1999/2000.
³³
We are thankful to an anonymous referee, who pointed out that we should make a comparison of our estimation of the size of the Colombian shadow economy with other Central and South American countries. However, we did not find studies for other South and Middle American countries using the currency demand approach. Hence, we refer to the MIMIC estimation of Schneider (2007). Due to this, only a rough comparison between our size and development of the shadow economy within the currency demand approach can be done with other Middle and South American countries.
³⁴
As the GDP per capita enters in the regression model for estimating the size of the shadow economy and then also appears in the model for calculating its influence on economic growth there is some risk of simultaneity. However, due to the fact that the size of the shadow economy does not directly depend on GDP but needs to be calculated through a simulation process, we do not deal with pure simultaneous equations here.
³⁵
In this point all our models, also the 2 variations including drug business, are consistent, showing a statistically highly significant negative influence of the shadow economy on real GDP growth.
³⁶
For a further discussion of integration strategies see Tokman (2001) and Lubell (1991).
³⁷
See for example O’Grady (2006) for a discussion of continuous drawbacks in taxation policy and Gracia and Urdinola (2000) for a debate on changes in labour market regulations.
³⁸
For a detailed explanation of the two-pillar strategy consult Schneider and Enste (2002).
³⁹
See Karmann (1986, 1990), Schneider (1997, 1998a), Johnson, Kaufmann, and Zoido-Lobatón (1998a), and Williams and Windebank (1995).
⁴⁰
See Thomas (1992, 1999), Feige (1986), Pozo (1996), Pedersen (2003) and Ahumada, Alvaredo, and Canavese (2006).
⁴¹
One (weak) justification for the only use of the tax variable is that this variable has by far the strongest impact on the size of the shadow economy in the studies known to the authors. The only exception is the study by Frey and Weck-Hannemann (1984) where the variable “tax immorality” has a quantitatively larger and statistically stronger influence than the direct tax share in the model approach. In the study of Pommerehne and Schneider (1985) for the US, besides various tax measures, data for regulation, tax immorality, minimum wage rates are available, the tax variable has a dominating influence and contributes roughly 60–70% to the size of the shadow economy. See also Zilberfarb (1986).
⁴²
Another study by Tanzi (1982, esp. 110–113) explicitely deals with this criticism. A very careful investigation of the amount of US dollars used abroad and US currency used in the shadow economy and for “classical” crime activities has been undertaken by Rogoff (1998), who concludes that large denomination bills are a major driving force for the growth of the shadow economy and classical crime activities, due largely to reduced transactions costs.
⁴³
However in studies for European countries Kirchgässner (1983, 1984) and Schneider (1986) conclude that the estimation results for Germany, Denmark, Norway and Sweden are quite robust when using the currency demand method. Hill and Kabir (1996) find for Canada that the rise of the shadow economy varies with respect to the tax variable used; they conclude “when the theoretically best tax rates are selected and a range of plausible velocity values is used, this method estimates underground economic growth between 1964 and 1995 at between 3% and 11% of GDP.” (p. 1553).
⁴⁴
Ahumada, Alvaredo, and Canavese (2007).

Appendix

Appendix A: Currency demand approach

The currency demand approach is one of the most commonly used approaches. It has been applied to many OECD countries³⁹ but has nevertheless been criticized on various grounds.⁴⁰ The most commonly raised objections to this method are: (1) Not all transactions in the shadow economy are paid in cash. Isachsen and Strom (1985) used the survey method to find out that in Norway, in 1980, roughly 80% of all transactions in the hidden sector were paid in cash. The size of the total shadow economy (including barter) may thus be even larger than previously estimated. (2) Most studies consider only one particular factor, the tax burden, as a cause of the shadow economy. But others (such as the impact of regulation, taxpayers’ attitudes toward the state, tax morality and so on) are not considered, because reliable data for most countries is not available. If, as seems likely, these other factors also have an impact on the extent of the hidden economy, it might again be higher than reported in most studies.⁴¹ (3) As discussed by Garcia (1978), Park (1979) and Feige (1996), increases in currency demand deposits are due largely to a slowdown in demand deposits rather than to an increase in currency caused by activities in the shadow economy, at least in the case of the US. (4) Blades (1982) and Feige (1986, 1996) criticize Tanzi’s studies on the grounds that the US dollar is used as an international currency so that Tanzi should have considered (and controlled for) the presence of US dollars, which are used as an international currency and held in cash abroad.⁴² Frey and Pommerehne (1984) and Thomas (1986, 1992, 1999) claim that Tanzi’s parameter estimates are not very stable.⁴³ (5) Most studies assume the same velocity of money in official and shadow economies. As argued by Hill and Kabir (1996) for Canada and by Klovland (1984) for the Scandinavian countries, there is considerable uncertainty about the velocity of money in the official economy, and the velocity of money in the hidden sector is even more difficult to estimate. Without knowledge about the velocity of currency in the shadow economy, one has to accept the assumption of an equal money velocity in both sectors. (6) Ahumada, Alvaredo, and Canavese (2006) show that the currency approach together with the assumption of equal income velocity of money in the reported and the hidden transaction is only correct if the income elasticity is 1 and suggest a correction method for that cases where the income elasticity does not equal 1.⁴⁴ (7) Finally, the assumption of no shadow economy in a base year is open to criticism. Relaxing this assumption would again imply an upward adjustment of the size of the shadow economy.

Appendix B: Detailed description of the used variables

See Table 7.

Table 7

Description of the variables used in the discussed regression models.

Variable		Obs	Mean	Std. Dev.	Min	Max	Source
Name	Label
CDC	Currency demand per capita in COP (Colombian Pesos)	33	163,279.40	198,866.80	1,759.71	1,759.71	[2, 5]
CD	Ratio of cash holdings to checkable deposits	33	0.6604	0.2289	0.3944	1.0005	[2, 5], o.c.
GDPPC	Real GDP per capita in COP, Base Year: 2005	33	7,136.59	1,330.59	5,379.49	10,106.59	[4, 8]
IRD	Yearly average interest rate on deposits at 90 days sight	33	0.2268	0.1302	0.0368	0.4006	[2, 5]
ER	Yearly average market exchange rate COP/USD	33	1219.006	926.8126	47.57167	2,875.05	[2]
TY	Average effective net tax rate on income	33	0.2679	0.0464	0.2021	0.3255	[1, 4, 9], o.c.
TC	Average effective net tax rate on consumption	33	0.1410	0.0256	0.0932	0.1748	[1, 4, 9], o.c.
TGDP	Total tax revenues in % of GDP	33	0.0733	0.0269	0.0333	0.1221	[2, 5, 7]
UNEMP	Unemployment rate	33	0.1139	0.0239	0.0700	0.1670	[3, 4]
EPE	Real expenditures for public employees in % of GDP	33	0.0939	0.0305	0.0496	0.1409	[2, 4, 5]
LAW	New laws enforced per year	33	726	195	123	1186	[2]
GGDPPC	Yearly growth of real GDP per capita in %	33	0.0186	0.0227	–0.0541	0.0563	[4, 8]
CPI	Consumer price index, base: Dec. 1998	33	85.05	74.56	2.25	213.16	[2, 8]
DI	Real capital investment, Mio COP, Base Year: 1998	33	37,592.45	14,945.78	19,922.64	72,440.20	[5, 8]
FDI	Foreign direct investment, Mio USD	33	3,467.04	4,191.54	157.14	15,822.94	[6]
SPC	Average years of schooling per capita	33	6.77	0.92	5.25	8.09	[5, 10]
LPA	Participation rate on labour market	33	0.5894	0.0291	0.5220	0.6366	[3, 4, 11]
POP	Colombian total population, 1.000 Pers.	33	3.770E+04	5.574E+03	2.845E+04	4.660E+04	[5, 8]
PCGDP	Public spending on consumption in % of nominal GDP	33	0.1297	0.0374	0.0826	0.1838	[4, 5], o.c.
ACC	Area used for coca cultivation (hectares)	33	60.906	42.765	1.400	166.875	[1, 12]
SECDC	Size of shadow economy in % of real GDP (estimation results model 1)	33	0.4454	0.0511	0.3581	0.5646	o.c.
SECD	Size of shadow economy in % of real GDP (estimation results model 2)	33	0.4177	0.0721	0.2729	0.5358	o.c.

Souces: see numbers in listing of empirical sources; o.c. = own calculations.

Appendix C: Comparing the Colombian shadow economy with other Middle and South American countries

See Table 8.

Table 8

The size of the shadow economy in 21 central and South American Countries¹⁾ (in % of official GDP).

No.	Country	Shadow Economy using the MIMIC and Currency Demand Method
		1999/2000	2001/2002	2002/2003	2003/2004	2004/2005
1	Argentina	25.4	27.1	28.9	28.6	27.2
2	Bolivia	67.1	68.1	68.3	68.0	67.2
3	Brazil	39.8	40.9	42.3	42.6	41.8
4	Chile	19.8	20.3	20.9	20.3	19.4
5	Colombia	39.1	41.3	43.4	43.0	42.7
6	Costa Rica	26.2	27.0	27.8	27.1	26.3
7	Dominican Republic	32.1	33.4	34.1	34.4	34.8
8	Ecuador	34.4	35.1	36.7	36.1	35.2
9	El Salvador	46.3	47.1	48.3	48.1	47.2
10	Guatemala	51.5	51.9	52.4	51.1	50.3
11	Haiti	55.4	57.1	58.6	59.3	59.6
12	Honduras	49.6	50.8	51.6	50.8	49.3
13	Jamaica	36.4	37.8	38.9	39.2	38.4
14	Mexico	30.1	31.8	33.2	32.6	31.7
15	Nicaragua	45.2	46.9	48.2	48.8	48.1
16	Panama	64.1	65.1	65.3	64.1	62.2
17	Paraguay	27.4	29.2	31.4	32.4	33.1
18	Peru	59.9	60.3	60.9	59.1	58.2
19	Puerto Rico	28.4	29.4	30.7	29.6	28.2
20	Uruguay	51.1	51.4	51.9	50.8	49.2
21	Venezuela, RB	33.6	35.1	36.7	36.1	35.4
Unweighted Average		41.1	42.2	43.4	43.0	42.2

¹⁾ Calculations are done using the MIMIC method. Source: Schneider (2007).

Empirical sources

[1] Arango, C., Misas, M., López, E., (2005), Economía Subterranea en Colombia 1976–2003 – Una medición a partir de la demanda de efectivo; Banco de la República de Colombia; http://www.banrep.gov.co/docum/ftp/borra335.pdf; Download: 29.01.2006.

[2] Banco de la República de Colombia, www.banrep.gov.co

[3] Colombia Viva (2000); El Tiempo; Santafé de Bogotá.

[4] Departamento Administrativo Nacional de Estadística (DANE), www.dane.gov.co

[5] Departamento Nacional de Planeación (DNP), www.dnp.gov.co

[6] United Nations Conference on Trade and Development (UNCTAD), www.unctad.org

[7] Ministerio de Hacienda y Crédito Público, www.minhacienda.gov.co

[8] International Monetary Fund (IMF), www.imf.org

[9] Dirección de Impuestos y Aduanas Nacionales de Colombia (DIAN), www.dian.gov.co

[10] United Nations Development Programme (UNDP), www.undp.org

[11] Ministerio de Trabajo, www.mintrabajo.gov.co

[12] Oficina de las Naciones Unidas contra la Droga y el Delito (UNODC), Colombia, Monitoreo de Cultivos de Coca, 2011.

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Published Online: 2014-3-18

Published in Print: 2014-4-1

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Articles in the same Issue

https://doi.org/10.1515/peps-2013-0059

Keywords for this article

Colombian shadow economy; currency demand method; taxation; unemployment; interaction between the shadow and official economy